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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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Zhang Z, Xie A, Chou CH, Liang W, Zhang J, Bi S, Lan N. Closed-Loop Force Control by Biorealistic Hand Prosthesis With Visual and Tactile Sensory Feedback. IEEE Trans Neural Syst Rehabil Eng 2024; 32:2939-2949. [PMID: 39110556 DOI: 10.1109/tnsre.2024.3439722] [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: 08/17/2024]
Abstract
The ability of a novel biorealistic hand prosthesis for grasp force control reveals improved neural compatibility between the human-prosthetic interaction. The primary purpose here was to validate a virtual training platform for amputee subjects and evaluate the respective roles of visual and tactile information in fundamental force control tasks. We developed a digital twin of tendon-driven prosthetic hand in the MuJoCo environment. Biorealistic controllers emulated a pair of antagonistic muscles controlling the index finger of the virtual hand by surface electromyographic (sEMG) signals from amputees' residual forearm muscles. Grasp force information was transmitted to amputees through evoked tactile sensation (ETS) feedback. Six forearm amputees participated in force tracking and holding tasks under different feedback conditions or using their intact hands. Test results showed that visual feedback played a predominant role than ETS feedback in force tracking and holding tasks. However, in the absence of visual feedback during the force holding task, ETS feedback significantly enhanced motor performance compared to feedforward control alone. Thus, ETS feedback still supplied reliable sensory information to facilitate amputee's ability of stable grasp force control. The effects of tactile and visual feedback on force control were subject-specific when both types of feedback were provided simultaneously. Amputees were able to integrate visual and tactile information to the biorealistic controllers and achieve a good sensorimotor performance in grasp force regulation. The virtual platform may provide a training paradigm for amputees to adapt the biorealistic hand controller and ETS feedback optimally.
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3
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Riley M, Tala FNU, Johnson KJ, Johnson BC. Multi-Channel Microscale Nerve Cuffs for Spatially Selective Neuromodulation. MICROMACHINES 2024; 15:1036. [PMID: 39203687 PMCID: PMC11356344 DOI: 10.3390/mi15081036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/08/2024] [Revised: 08/08/2024] [Accepted: 08/12/2024] [Indexed: 09/03/2024]
Abstract
Peripheral nerve modulation via electrical stimulation shows promise for treating several diseases, but current approaches lack selectivity, leading to side effects. Exploring selective neuromodulation with commercially available nerve cuffs is impractical due to their high cost and limited spatial resolution. While custom cuffs reported in the literature achieve high spatial resolutions, they require specialized microfabrication equipment and significant effort to produce even a single design. This inability to rapidly and cost-effectively prototype novel cuff designs impedes research into selective neuromodulation therapies in acute studies. To address this, we developed a reproducible method to easily create multi-channel epineural nerve cuffs for selective fascicular neuromodulation. Leveraging commercial flexible printed circuit (FPC) technology, we created cuffs with high spatial resolution (50 μm) and customizable parameters like electrode size, channel count, and cuff diameter. We designed cuffs to accommodate adult mouse or rat sciatic nerves (300-1500 μm diameter). We coated the electrodes with PEDOT:PSS to improve the charge injection capacity. We demonstrated selective neuromodulation in both rats and mice, achieving preferential activation of the tibialis anterior (TA) and lateral gastrocnemius (LG) muscles. Selectivity was confirmed through micro-computed tomography (μCT) and quantified through a selectivity index. These results demonstrate the potential of this fabrication method for enabling selective neuromodulation studies while significantly reducing production time and costs compared to traditional approaches.
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Affiliation(s)
- Morgan Riley
- Biomedical Engineering Doctoral Program, Boise State University, Boise, ID 83725, USA
| | - FNU Tala
- Department of Electrical and Computer Engineering, Boise State University, Boise, ID 83725, USA
| | | | - Benjamin C. Johnson
- Department of Electrical and Computer Engineering, Boise State University, Boise, ID 83725, USA
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4
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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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5
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Lambrecht JM, Cady SR, Peterson EJ, Dunning JL, Dinsmoor DA, Pape F, Graczyk EL, Tyler DJ. A distributed, high-channel-count, implanted bidirectional system for restoration of somatosensation and myoelectric control. J Neural Eng 2024; 21:036049. [PMID: 38861967 DOI: 10.1088/1741-2552/ad56c9] [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: 01/31/2024] [Accepted: 06/11/2024] [Indexed: 06/13/2024]
Abstract
Objective. We intend to chronically restore somatosensation and provide high-fidelity myoelectric control for those with limb loss via a novel, distributed, high-channel-count, implanted system.Approach.We have developed the implanted Somatosensory Electrical Neurostimulation and Sensing (iSens®) system to support peripheral nerve stimulation through up to 64, 96, or 128 electrode contacts with myoelectric recording from 16, 8, or 0 bipolar sites, respectively. The rechargeable central device has Bluetooth® wireless telemetry to communicate to external devices and wired connections for up to four implanted satellite stimulation or recording devices. We characterized the stimulation, recording, battery runtime, and wireless performance and completed safety testing to support its use in human trials.Results.The stimulator operates as expected across a range of parameters and can schedule multiple asynchronous, interleaved pulse trains subject to total charge delivery limits. Recorded signals in saline show negligible stimulus artifact when 10 cm from a 1 mA stimulating source. The wireless telemetry range exceeds 1 m (direction and orientation dependent) in a saline torso phantom. The bandwidth supports 100 Hz bidirectional update rates of stimulation commands and data features or streaming select full bandwidth myoelectric signals. Preliminary first-in-human data validates the bench testing result.Significance.We developed, tested, and clinically implemented an advanced, modular, fully implanted peripheral stimulation and sensing system for somatosensory restoration and myoelectric control. The modularity in electrode type and number, including distributed sensing and stimulation, supports a wide variety of applications; iSens® is a flexible platform to bring peripheral neuromodulation applications to clinical reality. ClinicalTrials.gov ID NCT04430218.
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Affiliation(s)
- Joris M Lambrecht
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States of America
- Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, OH, United States of America
| | - Sedona R Cady
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States of America
- Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, OH, United States of America
| | | | - Jeremy L Dunning
- Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, OH, United States of America
| | | | - Forrest Pape
- Medtronic plc, Minneapolis, MN, United States of America
| | - Emily L Graczyk
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States of America
- Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, OH, United States of America
| | - Dustin J Tyler
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States of America
- Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, OH, United States of America
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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 2024:10.1007/s10072-024-07634-1. [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] [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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7
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Micera S, Menciassi A, Cianferotti L, Gruppioni E, Lionetti V. Organ Neuroprosthetics: Connecting Transplanted and Artificial Organs with the Nervous System. Adv Healthc Mater 2024:e2302896. [PMID: 38656615 DOI: 10.1002/adhm.202302896] [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: 08/30/2023] [Revised: 04/01/2024] [Indexed: 04/26/2024]
Abstract
Implantable neural interfaces with the central and peripheral nervous systems are currently used to restore sensory, motor, and cognitive functions in disabled people with very promising results. They have also been used to modulate autonomic activities to treat diseases such as diabetes or hypertension. Here, this study proposes to extend the use of these technologies to (re-)establish the connection between new (transplanted or artificial) organs and the nervous system in order to increase the long-term efficacy and the effective biointegration of these solutions. In this perspective paper, some clinically relevant applications of this approach are briefly described. Then, the choices that neural engineers must implement about the type, implantation location, and closed-loop control algorithms to successfully realize this approach are highlighted. It is believed that these new "organ neuroprostheses" are going to become more and more valuable and very effective solutions in the years to come.
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Affiliation(s)
- Silvestro Micera
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, 56127, Italy
- Interdisciplinary Research Center Health Science, Scuola Superiore Sant'Anna, Pisa, 56127, Italy
- Bertarelli Foundation Chair in Translational Neuroengineering, Neuro-X Institute, School of Engineering, Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, 1015, Switzerland
| | - Arianna Menciassi
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, 56127, Italy
- Interdisciplinary Research Center Health Science, Scuola Superiore Sant'Anna, Pisa, 56127, Italy
| | - Luisella Cianferotti
- Department of Experimental and Clinical Biomedical Sciences, University of Florence, Florence, 50121, Italy
| | | | - Vincenzo Lionetti
- Interdisciplinary Research Center Health Science, Scuola Superiore Sant'Anna, Pisa, 56127, Italy
- UOSVD Anesthesia and Resuscitation, Fondazione Toscana G. Monasterio, Pisa, 56127, Italy
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8
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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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9
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Xia H, Zhang Y, Rajabi N, Taleb F, Yang Q, Kragic D, Li Z. Shaping high-performance wearable robots for human motor and sensory reconstruction and enhancement. Nat Commun 2024; 15:1760. [PMID: 38409128 PMCID: PMC10897332 DOI: 10.1038/s41467-024-46249-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 02/19/2024] [Indexed: 02/28/2024] Open
Abstract
Most wearable robots such as exoskeletons and prostheses can operate with dexterity, while wearers do not perceive them as part of their bodies. In this perspective, we contend that integrating environmental, physiological, and physical information through multi-modal fusion, incorporating human-in-the-loop control, utilizing neuromuscular interface, employing flexible electronics, and acquiring and processing human-robot information with biomechatronic chips, should all be leveraged towards building the next generation of wearable robots. These technologies could improve the embodiment of wearable robots. With optimizations in mechanical structure and clinical training, the next generation of wearable robots should better facilitate human motor and sensory reconstruction and enhancement.
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Affiliation(s)
- Haisheng Xia
- School of Mechanical Engineering, Tongji University, Shanghai, 201804, China
- Translational Research Center, Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), Tongji University, Shanghai, 201619, China
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, 230026, China
| | - Yuchong Zhang
- Robotics, Perception and Learning Lab, EECS at KTH Royal Institute of Technology Stockholm, 114 17, Stockholm, Sweden
| | - Nona Rajabi
- Robotics, Perception and Learning Lab, EECS at KTH Royal Institute of Technology Stockholm, 114 17, Stockholm, Sweden
| | - Farzaneh Taleb
- Robotics, Perception and Learning Lab, EECS at KTH Royal Institute of Technology Stockholm, 114 17, Stockholm, Sweden
| | - Qunting Yang
- Department of Automation, University of Science and Technology of China, Hefei, 230026, China
| | - Danica Kragic
- Robotics, Perception and Learning Lab, EECS at KTH Royal Institute of Technology Stockholm, 114 17, Stockholm, Sweden
| | - Zhijun Li
- School of Mechanical Engineering, Tongji University, Shanghai, 201804, China.
- Translational Research Center, Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), Tongji University, Shanghai, 201619, China.
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, 230026, China.
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10
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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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11
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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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12
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Donati E, Valle G. Neuromorphic hardware for somatosensory neuroprostheses. Nat Commun 2024; 15:556. [PMID: 38228580 PMCID: PMC10791662 DOI: 10.1038/s41467-024-44723-3] [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: 11/10/2022] [Accepted: 01/03/2024] [Indexed: 01/18/2024] Open
Abstract
In individuals with sensory-motor impairments, missing limb functions can be restored using neuroprosthetic devices that directly interface with the nervous system. However, restoring the natural tactile experience through electrical neural stimulation requires complex encoding strategies. Indeed, they are presently limited in effectively conveying or restoring tactile sensations by bandwidth constraints. Neuromorphic technology, which mimics the natural behavior of neurons and synapses, holds promise for replicating the encoding of natural touch, potentially informing neurostimulation design. In this perspective, we propose that incorporating neuromorphic technologies into neuroprostheses could be an effective approach for developing more natural human-machine interfaces, potentially leading to advancements in device performance, acceptability, and embeddability. We also highlight ongoing challenges and the required actions to facilitate the future integration of these advanced technologies.
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Affiliation(s)
- Elisa Donati
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland.
| | - Giacomo Valle
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL, USA.
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Gonzalez MA, Nwokeabia C, Vaskov AK, Vu PP, Lu CW, Patil PG, Cederna PS, Chestek CA, Gates DH. Electrical Stimulation of Regenerative Peripheral Nerve Interfaces (RPNIs) Induces Referred Sensations in People With Upper Limb Loss. IEEE Trans Neural Syst Rehabil Eng 2024; 32:339-349. [PMID: 38145529 PMCID: PMC10938368 DOI: 10.1109/tnsre.2023.3345164] [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] [Indexed: 12/27/2023]
Abstract
Individuals with upper limb loss lack sensation of the missing hand, which can negatively impact their daily function. Several groups have attempted to restore this sensation through electrical stimulation of residual nerves. The purpose of this study was to explore the utility of regenerative peripheral nerve interfaces (RPNIs) in eliciting referred sensation. In four participants with upper limb loss, we characterized the quality and location of sensation elicited through electrical stimulation of RPNIs over time. We also measured functional stimulation ranges (sensory perception and discomfort thresholds), sensitivity to changes in stimulation amplitude, and ability to differentiate objects of different stiffness and sizes. Over a period of up to 54 months, stimulation of RPNIs elicited sensations that were consistent in quality (e.g. tingling, kinesthesia) and were perceived in the missing hand and forearm. The location of elicited sensation was partially-stable to stable in 13 of 14 RPNIs. For 5 of 7 RPNIs tested, participants demonstrated a sensitivity to changes in stimulation amplitude, with an average just noticeable difference of 45 nC. In a case study, one participant was provided RPNI stimulation proportional to prosthetic grip force. She identified four objects of different sizes and stiffness with 56% accuracy with stimulation alone and 100% accuracy when stimulation was combined with visual feedback of hand position. Collectively, these experiments suggest that RPNIs have the potential to be used in future bi-directional prosthetic systems.
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Barberi F, Anselmino E, Mazzoni A, Goldfarb M, Micera S. Toward the Development of User-Centered Neurointegrated Lower Limb Prostheses. IEEE Rev Biomed Eng 2024; 17:212-228. [PMID: 37639425 DOI: 10.1109/rbme.2023.3309328] [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: 08/31/2023]
Abstract
The last few years witnessed radical improvements in lower-limb prostheses. Researchers have presented innovative solutions to overcome the limits of the first generation of prostheses, refining specific aspects which could be implemented in future prostheses designs. Each aspect of lower-limb prostheses has been upgraded, but despite these advances, a number of deficiencies remain and the most capable limb prostheses fall far short of the capabilities of the healthy limb. This article describes the current state of prosthesis technology; identifies a number of deficiencies across the spectrum of lower limb prosthetic components with respect to users' needs; and discusses research opportunities in design and control that would substantially improve functionality concerning each deficiency. In doing so, the authors present a roadmap of patients related issues that should be addressed in order to fulfill the vision of a next-generation, neurally-integrated, highly-functional lower limb prosthesis.
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Giannotti A, Musco S, Miragliotta V, Lazzarini G, Pirone A, Briganti A, Verardo C, Bernini F, Del Popolo G, Micera S. Swine Pudendal Nerve as a Model for Neuromodulation Studies to Restore Lower Urinary Tract Dysfunction. Int J Mol Sci 2024; 25:855. [PMID: 38255927 PMCID: PMC10815560 DOI: 10.3390/ijms25020855] [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: 12/21/2023] [Revised: 01/08/2024] [Accepted: 01/08/2024] [Indexed: 01/24/2024] Open
Abstract
Lower urinary tract dysfunction, such as incontinence or urinary retention, is one of the leading consequences of neurological diseases. This significantly impacts the quality of life for those affected, with implications extending not only to humans but also to clinical veterinary care. Having motor and sensory fibers, the pudendal nerve is an optimal candidate for neuromodulation therapies using bidirectional intraneural prostheses, paving the way towards the restoration of a more physiological urination cycle: bladder state can be detected from recorded neural signals, then an electrical current can be injected to the nerve based on the real-time need of the bladder. To develop such prostheses and investigate this novel approach, animal studies are still required since the morphology of the target nerve is fundamental to optimizing the prosthesis design. This study aims to describe the porcine pudendal nerve as a model for neuromodulation studies aiming at restoring lower urinary tract dysfunction. Five male farm pigs were involved in the study. First, a surgical procedure to access the porcine pudendal nerve without muscle resection was developed. Then, an intraneural interface was implanted to confirm the presence of fibers innervating the external urethral sphincter by measuring its electromyographic activity. Finally, the morphophysiology of the porcine pudendal nerve at the level of surgical exposure was described by using histological and immunohistochemical characterization. This analysis confirmed the fasciculate nature of the nerve and the presence of mixed fibers with a spatial and functional organization. These achievements pave the way for further pudendal neuromodulation studies by using a clinically relevant animal model with the potential for translating the findings into clinical applications.
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Affiliation(s)
- Alice Giannotti
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Scuola Superiore Sant’Anna, 56127 Pisa, Italy; (A.G.); (C.V.)
| | - Stefania Musco
- Neuro-Urology Department, Careggi University Hospital, 50134 Firenze, Italy; (S.M.); (G.D.P.)
| | - Vincenzo Miragliotta
- Department of Veterinary Sciences, University of Pisa, 56124 Pisa, Italy; (V.M.); (G.L.); (A.P.); (A.B.)
| | - Giulia Lazzarini
- Department of Veterinary Sciences, University of Pisa, 56124 Pisa, Italy; (V.M.); (G.L.); (A.P.); (A.B.)
| | - Andrea Pirone
- Department of Veterinary Sciences, University of Pisa, 56124 Pisa, Italy; (V.M.); (G.L.); (A.P.); (A.B.)
| | - Angela Briganti
- Department of Veterinary Sciences, University of Pisa, 56124 Pisa, Italy; (V.M.); (G.L.); (A.P.); (A.B.)
| | - Claudio Verardo
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Scuola Superiore Sant’Anna, 56127 Pisa, Italy; (A.G.); (C.V.)
| | - Fabio Bernini
- BioMedLab, Scuola Superiore Sant’Anna, 56127 Pisa, Italy;
| | - Giulio Del Popolo
- Neuro-Urology Department, Careggi University Hospital, 50134 Firenze, Italy; (S.M.); (G.D.P.)
| | - Silvestro Micera
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Scuola Superiore Sant’Anna, 56127 Pisa, Italy; (A.G.); (C.V.)
- Bertarelli Foundation Chair in Translational NeuroEngineering, Center for Neuroprosthetics and Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
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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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17
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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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18
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Smith BJ, Twohey EE, Dean KP, D'Souza RS. Peripheral Nerve Stimulation for the Treatment of Postamputation Pain: A Systematic Review. Am J Phys Med Rehabil 2023; 102:846-854. [PMID: 36917030 DOI: 10.1097/phm.0000000000002237] [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: 03/16/2023]
Abstract
ABSTRACT Despite numerous first-line treatment interventions, adequately managing a patient's postamputation pain can be difficult. Peripheral nerve stimulation has emerged as a safe neuromodulatory intervention that can be used for many etiologies of chronic pain. We performed a systemic review to appraise the evidence of peripheral nerve stimulation use for improvement in postamputation pain. This was performed in Ovid, Cochrane databases, OVID, Scopus, Web of Science Core Collection, and PubMed. The primary outcome was improvement in postamputation pain after use of peripheral nerve stimulation. Secondary outcomes included improvements in functional status, opioid usage, and mood. Data extraction and risk of bias assessments were performed independently in a blinded manner. Of the 989 studies identified, 13 studies were included consisting of three randomized control trials, seven observational studies, and three case series. While large heterogeneity limited definitive conclusions, the included studies generally demonstrated favorable outcomes regarding pain reduction. Each included study that used an objective pain scale demonstrated clinically significant pain improvements. Per the Grading of Recommendations, Assessment, Development, and Evaluations criteria, there is very low-quality Grading of Recommendations, Assessment, Development, and Evaluations evidence supporting that peripheral nerve stimulation is associated with improvements in pain intensity for postamputation pain. Future prospective, comparative, and well-powered studies assessing the use of peripheral nerve stimulation for postamputation pain are warranted.
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Affiliation(s)
- Brandon J Smith
- From the Department of Physical Medicine and Rehabilitation, Mayo Clinic, Rochester, Minnesota (BJS, EET, KPD); and Department of Anesthesiology and Perioperative Medicine, Mayo Clinic Hospital, Rochester, Minnesota (RSD)
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19
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Adkins MD, Buczak MK, Olsen CD, Iversen MM, George JA. Automated Quantifiable Assessments of Sensorimotor Function Using an Instrumented Fragile Object. IEEE Int Conf Rehabil Robot 2023; 2023:1-6. [PMID: 37941235 DOI: 10.1109/icorr58425.2023.10304693] [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: 11/10/2023]
Abstract
Accurate assessment of hand dexterity plays a critical role in informing rehabilitation and care of upper-limb hemiparetic stroke patients. Common upper-limb assessments, such as the Box and Blocks Test and Nine Hole Peg Test, primarily evaluate gross motor function in terms of speed. These assessments neglect an individual's ability to finely regulate grip force, which is critical in activities of daily living, such as manipulating fragile objects. Here we present the Electronic Grip Gauge (EGG), an instrumented fragile object that assesses both gross and fine motor function. Embedded with a load cell, accelerometer, and Hall-effect sensor, the EGG measures grip force, acceleration, and relative position (via magnetic fields) in real time. The EGG can emit an audible "break" sound when the applied grip force exceeds a threshold. The number of breaks, transfer duration, and applied forces are automatically logged in real-time. Using the EGG, we evaluated sensorimotor function in implicit grasping and gentle grasping for the non-paretic and paretic hands of 3 hemiparetic stroke patients. For all participants, the paretic hand took longer to transfer the EGG during implicit grasping. For 2 of 3 participants, grip forces were significantly greater for the paretic hand during gentle grasping. Differences in implicit grasping forces were unique to each participant. This work constitutes an important step towards more widespread and quantitative measures of sensorimotor function, which may ultimately lead to improved personalized rehabilitation and better patient outcomes.
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20
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Greenspon CM, Shelchkova ND, Valle G, Hobbs TG, Berger-Wolf EI, Hutchison BC, Dogruoz E, Verbarschott C, Callier T, Sobinov AR, Okorokova EV, Jordan PM, Prasad D, He Q, Liu F, Kirsch RF, Miller JP, Lee RC, Satzer D, Gonzalez-Martinez J, Warnke PC, Miller LE, Boninger ML, Ajiboye AB, Graczyk EL, Downey JE, Collinger JL, Hatsopoulos NG, Gaunt RA, Bensmaia SJ. Tessellation of artificial touch via microstimulation of human somatosensory cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.23.545425. [PMID: 37425877 PMCID: PMC10327055 DOI: 10.1101/2023.06.23.545425] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
When we interact with objects, we rely on signals from the hand that convey information about the object and our interaction with it. A basic feature of these interactions, the locations of contacts between the hand and object, is often only available via the sense of touch. Information about locations of contact between a brain-controlled bionic hand and an object can be signaled via intracortical microstimulation (ICMS) of somatosensory cortex (S1), which evokes touch sensations that are localized to a specific patch of skin. To provide intuitive location information, tactile sensors on the robotic hand drive ICMS through electrodes that evoke sensations at skin locations matching sensor locations. This approach requires that ICMS-evoked sensations be focal, stable, and distributed over the hand. To systematically investigate the localization of ICMS-evoked sensations, we analyzed the projected fields (PFs) of ICMS-evoked sensations - their location and spatial extent - from reports obtained over multiple years from three participants implanted with microelectrode arrays in S1. First, we found that PFs vary widely in their size across electrodes, are highly stable within electrode, are distributed over large swaths of each participant's hand, and increase in size as the amplitude or frequency of ICMS increases. Second, while PF locations match the locations of the receptive fields (RFs) of the neurons near the stimulating electrode, PFs tend to be subsumed by the corresponding RFs. Third, multi-channel stimulation gives rise to a PF that reflects the conjunction of the PFs of the component channels. By stimulating through electrodes with largely overlapping PFs, then, we can evoke a sensation that is experienced primarily at the intersection of the component PFs. To assess the functional consequence of this phenomenon, we implemented multichannel ICMS-based feedback in a bionic hand and demonstrated that the resulting sensations are more localizable than are those evoked via single-channel ICMS.
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Affiliation(s)
- Charles M Greenspon
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL
| | | | - Giacomo Valle
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL
| | - Taylor G Hobbs
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA
| | - Ev I Berger-Wolf
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL
| | - Brianna C Hutchison
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH
| | - Efe Dogruoz
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL
| | - Ceci Verbarschott
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA
| | - Thierri Callier
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL
| | - Anton R Sobinov
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL
| | | | - Patrick M Jordan
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL
| | - Dillan Prasad
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL
| | - Qinpu He
- Committee on Computational Neuroscience, University of Chicago, Chicago, IL
| | - Fang Liu
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA
| | - Robert F Kirsch
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH
- School of Medicine, Case Western Reserve University, Cleveland, OH
- Louis Stokes Cleveland VA Medical Center, Cleveland, OH
| | - Jonathan P Miller
- School of Medicine, Case Western Reserve University, Cleveland, OH
- The Neurological Institute, University Hospitals Cleveland Medical Center, Cleveland, OH
- Louis Stokes Cleveland VA Medical Center, Cleveland, OH
| | - Ray C Lee
- Schwab Rehabilitation Hospital, Chicago, IL
| | - David Satzer
- Department of Neurological Surgery, University of Chicago, Chicago, IL
| | | | - Peter C Warnke
- Department of Neurological Surgery, University of Chicago, Chicago, IL
| | - Lee E Miller
- Department of Neuroscience, Northwestern University, Chicago, IL
- Department of Biomedical Engineering, Northwestern University, Evanston, IL
- Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL
- Shirley Ryan Ability Lab, Chicago, IL
| | - Michael L Boninger
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA
| | - Abidemi B Ajiboye
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH
- School of Medicine, Case Western Reserve University, Cleveland, OH
- Louis Stokes Cleveland VA Medical Center, Cleveland, OH
| | - Emily L Graczyk
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH
- School of Medicine, Case Western Reserve University, Cleveland, OH
- Louis Stokes Cleveland VA Medical Center, Cleveland, OH
| | - John E Downey
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL
| | - Jennifer L Collinger
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA
| | - Nicholas G Hatsopoulos
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL
- Committee on Computational Neuroscience, University of Chicago, Chicago, IL
- Neuroscience Institute, University of Chicago, Chicago, IL
| | - Robert A Gaunt
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA
| | - Sliman J Bensmaia
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL
- Committee on Computational Neuroscience, University of Chicago, Chicago, IL
- Neuroscience Institute, University of Chicago, Chicago, IL
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Bensmaia SJ, Tyler DJ, Micera S. Restoration of sensory information via bionic hands. Nat Biomed Eng 2023; 7:443-455. [PMID: 33230305 PMCID: PMC10233657 DOI: 10.1038/s41551-020-00630-8] [Citation(s) in RCA: 85] [Impact Index Per Article: 85.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2019] [Accepted: 09/13/2020] [Indexed: 12/19/2022]
Abstract
Individuals who have lost the use of their hands because of amputation or spinal cord injury can use prosthetic hands to restore their independence. A dexterous prosthesis requires the acquisition of control signals that drive the movements of the robotic hand, and the transmission of sensory signals to convey information to the user about the consequences of these movements. In this Review, we describe non-invasive and invasive technologies for conveying artificial sensory feedback through bionic hands, and evaluate the technologies' long-term prospects.
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Affiliation(s)
- Sliman J Bensmaia
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL, USA.
- Committee on Computational Neuroscience, University of Chicago, Chicago, IL, USA.
- Grossman Institute for Neuroscience, Quantitative Biology, and Human Behavior, University of Chicago, Chicago, IL, USA.
| | - Dustin J Tyler
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
- Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH, USA
| | - Silvestro Micera
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.
- Translational Neural Engineering Laboratory, Center for Neuroprosthetics and Institute of Bioengineering, School of Engineering, École Polytechnique Federale de Lausanne, Lausanne, Switzerland.
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22
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Farina D, Vujaklija I, Brånemark R, Bull AMJ, Dietl H, Graimann B, Hargrove LJ, Hoffmann KP, Huang HH, Ingvarsson T, Janusson HB, Kristjánsson K, Kuiken T, Micera S, Stieglitz T, Sturma A, Tyler D, Weir RFF, Aszmann OC. Toward higher-performance bionic limbs for wider clinical use. Nat Biomed Eng 2023; 7:473-485. [PMID: 34059810 DOI: 10.1038/s41551-021-00732-x] [Citation(s) in RCA: 87] [Impact Index Per Article: 87.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2019] [Accepted: 04/01/2021] [Indexed: 12/19/2022]
Abstract
Most prosthetic limbs can autonomously move with dexterity, yet they are not perceived by the user as belonging to their own body. Robotic limbs can convey information about the environment with higher precision than biological limbs, but their actual performance is substantially limited by current technologies for the interfacing of the robotic devices with the body and for transferring motor and sensory information bidirectionally between the prosthesis and the user. In this Perspective, we argue that direct skeletal attachment of bionic devices via osseointegration, the amplification of neural signals by targeted muscle innervation, improved prosthesis control via implanted muscle sensors and advanced algorithms, and the provision of sensory feedback by means of electrodes implanted in peripheral nerves, should all be leveraged towards the creation of a new generation of high-performance bionic limbs. These technologies have been clinically tested in humans, and alongside mechanical redesigns and adequate rehabilitation training should facilitate the wider clinical use of bionic limbs.
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Affiliation(s)
- Dario Farina
- Department of Bioengineering, Imperial College London, London, UK.
| | - Ivan Vujaklija
- Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland
| | - Rickard Brånemark
- Center for Extreme Bionics, Biomechatronics Group, MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Orthopaedics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Anthony M J Bull
- Department of Bioengineering, Imperial College London, London, UK
| | - Hans Dietl
- Ottobock Products SE & Co. KGaA, Vienna, Austria
| | | | - Levi J Hargrove
- Center for Bionic Medicine, Shirley Ryan AbilityLab, Chicago, IL, USA
- Department of Physical Medicine & Rehabilitation, Northwestern University, Chicago, IL, USA
- Department of Biomedical Engineering, Northwestern University, Chicago, IL, USA
| | - Klaus-Peter Hoffmann
- Department of Medical Engineering & Neuroprosthetics, Fraunhofer-Institut für Biomedizinische Technik, Sulzbach, Germany
| | - He Helen Huang
- NCSU/UNC Joint Department of Biomedical Engineering, North Carolina State University, Raleigh, NC, USA
- University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Thorvaldur Ingvarsson
- Department of Research and Development, Össur Iceland, Reykjavík, Iceland
- Faculty of Medicine, University of Iceland, Reykjavík, Iceland
| | - Hilmar Bragi Janusson
- School of Engineering and Natural Sciences, University of Iceland, Reykjavík, Iceland
| | | | - Todd Kuiken
- Center for Bionic Medicine, Shirley Ryan AbilityLab, Chicago, IL, USA
- Department of Physical Medicine & Rehabilitation, Northwestern University, Chicago, IL, USA
- Department of Biomedical Engineering, Northwestern University, Chicago, IL, USA
| | - Silvestro Micera
- The Biorobotics Institute and Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pontedera, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pontedera, Italy
- Bertarelli Foundation Chair in Translational NeuroEngineering, Center for Neuroprosthetics and Institute of Bioengineering, School of Engineering, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
| | - Thomas Stieglitz
- Laboratory for Biomedical Microtechnology, Department of Microsystems Engineering-IMTEK, BrainLinks-BrainTools Center and Bernstein Center Freiburg, University of Freiburg, Freiburg, Germany
| | - Agnes Sturma
- Department of Bioengineering, Imperial College London, London, UK
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic and Reconstructive Surgery, Medical University of Vienna, Vienna, Austria
| | - Dustin Tyler
- Case School of Engineering, Case Western Reserve University, Cleveland, OH, USA
- Louis Stokes Veterans Affairs Medical Centre, Cleveland, OH, USA
| | - Richard F Ff Weir
- Biomechatronics Development Laboratory, Bioengineering Department, University of Colorado Denver and VA Eastern Colorado Healthcare System, Aurora, CO, USA
| | - Oskar C Aszmann
- Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic and Reconstructive Surgery, Medical University of Vienna, Vienna, Austria
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23
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Collu R, Paolini R, Bilotta M, Demofonti A, Cordella F, Zollo L, Barbaro M. Wearable High Voltage Compliant Current Stimulator for Restoring Sensory Feedback. MICROMACHINES 2023; 14:782. [PMID: 37421015 DOI: 10.3390/mi14040782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 03/28/2023] [Accepted: 03/29/2023] [Indexed: 07/09/2023]
Abstract
Transcutaneous Electrical Nerve Stimulation (TENS) is a promising technique for eliciting referred tactile sensations in patients with limb amputation. Although several studies show the validity of this technique, its application in daily life and away from laboratories is limited by the need for more portable instrumentation that guarantees the necessary voltage and current requirements for proper sensory stimulation. This study proposes a low-cost, wearable high-voltage compliant current stimulator with four independent channels based on Components-Off-The-Shelf (COTS). This microcontroller-based system implements a voltage-current converter controllable through a digital-to-analog converter that delivers up to 25 mA to load up to 3.6 kΩ. The high-voltage compliance enables the system to adapt to variations in electrode-skin impedance, allowing it to stimulate loads over 10 kΩ with currents of 5 mA. The system was realized on a four-layer PCB (115.9 mm × 61 mm, 52 g). The functionality of the device was tested on resistive loads and on an equivalent skin-like RC circuit. Moreover, the possibility of implementing an amplitude modulation was demonstrated.
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Affiliation(s)
- Riccardo Collu
- Department of Electrical and Electronics Engineering, University of Cagliari, Piazza D'Armi, 09123 Cagliari, Italy
| | - Roberto Paolini
- Research Unit of Advanced Robotics and Human-Centred Technologies (CREO Lab), Università Campus Bio-Medico di Roma, 00128 Rome, Italy
| | - Martina Bilotta
- Research Unit of Advanced Robotics and Human-Centred Technologies (CREO Lab), Università Campus Bio-Medico di Roma, 00128 Rome, Italy
| | - Andrea Demofonti
- Research Unit of Advanced Robotics and Human-Centred Technologies (CREO Lab), Università Campus Bio-Medico di Roma, 00128 Rome, Italy
| | - Francesca Cordella
- Research Unit of Advanced Robotics and Human-Centred Technologies (CREO Lab), Università Campus Bio-Medico di Roma, 00128 Rome, Italy
| | - Loredana Zollo
- Research Unit of Advanced Robotics and Human-Centred Technologies (CREO Lab), Università Campus Bio-Medico di Roma, 00128 Rome, Italy
| | - Massimo Barbaro
- Department of Electrical and Electronics Engineering, University of Cagliari, Piazza D'Armi, 09123 Cagliari, Italy
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24
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Symbiotic electroneural and musculoskeletal framework to encode proprioception via neurostimulation: ProprioStim. iScience 2023; 26:106248. [PMID: 36923003 PMCID: PMC10009292 DOI: 10.1016/j.isci.2023.106248] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 11/23/2022] [Accepted: 02/16/2023] [Indexed: 02/23/2023] Open
Abstract
Peripheral nerve stimulation in amputees achieved the restoration of touch, but not proprioception, which is critical in locomotion. A plausible reason is the lack of means to artificially replicate the complex activity of proprioceptors. To uncover this, we coupled neuromuscular models from ten subjects and nerve histologies from two implanted amputees to develop ProprioStim: a framework to encode proprioception by electrical evoking neural activity in close agreement with natural proprioceptive activity. We demonstrated its feasibility through non-invasive stimulation on seven healthy subjects comparing it with standard linear charge encoding. Results showed that ProprioStim multichannel stimulation was felt more natural, and hold promises for increasing accuracy in knee angle tracking, especially in future implantable solutions. Additionally, we quantified the importance of realistic 3D-nerve models against extruded models previously adopted for further design and validation of novel neurostimulation encoding strategies. ProprioStim provides clear guidelines for the development of neurostimulation policies restoring natural proprioception.
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25
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Roche AD, Bailey ZK, Gonzalez M, Vu PP, Chestek CA, Gates DH, Kemp SWP, Cederna PS, Ortiz-Catalan M, Aszmann OC. Upper limb prostheses: bridging the sensory gap. J Hand Surg Eur Vol 2023; 48:182-190. [PMID: 36649123 PMCID: PMC9996795 DOI: 10.1177/17531934221131756] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Replacing human hand function with prostheses goes far beyond only recreating muscle movement with feedforward motor control. Natural sensory feedback is pivotal for fine dexterous control and finding both engineering and surgical solutions to replace this complex biological function is imperative to achieve prosthetic hand function that matches the human hand. This review outlines the nature of the problems underlying sensory restitution, the engineering methods that attempt to address this deficit and the surgical techniques that have been developed to integrate advanced neural interfaces with biological systems. Currently, there is no single solution to restore sensory feedback. Rather, encouraging animal models and early human studies have demonstrated that some elements of sensation can be restored to improve prosthetic control. However, these techniques are limited to highly specialized institutions and much further work is required to reproduce the results achieved, with the goal of increasing availability of advanced closed loop prostheses that allow sensory feedback to inform more precise feedforward control movements and increase functionality.
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Affiliation(s)
- Aidan D Roche
- College of Medicine, The Queen's Medical Research Institute, Edinburgh, UK.,Department of Plastic Surgery, NHS Lothian, Livingston, UK
| | - Zachary K Bailey
- Department of Bioengineering, Imperial College London, South Kensington Campus, UK
| | | | - Philip P Vu
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.,Section of Plastic Surgery, University of Michigan, Ann Arbor, MI, USA
| | - Cynthia A Chestek
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.,Section of Plastic Surgery, University of Michigan, Ann Arbor, MI, USA.,Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA.,Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI, USA
| | - Deanna H Gates
- Robotics Institute, University of Michigan, Ann Arbor, MI, USA.,Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.,School of Kinesiology, University of Michigan, Ann Arbor, MI, USA
| | - Stephen W P Kemp
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.,Section of Plastic Surgery, University of Michigan, Ann Arbor, MI, USA
| | - Paul S Cederna
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.,Section of Plastic Surgery, University of Michigan, Ann Arbor, MI, USA
| | - Max Ortiz-Catalan
- Center for Bionics and Pain Research, Mölndal, Sweden.,Department of Electrical Engineering, Chalmers University of Technology, Sweden.,Operational Area 3, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Orthopaedics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Sweden
| | - Oskar C Aszmann
- Department of Plastic & Reconstructive Surgery, Medical University of Vienna, Austria.,Clinical Laboratory for Bionic Extremity Reconstruction, Medical University of Vienna, Austria
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26
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Preatoni G, Dell’Eva F, Valle G, Pedrocchi A, Raspopovic S. Reshaping the full body illusion through visuo-electro-tactile sensations. PLoS One 2023; 18:e0280628. [PMID: 36724146 PMCID: PMC9891501 DOI: 10.1371/journal.pone.0280628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 01/04/2023] [Indexed: 02/02/2023] Open
Abstract
The physical boundaries of our body do not define what we perceive as self. This malleable representation arises from the neural integration of sensory information coming from the environment. Manipulating the visual and haptic cues produces changes in body perception, inducing the Full Body Illusion (FBI), a vastly used approach to exploring humans' perception. After pioneering FBI demonstrations, issues arose regarding its setup, using experimenter-based touch and pre-recorded videos. Moreover, its outcome measures are based mainly on subjective reports, leading to biased results, or on heterogeneous objective ones giving poor consensus on their validity. To address these limitations, we developed and tested a multisensory platform allowing highly controlled experimental conditions, thanks to the leveraged use of innovative technologies: Virtual Reality (VR) and Transcutaneous Electrical Nerve Stimulation (TENS). This enabled a high spatial and temporal precision of the visual and haptic cues, efficiently eliciting FBI. While it matched the classic approach in subjective measures, our setup resulted also in significant results for all objective measurements. Importantly, FBI was elicited when all 4 limbs were multimodally stimulated but also in a single limb condition. Our results behoove the adoption of a comprehensive set of measures, introducing a new neuroscientific platform to investigate body representations.
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Affiliation(s)
- Greta Preatoni
- Department of Health Sciences and Technology, Laboratory for Neuroengineering, Institute for Robotics and Intelligent Systems, ETH Zürich, Zürich, Switzerland
| | - Francesca Dell’Eva
- NearLab, Department of Electronics Information and Bioengineering and We-Cobot Interdept, Lab, Politecnico di Milano, Milano, Italy
| | - Giacomo Valle
- Department of Health Sciences and Technology, Laboratory for Neuroengineering, Institute for Robotics and Intelligent Systems, ETH Zürich, Zürich, Switzerland
| | - Alessandra Pedrocchi
- NearLab, Department of Electronics Information and Bioengineering and We-Cobot Interdept, Lab, Politecnico di Milano, Milano, Italy
| | - Stanisa Raspopovic
- Department of Health Sciences and Technology, Laboratory for Neuroengineering, Institute for Robotics and Intelligent Systems, ETH Zürich, Zürich, Switzerland
- * E-mail:
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27
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Non-rectangular neurostimulation waveforms elicit varied sensation quality and perceptive fields on the hand. Sci Rep 2023; 13:1588. [PMID: 36709376 PMCID: PMC9884304 DOI: 10.1038/s41598-023-28594-0] [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: 09/28/2022] [Accepted: 01/20/2023] [Indexed: 01/30/2023] Open
Abstract
Electrical stimulation of the nerves is known to elicit distinct sensations perceived in distal parts of the body. The stimulation is typically modulated in current with charge-balanced rectangular shapes that, although easily generated by stimulators available on the market, are not able to cover the entire range of somatosensory experiences from daily life. In this regard, we have investigated the effect of electrical neurostimulation with four non-rectangular waveforms in an experiment involving 11 healthy able-bodied subjects. Weiss curves were estimated and rheobase and chronaxie values were obtained showing increases in stimulation time required to elicit sensations for some waveforms. The localization of the sensations reported in the hand also appeared to differ between waveforms, although the total area did not vary significantly. Finally, the possibility of distinguishing different charge- and amplitude-matched stimuli was demonstrated through a two-alternative-forced-choice (2AFC) match-to-sample task, showing the ability of participants to successfully distinguish between waveforms with similar electrical characteristics but different shapes and charge transfer rates. This study provides evidence that, by using different waveforms to stimulate nerves, it is possible to affect not only the required charge to elicit sensations but also the sensation quality and its localization.
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28
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Gupta A, Vardalakis N, Wagner FB. Neuroprosthetics: from sensorimotor to cognitive disorders. Commun Biol 2023; 6:14. [PMID: 36609559 PMCID: PMC9823108 DOI: 10.1038/s42003-022-04390-w] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 12/19/2022] [Indexed: 01/07/2023] Open
Abstract
Neuroprosthetics is a multidisciplinary field at the interface between neurosciences and biomedical engineering, which aims at replacing or modulating parts of the nervous system that get disrupted in neurological disorders or after injury. Although neuroprostheses have steadily evolved over the past 60 years in the field of sensory and motor disorders, their application to higher-order cognitive functions is still at a relatively preliminary stage. Nevertheless, a recent series of proof-of-concept studies suggest that electrical neuromodulation strategies might also be useful in alleviating some cognitive and memory deficits, in particular in the context of dementia. Here, we review the evolution of neuroprosthetics from sensorimotor to cognitive disorders, highlighting important common principles such as the need for neuroprosthetic systems that enable multisite bidirectional interactions with the nervous system.
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Affiliation(s)
- Ankur Gupta
- grid.462010.1Univ. Bordeaux, CNRS, IMN, UMR 5293, F-33000 Bordeaux, France
| | | | - Fabien B. Wagner
- grid.462010.1Univ. Bordeaux, CNRS, IMN, UMR 5293, F-33000 Bordeaux, France
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29
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Valle G. Peripheral neurostimulation for encoding artificial somatosensations. Eur J Neurosci 2022; 56:5888-5901. [PMID: 36097134 PMCID: PMC9826263 DOI: 10.1111/ejn.15822] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Revised: 08/08/2022] [Accepted: 09/08/2022] [Indexed: 01/11/2023]
Abstract
The direct neural stimulation of peripheral or central nervous systems has been shown as an effective tool to treat neurological conditions. The electrical activation of the nervous sensory pathway can be adopted to restore the artificial sense of touch and proprioception in people suffering from sensory-motor disorders. The modulation of the neural stimulation parameters has a direct effect on the electrically induced sensations, both when targeting the somatosensory cortex and the peripheral somatic nerves. The properties of the artificial sensations perceived, as their location, quality and intensity are strongly dependent on the direct modulation of pulse width, amplitude and frequency of the neural stimulation. Different sensory encoding schemes have been tested in patients showing distinct effects and outcomes according to their impact on the neural activation. Here, I reported the most adopted neural stimulation strategies to artificially encode somatosensation into the peripheral nervous system. The real-time implementation of these strategies in bionic devices is crucial to exploit the artificial sensory feedback in prosthetics. Thus, neural stimulation becomes a tool to directly communicate with the human nervous system. Given the importance of adding artificial sensory information to neuroprosthetic devices to improve their control and functionality, the choice of an optimal neural stimulation paradigm could increase the impact of prosthetic devices on the quality of life of people with sensorimotor disabilities.
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Affiliation(s)
- Giacomo Valle
- Laboratory for Neuroengineering, Department of Health Sciences and TechnologyInstitute for Robotics and Intelligent Systems, ETH ZürichZürichSwitzerland
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30
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Cometa A, Falasconi A, Biasizzo M, Carpaneto J, Horn A, Mazzoni A, Micera S. Clinical neuroscience and neurotechnology: An amazing symbiosis. iScience 2022; 25:105124. [PMID: 36193050 PMCID: PMC9526189 DOI: 10.1016/j.isci.2022.105124] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
In the last decades, clinical neuroscience found a novel ally in neurotechnologies, devices able to record and stimulate electrical activity in the nervous system. These technologies improved the ability to diagnose and treat neural disorders. Neurotechnologies are concurrently enabling a deeper understanding of healthy and pathological dynamics of the nervous system through stimulation and recordings during brain implants. On the other hand, clinical neurosciences are not only driving neuroengineering toward the most relevant clinical issues, but are also shaping the neurotechnologies thanks to clinical advancements. For instance, understanding the etiology of a disease informs the location of a therapeutic stimulation, but also the way stimulation patterns should be designed to be more effective/naturalistic. Here, we describe cases of fruitful integration such as Deep Brain Stimulation and cortical interfaces to highlight how this symbiosis between clinical neuroscience and neurotechnology is closer to a novel integrated framework than to a simple interdisciplinary interaction.
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Affiliation(s)
- Andrea Cometa
- The Biorobotics Institute, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56127 Pisa, Italy
| | - Antonio Falasconi
- Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland
- Biozentrum, University of Basel, 4056 Basel, Switzerland
| | - Marco Biasizzo
- The Biorobotics Institute, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56127 Pisa, Italy
| | - Jacopo Carpaneto
- The Biorobotics Institute, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56127 Pisa, Italy
| | - Andreas Horn
- Center for Brain Circuit Therapeutics Department of Neurology Brigham & Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- MGH Neurosurgery & Center for Neurotechnology and Neurorecovery (CNTR) at MGH Neurology Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt- Universität zu Berlin, Department of Neurology, 10117 Berlin, Germany
| | - Alberto Mazzoni
- The Biorobotics Institute, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56127 Pisa, Italy
| | - Silvestro Micera
- The Biorobotics Institute, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56127 Pisa, Italy
- Translational Neural Engineering Lab, School of Engineering, École Polytechnique Fèdèrale de Lausanne, 1015 Lausanne, Switzerland
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31
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Activating effective functional hand movements in individuals with complete tetraplegia through neural stimulation. Sci Rep 2022; 12:16189. [PMID: 36202865 PMCID: PMC9537317 DOI: 10.1038/s41598-022-19906-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 09/06/2022] [Indexed: 11/08/2022] Open
Abstract
Individuals with complete cervical spinal cord injury suffer from a permanent paralysis of upper limbs which prevents them from achieving most of the activities of daily living. We developed a neuroprosthetic solution to restore hand motor function. Electrical stimulation of the radial and median nerves by means of two epineural electrodes enabled functional movements of paralyzed hands. We demonstrated in two participants with complete tetraplegia that selective stimulation of nerve fascicles by means of optimized spreading of the current over the active contacts of the multicontact epineural electrodes induced functional and powerful grasping movements which remained stable over the 28 days of implantation. We also showed that participants were able to trigger the activation of movements of their paralyzed limb using an intuitive interface controlled by voluntary actions and that they were able to perform useful functional movements such as holding a can and drinking through a straw.
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32
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Valle G, Aiello G, Ciotti F, Cvancara P, Martinovic T, Kravic T, Navarro X, Stieglitz T, Bumbasirevic M, Raspopovic S. Multifaceted understanding of human nerve implants to design optimized electrodes for bioelectronics. Biomaterials 2022; 291:121874. [DOI: 10.1016/j.biomaterials.2022.121874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 10/23/2022] [Indexed: 11/24/2022]
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33
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Risso G, Bassolino M. Assess and rehabilitate body representations via (neuro)robotics: An emergent perspective. Front Neurorobot 2022; 16:964720. [PMID: 36160286 PMCID: PMC9498221 DOI: 10.3389/fnbot.2022.964720] [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: 06/08/2022] [Accepted: 08/02/2022] [Indexed: 11/23/2022] Open
Abstract
The perceptions of our own body (e.g., size and shape) do not always coincide with its real characteristics (e.g., dimension). To track the complexity of our perception, the concept of mental representations (model) of the body has been conceived. Body representations (BRs) are stored in the brain and are maintained and updated through multiple sensory information. Despite being altered in different clinical conditions and being tightly linked with self-consciousness, which is one of the most astonishing features of the human mind, the BRs and, especially, the underlying mechanisms and functions are still unclear. In this vein, here we suggest that (neuro)robotics can make an important contribution to the study of BRs. The first section of the study highlights the potential impact of robotics devices in investigating BRs. Far to be exhaustive, we illustrate major examples of its possible exploitation to further improve the assessment of motor, haptic, and multisensory information building up the BRs. In the second section, we review the main evidence showing the contribution of neurorobotics-based (multi)sensory stimulation in reducing BRs distortions in various clinical conditions (e.g., stroke, amputees). The present study illustrates an emergent multidisciplinary perspective combining the neuroscience of BRs and (neuro)robotics to understand and modulate the perception and experience of one's own body. We suggest that (neuro)robotics can enhance the study of BRs by improving experimental rigor and introducing new experimental conditions. Furthermore, it might pave the way for the rehabilitation of altered body perceptions.
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Affiliation(s)
- Gaia Risso
- School of Health Sciences, Haute École spécialisée de Suisse occidentale (HES-SO) Valais-Wallis, Sion, Switzerland
- The Sense Innovation and Research Center, Sion, Switzerland
- Robotics, Brain and Cognitive Sciences (RBCS), Istituto Italiano di Tecnologia, Genoa, Italy
| | - Michela Bassolino
- School of Health Sciences, Haute École spécialisée de Suisse occidentale (HES-SO) Valais-Wallis, Sion, Switzerland
- The Sense Innovation and Research Center, Sion, Switzerland
- Laboratoire MySpace, Université de Lausanne, Lausanne, Switzerland
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Gonzalez M, Bismuth A, Lee C, Chestek CA, Gates DH. Artificial referred sensation in upper and lower limb prosthesis users: a systematic review. J Neural Eng 2022; 19:10.1088/1741-2552/ac8c38. [PMID: 36001115 PMCID: PMC9514130 DOI: 10.1088/1741-2552/ac8c38] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 08/23/2022] [Indexed: 11/12/2022]
Abstract
Objective.Electrical stimulation can induce sensation in the phantom limb of individuals with amputation. It is difficult to generalize existing findings as there are many approaches to delivering stimulation and to assessing the characteristics and benefits of sensation. Therefore, the goal of this systematic review was to explore the stimulation parameters that effectively elicited referred sensation, the qualities of elicited sensation, and how the utility of referred sensation was assessed.Approach.We searched PubMed, Web of Science, and Engineering Village through January of 2022 to identify relevant papers. We included papers which electrically induced referred sensation in individuals with limb loss and excluded papers that did not contain stimulation parameters or outcome measures pertaining to stimulation. We extracted information on participant demographics, stimulation approaches, and participant outcomes.Main results.After applying exclusion criteria, 49 papers were included covering nine stimulation methods. Amplitude was the most commonly adjusted parameter (n= 25), followed by frequency (n= 22), and pulse width (n= 15). Of the 63 reports of sensation quality, most reported feelings of pressure (n= 52), paresthesia (n= 48), or vibration (n= 40) while less than half (n= 29) reported a sense of position or movement. Most papers evaluated the functional benefits of sensation (n= 33) using force matching or object identification tasks, while fewer papers quantified subjective measures (n= 16) such as pain or embodiment. Only 15 studies (36%) observed percept intensity, quality, or location over multiple sessions.Significance.Most studies that measured functional performance demonstrated some benefit to providing participants with sensory feedback. However, few studies could experimentally manipulate sensation location or quality. Direct comparisons between studies were limited by variability in methodologies and outcome measures. As such, we offer recommendations to aid in more standardized reporting for future research.
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Affiliation(s)
- Michael Gonzalez
- Department of Robotics, University of Michigan, Ann Arbor, MI, United States of America
| | - Alex Bismuth
- School of Kinesiology, University of Michigan, Ann Arbor, MI, United States of America
| | - Christina Lee
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States of America
| | - Cynthia A Chestek
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States of America
| | - Deanna H Gates
- School of Kinesiology, University of Michigan, Ann Arbor, MI, United States of America
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Silveira C, Khushaba RN, Brunton E, Nazarpour K. Spatio-temporal feature extraction in sensory electroneurographic signals. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2022; 380:20210268. [PMID: 35658682 PMCID: PMC9289791 DOI: 10.1098/rsta.2021.0268] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/24/2021] [Accepted: 11/08/2021] [Indexed: 06/15/2023]
Abstract
The recording and analysis of peripheral neural signal can provide insight for various prosthetic and bioelectronics medicine applications. However, there are few studies that investigate how informative features can be extracted from population activity electroneurographic (ENG) signals. In this study, five feature extraction frameworks were implemented on sensory ENG datasets and their classification performance was compared. The datasets were collected in acute rat experiments where multi-channel nerve cuffs recorded from the sciatic nerve in response to proprioceptive stimulation of the hindlimb. A novel feature extraction framework, which incorporates spatio-temporal focus and dynamic time warping, achieved classification accuracies above 90% while keeping a low computational cost. This framework outperformed the remaining frameworks tested in this study and has improved the discrimination accuracy of the sensory signals. Thus, this study has extended the tools available to extract features from sensory population activity ENG signals. This article is part of the theme issue 'Advanced neurotechnologies: translating innovation for health and well-being'.
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Affiliation(s)
- C. Silveira
- School of Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - R. N. Khushaba
- Australian Center for Field Robotics, The University of Sydney, New South Wales 2006, Australia
| | - E. Brunton
- National Vision Research Institute, Australian College of Optometry, Carlton, Victoria 3053, Australia
- Department of Optometry and Vision Sciences, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, Victoria 3010, Australia
| | - K. Nazarpour
- Edinburgh Neuroprosthetics Laboratory, School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK
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Jabban L, Metcalfe BW, Raines J, Zhang D, Ainsworth B. Experience of adults with upper-limb difference and their views on sensory feedback for prostheses: a mixed methods study. J Neuroeng Rehabil 2022; 19:80. [PMID: 35870940 PMCID: PMC9308922 DOI: 10.1186/s12984-022-01054-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Accepted: 07/06/2022] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Upper-limb prostheses are regularly abandoned, in part due to the mismatch between user needs and prostheses performance. Sensory feedback is among several technological advances that have been proposed to reduce device abandonment rates. While it has already been introduced in some high-end commercial prostheses, limited data is available about user expectations in relation to sensory feedback. The aim of this study is thus to use a mixed methods approach to provide a detailed insight of users' perceptions and expectations of sensory feedback technology, to ensure the addition of sensory feedback is as acceptable, engaging and ultimately as useful as possible for users and, in turn, reduce the reliance on compensatory movements that lead to overuse syndrome. METHODS The study involved an online survey (N = 37) and video call interviews (N = 15) where adults with upper-limb differences were asked about their experience with limb difference and prosthesis use (if applicable) and their expectations about sensory feedback to prostheses. The survey data were analysed quantitatively and descriptively to establish the range of sensory feedback needs and their variations across the different demographics. Reflexive thematic analysis was performed on the interview data, and data triangulation was used to understand key behavioural issues to generate actionable guiding principles for the development of sensory feedback systems. RESULTS The survey provided a list of practical examples and suggestions that did not vary with the different causes of limb difference or prosthesis use. The interviews showed that although sensory feedback is a desired feature, it must prove to have more benefits than drawbacks. The key benefit mentioned by participants was increasing trust, which requires a highly reliable system that provides input from several areas of the hand rather than just the fingertips. The feedback system should also complement existing implicit feedback sources without causing confusion or discomfort. Further, the effect sensory feedback has on the users' psychological wellbeing was highlighted as an important consideration that varies between individuals and should therefore be discussed. The results obtained were used to develop guiding principles for the design and implementation of sensory feedback systems. CONCLUSIONS This study provides a mixed-methods research on the sensory feedback needs of adults with upper-limb differences, enabling a deeper understanding of their expectations and worries. Guiding principles were developed based on the results of a survey and interviews to inform the development and assessment of sensory feedback for upper-limb prostheses.
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Affiliation(s)
- Leen Jabban
- Center for Biosensors, Bioelectronics and Biodevices (C3Bio), University of Bath, Bath, UK
| | - Benjamin W. Metcalfe
- Center for Biosensors, Bioelectronics and Biodevices (C3Bio), University of Bath, Bath, UK
| | | | - Dingguo Zhang
- Center for Biosensors, Bioelectronics and Biodevices (C3Bio), University of Bath, Bath, UK
| | - Ben Ainsworth
- Department of Psychology, University of Bath, Bath, UK
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Gonzalez MA, Vu PP, Vaskov AK, Cederna PS, Chestek CA, Gates DH. Characterizing sensory thresholds and intensity sensitivity of Regenerative Peripheral Nerve Interfaces: A Case Study . IEEE Int Conf Rehabil Robot 2022; 2022:1-6. [PMID: 36176116 DOI: 10.1109/icorr55369.2022.9896481] [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: 06/16/2023]
Abstract
Current prosthetic limbs offer little to no sensory feedback. Developments in peripheral nerve interfaces provide opportunities to restore some level of tactile feedback that is referred to the prosthetic limb. One such method is a Regenerative Peripheral Nerve Interface (RPNI), composed of a muscle graft wrapped around a free nerve ending. Here, we characterize perception and discomfort thresholds, as well as sensitivity to stimulation through two-alternative forced choice discrimination tasks. One person with transradial amputation who had one RPNI constructed from the median nerve and two constructed from the ulnar nerve participated. Average perception thresholds across all RPNIs were between 950 and 1120 nC with variance of less than 350 nC over a 36-month period. Discomfort thresholds were from 3880 nC to 9770 nC across all RPNIs. The just noticeable difference for the Median RPNI was 520 nC, larger than either the Ulnar-1 or Ulnar-2 RPNIs (210 nC, 470 nC, respectively). We also calculated Weber fractions to compare sensitivity between different RPNIs and relate our results to previous studies. Weber fractions for each of the Median, Ulnar-1, and Ulnar-2 RPNIs were 0.134, 0.088, 0.087, respectively. This work is the first to quantify the functional stimulation range and sensitivity of RPNIs in a human participant. Future work will focus on characterizing RPNI sensation in additional individuals to determine if these findings are generalizable to the amputee population.
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Eickenscheidt M, Herrmann T, Weisshap M, Mittnacht A, Rudmann L, Zeck G, Stieglitz T. An optoelectronic neural interface approach for precise superposition of optical and electrical stimulation in flexible array structures. Biosens Bioelectron 2022; 205:114090. [DOI: 10.1016/j.bios.2022.114090] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 02/07/2022] [Accepted: 02/09/2022] [Indexed: 11/27/2022]
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Corti L. The Role of Neuroergonomics in the Design of Personalized Prosthesis: Deepening the Centrality of Human Being. Front Neurorobot 2022; 16:867115. [PMID: 35599667 PMCID: PMC9121096 DOI: 10.3389/fnbot.2022.867115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 04/06/2022] [Indexed: 11/19/2022] Open
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Castellini C. Peripheral Nervous System Interfaces: Invasive or Non-invasive? Front Neurorobot 2022; 16:846866. [PMID: 35574233 PMCID: PMC9099407 DOI: 10.3389/fnbot.2022.846866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 03/25/2022] [Indexed: 11/13/2022] Open
Affiliation(s)
- Claudio Castellini
- Chair of Medical Robotics, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
- The Adaptive Bio-Interfaces Group, German Aerospace Center (DLR), Institute of Robotics and Mechatronics, Oberpfaffenhofen, Germany
- *Correspondence: Claudio Castellini
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Multisensory Integration in Bionics: Relevance and Perspectives. CURRENT PHYSICAL MEDICINE AND REHABILITATION REPORTS 2022. [DOI: 10.1007/s40141-022-00350-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Abstract
Purpose of review
The goal of the review is to highlight the growing importance of multisensory integration processes connected to bionic limbs and somatosensory feedback restoration.
Recent findings
Restoring quasi-realistic sensations by means of neurostimulation has been shown to provide functional and motor benefits in limb amputees. In the recent past, cognitive processes linked to the artificial sense of touch seemed to play a crucial role for a full prosthesis integration and acceptance.
Summary
Artificial sensory feedback implemented in bionic limbs enhances the cognitive integration of the prosthetic device in amputees. The multisensory experience can be measured and must be considered in the design of novel somatosensory neural prostheses where the goal is to provide a realistic sensory experience to the prosthetic user. The correct integration of these sensory signals will guarantee higher-level cognitive benefits as a better prosthesis embodiment and a reduction of perceived limb distortions.
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Heng W, Solomon S, Gao W. Flexible Electronics and Devices as Human-Machine Interfaces for Medical Robotics. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2022; 34:e2107902. [PMID: 34897836 PMCID: PMC9035141 DOI: 10.1002/adma.202107902] [Citation(s) in RCA: 117] [Impact Index Per Article: 58.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Revised: 12/08/2021] [Indexed: 05/02/2023]
Abstract
Medical robots are invaluable players in non-pharmaceutical treatment of disabilities. Particularly, using prosthetic and rehabilitation devices with human-machine interfaces can greatly improve the quality of life for impaired patients. In recent years, flexible electronic interfaces and soft robotics have attracted tremendous attention in this field due to their high biocompatibility, functionality, conformability, and low-cost. Flexible human-machine interfaces on soft robotics will make a promising alternative to conventional rigid devices, which can potentially revolutionize the paradigm and future direction of medical robotics in terms of rehabilitation feedback and user experience. In this review, the fundamental components of the materials, structures, and mechanisms in flexible human-machine interfaces are summarized by recent and renowned applications in five primary areas: physical and chemical sensing, physiological recording, information processing and communication, soft robotic actuation, and feedback stimulation. This review further concludes by discussing the outlook and current challenges of these technologies as a human-machine interface in medical robotics.
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Affiliation(s)
- Wenzheng Heng
- Andrew and Peggy Cherng Department of Medical Engineering, California Institute of Technology, Pasadena, CA, 91125, USA
| | - Samuel Solomon
- Andrew and Peggy Cherng Department of Medical Engineering, California Institute of Technology, Pasadena, CA, 91125, USA
| | - Wei Gao
- Andrew and Peggy Cherng Department of Medical Engineering, California Institute of Technology, Pasadena, CA, 91125, USA
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43
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Zhang J, Hao M, Yang F, Liang W, Sun A, Chou CH, Lan N. Evaluation of multiple perceptual qualities of transcutaneous electrical nerve stimulation for evoked tactile sensation in forearm amputees. J Neural Eng 2022; 19. [PMID: 35320789 DOI: 10.1088/1741-2552/ac6062] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 03/23/2022] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Evoked tactile sensation (ETS) elicited by transcutaneous electrical nerve stimulation (TENS) is promising to convey digit-specific sensory information to amputees naturally and non-invasively. Fitting ETS-based sensory feedback to amputees entails customizing coding of multiple sensory information for each stimulation site. This study was to elucidate the consistency of percepts and qualities by TENS at multiple stimulation sites in amputees retaining ETS. APPROACH Five transradial amputees with ETS and fourteen able-bodied subjects participated in this study. Surface electrodes with small size (10 mm in diameter) were adopted to fit the restricted projected finger map on the forearm stump of amputees. Effects of stimulus frequency on sensory types were assessed, and the map of perceptual threshold for each sensation was characterized. Sensitivity for vibration and buzz sensations was measured using distinguishable difference in stimulus pulse width. Rapid assessments for modulation ranges of pulse width at fixed amplitude and frequency were developed for coding sensory information. Buzz sensation was demonstrated for location discrimination relating to prosthetic fingers. MAIN RESULTS Vibration and buzz sensations were consistently evoked at 20 Hz and 50 Hz as dominant sensation types in all amputees and able-bodied subjects. Perceptual thresholds of different sensations followed a similar strength-duration curve relating stimulus amplitude to pulse width. The averaged distinguishable difference in pulse width was 12.84 ± 7.23 μs for vibration and 15.21 ± 6.47 μs for buzz in able-bodied subjects, and 14.91 ± 10.54 μs for vibration and 11.30 ± 3.42 μs for buzz in amputees. Buzz coding strategy enabled five amputees to discriminate contact of individual fingers with an overall accuracy of 77.85%. SIGNIFICANCE The consistency in perceptual qualities of dominant sensations can be exploited for coding multi-modality sensory feedback. A fast protocol of sensory coding is possible for fitting ETS-based, non-invasive sensory feedback to amputees.
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Affiliation(s)
- Jie Zhang
- Laboratory of Neurorehabilitaiton Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, Room 404 South Building Med-X, No.1954 Rd. Huashan, Shanghai, Shanghai, 200030, CHINA
| | - Manzhao Hao
- Laboratory of Neurorehabilitaiton Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, Room 401 South Building Med-X, No.1954 Rd. Huashan, Shanghai, Shanghai, 200030, CHINA
| | - Fei Yang
- Shanghai Jiao Tong University, Room 404 South Building Med-X, No. 1954 Rd. Huashan, Xuhui, Shanghai, Shanghai, 200030, CHINA
| | - Wenyuan Liang
- National Research Center for Rehabilitation Technical Aids, No.1 Rong Hua Zhong Road, Beijing Economic and Technological Development Area, Beijing, Beijing, 100176, CHINA
| | - Aiping Sun
- National Research Center for Rehabilitation Technical Aids, No.1 Rong Hua Zhong Road, Beijing Economic and Technological Development Area, Beijing, Beijing, 100176, CHINA
| | - Chi-Hong Chou
- Laboratory of Neurorehabilitaiton Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, Room 401 South Building Med-X, No.1954 Rd. Huashan, Shanghai, Shanghai, 200030, CHINA
| | - Ning Lan
- Laboratory of Neurorehabilitaiton Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, Room 405 South Building Med-X, No.1954 Rd. Huashan, Shanghai, Shanghai, 200030, CHINA
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44
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Jabban L, Dupan S, Zhang D, Ainsworth B, Nazarpour K, Metcalfe BW. Sensory Feedback for Upper-Limb Prostheses: Opportunities and Barriers. IEEE Trans Neural Syst Rehabil Eng 2022; 30:738-747. [PMID: 35290188 DOI: 10.1109/tnsre.2022.3159186] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
The addition of sensory feedback to upper-limb prostheses has been shown to improve control, increase embodiment, and reduce phantom limb pain. However, most commercial prostheses do not incorporate sensory feedback due to several factors. This paper focuses on the major challenges of a lack of deep understanding of user needs, the unavailability of tailored, realistic outcome measures and the segregation between research on control and sensory feedback. The use of methods such as the Person-Based Approach and co-creation can improve the design and testing process. Stronger collaboration between researchers can integrate different prostheses research areas to accelerate the translation process.
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45
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Dupan S, McNeill Z, Sarda E, Brunton E, Nazarpour K. How fast is too fast? Boundaries to the perception of electrical stimulation of peripheral nerves. IEEE Trans Neural Syst Rehabil Eng 2022; 30:782-788. [PMID: 35271444 DOI: 10.1109/tnsre.2022.3158067] [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: 11/06/2022]
Abstract
Transcutaneous electrical stimulation is a promising technique for providing prosthetic hand users with information about sensory events. However, questions remain over how to design the stimulation paradigms to provide users the best opportunity to discriminate these events. Here, we investigate if the refractory period influences how the amplitude of the applied stimulus is perceived. Twenty participants completed a two-alternative forced choice experiment. We delivered two stimuli spaced between 250 ms to 450 ms apart (inter-stimulus-interval, isi). The participants reported which stimulus they perceived as strongest. Each stimulus consisted of either a single or paired pulse delivered transcutaneously. The inter-pulse interval (ipi) for the paired pulse stimuli varied between 6 and 10 ms. We found paired pulses with an ipi of 6 ms were perceived stronger than a single pulse less often than paired pulses with an ipi of 8 ms (p = 0.001) or 10 ms (p < 0.0001). Additionally, we found when the isi was 250 ms, participants were less likely to identify the paired pulse as strongest, than when the isi was 350 or 450 ms. This study emphasizes the importance of basing stimulation paradigms on the underlying neural physiology. The results indicate there is an upper limit to the commonly accepted notion that higher stimulation frequencies lead to stronger perception. If frequency is to be used to encode sensory events, then the results suggest stimulus paradigms should be designed using frequencies below 125 Hz.
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46
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Pasluosta C, Kiele P, Čvančara P, Micera S, Aszmann OC, Stieglitz T. Bidirectional bionic limbs: a perspective bridging technology and physiology. J Neural Eng 2022; 19. [PMID: 35132954 DOI: 10.1088/1741-2552/ac4bff] [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: 07/12/2021] [Accepted: 01/17/2022] [Indexed: 11/11/2022]
Abstract
Precise control of bionic limbs relies on robust decoding of motor commands from nerves or muscles signals and sensory feedback from artificial limbs to the nervous system by interfacing the afferent nerve pathways. Implantable devices for bidirectional communication with bionic limbs have been developed in parallel with research on physiological alterations caused by an amputation. In this perspective article, we question whether increasing our effort on bridging these technologies with a deeper understanding of amputation pathophysiology and human motor control may help to overcome pressing stalls in the next generation of bionic limbs.
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Affiliation(s)
- C Pasluosta
- Laboratory for Biomedical Microtechnology, Department of Microsystems Engineering, University of Freiburg, Freiburg, Germany
| | - P Kiele
- Laboratory for Biomedical Microtechnology, Department of Microsystems Engineering, University of Freiburg, Freiburg, Germany
| | - P Čvančara
- Laboratory for Biomedical Microtechnology, Department of Microsystems Engineering, University of Freiburg, Freiburg, Germany.,BrainLinks-BrainTools, University of Freiburg, Freiburg, Germany
| | - S Micera
- School of Engineering, École Polytechnique Fédérale de Lausanne, Bertarelli Foundation Chair in Translational Neuroengineering, Centre for Neuroprosthetics and Institute of Bioengineering, Lausanne, Switzerland.,The BioRobotics Institute and Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Pisa, Italy
| | - O C Aszmann
- Clinical Laboratory for Bionic Extremity Reconstruction, Medical University of Vienna; Division of Plastic and Reconstructive Surgery, Department of Surgery, Medical University of Vienna, Vienna, Austria
| | - T Stieglitz
- Laboratory for Biomedical Microtechnology, Department of Microsystems Engineering, University of Freiburg, Freiburg, Germany.,Bernstein Center Freiburg, University of Freiburg, Freiburg, Germany.,BrainLinks-BrainTools, University of Freiburg, Freiburg, Germany
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47
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Surgical and Technological Advances in the Management of Upper Limb Amputation. CURRENT PHYSICAL MEDICINE AND REHABILITATION REPORTS 2022. [DOI: 10.1007/s40141-022-00341-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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48
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Vomero M, Ciarpella F, Zucchini E, Kirsch M, Fadiga L, Stieglitz T, Asplund M. On the longevity of flexible neural interfaces: Establishing biostability of polyimide-based intracortical implants. Biomaterials 2022; 281:121372. [DOI: 10.1016/j.biomaterials.2022.121372] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 12/27/2021] [Accepted: 01/10/2022] [Indexed: 11/02/2022]
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49
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Valle G, Iberite F, Strauss I, D'Anna E, Granata G, Di Iorio R, Stieglitz T, Raspopovic S, Petrini FM, Rossini PM, Micera S. A Psychometric Platform to Collect Somatosensory Sensations for Neuroprosthetic Use. FRONTIERS IN MEDICAL TECHNOLOGY 2022; 3:619280. [PMID: 35047903 PMCID: PMC8757828 DOI: 10.3389/fmedt.2021.619280] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Accepted: 02/08/2021] [Indexed: 11/13/2022] Open
Abstract
Somatosensory neuroprostheses exploit invasive and non-invasive feedback technologies to restore sensorimotor functions lost to disease or trauma. These devices use electrical stimulation to communicate sensory information to the brain. A sensation characterization procedure is thus necessary to determine the appropriate stimulation parameters and to establish a clear personalized map of the sensations that can be restored. Several questionnaires have been described in the literature to collect the quality, type, location, and intensity of the evoked sensations, but there is still no standard psychometric platform. Here, we propose a new psychometric system containing previously validated questionnaires on evoked sensations, which can be applied to any kind of somatosensory neuroprosthesis. The platform collects stimulation parameters used to elicit sensations and records subjects' percepts in terms of sensation location, type, quality, perceptual threshold, and intensity. It further collects data using standardized assessment questionnaires and scales, performs measurements over time, and collects phantom limb pain syndrome data. The psychometric platform is user-friendly and provides clinicians with all the information needed to assess the sensory feedback. The psychometric platform was validated with three trans-radial amputees. The platform was used to assess intraneural sensory feedback provided through implanted peripheral nerve interfaces. The proposed platform could act as a new standardized assessment toolbox to homogenize the reporting of results obtained with different technologies in the field of somatosensory neuroprosthetics.
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Affiliation(s)
- Giacomo Valle
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.,Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, Zurich, Switzerland
| | | | - Ivo Strauss
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Edoardo D'Anna
- Bertarelli Foundation Chair in Translational Neuroengineering, Centre for Neuroprosthetics, School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Institute of Bioengineering, Lausanne, Switzerland
| | - Giuseppe Granata
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS)-Policlinic A. Gemelli Foundation, Institute of Neurology, Catholic University of the Sacred Heart, Rome, Italy
| | - Riccardo Di Iorio
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS)-Policlinic A. Gemelli Foundation, Institute of Neurology, Catholic University of the Sacred Heart, Rome, Italy
| | - Thomas Stieglitz
- Laboratory for Biomedical Microtechnology, Department of Microsystems Engineering-IMTEK, Bernstein Center, BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Freiburg, Germany
| | - Stanisa Raspopovic
- Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, Zurich, Switzerland
| | - Francesco M Petrini
- Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, Zurich, Switzerland
| | - Paolo M Rossini
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS)-Policlinic A. Gemelli Foundation, Institute of Neurology, Catholic University of the Sacred Heart, Rome, Italy
| | - Silvestro Micera
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.,Bertarelli Foundation Chair in Translational Neuroengineering, Centre for Neuroprosthetics, School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Institute of Bioengineering, Lausanne, Switzerland
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50
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Losanno E, Badi M, Wurth S, Borgognon S, Courtine G, Capogrosso M, Rouiller EM, Micera S. Bayesian optimization of peripheral intraneural stimulation protocols to evoke distal limb movements. J Neural Eng 2021; 18. [PMID: 34874320 DOI: 10.1088/1741-2552/ac3f6c] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 12/02/2021] [Indexed: 11/12/2022]
Abstract
Objective.Motor neuroprostheses require the identification of stimulation protocols that effectively produce desired movements. Manual search for these protocols can be very time-consuming and often leads to suboptimal solutions, as several stimulation parameters must be personalized for each subject for a variety of target motor functions. Here, we present an algorithm that efficiently tunes peripheral intraneural stimulation protocols to elicit functionally relevant distal limb movements.Approach.We developed the algorithm using Bayesian optimization (BO) with multi-output Gaussian Processes (GPs) and defined objective functions based on coordinated muscle recruitment. We applied the algorithm offline to data acquired in rats for walking control and in monkeys for hand grasping control and compared different GP models for these two systems. We then performed a preliminary online test in a monkey to experimentally validate the functionality of our method.Main results.Offline, optimal intraneural stimulation protocols for various target motor functions were rapidly identified in both experimental scenarios. Using the model that performed best, the algorithm converged to stimuli that evoked functionally consistent movements with an average number of actions equal to 20% of the search space size in both the rat and monkey animal models. Online, the algorithm quickly guided the observations to stimuli that elicited functional hand gestures, although more selective motor outputs could have been achieved by refining the objective function used.Significance.These results demonstrate that BO can reliably and efficiently automate the tuning of peripheral neurostimulation protocols, establishing a translational framework to configure peripheral motor neuroprostheses in clinical applications. The proposed method can also potentially be applied to optimize motor functions using other stimulation modalities.
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Affiliation(s)
- E Losanno
- The Biorobotics Institute and Department of Excellent in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - M Badi
- Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics and Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - S Wurth
- Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics and Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - S Borgognon
- Department of Neuroscience and Movement Sciences, Platform of Translational Neurosciences, Section of Medicine, Faculty of Sciences and Medicine, University of Fribourg, Fribourg, Switzerland.,Center for Neuroprosthetics and BrainMind Institute, School of Life Sciences, Eécole Polytechnique Feédeérale de Lausanne (EPFL), Lausanne, Switzerland
| | - G Courtine
- Center for Neuroprosthetics and BrainMind Institute, School of Life Sciences, Eécole Polytechnique Feédeérale de Lausanne (EPFL), Lausanne, Switzerland.,Defitech Center for Interventional Neurotherapies (NeuroRestore), EPFL, University Hospital of Lausanne (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - M Capogrosso
- Department of Neurological Surgery, Rehabilitation and Neural Engineering Laboratories, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - E M Rouiller
- Department of Neuroscience and Movement Sciences, Platform of Translational Neurosciences, Section of Medicine, Faculty of Sciences and Medicine, University of Fribourg, Fribourg, Switzerland
| | - S Micera
- The Biorobotics Institute and Department of Excellent in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy.,Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics and Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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