1
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Ding K, Rakhshan M, Paredes-Acuña N, Cheng G, Thakor NV. Sensory integration for neuroprostheses: from functional benefits to neural correlates. Med Biol Eng Comput 2024; 62:2939-2960. [PMID: 38760597 DOI: 10.1007/s11517-024-03118-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 04/19/2024] [Indexed: 05/19/2024]
Abstract
In the field of sensory neuroprostheses, one ultimate goal is for individuals to perceive artificial somatosensory information and use the prosthesis with high complexity that resembles an intact system. To this end, research has shown that stimulation-elicited somatosensory information improves prosthesis perception and task performance. While studies strive to achieve sensory integration, a crucial phenomenon that entails naturalistic interaction with the environment, this topic has not been commensurately reviewed. Therefore, here we present a perspective for understanding sensory integration in neuroprostheses. First, we review the engineering aspects and functional outcomes in sensory neuroprosthesis studies. In this context, we summarize studies that have suggested sensory integration. We focus on how they have used stimulation-elicited percepts to maximize and improve the reliability of somatosensory information. Next, we review studies that have suggested multisensory integration. These works have demonstrated that congruent and simultaneous multisensory inputs provided cognitive benefits such that an individual experiences a greater sense of authority over prosthesis movements (i.e., agency) and perceives the prosthesis as part of their own (i.e., ownership). Thereafter, we present the theoretical and neuroscience framework of sensory integration. We investigate how behavioral models and neural recordings have been applied in the context of sensory integration. Sensory integration models developed from intact-limb individuals have led the way to sensory neuroprosthesis studies to demonstrate multisensory integration. Neural recordings have been used to show how multisensory inputs are processed across cortical areas. Lastly, we discuss some ongoing research and challenges in achieving and understanding sensory integration in sensory neuroprostheses. Resolving these challenges would help to develop future strategies to improve the sensory feedback of a neuroprosthetic system.
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Affiliation(s)
- Keqin Ding
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA.
| | - Mohsen Rakhshan
- Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, 32816, USA
- Disability, Aging, and Technology Cluster, University of Central Florida, Orlando, FL, 32816, USA
| | - Natalia Paredes-Acuña
- Institute for Cognitive Systems, School of Computation, Information and Technology, Technical University of Munich, 80333, Munich, Germany
| | - Gordon Cheng
- Institute for Cognitive Systems, School of Computation, Information and Technology, Technical University of Munich, 80333, Munich, Germany
| | - Nitish V Thakor
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, 21205, USA
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2
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Granata G, Di Iorio R, Ilari S, Angeloni BM, Tomasello F, Cimmino AT, Carrarini C, Marrone A, Iodice F. Phantom limb syndrome: from pathogenesis to treatment. A narrative review. Neurol Sci 2024; 45:4741-4755. [PMID: 38853232 DOI: 10.1007/s10072-024-07634-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Accepted: 06/04/2024] [Indexed: 06/11/2024]
Abstract
Phantom Limb Syndrome (PLS) can be defined as the disabling or painful sensation of the presence of a body part that is no longer present after its amputation. Anatomical changes involved in Phantom Limb Syndrome, occurring at peripheral, spinal and brain levels and include the formation of neuromas and scars, dorsal horn sensitization and plasticity, short-term and long-term modifications at molecular and topographical levels. The molecular reorganization processes of Phantom Limb Syndrome include NMDA receptors hyperactivation in the dorsal horn of the spinal column leading to inflammatory mechanisms both at a peripheral and central level. At the brain level, a central role has been recognized for sodium channels, BDNF and adenosine triphosphate receptors. In the paper we discuss current available pharmacological options with a final overview on non-pharmacological options in the pipeline.
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Affiliation(s)
- Giuseppe Granata
- Institute of Neurology, Fondazione Policlinico Gemelli IRCCS, Rome, Italy
| | - Riccardo Di Iorio
- Institute of Neurology, Fondazione Policlinico Gemelli IRCCS, Rome, Italy
| | - Sara Ilari
- Laboratory of Physiology and Pharmacology of Pain, IRCCS San Raffaele, Rome, Italy
| | | | - Fabiola Tomasello
- Department of Neuroscience, Catholic University of the Sacred Heart, Rome, Italy
| | | | - Claudia Carrarini
- Department of Neuroscience, Catholic University of the Sacred Heart, Rome, Italy
- Institute of Neurology and Neurorehabilitation, IRCCS San Raffaele, Via Della Pisana 235, 00160, Rome, Italy
| | - Antonio Marrone
- Institute of Neurology and Neurorehabilitation, IRCCS San Raffaele, Via Della Pisana 235, 00160, Rome, Italy
| | - Francesco Iodice
- Institute of Neurology and Neurorehabilitation, IRCCS San Raffaele, Via Della Pisana 235, 00160, Rome, Italy.
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3
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Gherardini M, Ianniciello V, Masiero F, Paggetti F, D'Accolti D, La Frazia E, Mani O, Dalise S, Dejanovic K, Fragapane N, Maggiani L, Ipponi E, Controzzi M, Nicastro M, Chisari C, Andreani L, Cipriani C. Restoration of grasping in an upper limb amputee using the myokinetic prosthesis with implanted magnets. Sci Robot 2024; 9:eadp3260. [PMID: 39259781 DOI: 10.1126/scirobotics.adp3260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Accepted: 08/15/2024] [Indexed: 09/13/2024]
Abstract
The loss of a hand disrupts the sophisticated neural pathways between the brain and the hand, severely affecting the level of independence of the patient and the ability to carry out daily work and social activities. Recent years have witnessed a rapid evolution of surgical techniques and technologies aimed at restoring dexterous motor functions akin to those of the human hand through bionic solutions, mainly relying on probing of electrical signals from the residual nerves and muscles. Here, we report the clinical implementation of an interface aimed at achieving this goal by exploiting muscle deformation, sensed through passive magnetic implants: the myokinetic interface. One participant with a transradial amputation received an implantation of six permanent magnets in three muscles of the residual limb. A truly self-contained myokinetic prosthetic arm embedding all hardware components and the battery within the prosthetic socket was developed. By retrieving muscle deformation caused by voluntary contraction through magnet localization, we were able to control in real time a dexterous robotic hand following both a direct control strategy and a pattern recognition approach. In just 6 weeks, the participant successfully completed a series of functional tests, achieving scores similar to those achieved when using myoelectric controllers, a standard-of-care solution, with comparable physical and mental workloads. This experience raised conceptual and technical limits of the interface, which nevertheless pave the way for further investigations in a partially unexplored field. This study also demonstrates a viable possibility for intuitively interfacing humans with robotic technologies.
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Affiliation(s)
- Marta Gherardini
- BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Valerio Ianniciello
- BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Federico Masiero
- BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Flavia Paggetti
- BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Daniele D'Accolti
- BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Eliana La Frazia
- BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Olimpia Mani
- Orthopaedics and Traumatology Unit, University Hospital of Pisa, Pisa, Italy
| | - Stefania Dalise
- Neurorehabilitation Unit, University Hospital of Pisa, Pisa, Italy
| | - Katarina Dejanovic
- BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Noemi Fragapane
- Neurorehabilitation Unit, University Hospital of Pisa, Pisa, Italy
| | - Luca Maggiani
- Neurorehabilitation Unit, University Hospital of Pisa, Pisa, Italy
| | - Edoardo Ipponi
- Orthopaedics and Traumatology Unit, University Hospital of Pisa, Pisa, Italy
| | - Marco Controzzi
- BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Manuela Nicastro
- Orthopaedic and Burn Centre Anaesthesiology and Reanimation, University Hospital of Pisa, Pisa, Italy
| | - Carmelo Chisari
- Neurorehabilitation Unit, University Hospital of Pisa, Pisa, Italy
| | - Lorenzo Andreani
- Orthopaedics and Traumatology Unit, University Hospital of Pisa, Pisa, Italy
| | - Christian Cipriani
- BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
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4
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Li H, Lin J, Lin S, Zhong H, Jiang B, Liu X, Wu W, Li W, Iranmanesh E, Zhou Z, Li W, Wang K. A bioinspired tactile scanner for computer haptics. Nat Commun 2024; 15:7632. [PMID: 39223115 PMCID: PMC11369279 DOI: 10.1038/s41467-024-51674-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Accepted: 08/15/2024] [Indexed: 09/04/2024] Open
Abstract
Computer haptics (CH) is about integration of tactile sensation and rendering in Metaverse. However, unlike computer vision (CV) where both hardware infrastructure and software programs are well developed, a generic tactile data capturing device that serves the same role as what a camera does for CV, is missing. Bioinspired by electrophysiological processes in human tactile somatosensory nervous system, here we propose a tactile scanner along with a neuromorphically-engineered system, in which a closed-loop tactile acquisition and rendering (re-creation) are preliminarily achieved. Based on the architecture of afferent nerves and intelligent functions of mechano-gating and leaky integrate-and-fire models, such a tactile scanner is designed and developed by using piezoelectric transducers as axon neurons and thin film transistor (TFT)-based neuromorphic circuits to mimic synaptic behaviours and neural functions. As an example, the neuron-like tactile information of surface textures is captured and further used to render the texture friction of a virtual surface for "recreating" a "true" feeling of touch.
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Affiliation(s)
- Huimin Li
- Guangdong Province Key Laboratory of Display Material and Technology, State Key Laboratory of Optoelectronic Materials and Technologies, School of Electronics and Information Technology (School of Microelectronics), Sun Yat-sen University, Guangzhou, 510275, China
| | - Jianle Lin
- Guangdong Province Key Laboratory of Display Material and Technology, State Key Laboratory of Optoelectronic Materials and Technologies, School of Electronics and Information Technology (School of Microelectronics), Sun Yat-sen University, Guangzhou, 510275, China
| | - Shuxin Lin
- Guangdong Province Key Laboratory of Display Material and Technology, State Key Laboratory of Optoelectronic Materials and Technologies, School of Electronics and Information Technology (School of Microelectronics), Sun Yat-sen University, Guangzhou, 510275, China
| | - Haojie Zhong
- Guangdong Province Key Laboratory of Display Material and Technology, State Key Laboratory of Optoelectronic Materials and Technologies, School of Electronics and Information Technology (School of Microelectronics), Sun Yat-sen University, Guangzhou, 510275, China
| | - Bowei Jiang
- Guangdong Province Key Laboratory of Display Material and Technology, State Key Laboratory of Optoelectronic Materials and Technologies, School of Electronics and Information Technology (School of Microelectronics), Sun Yat-sen University, Guangzhou, 510275, China
| | - Xinghui Liu
- Shenzhen Chipwey Innovation Technologies Co. Ltd., Shenzhen, 518100, China
| | - Weisheng Wu
- Guangdong Province Key Laboratory of Display Material and Technology, State Key Laboratory of Optoelectronic Materials and Technologies, School of Electronics and Information Technology (School of Microelectronics), Sun Yat-sen University, Guangzhou, 510275, China
| | - Weiwei Li
- State Key Laboratory of Microelectronic Devices & Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Emad Iranmanesh
- Guangdong Province Key Laboratory of Display Material and Technology, State Key Laboratory of Optoelectronic Materials and Technologies, School of Electronics and Information Technology (School of Microelectronics), Sun Yat-sen University, Guangzhou, 510275, China
| | - Zhongyi Zhou
- Shenzhen Chipwey Innovation Technologies Co. Ltd., Shenzhen, 518100, China
| | - Wenjun Li
- School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, 510275, China
| | - Kai Wang
- Guangdong Province Key Laboratory of Display Material and Technology, State Key Laboratory of Optoelectronic Materials and Technologies, School of Electronics and Information Technology (School of Microelectronics), Sun Yat-sen University, Guangzhou, 510275, China.
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5
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Huang Y, Yao K, Zhang Q, Huang X, Chen Z, Zhou Y, Yu X. Bioelectronics for electrical stimulation: materials, devices and biomedical applications. Chem Soc Rev 2024; 53:8632-8712. [PMID: 39132912 DOI: 10.1039/d4cs00413b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Bioelectronics is a hot research topic, yet an important tool, as it facilitates the creation of advanced medical devices that interact with biological systems to effectively diagnose, monitor and treat a broad spectrum of health conditions. Electrical stimulation (ES) is a pivotal technique in bioelectronics, offering a precise, non-pharmacological means to modulate and control biological processes across molecular, cellular, tissue, and organ levels. This method holds the potential to restore or enhance physiological functions compromised by diseases or injuries by integrating sophisticated electrical signals, device interfaces, and designs tailored to specific biological mechanisms. This review explains the mechanisms by which ES influences cellular behaviors, introduces the essential stimulation principles, discusses the performance requirements for optimal ES systems, and highlights the representative applications. From this review, we can realize the potential of ES based bioelectronics in therapy, regenerative medicine and rehabilitation engineering technologies, ranging from tissue engineering to neurological technologies, and the modulation of cardiovascular and cognitive functions. This review underscores the versatility of ES in various biomedical contexts and emphasizes the need to adapt to complex biological and clinical landscapes it addresses.
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Affiliation(s)
- Ya Huang
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Kuanming Yao
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Qiang Zhang
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Xingcan Huang
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Zhenlin Chen
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Yu Zhou
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China.
| | - Xinge Yu
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
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6
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Giannotti A, Santanché R, Zinno C, Carpaneto J, Micera S, Riva ER. Characterization of a conductive hydrogel@Carbon fibers electrode as a novel intraneural interface. Bioelectron Med 2024; 10:20. [PMID: 39187894 PMCID: PMC11348655 DOI: 10.1186/s42234-024-00154-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2024] [Accepted: 08/02/2024] [Indexed: 08/28/2024] Open
Abstract
Peripheral neural interfaces facilitate bidirectional communication between the nervous system and external devices, enabling precise control for prosthetic limbs, sensory feedback systems, and therapeutic interventions in the field of Bioelectronic Medicine. Intraneural interfaces hold great promise since they ensure high selectivity in communicating only with the desired nerve fascicles. Despite significant advancements, challenges such as chronic immune response, signal degradation over time, and lack of long-term biocompatibility remain critical considerations in the development of such devices. Here we report on the development and benchtop characterization of a novel design of an intraneural interface based on carbon fiber bundles. Carbon fibers possess low impedance, enabling enhanced signal detection and stimulation efficacy compared to traditional metal electrodes. We provided a 3D-stabilizing structure for the carbon fiber bundles made of PEDOT:PSS hydrogel, to enhance the biocompatibility between the carbon fibers and the nervous tissue. We further coated the overall bundles with a thin layer of elastomeric material to provide electrical insulation. Taken together, our results demonstrated that our electrode possesses adequate structural and electrochemical properties to ensure proper stimulation and recording of peripheral nerve fibers and a biocompatible interface with the nervous tissue.
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Affiliation(s)
- Alice Giannotti
- The Biorobotic Institute, Scuola Superiore Sant'Anna, Piazza Martiri Della Libertà 33, 56127, Pisa, Italy
- Department of Excellence in Robotics&AI, Scuola Superiore Sant'Anna, Piazza Martiri Della Libertà 33, 56127, Pisa, Italy
| | - Ranieri Santanché
- Dipartimento Di Ingegneria Civile E Industriale (DICI), Università Di Pisa, Largo Lucio Lazzarino 1, 56122, Pisa, Italy
| | - Ciro Zinno
- The Biorobotic Institute, Scuola Superiore Sant'Anna, Piazza Martiri Della Libertà 33, 56127, Pisa, Italy
- Department of Excellence in Robotics&AI, Scuola Superiore Sant'Anna, Piazza Martiri Della Libertà 33, 56127, Pisa, Italy
| | - Jacopo Carpaneto
- The Biorobotic Institute, Scuola Superiore Sant'Anna, Piazza Martiri Della Libertà 33, 56127, Pisa, Italy
- Department of Excellence in Robotics&AI, Scuola Superiore Sant'Anna, Piazza Martiri Della Libertà 33, 56127, Pisa, Italy
| | - Silvestro Micera
- The Biorobotic Institute, Scuola Superiore Sant'Anna, Piazza Martiri Della Libertà 33, 56127, Pisa, Italy
- Centre for Neuroprosthetics and Institute of Bioengineering, School of Engineering, Bertarelli Foundation Chair in Translational Neuroengineering, ÉcolePolytechniqueFédérale de Lausanne (EPFL), 1007, Lausanne, Switzerland
| | - Eugenio Redolfi Riva
- The Biorobotic Institute, Scuola Superiore Sant'Anna, Piazza Martiri Della Libertà 33, 56127, Pisa, Italy.
- Department of Excellence in Robotics&AI, Scuola Superiore Sant'Anna, Piazza Martiri Della Libertà 33, 56127, Pisa, Italy.
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7
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Dalrymple AN, Fisher LE, Weber DJ. A preliminary study exploring the effects of transcutaneous spinal cord stimulation on spinal excitability and phantom limb pain in people with a transtibial amputation. J Neural Eng 2024; 21:046058. [PMID: 39094627 PMCID: PMC11391861 DOI: 10.1088/1741-2552/ad6a8d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Accepted: 08/02/2024] [Indexed: 08/04/2024]
Abstract
Objective. Phantom limb pain (PLP) is debilitating and affects over 70% of people with lower-limb amputation. Other neuropathic pain conditions correspond with increased spinal excitability, which can be measured using reflexes andF-waves. Spinal cord neuromodulation can be used to reduce neuropathic pain in a variety of conditions and may affect spinal excitability, but has not been extensively used for treating PLP. Here, we propose using a non-invasive neuromodulation method, transcutaneous spinal cord stimulation (tSCS), to reduce PLP and modulate spinal excitability after transtibial amputation.Approach. We recruited three participants, two males (5- and 9-years post-amputation, traumatic and alcohol-induced neuropathy) and one female (3 months post-amputation, diabetic neuropathy) for this 5 d study. We measured pain using the McGill Pain Questionnaire (MPQ), visual analog scale (VAS), and pain pressure threshold (PPT) test. We measured spinal reflex and motoneuron excitability using posterior root-muscle (PRM) reflexes andF-waves, respectively. We delivered tSCS for 30 min d-1for 5 d.Main Results. After 5 d of tSCS, MPQ scores decreased by clinically-meaningful amounts for all participants from 34.0 ± 7.0-18.3 ± 6.8; however, there were no clinically-significant decreases in VAS scores. Two participants had increased PPTs across the residual limb (Day 1: 5.4 ± 1.6 lbf; Day 5: 11.4 ± 1.0 lbf).F-waves had normal latencies but small amplitudes. PRM reflexes had high thresholds (59.5 ± 6.1μC) and low amplitudes, suggesting that in PLP, the spinal cord is hypoexcitable. After 5 d of tSCS, reflex thresholds decreased significantly (38.6 ± 12.2μC;p< 0.001).Significance. These preliminary results in this non-placebo-controlled study suggest that, overall, limb amputation and PLP may be associated with reduced spinal excitability and tSCS can increase spinal excitability and reduce PLP.
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Affiliation(s)
- Ashley N Dalrymple
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States of America
- NeuroMechatronics Lab, Carnegie Mellon University, Pittsburgh, PA, United States of America
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, United States of America
- Department of Physical Medicine & Rehabilitation, University of Utah, Salt Lake City, UT, United States of America
- NERVES Lab, University of Utah, Salt Lake City, UT, United States of America
| | - Lee E Fisher
- Department of Physical Medicine & Rehabilitation, University of Pittsburgh, Pittsburgh, PA, United States of America
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America
- Center for Neural Basis of Cognition, Pittsburgh, PA, United States of America
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Douglas J Weber
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States of America
- NeuroMechatronics Lab, Carnegie Mellon University, Pittsburgh, PA, United States of America
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, United States of America
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8
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Wei Y, Marshall AG, McGlone FP, Makdani A, Zhu Y, Yan L, Ren L, Wei G. Human tactile sensing and sensorimotor mechanism: from afferent tactile signals to efferent motor control. Nat Commun 2024; 15:6857. [PMID: 39127772 PMCID: PMC11316806 DOI: 10.1038/s41467-024-50616-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 07/12/2024] [Indexed: 08/12/2024] Open
Abstract
In tactile sensing, decoding the journey from afferent tactile signals to efferent motor commands is a significant challenge primarily due to the difficulty in capturing population-level afferent nerve signals during active touch. This study integrates a finite element hand model with a neural dynamic model by using microneurography data to predict neural responses based on contact biomechanics and membrane transduction dynamics. This research focuses specifically on tactile sensation and its direct translation into motor actions. Evaluations of muscle synergy during in -vivo experiments revealed transduction functions linking tactile signals and muscle activation. These functions suggest similar sensorimotor strategies for grasping influenced by object size and weight. The decoded transduction mechanism was validated by restoring human-like sensorimotor performance on a tendon-driven biomimetic hand. This research advances our understanding of translating tactile sensation into motor actions, offering valuable insights into prosthetic design, robotics, and the development of next-generation prosthetics with neuromorphic tactile feedback.
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Affiliation(s)
- Yuyang Wei
- Department of Engineering Science, University of Oxford, Oxford, OX1 3PJ, UK
- Department of Mechanical, Aerospace and Civil Engineering, The University of Manchester, Manchester, M13 9PL, UK
| | - Andrew G Marshall
- Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, L69 3BX, UK
| | - Francis P McGlone
- Department of Neuroscience and Biomedical Engineering, Aalto University, Otakaari 24, Helsinki, Finland
| | - Adarsh Makdani
- School of Natural Sciences and Psychology, Liverpool John Moores University, Liverpool, L3 5UX, UK
| | - Yiming Zhu
- Department of Mechanical, Aerospace and Civil Engineering, The University of Manchester, Manchester, M13 9PL, UK
| | - Lingyun Yan
- Department of Mechanical, Aerospace and Civil Engineering, The University of Manchester, Manchester, M13 9PL, UK
| | - Lei Ren
- Department of Mechanical, Aerospace and Civil Engineering, The University of Manchester, Manchester, M13 9PL, UK.
- Key Laboratory of Bionic Engineering, Ministry of Education, Jilin University, Jilin, China.
| | - Guowu Wei
- School of Science, Engineering and Environment, University of Salford, Manchester, M5 4WT, UK.
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9
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Nanivadekar AC, Bose R, Petersen BA, Okorokova EV, Sarma D, Madonna TJ, Barra B, Farooqui J, Dalrymple AN, Levy I, Helm ER, Miele VJ, Boninger ML, Capogrosso M, Bensmaia SJ, Weber DJ, Fisher LE. Restoration of sensory feedback from the foot and reduction of phantom limb pain via closed-loop spinal cord stimulation. Nat Biomed Eng 2024; 8:992-1003. [PMID: 38097809 PMCID: PMC11404213 DOI: 10.1038/s41551-023-01153-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 10/27/2023] [Indexed: 12/30/2023]
Abstract
Restoring somatosensory feedback in individuals with lower-limb amputations would reduce the risk of falls and alleviate phantom limb pain. Here we show, in three individuals with transtibial amputation (one traumatic and two owing to diabetic peripheral neuropathy), that sensations from the missing foot, with control over their location and intensity, can be evoked via lateral lumbosacral spinal cord stimulation with commercially available electrodes and by modulating the intensity of stimulation in real time on the basis of signals from a wireless pressure-sensitive shoe insole. The restored somatosensation via closed-loop stimulation improved balance control (with a 19-point improvement in the composite score of the Sensory Organization Test in one individual) and gait stability (with a 5-point improvement in the Functional Gait Assessment in one individual). And over the implantation period of the stimulation leads, the three individuals experienced a clinically meaningful decrease in phantom limb pain (with an average reduction of nearly 70% on a visual analogue scale). Our findings support the further clinical assessment of lower-limb neuroprostheses providing somatosensory feedback.
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Affiliation(s)
- Ameya C Nanivadekar
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Rohit Bose
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Bailey A Petersen
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Elizaveta V Okorokova
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL, USA
| | - Devapratim Sarma
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Tyler J Madonna
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beatrice Barra
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Neuroscience and Movement Science, University of Fribourg, Fribourg, Switzerland
| | - Juhi Farooqui
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Ashley N Dalrymple
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA
- Department of Physical Medicine and Rehabilitation, University of Utah, Salt Lake City, UT, USA
| | - Isaiah Levy
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Eric R Helm
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Vincent J Miele
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Michael L Boninger
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Marco Capogrosso
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Sliman J Bensmaia
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL, USA
| | - Douglas J Weber
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Lee E Fisher
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA.
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA.
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10
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Vassiliadis P, Beanato E, Popa T, Windel F, Morishita T, Neufeld E, Duque J, Derosiere G, Wessel MJ, Hummel FC. Non-invasive stimulation of the human striatum disrupts reinforcement learning of motor skills. Nat Hum Behav 2024; 8:1581-1598. [PMID: 38811696 PMCID: PMC11343719 DOI: 10.1038/s41562-024-01901-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 04/23/2024] [Indexed: 05/31/2024]
Abstract
Reinforcement feedback can improve motor learning, but the underlying brain mechanisms remain underexplored. In particular, the causal contribution of specific patterns of oscillatory activity within the human striatum is unknown. To address this question, we exploited a recently developed non-invasive deep brain stimulation technique called transcranial temporal interference stimulation (tTIS) during reinforcement motor learning with concurrent neuroimaging, in a randomized, sham-controlled, double-blind study. Striatal tTIS applied at 80 Hz, but not at 20 Hz, abolished the benefits of reinforcement on motor learning. This effect was related to a selective modulation of neural activity within the striatum. Moreover, 80 Hz, but not 20 Hz, tTIS increased the neuromodulatory influence of the striatum on frontal areas involved in reinforcement motor learning. These results show that tTIS can non-invasively and selectively modulate a striatal mechanism involved in reinforcement learning, expanding our tools for the study of causal relationships between deep brain structures and human behaviour.
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Affiliation(s)
- Pierre Vassiliadis
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland
- Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium
| | - Elena Beanato
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland
| | - Traian Popa
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland
| | - Fabienne Windel
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland
| | - Takuya Morishita
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland
| | - Esra Neufeld
- Foundation for Research on Information Technologies in Society, Zurich, Switzerland
| | - Julie Duque
- Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium
| | - Gerard Derosiere
- Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium
- Lyon Neuroscience Research Center, Impact Team, Inserm U1028, CNRS UMR5292, Lyon 1 University, Bron, France
| | - Maximilian J Wessel
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - Friedhelm C Hummel
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland.
- Clinical Neuroscience, University of Geneva Medical School, Geneva, Switzerland.
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11
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Micera S, Shokur S. Our research path toward the restoration of natural sensations in hand prostheses. Artif Organs 2024. [PMID: 38994666 DOI: 10.1111/aor.14823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2024] [Accepted: 06/24/2024] [Indexed: 07/13/2024]
Abstract
The human hand, with its intricate sensory capabilities, plays a pivotal role in our daily interactions with the world. This remarkable organ possesses a wide range of natural sensors that enrich our experiences, enabling us to perceive touch, position, and temperature. These natural sensors work in concert to provide us with a rich sensory experience, enabling us to distinguish between various textures, gauge the force of our grip, determine the position of our fingers without needing to see them, perceive the temperature of objects we come into contact with or detect if a cloth is wet or dry. This complex sensory system is fundamental to our ability to manipulate objects, explore our surroundings, and interact with the world and people around us. In this article, we summarize the research performed in our laboratories over the years and our findings to restore both touch, position, and temperature modalities. The combination of intraneural stimulation, sensory substitution, and wearable technology opens new possibilities for enhancing sensory feedback in prosthetic hands, promising improved functionality and a closer approximation to natural sensory experiences for individuals with limb differences.
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Affiliation(s)
- Silvestro Micera
- Bertarelli Foundation Chair in Translational Neuroengineering, Neuro-X Institute, School of Engineering, Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland
- The BioRobotics Institute, Interdisciplinary Health Center, and Department of Excellence in Robotics and AI Scuola Superiore Sant'Anna, Pisa, Italy
| | - Solaiman Shokur
- Bertarelli Foundation Chair in Translational Neuroengineering, Neuro-X Institute, School of Engineering, Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland
- The BioRobotics Institute, Interdisciplinary Health Center, and Department of Excellence in Robotics and AI Scuola Superiore Sant'Anna, Pisa, Italy
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12
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Manero A, Rivera V, Fu Q, Schwartzman JD, Prock-Gibbs H, Shah N, Gandhi D, White E, Crawford KE, Coathup MJ. Emerging Medical Technologies and Their Use in Bionic Repair and Human Augmentation. Bioengineering (Basel) 2024; 11:695. [PMID: 39061777 PMCID: PMC11274085 DOI: 10.3390/bioengineering11070695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2024] [Revised: 07/04/2024] [Accepted: 07/07/2024] [Indexed: 07/28/2024] Open
Abstract
As both the proportion of older people and the length of life increases globally, a rise in age-related degenerative diseases, disability, and prolonged dependency is projected. However, more sophisticated biomedical materials, as well as an improved understanding of human disease, is forecast to revolutionize the diagnosis and treatment of conditions ranging from osteoarthritis to Alzheimer's disease as well as impact disease prevention. Another, albeit quieter, revolution is also taking place within society: human augmentation. In this context, humans seek to improve themselves, metamorphosing through self-discipline or more recently, through use of emerging medical technologies, with the goal of transcending aging and mortality. In this review, and in the pursuit of improved medical care following aging, disease, disability, or injury, we first highlight cutting-edge and emerging materials-based neuroprosthetic technologies designed to restore limb or organ function. We highlight the potential for these technologies to be utilized to augment human performance beyond the range of natural performance. We discuss and explore the growing social movement of human augmentation and the idea that it is possible and desirable to use emerging technologies to push the boundaries of what it means to be a healthy human into the realm of superhuman performance and intelligence. This potential future capability is contrasted with limitations in the right-to-repair legislation, which may create challenges for patients. Now is the time for continued discussion of the ethical strategies for research, implementation, and long-term device sustainability or repair.
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Affiliation(s)
- Albert Manero
- Limbitless Solutions, University of Central Florida, 12703 Research Parkway, Suite 100, Orlando, FL 32826, USA (V.R.)
- Biionix Cluster, University of Central Florida, Orlando, FL 32827, USA; (Q.F.); (K.E.C.)
| | - Viviana Rivera
- Limbitless Solutions, University of Central Florida, 12703 Research Parkway, Suite 100, Orlando, FL 32826, USA (V.R.)
| | - Qiushi Fu
- Biionix Cluster, University of Central Florida, Orlando, FL 32827, USA; (Q.F.); (K.E.C.)
- Department of Mechanical and Aerospace Engineering, University of Central Florida, Orlando, FL 32816, USA
| | - Jonathan D. Schwartzman
- College of Medicine, University of Central Florida, Orlando, FL 32827, USA; (J.D.S.); (H.P.-G.); (N.S.); (D.G.); (E.W.)
| | - Hannah Prock-Gibbs
- College of Medicine, University of Central Florida, Orlando, FL 32827, USA; (J.D.S.); (H.P.-G.); (N.S.); (D.G.); (E.W.)
| | - Neel Shah
- College of Medicine, University of Central Florida, Orlando, FL 32827, USA; (J.D.S.); (H.P.-G.); (N.S.); (D.G.); (E.W.)
| | - Deep Gandhi
- College of Medicine, University of Central Florida, Orlando, FL 32827, USA; (J.D.S.); (H.P.-G.); (N.S.); (D.G.); (E.W.)
| | - Evan White
- College of Medicine, University of Central Florida, Orlando, FL 32827, USA; (J.D.S.); (H.P.-G.); (N.S.); (D.G.); (E.W.)
| | - Kaitlyn E. Crawford
- Biionix Cluster, University of Central Florida, Orlando, FL 32827, USA; (Q.F.); (K.E.C.)
- Department of Materials Science and Engineering, University of Central Florida, Orlando, FL 32816, USA
| | - Melanie J. Coathup
- Biionix Cluster, University of Central Florida, Orlando, FL 32827, USA; (Q.F.); (K.E.C.)
- College of Medicine, University of Central Florida, Orlando, FL 32827, USA; (J.D.S.); (H.P.-G.); (N.S.); (D.G.); (E.W.)
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13
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Festin C, Ortmayr J, Maierhofer U, Tereshenko V, Blumer R, Schmoll M, Carrero-Rojas G, Luft M, Laengle G, Farina D, Bergmeister KD, Aszmann OC. Creation of a biological sensorimotor interface for bionic reconstruction. Nat Commun 2024; 15:5337. [PMID: 38914540 PMCID: PMC11196281 DOI: 10.1038/s41467-024-49580-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 06/12/2024] [Indexed: 06/26/2024] Open
Abstract
Neuromuscular control of bionic arms has constantly improved over the past years, however, restoration of sensation remains elusive. Previous approaches to reestablish sensory feedback include tactile, electrical, and peripheral nerve stimulation, however, they cannot recreate natural, intuitive sensations. Here, we establish an experimental biological sensorimotor interface and demonstrate its potential use in neuroprosthetics. We transfer a mixed nerve to a skeletal muscle combined with glabrous dermal skin transplantation, thus forming a bi-directional communication unit in a rat model. Morphological analyses indicate reinnervation of the skin, mechanoreceptors, NMJs, and muscle spindles. Furthermore, sequential retrograde labeling reveals specific sensory reinnervation at the level of the dorsal root ganglia. Electrophysiological recordings show reproducible afferent signals upon tactile stimulation and tendon manipulation. The results demonstrate the possibility of surgically creating an interface for both decoding efferent motor control, as well as encoding afferent tactile and proprioceptive feedback, and may indicate the way forward regarding clinical translation of biological communication pathways for neuroprosthetic applications.
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Affiliation(s)
- Christopher Festin
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
- Center for Biomedical Research, Medical University of Vienna, Vienna, Austria
| | - Joachim Ortmayr
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
| | - Udo Maierhofer
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
- Center for Biomedical Research, Medical University of Vienna, Vienna, Austria
| | - Vlad Tereshenko
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
- Center for Biomedical Research, Medical University of Vienna, Vienna, Austria
- Division of Plastic and Reconstructive Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Roland Blumer
- Center for Anatomy and Cell Biology, Medical University of Vienna, Vienna, Austria
| | - Martin Schmoll
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Génova Carrero-Rojas
- Center for Anatomy and Cell Biology, Medical University of Vienna, Vienna, Austria
| | - Matthias Luft
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
- Center for Biomedical Research, Medical University of Vienna, Vienna, Austria
- Department of Plastic, Aesthetic and Reconstructive Surgery, University Hospital St. Poelten, Karl Landsteiner University of Health Sciences, Krems, Austria
| | - Gregor Laengle
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
- Center for Biomedical Research, Medical University of Vienna, Vienna, Austria
- Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
| | - Dario Farina
- Department of Bioengineering, Imperial College London, London, United Kingdom
| | - Konstantin D Bergmeister
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
- Department of Plastic, Aesthetic and Reconstructive Surgery, University Hospital St. Poelten, Karl Landsteiner University of Health Sciences, Krems, Austria
| | - Oskar C Aszmann
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria.
- Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria.
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14
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Ma C, Nazarpour K. DistaNet: grasp-specific distance biofeedback promotes the retention of myoelectric skills. J Neural Eng 2024; 21:036037. [PMID: 38742365 DOI: 10.1088/1741-2552/ad4af7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Accepted: 04/24/2024] [Indexed: 05/16/2024]
Abstract
Objective.An active myoelectric interface responds to the user's muscle signals to enable movements. Machine learning can decode user intentions from myoelectric signals. However, machine learning-based interface control lacks continuous, intuitive feedback about task performance, needed to facilitate the acquisition and retention of myoelectric control skills.Approach.We propose DistaNet as a neural network-based framework that extracts smooth, continuous, and low-dimensional signatures of the hand grasps from multi-channel myoelectric signals and provides grasp-specific biofeedback to the users.Main results.Experimental results show its effectiveness in decoding user gestures and providing biofeedback, helping users retain the acquired motor skills.Significance.We demonstrates myoelectric skill retention in a pattern recognition setting for the first time.
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Affiliation(s)
- Chenfei Ma
- School of Informatics, The University of Edinburgh, Edinburgh EH8 9AB, United Kingdom
| | - Kianoush Nazarpour
- School of Informatics, The University of Edinburgh, Edinburgh EH8 9AB, United Kingdom
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15
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Erbaş İ, Güçlü B. Real-time vibrotactile pattern generation and identification using discrete event-driven feedback. Somatosens Mot Res 2024; 41:77-89. [PMID: 36751096 DOI: 10.1080/08990220.2023.2175811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Accepted: 01/30/2023] [Indexed: 02/09/2023]
Abstract
This study assesses human identification of vibrotactile patterns by using real-time discrete event-driven feedback. Previously acquired force and bend sensor data from a robotic hand were used to predict movement-type (stationary, flexion, contact, extension, release) and object-type (no object, hard object, soft object) states by using decision tree (DT) algorithms implemented in a field-programmable gate array (FPGA). Six able-bodied humans performed a 2- and 3-step sequential pattern recognition task in which state transitions were signaled as vibrotactile feedback. The stimuli were generated according to predicted classes represented by two frequencies (F1: 80 Hz, F2: 180 Hz) and two magnitudes (M1: low, M2: high) calibrated psychophysically for each participant; and they were applied by two actuators (Haptuators) placed on upper arms. A soft/hard object was mapped to F1/F2; and manipulating it with low/high force was assigned to M1/M2 in the left actuator. On the other hand, flexion/extension movement was mapped to F1/F2 in the right actuator, with movement in air as M1 and during object manipulation as M2. DT algorithm performed better for the object-type (97%) than the movement-type (88%) classification in real time. Participants could recognize feedback associated with 14 discrete-event sequences with low-to-medium accuracy. The performance was higher (76 ± 9% recall, 76 ± 17% precision, 78 ± 4% accuracy) for recognizing any one event in the sequences. The results show that FPGA implementation of classification for discrete event-driven vibrotactile feedback can be feasible in haptic devices with additional cues in the physical context.
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Affiliation(s)
- İsmail Erbaş
- Biomedical Engineering Department, Rensselaer Polytechnic Institute, Troy, NY, USA
| | - Burak Güçlü
- Institute of Biomedical Engineering, Boğaziçi University, İstanbul, Turkey
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16
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Wang X, Zhang Y, Guo T, Wu S, Zhong J, Cheng C, Sui X. Selective intrafascicular stimulation of myelinated and unmyelinated nerve fibers through a longitudinal electrode: A computational study. Comput Biol Med 2024; 176:108556. [PMID: 38733726 DOI: 10.1016/j.compbiomed.2024.108556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Accepted: 05/05/2024] [Indexed: 05/13/2024]
Abstract
Carbon nanotube (CNT) fiber electrodes have demonstrated exceptional spatial selectivity and sustained reliability in the context of intrafascicular electrical stimulation, as evidenced through rigorous animal experimentation. A significant presence of unmyelinated C fibers, known to induce uncomfortable somatosensory experiences, exists within peripheral nerves. This presence poses a considerable challenge to the excitation of myelinated Aβ fibers, which are crucial for tactile sensation. To achieve nuanced tactile sensory feedback utilizing CNT fiber electrodes, the selective stimulation of Aβ sensory afferents emerges as a critical factor. In confronting this challenge, the present investigation sought to refine and apply a rat sciatic-nerve model leveraging the capabilities of the COMSOL-NEURON framework. This approach enables a systematic evaluation of the influence exerted by stimulation parameters and electrode geometry on the activation dynamics of both myelinated Aβ and unmyelinated C fibers. The findings advocate for the utilization of current pulses featuring a pulse width of 600 μs, alongside the deployment of CNT fibers characterized by a diminutive diameter of 10 μm, with an exclusively exposed cross-sectional area, to facilitate reduced activation current thresholds. Comparative analysis under monopolar and bipolar electrical stimulation conditions revealed proximate activation thresholds, albeit with bipolar stimulation exhibiting superior fiber selectivity relative to its monopolar counterpart. Concerning pulse waveform characteristics, the adoption of an anodic-first biphasic stimulation modality is favored, taking into account the dual criteria of activation threshold and fiber selectivity optimization. Consequently, this investigation furnishes an efficacious stimulation paradigm for the selective activation of touch-related nerve fibers, alongside provisioning a comprehensive theoretical foundation for the realization of natural tactile feedback within the domain of prosthetic hand applications.
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Affiliation(s)
- Xintong Wang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Yapeng Zhang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Tianruo Guo
- Graduate School of Biomedical Engineering, The University of New South Wales, Sydney, NSW, 2052, Australia
| | - Shuhui Wu
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Junwen Zhong
- Department of Electromechanical Engineering, University of Macau, Macau SAR, 999078, China
| | - Chengkung Cheng
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China; Med-X Research Institute, Shanghai Jiao Tong University, Engineering Research Center of Digital Medicine, Ministry of Education, Shanghai, China
| | - Xiaohong Sui
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
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17
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Schone HR, Udeozor M, Moninghoff M, Rispoli B, Vandersea J, Lock B, Hargrove L, Makin TR, Baker CI. Biomimetic versus arbitrary motor control strategies for bionic hand skill learning. Nat Hum Behav 2024; 8:1108-1123. [PMID: 38499772 PMCID: PMC11199138 DOI: 10.1038/s41562-023-01811-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 12/21/2023] [Indexed: 03/20/2024]
Abstract
A long-standing engineering ambition has been to design anthropomorphic bionic limbs: devices that look like and are controlled in the same way as the biological body (biomimetic). The untested assumption is that biomimetic motor control enhances device embodiment, learning, generalization and automaticity. To test this, we compared biomimetic and non-biomimetic control strategies for non-disabled participants when learning to control a wearable myoelectric bionic hand operated by an eight-channel electromyography pattern-recognition system. We compared motor learning across days and behavioural tasks for two training groups: biomimetic (mimicking the desired bionic hand gesture with biological hand) and arbitrary control (mapping an unrelated biological hand gesture with the desired bionic gesture). For both trained groups, training improved bionic limb control, reduced cognitive reliance and increased embodiment over the bionic hand. Biomimetic users had more intuitive and faster control early in training. Arbitrary users matched biomimetic performance later in training. Furthermore, arbitrary users showed increased generalization to a new control strategy. Collectively, our findings suggest that biomimetic and arbitrary control strategies provide different benefits. The optimal strategy is probably not strictly biomimetic, but rather a flexible strategy within the biomimetic-to-arbitrary spectrum, depending on the user, available training opportunities and user requirements.
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Affiliation(s)
- Hunter R Schone
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA.
- Institute of Cognitive Neuroscience, University College London, London, UK.
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Malcolm Udeozor
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Mae Moninghoff
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Beth Rispoli
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - James Vandersea
- Medical Center Orthotics and Prosthetics, Silver Spring, MD, USA
| | | | - Levi Hargrove
- Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL, USA
- The Regenstein Foundation Center for Bionic Medicine, Shirley Ryan AbilityLab, Chicago, IL, USA
| | - Tamar R Makin
- Institute of Cognitive Neuroscience, University College London, London, UK.
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
| | - Chris I Baker
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
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18
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Sagastegui Alva PG, Boesendorfer A, Aszmann OC, Ibáñez J, Farina D. Excitation of natural spinal reflex loops in the sensory-motor control of hand prostheses. Sci Robot 2024; 9:eadl0085. [PMID: 38809994 DOI: 10.1126/scirobotics.adl0085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Accepted: 04/30/2024] [Indexed: 05/31/2024]
Abstract
Sensory feedback for prosthesis control is typically based on encoding sensory information in specific types of sensory stimuli that the users interpret to adjust the control of the prosthesis. However, in physiological conditions, the afferent feedback received from peripheral nerves is not only processed consciously but also modulates spinal reflex loops that contribute to the neural information driving muscles. Spinal pathways are relevant for sensory-motor integration, but they are commonly not leveraged for prosthesis control. We propose an approach to improve sensory-motor integration for prosthesis control based on modulating the excitability of spinal circuits through the vibration of tendons in a closed loop with muscle activity. We measured muscle signals in healthy participants and amputees during different motor tasks, and we closed the loop by applying vibration on tendons connected to the muscles, which modulated the excitability of motor neurons. The control signals to the prosthesis were thus the combination of voluntary control and additional spinal reflex inputs induced by tendon vibration. Results showed that closed-loop tendon vibration was able to modulate the neural drive to the muscles. When closed-loop tendon vibration was used, participants could achieve similar or better control performance in interfaces using muscle activation than without stimulation. Stimulation could even improve prosthetic grasping in amputees. Overall, our results indicate that closed-loop tendon vibration can integrate spinal reflex pathways in the myocontrol system and open the possibility of incorporating natural feedback loops in prosthesis control.
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Affiliation(s)
| | - Anna Boesendorfer
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
| | - Oskar C Aszmann
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
- Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
| | - Jaime Ibáñez
- Department of Bioengineering, Imperial College London, London, UK
- BSICoS group, I3A Institute, University of Zaragoza, IIS Aragón, Zaragoza, Spain
| | - Dario Farina
- Department of Bioengineering, Imperial College London, London, UK
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19
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Chen L, Karilanova S, Chaki S, Wen C, Wang L, Winblad B, Zhang SL, Özçelikkale A, Zhang ZB. Spike timing-based coding in neuromimetic tactile system enables dynamic object classification. Science 2024; 384:660-665. [PMID: 38723082 DOI: 10.1126/science.adf3708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 03/13/2024] [Indexed: 05/31/2024]
Abstract
Rapid processing of tactile information is essential to human haptic exploration and dexterous object manipulation. Conventional electronic skins generate frames of tactile signals upon interaction with objects. Unfortunately, they are generally ill-suited for efficient coding of temporal information and rapid feature extraction. In this work, we report a neuromorphic tactile system that uses spike timing, especially the first-spike timing, to code dynamic tactile information about touch and grasp. This strategy enables the system to seamlessly code highly dynamic information with millisecond temporal resolution on par with the biological nervous system, yielding dynamic extraction of tactile features. Upon interaction with objects, the system rapidly classifies them in the initial phase of touch and grasp, thus paving the way to fast tactile feedback desired for neuro-robotics and neuro-prosthetics.
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Affiliation(s)
- Libo Chen
- Division of Solid-State Electronics, Department of Electrical Engineering, Uppsala University, Uppsala 75121, Sweden
| | - Sanja Karilanova
- Division of Signals and Systems, Department of Electrical Engineering, Uppsala University, Uppsala 75121, Sweden
| | - Soumi Chaki
- Division of Signals and Systems, Department of Electrical Engineering, Uppsala University, Uppsala 75121, Sweden
| | - Chenyu Wen
- Division of Solid-State Electronics, Department of Electrical Engineering, Uppsala University, Uppsala 75121, Sweden
| | - Lisha Wang
- Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Solna 17164, Sweden
| | - Bengt Winblad
- Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Solna 17164, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Huddinge 14186, Sweden
| | - Shi-Li Zhang
- Division of Solid-State Electronics, Department of Electrical Engineering, Uppsala University, Uppsala 75121, Sweden
| | - Ayça Özçelikkale
- Division of Signals and Systems, Department of Electrical Engineering, Uppsala University, Uppsala 75121, Sweden
| | - Zhi-Bin Zhang
- Division of Solid-State Electronics, Department of Electrical Engineering, Uppsala University, Uppsala 75121, Sweden
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20
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Micera S. Toward more naturalistic tactile sensors. Science 2024; 384:624-625. [PMID: 38723096 DOI: 10.1126/science.adp2623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2024]
Abstract
An artificial tactile system mimicking human touch enables effective object recognition.
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Affiliation(s)
- Silvestro Micera
- The BioRobotics Institute and Department of AI and Robotics, Scuola Superiore Sant'Anna, Pisa, Italy
- Translational Neural Engineering Laboratory, Neuro-X Institute, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
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21
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Flanagan W, Becraft K, Warren H, Stavrakis AI, Bernthal NM, Hardin TJ, Clites TR. Prosthetic Limb Attachment via Electromagnetic Attraction Through a Closed Skin Envelope. IEEE Trans Biomed Eng 2024; 71:1552-1564. [PMID: 38090864 DOI: 10.1109/tbme.2023.3342652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
OBJECTIVE Current socket-based methods of prosthetic limb attachment are responsible for many of the dominant problems reported by persons with amputation. In this work, we introduce a new paradigm for attachment via electromagnetic attraction between a bone-anchored ferromagnetic implant and an external electromagnet. Our objective was to develop a design framework for electromagnetic attachment, and to evaluate this framework in the context of transfemoral amputation. METHODS We first used inverse dynamics to calculate the forces required to suspend a knee-ankle-foot prosthesis during gait. We then conducted cadaveric dissections to inform implant geometry and design a surgical methodology for covering the implant. We also developed an in silico framework to investigate how electromagnet design affects system performance. Simulations were validated against benchtop testing of a custom-built electromagnet. RESULTS The physical electromagnet matched simulations, with a root-mean-square percentage error of 4.2% between measured and predicted forces. Using this electromagnet, we estimate that suspension of a prosthesis during gait would require 33 W of average power. After 200 and 1000 steps of simulated walking, the temperature at the skin would increase 2.3 °C and 15.4 °C relative to ambient, respectively. CONCLUSION Our design framework produced an implant and electromagnet that could feasibly suspend a knee-ankle-foot prosthesis during short walking bouts. Future work will focus on optimization of this system to reduce heating during longer bouts. SIGNIFICANCE This work demonstrates the initial feasibility of an electromagnetic prosthetic attachment paradigm that has the potential to increase comfort and improve residual limb health for persons with amputation.
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Xie A, Li C, Chou CH, Li T, Dai C, Lan N. A hybrid sensory feedback system for thermal nociceptive warning and protection in prosthetic hand. Front Neurosci 2024; 18:1351348. [PMID: 38650624 PMCID: PMC11033464 DOI: 10.3389/fnins.2024.1351348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 03/25/2024] [Indexed: 04/25/2024] Open
Abstract
Background Advanced prosthetic hands may embed nanosensors and microelectronics in their cosmetic skin. Heat influx may cause damage to these delicate structures. Protecting the integrity of the prosthetic hand becomes critical and necessary to ensure sustainable function. This study aims to mimic the sensorimotor control strategy of the human hand in perceiving nociceptive stimuli and triggering self-protective mechanisms and to investigate how similar neuromorphic mechanisms implemented in prosthetic hand can allow amputees to both volitionally release a hot object upon a nociceptive warning and achieve reinforced release via a bionic withdrawal reflex. Methods A steady-state temperature prediction algorithm was proposed to shorten the long response time of a thermosensitive temperature sensor. A hybrid sensory strategy for transmitting force and a nociceptive temperature warning using transcutaneous electrical nerve stimulation based on evoked tactile sensations was designed to reconstruct the nociceptive sensory loop for amputees. A bionic withdrawal reflex using neuromorphic muscle control technology was used so that the prosthetic hand reflexively opened when a harmful temperature was detected. Four able-bodied subjects and two forearm amputees randomly grasped a tube at the different temperatures based on these strategies. Results The average prediction error of temperature prediction algorithm was 8.30 ± 6.00%. The average success rate of six subjects in perceiving force and nociceptive temperature warnings was 86.90 and 94.30%, respectively. Under the reinforcement control mode in Test 2, the median reaction time of all subjects was 1.39 s, which was significantly faster than the median reaction time of 1.93 s in Test 1, in which two able-bodied subjects and two amputees participated. Results demonstrated the effectiveness of the integration of nociceptive sensory strategy and withdrawal reflex control strategy in a closed loop and also showed that amputees restored the warning of nociceptive sensation while also being able to withdraw from thermal danger through both voluntary and reflexive protection. Conclusion This study demonstrated that it is feasible to restore the sensorimotor ability of amputees to warn and react against thermal nociceptive stimuli. Results further showed that the voluntary release and withdrawal reflex can work together to reinforce heat protection. Nevertheless, fusing voluntary and reflex functions for prosthetic performance in activities of daily living awaits a more cogent strategy in sensorimotor control.
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Affiliation(s)
- Anran Xie
- Laboratory of NeuroRehabilitation Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Chen Li
- Laboratory of NeuroRehabilitation Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Chih-hong Chou
- Laboratory of NeuroRehabilitation Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
- Institute of Medical Robotics, School of Biomedical Engineering Shanghai Jiao Tong University, Shanghai, China
| | - Tie Li
- i-Lab, Suzhou Institute of Nano-Tech and Nano-Bionics (SINANO), Chinese Academy of Sciences (CAS), Suzhou, China
| | - Chenyun Dai
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Ning Lan
- Laboratory of NeuroRehabilitation Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
- Institute of Medical Robotics, School of Biomedical Engineering Shanghai Jiao Tong University, Shanghai, China
- Richard and Loan Hill Department of Biomedical Engineering, University of Illinois Chicago, Chicago, IL, United States
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23
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Viana D, Walston ST, Masvidal-Codina E, Illa X, Rodríguez-Meana B, Del Valle J, Hayward A, Dodd A, Loret T, Prats-Alfonso E, de la Oliva N, Palma M, Del Corro E, Del Pilar Bernicola M, Rodríguez-Lucas E, Gener T, de la Cruz JM, Torres-Miranda M, Duvan FT, Ria N, Sperling J, Martí-Sánchez S, Spadaro MC, Hébert C, Savage S, Arbiol J, Guimerà-Brunet A, Puig MV, Yvert B, Navarro X, Kostarelos K, Garrido JA. Nanoporous graphene-based thin-film microelectrodes for in vivo high-resolution neural recording and stimulation. NATURE NANOTECHNOLOGY 2024; 19:514-523. [PMID: 38212522 PMCID: PMC11026161 DOI: 10.1038/s41565-023-01570-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 11/07/2023] [Indexed: 01/13/2024]
Abstract
One of the critical factors determining the performance of neural interfaces is the electrode material used to establish electrical communication with the neural tissue, which needs to meet strict electrical, electrochemical, mechanical, biological and microfabrication compatibility requirements. This work presents a nanoporous graphene-based thin-film technology and its engineering to form flexible neural interfaces. The developed technology allows the fabrication of small microelectrodes (25 µm diameter) while achieving low impedance (∼25 kΩ) and high charge injection (3-5 mC cm-2). In vivo brain recording performance assessed in rodents reveals high-fidelity recordings (signal-to-noise ratio >10 dB for local field potentials), while stimulation performance assessed with an intrafascicular implant demonstrates low current thresholds (<100 µA) and high selectivity (>0.8) for activating subsets of axons within the rat sciatic nerve innervating tibialis anterior and plantar interosseous muscles. Furthermore, the tissue biocompatibility of the devices was validated by chronic epicortical (12 week) and intraneural (8 week) implantation. This work describes a graphene-based thin-film microelectrode technology and demonstrates its potential for high-precision and high-resolution neural interfacing.
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Affiliation(s)
- Damià Viana
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - Steven T Walston
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - Eduard Masvidal-Codina
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - Xavi Illa
- Institut de Microelectrònica de Barcelona, IMB-CNM (CSIC), Campus UAB, Bellaterra, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Madrid, Spain
| | - Bruno Rodríguez-Meana
- Institute of Neurosciences, Department of Cell Biology, Physiology and Immunology, Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Jaume Del Valle
- Institute of Neurosciences, Department of Cell Biology, Physiology and Immunology, Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Universitat Autònoma de Barcelona, Barcelona, Spain
- Secció de Fisiologia, Department de Bioquímica i Fisiologia, Facultat de Farmàcia i Ciències de l'Alimentació, Institut de Neurociències, Universitat de Barcelona, Barcelona, Spain
| | - Andrew Hayward
- Nanomedicine Lab, National Graphene Institute and Faculty of Biology, Medicine & Health, Manchester, UK
| | - Abbie Dodd
- Nanomedicine Lab, National Graphene Institute and Faculty of Biology, Medicine & Health, Manchester, UK
| | - Thomas Loret
- Nanomedicine Lab, National Graphene Institute and Faculty of Biology, Medicine & Health, Manchester, UK
| | - Elisabet Prats-Alfonso
- Institut de Microelectrònica de Barcelona, IMB-CNM (CSIC), Campus UAB, Bellaterra, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Madrid, Spain
| | - Natàlia de la Oliva
- Institute of Neurosciences, Department of Cell Biology, Physiology and Immunology, Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Marie Palma
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
| | - Elena Del Corro
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - María Del Pilar Bernicola
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - Elisa Rodríguez-Lucas
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
- Hospital del Mar Research Institute, Barcelona, Spain
| | - Thomas Gener
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
- Hospital del Mar Research Institute, Barcelona, Spain
| | - Jose Manuel de la Cruz
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - Miguel Torres-Miranda
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - Fikret Taygun Duvan
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - Nicola Ria
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - Justin Sperling
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - Sara Martí-Sánchez
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - Maria Chiara Spadaro
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - Clément Hébert
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
| | - Sinead Savage
- Nanomedicine Lab, National Graphene Institute and Faculty of Biology, Medicine & Health, Manchester, UK
| | - Jordi Arbiol
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
- ICREA, Barcelona, Spain
| | - Anton Guimerà-Brunet
- Institut de Microelectrònica de Barcelona, IMB-CNM (CSIC), Campus UAB, Bellaterra, Spain
| | - M Victoria Puig
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain
- Hospital del Mar Research Institute, Barcelona, Spain
| | - Blaise Yvert
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
| | - Xavier Navarro
- Institute of Neurosciences, Department of Cell Biology, Physiology and Immunology, Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Kostas Kostarelos
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain.
- Institute of Neurosciences, Department of Cell Biology, Physiology and Immunology, Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Universitat Autònoma de Barcelona, Barcelona, Spain.
- Nanomedicine Lab, National Graphene Institute and Faculty of Biology, Medicine & Health, Manchester, UK.
| | - Jose A Garrido
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Barcelona, Spain.
- ICREA, Barcelona, Spain.
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24
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Devecioğlu İ, Karakulak E. Three Sliding Probes Placed on Forelimb Skin for Proprioceptive Feedback Differentially yet Complementarily Contribute to Hand Gesture Detection and Object-Size Discrimination. Ann Biomed Eng 2024; 52:982-996. [PMID: 38246964 PMCID: PMC10940487 DOI: 10.1007/s10439-023-03434-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 12/22/2023] [Indexed: 01/23/2024]
Abstract
The purpose was to assess the effectiveness of three sliding tactile probes placed on the forelimb skin to provide proprioceptive feedback for the detection of hand gestures and discrimination of object size. Tactile contactors representing the first three fingers were driven along the proximodistal axis by linear servo motors. Twenty healthy subjects were involved in the gesture detection test, with 10 of them also participating in the object-size discrimination task. Motors were controlled by computer in the first four sessions of the gesture detection experiment, while the fifth session utilized a sensorized glove. Both the volar and dorsal sides of the forearm were examined. In the object-size discrimination experiment, the method was exclusively assessed on the volar surface under four distinct feedback conditions, including all fingers and each finger separately. The psychophysical data were further analyzed using a structural equation model (SEM) to evaluate the specific contributions of each individual contactor. Subjects consistently outperformed the chance level in detecting gestures. Performance improved up to the third session, with better results obtained on the volar side. The performances were similar in the fourth and fifth sessions. The just noticeable difference for achieving a 75% discrimination accuracy was found to be 2.90 mm of movement on the skin. SEM analysis indicated that the contactor for the index finger had the lowest importance in gesture detection, while it played a more significant role in object-size discrimination. However, all fingers were found to be significant predictors of subjects' responses in both experiments, except for the thumb, which was deemed insignificant in object-size discrimination. The study highlights the importance of considering the partial contribution of each degree of freedom in a sensory feedback system, especially concerning the task, when designing such systems.
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Affiliation(s)
- İsmail Devecioğlu
- Biomedical Engineering Department, Çorlu Faculty of Engineering, Tekirdağ Namık Kemal University, Tekirdağ, Turkey.
| | - Ertuğrul Karakulak
- Department of Biomedical Device Technologies, Vocational School of Technical Sciences, Tekirdağ Namık Kemal University, Tekirdağ, Turkey
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25
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Mereu F, Cordella F, Paolini R, Scarpelli A, Demofonti A, Zollo L, Gruppioni E. A Sensory Feedback Neural Stimulator Prototype for Both Implantable and Wearable Applications. MICROMACHINES 2024; 15:480. [PMID: 38675291 PMCID: PMC11051761 DOI: 10.3390/mi15040480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 03/23/2024] [Accepted: 03/29/2024] [Indexed: 04/28/2024]
Abstract
The restoration of sensory feedback is one of the current challenges in the field of prosthetics. This work, following the analysis of the various types of sensory feedback, aims to present a prototype device that could be used both for implantable applications to perform PNS and for wearable applications, performing TENS, to restore sensory feedback. The two systems are composed of three electronic boards that are presented in detail, as well as the bench tests carried out. To the authors' best knowledge, this work presents the first device that can be used in a dual scenario for restoring sensory feedback. Both the implantable and wearable versions respected the expected values regarding the stimulation parameters. In its implantable version, the proposed system allows simultaneous and independent stimulation of 30 channels. Furthermore, the capacity of the wearable version to elicit somatic sensations was evaluated on healthy participants demonstrating performance comparable with commercial solutions.
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Affiliation(s)
- Federico Mereu
- Centro Protesi Inail, Vigorso di Budrio, 40054 Bologna, Italy;
- Unit of Advanced Robotics and Human-Centred Technologies, Università Campus Bio-Medico di Roma, 00128 Rome, Italy; (F.C.); (R.P.); (A.S.); (A.D.); (L.Z.)
| | - Francesca Cordella
- Unit of Advanced Robotics and Human-Centred Technologies, Università Campus Bio-Medico di Roma, 00128 Rome, Italy; (F.C.); (R.P.); (A.S.); (A.D.); (L.Z.)
| | - Roberto Paolini
- Unit of Advanced Robotics and Human-Centred Technologies, Università Campus Bio-Medico di Roma, 00128 Rome, Italy; (F.C.); (R.P.); (A.S.); (A.D.); (L.Z.)
| | - Alessia Scarpelli
- Unit of Advanced Robotics and Human-Centred Technologies, Università Campus Bio-Medico di Roma, 00128 Rome, Italy; (F.C.); (R.P.); (A.S.); (A.D.); (L.Z.)
| | - Andrea Demofonti
- Unit of Advanced Robotics and Human-Centred Technologies, Università Campus Bio-Medico di Roma, 00128 Rome, Italy; (F.C.); (R.P.); (A.S.); (A.D.); (L.Z.)
| | - Loredana Zollo
- Unit of Advanced Robotics and Human-Centred Technologies, Università Campus Bio-Medico di Roma, 00128 Rome, Italy; (F.C.); (R.P.); (A.S.); (A.D.); (L.Z.)
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26
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Losanno E, Badi M, Roussinova E, Bogaard A, Delacombaz M, Shokur S, Micera S. An Investigation of Manifold-Based Direct Control for a Brain-to-Body Neural Bypass. IEEE OPEN JOURNAL OF ENGINEERING IN MEDICINE AND BIOLOGY 2024; 5:271-280. [PMID: 38766541 PMCID: PMC11100864 DOI: 10.1109/ojemb.2024.3381475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 02/06/2024] [Accepted: 03/11/2024] [Indexed: 05/22/2024] Open
Abstract
Objective: Brain-body interfaces (BBIs) have emerged as a very promising solution for restoring voluntary hand control in people with upper-limb paralysis. The BBI module decoding motor commands from brain signals should provide the user with intuitive, accurate, and stable control. Here, we present a preliminary investigation in a monkey of a brain decoding strategy based on the direct coupling between the activity of intrinsic neural ensembles and output variables, aiming at achieving ease of learning and long-term robustness. Results: We identified an intrinsic low-dimensional space (called manifold) capturing the co-variation patterns of the monkey's neural activity associated to reach-to-grasp movements. We then tested the animal's ability to directly control a computer cursor using cortical activation along the manifold axes. By daily recalibrating only scaling factors, we achieved rapid learning and stable high performance in simple, incremental 2D tasks over more than 12 weeks of experiments. Finally, we showed that this brain decoding strategy can be effectively coupled to peripheral nerve stimulation to trigger voluntary hand movements. Conclusions: These results represent a proof of concept of manifold-based direct control for BBI applications.
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Affiliation(s)
- E. Losanno
- The Biorobotics Institute and Department of Excellence in Robotics and AIScuola Superiore Sant'Anna56025PisaItaly
- Modular Implantable Neuroprostheses (MINE) LaboratoryUniversità Vita-Salute San Raffaele and Scuola Superiore Sant'AnnaMilanItaly
| | - M. Badi
- Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics and Institute of BioengineeringÉcole Polytechnique Fédérale de Lausanne (EPFL)1015LausanneSwitzerland
| | - E. Roussinova
- Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics and Institute of BioengineeringÉcole Polytechnique Fédérale de Lausanne (EPFL)1015LausanneSwitzerland
| | - A. Bogaard
- Department of Neuroscience and Movement Sciences, Platform of Translational Neurosciences, Section of Medicine, Faculty of Sciences and MedicineUniversity of Fribourg1700FribourgSwitzerland
| | - M. Delacombaz
- Department of Neuroscience and Movement Sciences, Platform of Translational Neurosciences, Section of Medicine, Faculty of Sciences and MedicineUniversity of Fribourg1700FribourgSwitzerland
| | - S. Shokur
- Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics and Institute of BioengineeringÉcole Polytechnique Fédérale de Lausanne (EPFL)1015LausanneSwitzerland
| | - S. Micera
- The Biorobotics Institute and Department of Excellence in Robotics and AIScuola Superiore Sant'Anna56025PisaItaly
- Modular Implantable Neuroprostheses (MINE) LaboratoryUniversità Vita-Salute San Raffaele and Scuola Superiore Sant'AnnaMilanItaly
- Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics and Institute of BioengineeringÉcole Polytechnique Fédérale de Lausanne (EPFL)1015LausanneSwitzerland
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Dadarlat MC, Sun YJ, Stryker MP. Activity-dependent recruitment of inhibition and excitation in the awake mammalian cortex during electrical stimulation. Neuron 2024; 112:821-834.e4. [PMID: 38134920 PMCID: PMC10949925 DOI: 10.1016/j.neuron.2023.11.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 08/04/2023] [Accepted: 11/22/2023] [Indexed: 12/24/2023]
Abstract
Electrical stimulation is an effective tool for mapping and altering brain connectivity, with applications ranging from treating pharmacology-resistant neurological disorders to providing sensory feedback for neural prostheses. Paramount to the success of these applications is the ability to manipulate electrical currents to precisely control evoked neural activity patterns. However, little is known about stimulation-evoked responses in inhibitory neurons nor how stimulation-evoked activity patterns depend on ongoing neural activity. In this study, we used 2-photon imaging and cell-type specific labeling to measure single-cell responses of excitatory and inhibitory neurons to electrical stimuli in the visual cortex of awake mice. Our data revealed strong interactions between electrical stimulation and pre-stimulus activity of single neurons in awake animals and distinct recruitment and response patterns for excitatory and inhibitory neurons. This work demonstrates the importance of cell-type-specific labeling of neurons in future studies.
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Affiliation(s)
- Maria C Dadarlat
- Department of Physiology, University of California, San Francisco, San Francisco, CA 94158, USA; Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN 47906, USA.
| | - Yujiao Jennifer Sun
- Department of Physiology, University of California, San Francisco, San Francisco, CA 94158, USA; Institute of Ophthalmology, University College London, London EC1V 9EL, UK
| | - Michael P Stryker
- Department of Physiology, University of California, San Francisco, San Francisco, CA 94158, USA
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28
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Slack JC, Zeiser SL, Yadav AP. The role of stimulus periodicity on spinal cord stimulation-induced artificial sensations in rodents. J Neural Eng 2024; 21:026003. [PMID: 38382104 PMCID: PMC10912903 DOI: 10.1088/1741-2552/ad2b89] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Revised: 01/26/2024] [Accepted: 02/21/2024] [Indexed: 02/23/2024]
Abstract
Objective.Sensory feedback is critical for effectively controlling brain-machine interfaces and neuroprosthetic devices. Spinal cord stimulation (SCS) is proposed as a technique to induce artificial sensory perceptions in rodents, monkeys, and humans. However, to realize the full potential of SCS as a sensory neuroprosthetic technology, a better understanding of the effect of SCS pulse train parameter changes on sensory detection and discrimination thresholds is necessary.Approach.Here we investigated whether stimulation periodicity impacts rats' ability to detect and discriminate SCS-induced perceptions at different frequencies.Main results.By varying the coefficient of variation (CV) of interstimulus pulse interval, we showed that at lower frequencies, rats could detect highly aperiodic SCS pulse trains at lower amplitudes (i.e. decreased detection thresholds). Furthermore, rats learned to discriminate stimuli with subtle differences in periodicity, and the just-noticeable differences from a highly aperiodic stimulus were smaller than those from a periodic stimulus.Significance.These results demonstrate that the temporal structure of an SCS pulse train is an integral parameter for modulating sensory feedback in neuroprosthetic applications.
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Affiliation(s)
- Jacob C Slack
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill and North Carolina State University, Chapel Hill, NC, United States of America
| | - Sidnee L Zeiser
- Department of Biomedical Engineering, Purdue University Indianapolis, Indianapolis, IN, United States of America
| | - Amol P Yadav
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill and North Carolina State University, Chapel Hill, NC, United States of America
- Department of Neurosurgery, UNC School of Medicine, Chapel Hill, NC, United States of America
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America
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29
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Katic Secerovic N, Balaguer JM, Gorskii O, Pavlova N, Liang L, Ho J, Grigsby E, Gerszten PC, Karal-Ogly D, Bulgin D, Orlov S, Pirondini E, Musienko P, Raspopovic S, Capogrosso M. Neural population dynamics reveals disruption of spinal circuits' responses to proprioceptive input during electrical stimulation of sensory afferents. Cell Rep 2024; 43:113695. [PMID: 38245870 PMCID: PMC10962447 DOI: 10.1016/j.celrep.2024.113695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 11/08/2023] [Accepted: 01/06/2024] [Indexed: 01/23/2024] Open
Abstract
While neurostimulation technologies are rapidly approaching clinical applications for sensorimotor disorders, the impact of electrical stimulation on network dynamics is still unknown. Given the high degree of shared processing in neural structures, it is critical to understand if neurostimulation affects functions that are related to, but not targeted by, the intervention. Here, we approach this question by studying the effects of electrical stimulation of cutaneous afferents on unrelated processing of proprioceptive inputs. We recorded intraspinal neural activity in four monkeys while generating proprioceptive inputs from the radial nerve. We then applied continuous stimulation to the radial nerve cutaneous branch and quantified the impact of the stimulation on spinal processing of proprioceptive inputs via neural population dynamics. Proprioceptive pulses consistently produce neural trajectories that are disrupted by concurrent cutaneous stimulation. This disruption propagates to the somatosensory cortex, suggesting that electrical stimulation can perturb natural information processing across the neural axis.
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Affiliation(s)
- Natalija Katic Secerovic
- School of Electrical Engineering, University of Belgrade, 11000 Belgrade, Serbia; The Mihajlo Pupin Institute, University of Belgrade, 11060 Belgrade, Serbia; Laboratory for Neuroengineering, Institute for Robotics and Intelligent Systems, ETH Zürich, 8092 Zürich, Switzerland
| | - Josep-Maria Balaguer
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA; Center for Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Oleg Gorskii
- Institute of Translational Biomedicine, Saint-Petersburg State University, 199034 Saint-Petersburg, Russia; Pavlov Institute of Physiology, Russian Academy of Sciences, 199034 Saint-Petersburg, Russia; National University of Science and Technology "MISIS," 4 Leninskiy Pr., 119049 Moscow, Russia
| | - Natalia Pavlova
- Institute of Translational Biomedicine, Saint-Petersburg State University, 199034 Saint-Petersburg, Russia
| | - Lucy Liang
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA; Center for Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Jonathan Ho
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Erinn Grigsby
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Peter C Gerszten
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Dzhina Karal-Ogly
- National Research Centre "Kurchatov Institute," 123098 Moscow, Russia
| | - Dmitry Bulgin
- National Research Centre "Kurchatov Institute," 123098 Moscow, Russia; Sirius University of Science and Technology, 354340 Sochi, Russia
| | - Sergei Orlov
- National Research Centre "Kurchatov Institute," 123098 Moscow, Russia
| | - Elvira Pirondini
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA; Center for Neural Basis of Cognition, Pittsburgh, PA, USA; Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Pavel Musienko
- Institute of Translational Biomedicine, Saint-Petersburg State University, 199034 Saint-Petersburg, Russia; Sirius University of Science and Technology, 354340 Sochi, Russia; Life Improvement by Future Technologies Center "LIFT," 143025 Moscow, Russia
| | - Stanisa Raspopovic
- Laboratory for Neuroengineering, Institute for Robotics and Intelligent Systems, ETH Zürich, 8092 Zürich, Switzerland.
| | - Marco Capogrosso
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA; Center for Neural Basis of Cognition, Pittsburgh, PA, USA; Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA.
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30
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Valle G, Katic Secerovic N, Eggemann D, Gorskii O, Pavlova N, Petrini FM, Cvancara P, Stieglitz T, Musienko P, Bumbasirevic M, Raspopovic S. Biomimetic computer-to-brain communication enhancing naturalistic touch sensations via peripheral nerve stimulation. Nat Commun 2024; 15:1151. [PMID: 38378671 PMCID: PMC10879152 DOI: 10.1038/s41467-024-45190-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 01/17/2024] [Indexed: 02/22/2024] Open
Abstract
Artificial communication with the brain through peripheral nerve stimulation shows promising results in individuals with sensorimotor deficits. However, these efforts lack an intuitive and natural sensory experience. In this study, we design and test a biomimetic neurostimulation framework inspired by nature, capable of "writing" physiologically plausible information back into the peripheral nervous system. Starting from an in-silico model of mechanoreceptors, we develop biomimetic stimulation policies. We then experimentally assess them alongside mechanical touch and common linear neuromodulations. Neural responses resulting from biomimetic neuromodulation are consistently transmitted towards dorsal root ganglion and spinal cord of cats, and their spatio-temporal neural dynamics resemble those naturally induced. We implement these paradigms within the bionic device and test it with patients (ClinicalTrials.gov identifier NCT03350061). He we report that biomimetic neurostimulation improves mobility (primary outcome) and reduces mental effort (secondary outcome) compared to traditional approaches. The outcomes of this neuroscience-driven technology, inspired by the human body, may serve as a model for advancing assistive neurotechnologies.
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Affiliation(s)
- Giacomo Valle
- Laboratory for Neuroengineering, Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, Zürich, Switzerland
| | - Natalija Katic Secerovic
- Laboratory for Neuroengineering, Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, Zürich, Switzerland
- School of Electrical Engineering, University of Belgrade, 11000, Belgrade, Serbia
- The Mihajlo Pupin Institute, University of Belgrade, 11000, Belgrade, Serbia
| | - Dominic Eggemann
- Laboratory for Neuroengineering, Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, Zürich, Switzerland
| | - Oleg Gorskii
- Laboratory for Neuroprosthetics, Institute of Translational Biomedicine, Saint-Petersburg State University, Saint-Petersburg, Russia
- Laboratory for Neuromodulation, Pavlov Institute of Physiology, Russian Academy of Sciences, Saint Petersburg, 199034, Russia
- Center for Biomedical Engineering, National University of Science and Technology "MISIS", 119049, Moscow, Russia
| | - Natalia Pavlova
- Laboratory for Neuroprosthetics, Institute of Translational Biomedicine, Saint-Petersburg State University, Saint-Petersburg, Russia
| | | | - Paul Cvancara
- Laboratory for Biomedical Microtechnology, Department of Microsystems Engineering-IMTEK, Bernstein Center, BrainLinks-BrainTools Center of Excellence, University of Freiburg, D-79110, Freiburg, Germany
| | - Thomas Stieglitz
- Laboratory for Biomedical Microtechnology, Department of Microsystems Engineering-IMTEK, Bernstein Center, BrainLinks-BrainTools Center of Excellence, University of Freiburg, D-79110, Freiburg, Germany
| | - Pavel Musienko
- Laboratory for Neuroprosthetics, Institute of Translational Biomedicine, Saint-Petersburg State University, Saint-Petersburg, Russia
- Sirius University of Science and Technology, Neuroscience Program, Sirius, Russia
- Laboratory for Neurorehabilitation Technologies, Life Improvement by Future Technologies Center "LIFT", Moscow, Russia
| | - Marko Bumbasirevic
- Orthopaedic Surgery Department, School of Medicine, University of Belgrade, 11000, Belgrade, Serbia
| | - Stanisa Raspopovic
- Laboratory for Neuroengineering, Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, Zürich, Switzerland.
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31
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Kundu A, Patrick E, Currlin S, Madler R, Delgado F, Fahmy A, Verplancke R, Ballini M, Braeken D, de Beeck MO, Maghari N, Otto KJ, Bashirullah R. Using Compound Neural Action Potentials for Functional Validation of a High-Density Intraneural Interface: A Preliminary Study. MICROMACHINES 2024; 15:280. [PMID: 38399008 PMCID: PMC10891740 DOI: 10.3390/mi15020280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 02/14/2024] [Accepted: 02/15/2024] [Indexed: 02/25/2024]
Abstract
Compound nerve action potentials (CNAPs) were used as a metric to assess the stimulation performance of a novel high-density, transverse, intrafascicular electrode in rat models. We show characteristic CNAPs recorded from distally implanted cuff electrodes. Evaluation of the CNAPs as a function of stimulus current and calculation of recruitment plots were used to obtain a qualitative approximation of the neural interface's placement and orientation inside the nerve. This method avoids elaborate surgeries required for the implantation of EMG electrodes and thus minimizes surgical complications and may accelerate the healing process of the implanted subject.
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Affiliation(s)
- Aritra Kundu
- Department of Bioengineering, Imperial College London, SW7 2AZ London, UK
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, USA; (E.P.); (N.M.)
| | - Erin Patrick
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, USA; (E.P.); (N.M.)
| | - Seth Currlin
- Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA (K.J.O.)
| | - Ryan Madler
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, USA; (E.P.); (N.M.)
| | - Francisco Delgado
- Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA (K.J.O.)
| | - Ahmed Fahmy
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, USA; (E.P.); (N.M.)
| | - Rik Verplancke
- Centre for Microsystems Technology (CMST), IMEC and Ghent University, 9052 Zwijnaarde, Belgium (M.O.d.B.)
| | | | | | - Maaike Op de Beeck
- Centre for Microsystems Technology (CMST), IMEC and Ghent University, 9052 Zwijnaarde, Belgium (M.O.d.B.)
- IMEC, Kapeldreef 75, 3001 Leuven, Belgium;
| | - Nima Maghari
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, USA; (E.P.); (N.M.)
| | - Kevin J. Otto
- Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA (K.J.O.)
| | - Rizwan Bashirullah
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, USA; (E.P.); (N.M.)
- Galvani Bioelectronics, South San Francisco, CA 94080, USA
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32
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Harnoncourt L, Gstoettner C, Laengle G, Boesendorfer A, Aszmann O. [Prosthetic Fitting Concepts after Major Amputation in the Upper Limb - an Overview of Current Possibilities]. HANDCHIR MIKROCHIR P 2024; 56:84-92. [PMID: 38417811 PMCID: PMC10954373 DOI: 10.1055/a-2260-9842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 01/31/2024] [Indexed: 03/01/2024] Open
Abstract
BACKGROUND The upper extremity and particularly the hands are crucial for patients in interacting with their environment, therefore amputations or severe damage with loss of hand function significantly impact their quality of life. In cases where biological reconstruction is not feasible or does not lead to sufficient success, bionic reconstruction plays a key role in patient care. Classical myoelectric prostheses are controlled using two signals derived from surface electrodes in the area of the stump muscles. Prosthesis control, especially in high amputations, is then limited and cumbersome. The surgical technique of Targeted Muscle Reinnervation (TMR) offers an innovative solution: The major arm nerves that have lost their target organs due to amputation are rerouted to muscles in the stump area. This enables the establishment of cognitive control signals that allow significantly improved prosthesis control. PATIENTS/MATERIALS AND METHODS A selective literature review on TMR and bionic reconstruction was conducted, incorporating relevant articles and discussing them considering the clinical experience of our research group. Additionally, a clinical case is presented. RESULTS Bionic reconstruction combined with Targeted Muscle Reinnervation enables intuitive prosthetic control with simultaneous movement of various prosthetic degrees of freedom and the treatment of neuroma and phantom limb pain. Long-term success requires a high level of patient compliance and intensive signal training during the prosthetic rehabilitation phase. Despite technological advances, challenges persist, especially in enhancing signal transmission and integrating natural sensory feedback into bionic prostheses. CONCLUSION TMR surgery represents a significant advancement in the bionic care of amputees. Employing selective nerve transfers for signal multiplication and amplification, opens up possibilities for improving myoelectric prosthesis function and thus enhancing patient care. Advances in the area of external prosthetic components, improvements in the skeletal connection due to osseointegration and more fluid signal transmission using wireless, fully implanted electrode systems will lead to significant progress in bionic reconstruction, both in terms of precision of movement and embodiment.
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Affiliation(s)
- Leopold Harnoncourt
- Klinisches Labor für Bionische Extremitätenrekonstruktion,
Universitätsklinik für Plastische, Rekonstruktive und Ästhetische Chirurgie,
Medizinische Universität Wien, Wien, Austria
| | - Clemens Gstoettner
- Klinisches Labor für Bionische Extremitätenrekonstruktion,
Universitätsklinik für Plastische, Rekonstruktive und Ästhetische Chirurgie,
Medizinische Universität Wien, Wien, Austria
- Universitätsklinik für Plastische, Rekonstruktive und Ästhetische
Chirurgie, Medizinische Universität Wien, Wien, Austria
| | - Gregor Laengle
- Klinisches Labor für Bionische Extremitätenrekonstruktion,
Universitätsklinik für Plastische, Rekonstruktive und Ästhetische Chirurgie,
Medizinische Universität Wien, Wien, Austria
- Universitätsklinik für Plastische, Rekonstruktive und Ästhetische
Chirurgie, Medizinische Universität Wien, Wien, Austria
| | - Anna Boesendorfer
- Klinisches Labor für Bionische Extremitätenrekonstruktion,
Universitätsklinik für Plastische, Rekonstruktive und Ästhetische Chirurgie,
Medizinische Universität Wien, Wien, Austria
| | - Oskar Aszmann
- Klinisches Labor für Bionische Extremitätenrekonstruktion,
Universitätsklinik für Plastische, Rekonstruktive und Ästhetische Chirurgie,
Medizinische Universität Wien, Wien, Austria
- Universitätsklinik für Plastische, Rekonstruktive und Ästhetische
Chirurgie, Medizinische Universität Wien, Wien, Austria
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33
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Tian Y, Vaskov AK, Adidharma W, Cederna PS, Kemp SW. Merging Humans and Neuroprosthetics through Regenerative Peripheral Nerve Interfaces. Semin Plast Surg 2024; 38:10-18. [PMID: 38495064 PMCID: PMC10942838 DOI: 10.1055/s-0044-1779028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Limb amputations can be devastating and significantly affect an individual's independence, leading to functional and psychosocial challenges in nearly 2 million people in the United States alone. Over the past decade, robotic devices driven by neural signals such as neuroprostheses have shown great potential to restore the lost function of limbs, allowing amputees to regain movement and sensation. However, current neuroprosthetic interfaces have challenges in both signal quality and long-term stability. To overcome these limitations and work toward creating bionic limbs, the Neuromuscular Laboratory at University of Michigan Plastic Surgery has developed the Regenerative Peripheral Nerve Interface (RPNI). This surgical construct embeds a transected peripheral nerve into a free muscle graft, effectively amplifying small peripheral nerve signals to provide enhanced control signals for a neuroprosthetic limb. Furthermore, the RPNI has the potential to provide sensory feedback to the user and facilitate neuroprosthesis embodiment. This review focuses on the animal studies and clinical trials of the RPNI to recapitulate the promising trajectory toward neurobionics where the boundary between an artificial device and the human body becomes indistinct. This paper also sheds light on the prospects of the improvement and dissemination of the RPNI technology.
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Affiliation(s)
- Yucheng Tian
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
| | - Alex K. Vaskov
- Section of Plastic Surgery, Department of Surgery, University of Michigan, Ann Arbor, Michigan
| | - Widya Adidharma
- Section of Plastic Surgery, Department of Surgery, University of Michigan, Ann Arbor, Michigan
| | - Paul S. Cederna
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
- Section of Plastic Surgery, Department of Surgery, University of Michigan, Ann Arbor, Michigan
| | - Stephen W.P. Kemp
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
- Section of Plastic Surgery, Department of Surgery, University of Michigan, Ann Arbor, Michigan
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34
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Taghlabi KM, Cruz-Garza JG, Hassan T, Potnis O, Bhenderu LS, Guerrero JR, Whitehead RE, Wu Y, Luan L, Xie C, Robinson JT, Faraji AH. Clinical outcomes of peripheral nerve interfaces for rehabilitation in paralysis and amputation: a literature review. J Neural Eng 2024; 21:011001. [PMID: 38237175 DOI: 10.1088/1741-2552/ad200f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 01/18/2024] [Indexed: 02/02/2024]
Abstract
Peripheral nerve interfaces (PNIs) are electrical systems designed to integrate with peripheral nerves in patients, such as following central nervous system (CNS) injuries to augment or replace CNS control and restore function. We review the literature for clinical trials and studies containing clinical outcome measures to explore the utility of human applications of PNIs. We discuss the various types of electrodes currently used for PNI systems and their functionalities and limitations. We discuss important design characteristics of PNI systems, including biocompatibility, resolution and specificity, efficacy, and longevity, to highlight their importance in the current and future development of PNIs. The clinical outcomes of PNI systems are also discussed. Finally, we review relevant PNI clinical trials that were conducted, up to the present date, to restore the sensory and motor function of upper or lower limbs in amputees, spinal cord injury patients, or intact individuals and describe their significant findings. This review highlights the current progress in the field of PNIs and serves as a foundation for future development and application of PNI systems.
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Affiliation(s)
- Khaled M Taghlabi
- Department of Neurological Surgery, Houston Methodist Hospital, Houston, TX 77030, United States of America
- Center for Neural Systems Restoration, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Clinical Innovations Laboratory, Houston Methodist Research Institute, Houston, TX 77030, United States of America
| | - Jesus G Cruz-Garza
- Department of Neurological Surgery, Houston Methodist Hospital, Houston, TX 77030, United States of America
- Center for Neural Systems Restoration, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Clinical Innovations Laboratory, Houston Methodist Research Institute, Houston, TX 77030, United States of America
| | - Taimur Hassan
- Department of Neurological Surgery, Houston Methodist Hospital, Houston, TX 77030, United States of America
- Center for Neural Systems Restoration, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Clinical Innovations Laboratory, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- School of Medicine, Texas A&M University, Bryan, TX 77807, United States of America
| | - Ojas Potnis
- Department of Neurological Surgery, Houston Methodist Hospital, Houston, TX 77030, United States of America
- Center for Neural Systems Restoration, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Clinical Innovations Laboratory, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- School of Engineering Medicine, Texas A&M University, Houston, TX 77030, United States of America
| | - Lokeshwar S Bhenderu
- Department of Neurological Surgery, Houston Methodist Hospital, Houston, TX 77030, United States of America
- Center for Neural Systems Restoration, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Clinical Innovations Laboratory, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- School of Medicine, Texas A&M University, Bryan, TX 77807, United States of America
| | - Jaime R Guerrero
- Department of Neurological Surgery, Houston Methodist Hospital, Houston, TX 77030, United States of America
- Center for Neural Systems Restoration, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Clinical Innovations Laboratory, Houston Methodist Research Institute, Houston, TX 77030, United States of America
| | - Rachael E Whitehead
- Department of Academic Affairs, Houston Methodist Academic Institute, Houston, TX 77030, United States of America
| | - Yu Wu
- Rice Neuroengineering Initiative, Rice University, Houston, TX 77005, United States of America
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, United States of America
| | - Lan Luan
- Rice Neuroengineering Initiative, Rice University, Houston, TX 77005, United States of America
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, United States of America
| | - Chong Xie
- Rice Neuroengineering Initiative, Rice University, Houston, TX 77005, United States of America
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, United States of America
| | - Jacob T Robinson
- Rice Neuroengineering Initiative, Rice University, Houston, TX 77005, United States of America
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, United States of America
| | - Amir H Faraji
- Department of Neurological Surgery, Houston Methodist Hospital, Houston, TX 77030, United States of America
- Center for Neural Systems Restoration, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Clinical Innovations Laboratory, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Rice Neuroengineering Initiative, Rice University, Houston, TX 77005, United States of America
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, United States of America
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35
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Sparling T, Iyer L, Pasquina P, Petrus E. Cortical Reorganization after Limb Loss: Bridging the Gap between Basic Science and Clinical Recovery. J Neurosci 2024; 44:e1051232024. [PMID: 38171645 PMCID: PMC10851691 DOI: 10.1523/jneurosci.1051-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 08/28/2023] [Accepted: 09/29/2023] [Indexed: 01/05/2024] Open
Abstract
Despite the increasing incidence and prevalence of amputation across the globe, individuals with acquired limb loss continue to struggle with functional recovery and chronic pain. A more complete understanding of the motor and sensory remodeling of the peripheral and central nervous system that occurs postamputation may help advance clinical interventions to improve the quality of life for individuals with acquired limb loss. The purpose of this article is to first provide background clinical context on individuals with acquired limb loss and then to provide a comprehensive review of the known motor and sensory neural adaptations from both animal models and human clinical trials. Finally, the article bridges the gap between basic science researchers and clinicians that treat individuals with limb loss by explaining how current clinical treatments may restore function and modulate phantom limb pain using the underlying neural adaptations described above. This review should encourage the further development of novel treatments with known neurological targets to improve the recovery of individuals postamputation.Significance Statement In the United States, 1.6 million people live with limb loss; this number is expected to more than double by 2050. Improved surgical procedures enhance recovery, and new prosthetics and neural interfaces can replace missing limbs with those that communicate bidirectionally with the brain. These advances have been fairly successful, but still most patients experience persistent problems like phantom limb pain, and others discontinue prostheses instead of learning to use them daily. These problematic patient outcomes may be due in part to the lack of consensus among basic and clinical researchers regarding the plasticity mechanisms that occur in the brain after amputation injuries. Here we review results from clinical and animal model studies to bridge this clinical-basic science gap.
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Affiliation(s)
- Tawnee Sparling
- Department of Physical Medicine and Rehabilitation, Uniformed Services University of the Health Sciences, Bethesda, Maryland 20814
| | - Laxmi Iyer
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, Maryland 20817
| | - Paul Pasquina
- Department of Physical Medicine and Rehabilitation, Uniformed Services University of the Health Sciences, Bethesda, Maryland 20814
| | - Emily Petrus
- Department of Anatomy, Physiology and Genetics, Uniformed Services University, Bethesda, Maryland 20814
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36
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Andreis FR, Metcalfe B, Janjua TAM, Fazan VPS, Jensen W, Meijs S, Nielsen TGNDS. Morphology and morphometry of the ulnar nerve in the forelimb of pigs. Anat Histol Embryol 2024; 53:e12972. [PMID: 37715494 DOI: 10.1111/ahe.12972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 08/24/2023] [Accepted: 09/09/2023] [Indexed: 09/17/2023]
Abstract
The knowledge of the morphology and morphometry of peripheral nerves is essential for developing neural interfaces and understanding nerve regeneration in basic and applied research. Currently, the most adopted animal model is the rat, even though recent studies have suggested that the neuroanatomy of large animal models is more comparable to humans. The present knowledge of the morphological structure of large animal models is limited; therefore, the present study aims to describe the morphological characteristics of the Ulnar Nerve (UN) in pigs. UN cross-sections were taken from seven Danish landrace pigs at three distinct locations: distal UN, proximal UN and at the dorsal cutaneous branch of the UN (DCBUN). The nerve diameter, fascicle diameter and number, number of fibres and fibre size were quantified. The UN diameter was larger in the proximal section compared to the distal segment and the DCBUN. The proximal branch also had a more significant number of fascicles (median: 15) than the distal (median: 10) and the DCBUN (median: 11) segments. Additionally, the mean fascicle diameter was smaller at the DCBUN (mean: 165 μm) than at the distal (mean: 197 μm) and proximal (mean: 199 μm) segments of the UN. Detailed knowledge of the microscopical structure of the UN in pigs is critical for further studies investigating neural interface designs and computational models of the peripheral nervous system.
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Affiliation(s)
- Felipe Rettore Andreis
- Department of Health Science and Technology, Center for Neuroplasticity and Pain (CNAP), Aalborg University, Aalborg, Denmark
| | - Benjamin Metcalfe
- Bath Institute for the Augmented Human, University of Bath, Bath, UK
| | - Taha Al Muhammadee Janjua
- Department of Health Science and Technology, Center for Neuroplasticity and Pain (CNAP), Aalborg University, Aalborg, Denmark
| | - Valéria Paula Sassoli Fazan
- Department of Surgery and Anatomy, School of Medicine of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | - Winnie Jensen
- Department of Health Science and Technology, Center for Neuroplasticity and Pain (CNAP), Aalborg University, Aalborg, Denmark
| | - Suzan Meijs
- Department of Health Science and Technology, Center for Neuroplasticity and Pain (CNAP), Aalborg University, Aalborg, Denmark
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37
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Abstract
Efforts to design devices emulating complex cognitive abilities and response processes of biological systems have long been a coveted goal. Recent advancements in flexible electronics, mirroring human tissue's mechanical properties, hold significant promise. Artificial neuron devices, hinging on flexible artificial synapses, bioinspired sensors, and actuators, are meticulously engineered to mimic the biological systems. However, this field is in its infancy, requiring substantial groundwork to achieve autonomous systems with intelligent feedback, adaptability, and tangible problem-solving capabilities. This review provides a comprehensive overview of recent advancements in artificial neuron devices. It starts with fundamental principles of artificial synaptic devices and explores artificial sensory systems, integrating artificial synapses and bioinspired sensors to replicate all five human senses. A systematic presentation of artificial nervous systems follows, designed to emulate fundamental human nervous system functions. The review also discusses potential applications and outlines existing challenges, offering insights into future prospects. We aim for this review to illuminate the burgeoning field of artificial neuron devices, inspiring further innovation in this captivating area of research.
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Affiliation(s)
- Ke He
- Innovative Centre for Flexible Devices (iFLEX), Max Planck-NTU Joint Lab for Artificial Senses, School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
| | - Cong Wang
- Innovative Centre for Flexible Devices (iFLEX), Max Planck-NTU Joint Lab for Artificial Senses, School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
| | - Yongli He
- Innovative Centre for Flexible Devices (iFLEX), Max Planck-NTU Joint Lab for Artificial Senses, School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
| | - Jiangtao Su
- Innovative Centre for Flexible Devices (iFLEX), Max Planck-NTU Joint Lab for Artificial Senses, School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
| | - Xiaodong Chen
- Innovative Centre for Flexible Devices (iFLEX), Max Planck-NTU Joint Lab for Artificial Senses, School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
- Institute for Digital Molecular Analytics and Science (IDMxS), Nanyang Technological University, 59 Nanyang Drive, Singapore 636921, Singapore
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Zhang J, Chou CH, Hao M, Li Y, Yu Y, Lan N. Fusion of dual modalities of non-invasive sensory feedback for object profiling with prosthetic hands. Front Neurorobot 2023; 17:1298176. [PMID: 38162892 PMCID: PMC10757719 DOI: 10.3389/fnbot.2023.1298176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 11/24/2023] [Indexed: 01/03/2024] Open
Abstract
Introduction Either non-invasive somatotopic or substitute sensory feedback is capable of conveying a single modality of sensory information from prosthetic hands to amputees. However, the neurocognitive ability of amputees to integrate multi-modality sensory information for functional discrimination is unclear. The purpose of this study was to assess the fusion of non-invasive somatotopic tactile and substitute aperture feedbacks for profile perception of multiple physical features during grasping objects. Methods Two left transradial amputees with somatotopic evoked tactile sensation (ETS) of five fingers participated in the study. The tactile information of prosthetic hand was provided to amputees by the ETS feedback elicited on the stump projected finger map. Hand aperture information was conveyed to amputees with substitute electrotactile stimulation on the forearm or upper arm. Two types of sensory feedback were integrated to a commercial prosthetic hand. The efficacy of somatotopic ETS feedback on object length identification task was assessed with or without substitute aperture stimulation. The object size identification task was utilized to assess how ETS stimulation at the stump may affect aperture perception with stimulation on the ipsilateral upper arm or forearm. Finally, the task of identifying combined length and size was conducted to evaluate the ability of amputees to integrate the dual modalities of sensory feedback for perceiving profile features. Results The study revealed that amputee subjects can effectively integrate the ETS feedback with electrotactile substitutive feedback for object profile discrimination. Specifically, ETS was robust to provide object length information with electrotactile stimulation at either the forearm or upper arm. However, electrotactile stimulation at the upper arm for aperture perception was less susceptible to the interference of ETS stimulation than at the forearm. Discussion Amputee subjects are able to combine somatotopic ETS and aperture feedbacks for identifying multi-dimensional features in object profiling. The two sensory streams of information can be fused effectively without mutual interference for functional discrimination.
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Affiliation(s)
- Jie Zhang
- Laboratory of NeuroRehabilitation Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Chih-Hong Chou
- Laboratory of NeuroRehabilitation Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
- Institute of Medical Robotics, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Manzhao Hao
- Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yan Li
- Laboratory of NeuroRehabilitation Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yashuo Yu
- Laboratory of NeuroRehabilitation Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Ning Lan
- Laboratory of NeuroRehabilitation Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
- Institute of Medical Robotics, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
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Fisher LE, Gaunt RA, Huang H. Sensory Restoration for Improved Motor Control of Prostheses. CURRENT OPINION IN BIOMEDICAL ENGINEERING 2023; 28:100498. [PMID: 37860289 PMCID: PMC10583965 DOI: 10.1016/j.cobme.2023.100498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2023]
Abstract
Somatosensory neuroprostheses are devices with the potential to restore the senses of touch and movement from prosthetic limbs for people with limb amputation or paralysis. By electrically stimulating the peripheral or central nervous system, these devices evoke sensations that appear to emanate from the missing or insensate limb, and when paired with sensors on the prosthesis, they can improve the functionality and embodiment of the prosthesis. There have been major advances in the design of these systems over the past decade, although several important steps remain before they can achieve widespread clinical adoption outside the lab setting. Here, we provide a brief overview of somatosensory neuroprostheses and explores these hurdles and potential next steps towards clinical translation.
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Affiliation(s)
- Lee E. Fisher
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA 15213, USA
- Department of Physical Medicine & Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA
- Center for Neural Basis of Cognition, Pittsburgh, PA 15213, USA
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Robert A. Gaunt
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA 15213, USA
- Department of Physical Medicine & Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA
- Center for Neural Basis of Cognition, Pittsburgh, PA 15213, USA
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - He Huang
- UNC/NC State Joint Department of Biomedical Engineering, North Carolina State University, Raleigh, NC 27695, USA
- UNC/NC State Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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40
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Sarwar MS, Ishizaki R, Morton K, Preston C, Nguyen T, Fan X, Dupont B, Hogarth L, Yoshiike T, Qiu R, Wu Y, Mirabbasi S, Madden JDW. Touch, press and stroke: a soft capacitive sensor skin. Sci Rep 2023; 13:17390. [PMID: 37880294 PMCID: PMC10600100 DOI: 10.1038/s41598-023-43714-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 09/26/2023] [Indexed: 10/27/2023] Open
Abstract
Soft sensors that can discriminate shear and normal force could help provide machines the fine control desirable for safe and effective physical interactions with people. A capacitive sensor is made for this purpose, composed of patterned elastomer and containing both fixed and sliding pillars that allow the sensor to deform and buckle, much like skin itself. The sensor differentiates between simultaneously applied normal force and shear using summation and differences of signals from four deformable capacitors. Cross talk from shear to normal force is less than 2.5%, and between shear axes is less than 10%. Normal and shear stress sensitivity is 0.49 kPa and 0.31 kPa respectively, with a minimum displacement resolution of 40 μm. In addition, finger proximity is detectable at a range of up to 15 mm. The operation is demonstrated on a simple gripper holding a cup. The combination of features and the straightforward fabrication method make this sensor a candidate for implementation as a sensing skin for humanoid robotics applications.
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Affiliation(s)
- Mirza S Sarwar
- Electrical and Computer Engineering, Advanced Materials and Process Engineering Laboratory, University of British Columbia, Vancouver, V6T 1Z4, Canada.
| | - Ryusuke Ishizaki
- Frontier Robotics, Innovative Research Excellence, Honda R&D Co., Ltd, 8-1 Honcho, Wako-shi, Saitama, 351-0188, Japan
| | - Kieran Morton
- Electrical and Computer Engineering, Advanced Materials and Process Engineering Laboratory, University of British Columbia, Vancouver, V6T 1Z4, Canada
| | - Claire Preston
- Electrical and Computer Engineering, Advanced Materials and Process Engineering Laboratory, University of British Columbia, Vancouver, V6T 1Z4, Canada
| | - Tan Nguyen
- Electrical and Computer Engineering, Advanced Materials and Process Engineering Laboratory, University of British Columbia, Vancouver, V6T 1Z4, Canada
| | - Xu Fan
- Electrical and Computer Engineering, Advanced Materials and Process Engineering Laboratory, University of British Columbia, Vancouver, V6T 1Z4, Canada
| | - Bertille Dupont
- Electrical and Computer Engineering, Advanced Materials and Process Engineering Laboratory, University of British Columbia, Vancouver, V6T 1Z4, Canada
| | - Leanna Hogarth
- Electrical and Computer Engineering, Advanced Materials and Process Engineering Laboratory, University of British Columbia, Vancouver, V6T 1Z4, Canada
| | - Takahide Yoshiike
- Frontier Robotics, Innovative Research Excellence, Honda R&D Co., Ltd, 8-1 Honcho, Wako-shi, Saitama, 351-0188, Japan
| | - Ruixin Qiu
- Electrical and Computer Engineering, Advanced Materials and Process Engineering Laboratory, University of British Columbia, Vancouver, V6T 1Z4, Canada
| | - Yiting Wu
- Electrical and Computer Engineering, Advanced Materials and Process Engineering Laboratory, University of British Columbia, Vancouver, V6T 1Z4, Canada
| | - Shahriar Mirabbasi
- Electrical and Computer Engineering, Advanced Materials and Process Engineering Laboratory, University of British Columbia, Vancouver, V6T 1Z4, Canada
| | - John D W Madden
- Electrical and Computer Engineering, Advanced Materials and Process Engineering Laboratory, University of British Columbia, Vancouver, V6T 1Z4, Canada.
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41
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Chen F, Wang F, Dong Y, Yong Q, Yang X, Zheng L, Gao Y, Su H. Sensor Fusion-Based Anthropomorphic Control of a Robotic Arm. Bioengineering (Basel) 2023; 10:1243. [PMID: 38002367 PMCID: PMC10669049 DOI: 10.3390/bioengineering10111243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 10/12/2023] [Accepted: 10/20/2023] [Indexed: 11/26/2023] Open
Abstract
The main goal of this research is to develop a highly advanced anthropomorphic control system utilizing multiple sensor technologies to achieve precise control of a robotic arm. Combining Kinect and IMU sensors, together with a data glove, we aim to create a multimodal sensor system for capturing rich information of human upper body movements. Specifically, the four angles of upper limb joints are collected using the Kinect sensor and IMU sensor. In order to improve the accuracy and stability of motion tracking, we use the Kalman filter method to fuse the Kinect and IMU data. In addition, we introduce data glove technology to collect the angle information of the wrist and fingers in seven different directions. The integration and fusion of multiple sensors provides us with full control over the robotic arm, giving it flexibility with 11 degrees of freedom. We successfully achieved a variety of anthropomorphic movements, including shoulder flexion, abduction, rotation, elbow flexion, and fine movements of the wrist and fingers. Most importantly, our experimental results demonstrate that the anthropomorphic control system we developed is highly accurate, real-time, and operable. In summary, the contribution of this study lies in the creation of a multimodal sensor system capable of capturing and precisely controlling human upper limb movements, which provides a solid foundation for the future development of anthropomorphic control technologies. This technology has a wide range of application prospects and can be used for rehabilitation in the medical field, robot collaboration in industrial automation, and immersive experience in virtual reality environments.
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Affiliation(s)
- Furong Chen
- Department of Mechanical Engineering, College of Mechanical and Electrical Engineering, Changchun University of Science and Technology, Changchun 130012, China; (F.C.); (F.W.)
- Key Laboratory of Bionic Engineering, Ministry of Education, Jilin University, Changchun 130022, China
- Weihai Institute for Bionics, Jilin University, Weihai 264402, China
| | - Feilong Wang
- Department of Mechanical Engineering, College of Mechanical and Electrical Engineering, Changchun University of Science and Technology, Changchun 130012, China; (F.C.); (F.W.)
- Key Laboratory of Bionic Engineering, Ministry of Education, Jilin University, Changchun 130022, China
- Weihai Institute for Bionics, Jilin University, Weihai 264402, China
| | - Yanling Dong
- School of Foreign Languages & Literature, Shandong University, Jinan 250000, China;
| | - Qi Yong
- ESIEE Paris, 2 Boulevard Blaise Pascal, 93160 Noisy-le-Grand, France;
| | - Xiaolong Yang
- Department of Mechanical Engineering, College of Mechanical and Electrical Engineering, Changchun University of Science and Technology, Changchun 130012, China; (F.C.); (F.W.)
- Key Laboratory of Bionic Engineering, Ministry of Education, Jilin University, Changchun 130022, China
- Weihai Institute for Bionics, Jilin University, Weihai 264402, China
| | - Long Zheng
- Key Laboratory of Bionic Engineering, Ministry of Education, Jilin University, Changchun 130022, China
- Weihai Institute for Bionics, Jilin University, Weihai 264402, China
| | - Yi Gao
- Department of Mechanical Engineering, College of Mechanical and Electrical Engineering, Changchun University of Science and Technology, Changchun 130012, China; (F.C.); (F.W.)
| | - Hang Su
- Weihai Institute for Bionics, Jilin University, Weihai 264402, China
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Ortiz-Catalan M, Zbinden J, Millenaar J, D'Accolti D, Controzzi M, Clemente F, Cappello L, Earley EJ, Mastinu E, Kolankowska J, Munoz-Novoa M, Jönsson S, Cipriani C, Sassu P, Brånemark R. A highly integrated bionic hand with neural control and feedback for use in daily life. Sci Robot 2023; 8:eadf7360. [PMID: 37820004 DOI: 10.1126/scirobotics.adf7360] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 09/14/2023] [Indexed: 10/13/2023]
Abstract
Restoration of sensorimotor function after amputation has remained challenging because of the lack of human-machine interfaces that provide reliable control, feedback, and attachment. Here, we present the clinical implementation of a transradial neuromusculoskeletal prosthesis-a bionic hand connected directly to the user's nervous and skeletal systems. In one person with unilateral below-elbow amputation, titanium implants were placed intramedullary in the radius and ulna bones, and electromuscular constructs were created surgically by transferring the severed nerves to free muscle grafts. The native muscles, free muscle grafts, and ulnar nerve were implanted with electrodes. Percutaneous extensions from the titanium implants provided direct skeletal attachment and bidirectional communication between the implanted electrodes and a prosthetic hand. Operation of the bionic hand in daily life resulted in improved prosthetic function, reduced postamputation, and increased quality of life. Sensations elicited via direct neural stimulation were consistently perceived on the phantom hand throughout the study. To date, the patient continues using the prosthesis in daily life. The functionality of conventional artificial limbs is hindered by discomfort and limited and unreliable control. Neuromusculoskeletal interfaces can overcome these hurdles and provide the means for the everyday use of a prosthesis with reliable neural control fixated into the skeleton.
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Affiliation(s)
- Max Ortiz-Catalan
- Center for Bionics and Pain Research, Mölndal, Sweden
- Bionics Institute, Melbourne, Australia
- Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden
- University of Melbourne, Melbourne, Australia
| | - Jan Zbinden
- Center for Bionics and Pain Research, Mölndal, Sweden
- Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | | | - Daniele D'Accolti
- Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Marco Controzzi
- Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | | | - Leonardo Cappello
- Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Eric J Earley
- Center for Bionics and Pain Research, Mölndal, Sweden
- Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden
- Osseointegration Research Consortium, University of Colorado, Aurora, CO, USA
| | - Enzo Mastinu
- Center for Bionics and Pain Research, Mölndal, Sweden
- Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden
- Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | | | - Maria Munoz-Novoa
- Center for Bionics and Pain Research, Mölndal, Sweden
- Center for Advanced Reconstruction of Extremities, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Stewe Jönsson
- TeamOlmed, Department of Upper Limb Prosthetics, Kungsbacka, Sweden
| | - Christian Cipriani
- Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Paolo Sassu
- Center for Bionics and Pain Research, Mölndal, Sweden
- Department of Hand Surgery, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Orthopaedics, IRCCS, Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Rickard Brånemark
- Integrum AB, Mölndal, Sweden
- Department of Orthopaedics, Gothenburg University, Gothenburg, Sweden
- K. Lisa Yang Center for Bionics, MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
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Baek J, Shan Y, Mylvaganan M, Zhang Y, Yang X, Qin F, Zhao K, Song HW, Mao H, Lee S. Mold-Free Manufacturing of Highly Sensitive and Fast-Response Pressure Sensors Through High-Resolution 3D Printing and Conformal Oxidative Chemical Vapor Deposition Polymers. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2304070. [PMID: 37463430 DOI: 10.1002/adma.202304070] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 07/03/2023] [Accepted: 07/13/2023] [Indexed: 07/20/2023]
Abstract
A new manufacturing paradigm is showcased to exclude conventional mold-dependent manufacturing of pressure sensors, which typically requires a series of complex and expensive patterning processes. This mold-free manufacturing leverages high-resolution 3D-printed multiscale microstructures as the substrate and a gas-phase conformal polymer coating technique to complete the mold-free sensing platform. The array of dome and spike structures with a controlled spike density of a 3D-printed substrate ensures a large contact surface with pressures applied and extended linearity in a wider pressure range. For uniform coating of sensing elements on the microstructured surface, oxidative chemical vapor deposition is employed to deposit a highly conformal and conductive sensing element, poly(3,4-ethylenedioxythiophene) at low temperatures (<60 °C). The fabricated pressure sensor reacts sensitively to various ranges of pressures (up to 185 kPa-1 ) depending on the density of the multiscale features and shows an ultrafast response time (≈36 µs). The mechanism investigations through the finite element analysis identify the effect of the multiscale structure on the figure-of-merit sensing performance. These unique findings are expected to be of significant relevance to technology that requires higher sensing capability, scalability, and facile adjustment of a sensor geometry in a cost-effective manufacturing manner.
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Affiliation(s)
- Jinwook Baek
- School of Engineering Technology, Purdue University, 401 N. Grant Street, West Lafayette, IN, 47907, USA
| | - Yujie Shan
- School of Engineering Technology, Purdue University, 401 N. Grant Street, West Lafayette, IN, 47907, USA
| | - Mitesh Mylvaganan
- School of Engineering Technology, Purdue University, 401 N. Grant Street, West Lafayette, IN, 47907, USA
| | - Yuxuan Zhang
- School of Engineering Technology, Purdue University, 401 N. Grant Street, West Lafayette, IN, 47907, USA
| | - Xixian Yang
- School of Mechanical Engineering, Purdue University, 585 Purdue Mall, West Lafayette, IN, 47907, USA
| | - Fei Qin
- School of Engineering Technology, Purdue University, 401 N. Grant Street, West Lafayette, IN, 47907, USA
| | - Kejie Zhao
- School of Mechanical Engineering, Purdue University, 585 Purdue Mall, West Lafayette, IN, 47907, USA
| | - Han Wook Song
- Center for Mass and Related Quantities, Korea Research Institute of Standards and Science (KRISS), 267 Gajeong-ro, Yuseong-gu, Daejeon, 34113, Republic of Korea
| | - Huachao Mao
- School of Engineering Technology, Purdue University, 401 N. Grant Street, West Lafayette, IN, 47907, USA
| | - Sunghwan Lee
- School of Engineering Technology, Purdue University, 401 N. Grant Street, West Lafayette, IN, 47907, USA
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Castro F, Lenggenhager B, Zeller D, Pellegrino G, D'Alonzo M, Di Pino G. From rubber hands to neuroprosthetics: Neural correlates of embodiment. Neurosci Biobehav Rev 2023; 153:105351. [PMID: 37544389 PMCID: PMC10582798 DOI: 10.1016/j.neubiorev.2023.105351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Revised: 07/10/2023] [Accepted: 08/03/2023] [Indexed: 08/08/2023]
Abstract
Our interaction with the world rests on the knowledge that we are a body in space and time, which can interact with the environment. This awareness is usually referred to as sense of embodiment. For the good part of the past 30 years, the rubber hand illusion (RHI) has been a prime tool to study embodiment in healthy and people with a variety of clinical conditions. In this paper, we provide a critical overview of this research with a focus on the RHI paradigm as a tool to study prothesis embodiment in individuals with amputation. The RHI relies on well-documented multisensory integration mechanisms based on sensory precision, where parietal areas are involved in resolving the visuo-tactile conflict, and premotor areas in updating the conscious bodily representation. This mechanism may be transferable to prosthesis ownership in amputees. We discuss how these results might transfer to technological development of sensorised prostheses, which in turn might progress the acceptability by users.
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Affiliation(s)
- Fabio Castro
- Neurophysiology and Neuroengineering of Human-Technology Interaction Research Unit, Campus Bio-Medico University, via Alvaro del Portillo 5, 00128 Rome, Italy; Institute of Sport, School of Life and Medical Sciences, University of Hertfordshire, Hatfield, United Kingdom
| | - Bigna Lenggenhager
- Department of Psychology, Cognitive Psychology, University of Konstanz, Universitätsstraße 10, 78464 Konstanz, Germany; Department of Psychology, University of Zurich, Binzmuehlestrasse 14, 8050 Zurich, Switzerland
| | - Daniel Zeller
- Department of Neurology, University Hospital Würzburg, Josef-Schneider-Str. 11, 97080 Würzburg, Germany
| | - Giovanni Pellegrino
- Epilepsy program, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Marco D'Alonzo
- Neurophysiology and Neuroengineering of Human-Technology Interaction Research Unit, Campus Bio-Medico University, via Alvaro del Portillo 5, 00128 Rome, Italy.
| | - Giovanni Di Pino
- Neurophysiology and Neuroengineering of Human-Technology Interaction Research Unit, Campus Bio-Medico University, via Alvaro del Portillo 5, 00128 Rome, Italy
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45
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Borda L, Gozzi N, Preatoni G, Valle G, Raspopovic S. Automated calibration of somatosensory stimulation using reinforcement learning. J Neuroeng Rehabil 2023; 20:131. [PMID: 37752607 PMCID: PMC10523674 DOI: 10.1186/s12984-023-01246-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 09/13/2023] [Indexed: 09/28/2023] Open
Abstract
BACKGROUND The identification of the electrical stimulation parameters for neuromodulation is a subject-specific and time-consuming procedure that presently mostly relies on the expertise of the user (e.g., clinician, experimenter, bioengineer). Since the parameters of stimulation change over time (due to displacement of electrodes, skin status, etc.), patients undergo recurrent, long calibration sessions, along with visits to the clinics, which are inefficient and expensive. To address this issue, we developed an automatized calibration system based on reinforcement learning (RL) allowing for accurate and efficient identification of the peripheral nerve stimulation parameters for somatosensory neuroprostheses. METHODS We developed an RL algorithm to automatically select neurostimulation parameters for restoring sensory feedback with transcutaneous electrical nerve stimulation (TENS). First, the algorithm was trained offline on a dataset comprising 49 subjects. Then, the neurostimulation was then integrated with a graphical user interface (GUI) to create an intuitive AI-based mapping platform enabling the user to autonomously perform the sensation characterization procedure. We assessed the algorithm against the performance of both experienced and naïve and of a brute force algorithm (BFA), on 15 nerves from five subjects. Then, we validated the AI-based platform on six neuropathic nerves affected by distal sensory loss. RESULTS Our automatized approach demonstrated the ability to find the optimal values of neurostimulation achieving reliable and comfortable elicited sensations. When compared to alternatives, RL outperformed the naïve and BFA, significantly decreasing the time for mapping and the number of delivered stimulation trains, while improving the overall quality. Furthermore, the RL algorithm showed performance comparable to trained experimenters. Finally, we exploited it successfully for eliciting sensory feedback in neuropathic patients. CONCLUSIONS Our findings demonstrated that the AI-based platform based on a RL algorithm can automatically and efficiently calibrate parameters for somatosensory nerve stimulation. This holds promise to avoid experts' employment in similar scenarios, thanks to the merging between AI and neurotech. Our RL algorithm has the potential to be used in other neuromodulation fields requiring a mapping process of the stimulation parameters. TRIAL REGISTRATION ClinicalTrial.gov (Identifier: NCT04217005).
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Affiliation(s)
- Luigi Borda
- Laboratory for Neuroengineering, Department of Health Science and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, 8092, Zurich, Switzerland
| | - Noemi Gozzi
- Laboratory for Neuroengineering, Department of Health Science and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, 8092, Zurich, Switzerland
| | - Greta Preatoni
- Laboratory for Neuroengineering, Department of Health Science and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, 8092, Zurich, Switzerland
| | - Giacomo Valle
- Laboratory for Neuroengineering, Department of Health Science and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, 8092, Zurich, Switzerland
| | - Stanisa Raspopovic
- Laboratory for Neuroengineering, Department of Health Science and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, 8092, Zurich, Switzerland.
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46
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Papaleo ED, D'Alonzo M, Fiori F, Piombino V, Falato E, Pilato F, De Liso A, Di Lazzaro V, Di Pino G. Integration of proprioception in upper limb prostheses through non-invasive strategies: a review. J Neuroeng Rehabil 2023; 20:118. [PMID: 37689701 PMCID: PMC10493033 DOI: 10.1186/s12984-023-01242-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 08/24/2023] [Indexed: 09/11/2023] Open
Abstract
Proprioception plays a key role in moving our body dexterously and effortlessly. Nevertheless, the majority of investigations evaluating the benefits of providing supplemental feedback to prosthetics users focus on delivering touch restitution. These studies evaluate the influence of touch sensation in an attempt to improve the controllability of current robotic devices. Contrarily, investigations evaluating the capabilities of proprioceptive supplemental feedback have yet to be comprehensively analyzed to the same extent, marking a major gap in knowledge within the current research climate. The non-invasive strategies employed so far to restitute proprioception are reviewed in this work. In the absence of a clearly superior strategy, approaches employing vibrotactile, electrotactile and skin-stretch stimulation achieved better and more consistent results, considering both kinesthetic and grip force information, compared with other strategies or any incidental feedback. Although emulating the richness of the physiological sensory return through artificial feedback is the primary hurdle, measuring its effects to eventually support the integration of cumbersome and energy intensive hardware into commercial prosthetic devices could represent an even greater challenge. Thus, we analyze the strengths and limitations of previous studies and discuss the possible benefits of coupling objective measures, like neurophysiological parameters, as well as measures of prosthesis embodiment and cognitive load with behavioral measures of performance. Such insights aim to provide additional and collateral outcomes to be considered in the experimental design of future investigations of proprioception restitution that could, in the end, allow researchers to gain a more detailed understanding of possibly similar behavioral results and, thus, support one strategy over another.
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Affiliation(s)
- Ermanno Donato Papaleo
- Research Unit of Neurophysiology and Neuroengineering of Human-Technology Interaction (NeXTlab), Università Campus Bio-Medico Di Roma, Via Álvaro Del Portillo 21, 00128, Rome, Italy
| | - Marco D'Alonzo
- Research Unit of Neurophysiology and Neuroengineering of Human-Technology Interaction (NeXTlab), Università Campus Bio-Medico Di Roma, Via Álvaro Del Portillo 21, 00128, Rome, Italy
| | - Francesca Fiori
- Research Unit of Neurophysiology and Neuroengineering of Human-Technology Interaction (NeXTlab), Università Campus Bio-Medico Di Roma, Via Álvaro Del Portillo 21, 00128, Rome, Italy
| | - Valeria Piombino
- Research Unit of Neurophysiology and Neuroengineering of Human-Technology Interaction (NeXTlab), Università Campus Bio-Medico Di Roma, Via Álvaro Del Portillo 21, 00128, Rome, Italy
| | - Emma Falato
- Research Unit of Neurology, Department of Medicine and Surgery, Università Campus Bio-Medico Di Roma, Via Alvaro del Portillo, 21, 00128, Rome, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo 200, 00128, Rome, Italy
| | - Fabio Pilato
- Research Unit of Neurology, Department of Medicine and Surgery, Università Campus Bio-Medico Di Roma, Via Alvaro del Portillo, 21, 00128, Rome, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo 200, 00128, Rome, Italy
| | - Alfredo De Liso
- Research Unit of Neurology, Department of Medicine and Surgery, Università Campus Bio-Medico Di Roma, Via Alvaro del Portillo, 21, 00128, Rome, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo 200, 00128, Rome, Italy
| | - Vincenzo Di Lazzaro
- Research Unit of Neurology, Department of Medicine and Surgery, Università Campus Bio-Medico Di Roma, Via Alvaro del Portillo, 21, 00128, Rome, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo 200, 00128, Rome, Italy
| | - Giovanni Di Pino
- Research Unit of Neurophysiology and Neuroengineering of Human-Technology Interaction (NeXTlab), Università Campus Bio-Medico Di Roma, Via Álvaro Del Portillo 21, 00128, Rome, Italy.
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Ritter C, Geisler M, Blume KR, Nehrdich S, Hofmann GO, Koehler H, Miltner WHR, Weiss T. Stimulation of peroneal nerves reveals maintained somatosensory representation in transtibial amputees. Front Hum Neurosci 2023; 17:1240937. [PMID: 37746055 PMCID: PMC10512738 DOI: 10.3389/fnhum.2023.1240937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 08/18/2023] [Indexed: 09/26/2023] Open
Abstract
Introduction Several studies have found changes in the organization of the primary somatosensory cortex (SI) after amputation. This SI reorganization was mainly investigated by stimulating neighboring areas to amputation. Unexpectedly, the somatosensory representation of the deafferented limb has rarely been directly tested. Methods We stimulated the truncated peroneal nerve in 24 unilateral transtibial amputees and 15 healthy controls. The stimulation intensity was adjusted to make the elicited percept comparable between both stimulation sides. Neural sources of the somatosensory-evoked magnetic fields (SEFs) to peroneal stimulation were localized in the contralateral foot/leg areas of SI in 19 patients and 14 healthy controls. Results We demonstrated the activation of functionally preserved cortical representations of amputated lower limbs. None of the patients reported evoked phantom limb pain (PLP) during stimulation. Stimulation that evoked perceptions in the foot required stronger intensities on the amputated side than on the intact side. In addition to this, stronger stimulation intensities were required for amputees than for healthy controls. Exploratorily, PLP intensity was neither associated with stimulation intensity nor dipole strength nor with differences in Euclidean distances (between SEF sources of the healthy peroneus and mirrored SEF sources of the truncated peroneus). Discussion Our results provide hope that the truncated nerve may be used to establish both motor control and somatosensory feedback via the nerve trunk when a permanently functional connection between the nerve trunk and the prosthesis becomes available.
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Affiliation(s)
- Caroline Ritter
- Department of Clinical Psychology, Institute of Psychology, Friedrich Schiller University Jena, Jena, Germany
- Clinic for Psychosomatics and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Maria Geisler
- Department of Clinical Psychology, Institute of Psychology, Friedrich Schiller University Jena, Jena, Germany
- Clinic for Psychosomatics and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Kathrin R. Blume
- Department of Clinical Psychology, Institute of Psychology, Friedrich Schiller University Jena, Jena, Germany
- Institute of Psychosocial Medicine, Psychotherapy and Psychooncology, Jena University Hospital, Jena, Germany
| | - Sandra Nehrdich
- Department of Clinical Psychology, Institute of Psychology, Friedrich Schiller University Jena, Jena, Germany
- Clinic for Psychosomatics and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Gunther O. Hofmann
- Berufsgenossenschaftliche Kliniken Bergmannstrost Halle/Saale, Halle, Germany
- Department of Trauma, Hand and Reconstructive Surgery, University Hospital Jena, Jena, Germany
| | - Hanna Koehler
- Department of Clinical Psychology, Institute of Psychology, Friedrich Schiller University Jena, Jena, Germany
- Biomagnetic Center, Department of Neurology, University Hospital Jena, Jena, Germany
| | - Wolfgang H. R. Miltner
- Department of Clinical Psychology, Institute of Psychology, Friedrich Schiller University Jena, Jena, Germany
| | - Thomas Weiss
- Department of Clinical Psychology, Institute of Psychology, Friedrich Schiller University Jena, Jena, Germany
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Xie Y, Qin P, Guo T, Al Abed A, Lovell NH, Tsai D. Modulating individual axons and axonal populations in the peripheral nerve using transverse intrafascicular multichannel electrodes. J Neural Eng 2023; 20:046032. [PMID: 37536318 DOI: 10.1088/1741-2552/aced20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 08/03/2023] [Indexed: 08/05/2023]
Abstract
Objective.A transverse intrafascicular multichannel electrode (TIME) may offer advantages over more conventional cuff electrodes including higher spatial selectivity and reduced stimulation charge requirements. However, the performance of TIME, especially in the context of non-conventional stimulation waveforms, remains relatively unexplored. As part of our overarching goal of investigating stimulation efficacy of TIME, we developed a computational toolkit that automates the creation and usage ofin siliconerve models with TIME setup, which solves nerve responses using cable equations and computes extracellular potentials using finite element method.Approach.We began by implementing a flexible and scalable Python/MATLAB-based toolkit for automatically creating models of nerve stimulation in the hybrid NEURON/COMSOL ecosystems. We then developed a sciatic nerve model containing 14 fascicles with 1,170 myelinated (A-type, 30%) and unmyelinated (C-type, 70%) fibers to study fiber responses over a variety of TIME arrangements (monopolar and hexapolar) and stimulation waveforms (kilohertz stimulation and cathodic ramp modulation).Main results.Our toolkit obviates the conventional need to re-create the same nerve in two disparate modeling environments and automates bi-directional transfer of results. Our population-based simulations suggested that kilohertz stimuli provide selective activation of targeted C fibers near the stimulating electrodes but also tended to activate non-targeted A fibers further away. However, C fiber selectivity can be enhanced by hexapolar TIME arrangements that confined the spatial extent of electrical stimuli. Improved upon prior findings, we devised a high-frequency waveform that incorporates cathodic DC ramp to completely remove undesirable onset responses.Conclusion.Our toolkit allows agile, iterative design cycles involving the nerve and TIME, while minimizing the potential operator errors during complex simulation. The nerve model created by our toolkit allowed us to study and optimize the design of next-generation intrafascicular implants for improved spatial and fiber-type selectivity.
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Affiliation(s)
- Yuyang Xie
- Graduate School of Biomedical Engineering, UNSW Sydney, NSW 2052, Australia
| | - Peijun Qin
- Graduate School of Biomedical Engineering, UNSW Sydney, NSW 2052, Australia
| | - Tianruo Guo
- Graduate School of Biomedical Engineering, UNSW Sydney, NSW 2052, Australia
| | - Amr Al Abed
- Graduate School of Biomedical Engineering, UNSW Sydney, NSW 2052, Australia
| | - Nigel H Lovell
- Graduate School of Biomedical Engineering, UNSW Sydney, NSW 2052, Australia
- Tyree Institute of Health Engineering (IHealthE), UNSW Sydney, NSW 2052, Australia
| | - David Tsai
- Graduate School of Biomedical Engineering, UNSW Sydney, NSW 2052, Australia
- School of Electrical Engineering & Telecommunications, UNSW Sydney, NSW 2052, Australia
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49
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Capsi-Morales P, Piazza C, Sjoberg L, Catalano MG, Grioli G, Bicchi A, Hermansson LM. Functional assessment of current upper limb prostheses: An integrated clinical and technological perspective. PLoS One 2023; 18:e0289978. [PMID: 37585427 PMCID: PMC10431634 DOI: 10.1371/journal.pone.0289978] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Accepted: 07/31/2023] [Indexed: 08/18/2023] Open
Abstract
Although recent technological developments in the field of bionic upper limb prostheses, their rejection rate remains excessively high. The reasons are diverse (e.g. lack of functionality, control complexity, and comfortability) and most of these are reported only through self-rated questionnaires. Indeed, there is no quantitative evaluation of the extent to which a novel prosthetic solution can effectively address users' needs compared to other technologies. This manuscript discusses the challenges and limitations of current upper limb prosthetic devices and evaluates their functionality through a standard functional assessment, the Assessment of Capacity for Myoelectric Control (ACMC). To include a good representation of technologies, the authors collect information from participants in the Cybathlon Powered Arm Prostheses Race 2016 and 2020. The article analyzes 7 hour and 41 min of video footage to evaluate the performance of different prosthetic devices in various tasks inspired by activities of daily living (ADL). The results show that commercially-available rigid hands perform well in dexterous grasping, while body-powered solutions are more reliable and convenient for competitive environments. The article also highlights the importance of wrist design and control modality for successful execution of ADL. Moreover, we discuss the limitations of the evaluation methodology and suggest improvements for future assessments. With regard to future development, this work highlights the need for research in intuitive control of multiple degrees of freedom, adaptive solutions, and the integration of sensory feedback.
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Affiliation(s)
- Patricia Capsi-Morales
- School of Computation, Information and Technology, Technische Universität München, Garching, Germany
| | - Cristina Piazza
- School of Computation, Information and Technology, Technische Universität München, Garching, Germany
| | - Lis Sjoberg
- School of Health Sciences, Örebro University, Örebro, Swede
| | | | - Giorgio Grioli
- Instituto Italiano di Tecnologia, Genoa, Italy
- Centro "E. Piaggio" and Dipartimento di Ingegneria dell'Informazione, University of Pisa, Pisa, Italy
| | - Antonio Bicchi
- Instituto Italiano di Tecnologia, Genoa, Italy
- Centro "E. Piaggio" and Dipartimento di Ingegneria dell'Informazione, University of Pisa, Pisa, Italy
| | - Liselotte M Hermansson
- University Health Care Research Centre, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
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Taleei T, Nazem-Zadeh MR, Amiri M, Keliris GA. EEG-based functional connectivity for tactile roughness discrimination. Cogn Neurodyn 2023; 17:921-940. [PMID: 37522039 PMCID: PMC10374498 DOI: 10.1007/s11571-022-09876-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 07/26/2022] [Accepted: 08/13/2022] [Indexed: 11/03/2022] Open
Abstract
Tactile sensation and perception involve cooperation between different parts of the brain. Roughness discrimination is an important phase of texture recognition. In this study, we investigated how different roughness levels would influence the brain network characteristics. We recorded EEG signals from nine right-handed healthy subjects who underwent touching three surfaces with different levels of roughness. The experiment was separately repeated in 108 trials for each hand for both static and dynamic touch. For estimation of the functional connectivity between brain regions, the phase lag index method was employed. Frequency-specific connectivity patterns were observed in the ipsilateral and contralateral hemispheres to the hand of interest, for delta, theta, alpha, and beta frequency bands under the study. A number of connections were identified to be in charge of discrimination between surfaces in both alpha and beta frequency bands for the left hand in static touch and for the right hand in dynamic touch. In addition, common connections were determined in both hands for all three roughness in alpha band for static touch and in theta band for dynamic touch. The common connections were identified for the smooth surface in beta band for static touch and in delta and alpha bands for dynamic touch. As observed for static touch in alpha band and for dynamic touch in theta band, the number of common connections between the two hands was decreased by increasing the surface roughness. The results of this research would extend the current knowledge about tactile information processing in the brain. Supplementary Information The online version contains supplementary material available at 10.1007/s11571-022-09876-1.
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Affiliation(s)
- Tahereh Taleei
- Medical Biology Research Center, Institute of Health Technology, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Mohammad-Reza Nazem-Zadeh
- Research Center for Molecular and Cellular Imaging, Advanced Medical Technologies and Equipment Institute (AMTEI), Tehran University of Medical Sciences (TUMS), Tehran, Iran
- Medical Physics and Biomedical Engineering Department, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Mahmood Amiri
- Medical Technology Research Center, Institute of Health Technology, Kermanshah University of Medical Sciences, Kermanshah, Iran
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