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Graczyk E, Hutchison B, Valle G, Bjanes D, Gates D, Raspopovic S, Gaunt R. Clinical Applications and Future Translation of Somatosensory Neuroprostheses. J Neurosci 2024; 44:e1237242024. [PMID: 39358021 PMCID: PMC11450537 DOI: 10.1523/jneurosci.1237-24.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2024] [Revised: 07/28/2024] [Accepted: 07/29/2024] [Indexed: 10/04/2024] Open
Abstract
Somatosensory neuroprostheses restore, replace, or enhance tactile and proprioceptive feedback for people with sensory impairments due to neurological disorders or injury. Somatosensory neuroprostheses typically couple sensor inputs from a wearable device, prosthesis, robotic device, or virtual reality system with electrical stimulation applied to the somatosensory nervous system via noninvasive or implanted interfaces. While prior research has mainly focused on technology development and proof-of-concept studies, recent acceleration of clinical studies in this area demonstrates the translational potential of somatosensory neuroprosthetic systems. In this review, we provide an overview of neurostimulation approaches currently undergoing human testing and summarize recent clinical findings on the perceptual, functional, and psychological impact of somatosensory neuroprostheses. We also cover current work toward the development of advanced stimulation paradigms to produce more natural and informative sensory feedback. Finally, we provide our perspective on the remaining challenges that need to be addressed prior to translation of somatosensory neuroprostheses.
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Affiliation(s)
- Emily Graczyk
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106
- Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, Ohio 44106
| | - Brianna Hutchison
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106
| | - Giacomo Valle
- Department of Electrical Engineering, Chalmers University of Technology, Goteborg 41296, Sweden
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, Illinois 60637
| | - David Bjanes
- Division of Biology and Biological Engineering and Tianqiao & Chrissy Chen Brain-Machine Interface Center, California Institute of Technology, Pasadena, California 91125
| | - Deanna Gates
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan 48109
- School of Kinesiology, University of Michigan, Ann Arbor, Michigan 48109
| | - Stanisa Raspopovic
- Laboratory for Neuroengineering, Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH Zurich, Zurich 8092, Switzerland
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna 1090, Austria
| | - Robert Gaunt
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, Pennsylvania 15219
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, Pennsylvania 15213
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2
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Rosario M, Zhang J, Kaleem MI, Chandra N, Yan Y, Moran D, Wood M, Ray WZ, MacEwan M. A method for quantitative spatial analysis of immunolabeled fibers at regenerative electrode interfaces. J Neurosci Methods 2024; 412:110295. [PMID: 39321988 DOI: 10.1016/j.jneumeth.2024.110295] [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: 06/15/2024] [Revised: 09/10/2024] [Accepted: 09/22/2024] [Indexed: 09/27/2024]
Abstract
BACKGROUND Regenerative electrodes are being explored as robust peripheral nerve interfaces for neuro-prosthetic control and sensory feedback. Current designs differ in electrode number, spatial arrangement, and porosity which impacts the regeneration, activation, and spatial distribution of fibers at the device interface. Knowledge of sensory and motor fiber distributions are important in optimizing selective fiber activation and recording. NEW METHOD We use confocal microscopy and immunofluorescence methods to conduct spatial analysis of immunolabeled fibers across whole nerve cross sections. RESULTS This protocol was implemented to characterize motor fiber distribution within 3 macro-sieve electrode regenerated (MSE), 3 silicone-conduit regenerated, and 3 unmanipulated control rodent sciatic nerves. Total motor fiber counts were 1485 [SD: +/- 50.11], 1899 [SD: +/- 359], and 5732 [SD: +/- 1410] for control, MSE, and conduit nerves respectively. MSE motor fiber distributions exhibited evidence of deviation from complete spatial randomness and evidence of dispersion and clustering tendencies at varying scales. Notably, MSE motor fibers exhibited clustering within the central portion of the cross section, whereas conduit regenerated motor fibers exhibited clustering along the periphery. COMPARISON WITH EXISTING METHODS Prior exploration of fiber distributions at regenerative interfaces was limited to either quadrant-based density analysis of randomly sampled subregions or qualitative description. This method extends existing sample preparation and microscopy techniques to quantitatively assess immunolabeled fiber distributions within whole nerve cross-sections. CONCLUSIONS This approach is an effective way to examine the spatial organization of fiber subsets at regenerative electrode interfaces, enabling robust assessment of fiber distributions relative to electrode arrangement.
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Affiliation(s)
- Michael Rosario
- Washington University School of Medicine in Saint Louis, Saint Louis, MO, USA
| | - Jingyuan Zhang
- Department of Neurological Surgery, Washington University School of Medicine in Saint Louis, Saint Louis, MO, USA
| | - Muhammad Irfan Kaleem
- Department of Neurological Surgery, Washington University School of Medicine in Saint Louis, Saint Louis, MO, USA
| | - Nikhil Chandra
- Department of Neurological Surgery, Washington University School of Medicine in Saint Louis, Saint Louis, MO, USA
| | - Ying Yan
- Department of Neurological Surgery, Washington University School of Medicine in Saint Louis, Saint Louis, MO, USA
| | - Daniel Moran
- McKelvey School of Biomedical Engineering, Washington University in Saint Louis, Saint Louis, MO, USA
| | - Matthew Wood
- Division of Plastic and Reconstructive Surgery, Department of Surgery, Washington University School of Medicine in Saint Louis, St. Louis, MO 63110, USA
| | - Wilson Z Ray
- Department of Neurological Surgery, Washington University School of Medicine in Saint Louis, Saint Louis, MO, USA; McKelvey School of Biomedical Engineering, Washington University in Saint Louis, Saint Louis, MO, USA
| | - Matthew MacEwan
- Department of Neurological Surgery, Washington University School of Medicine in Saint Louis, Saint Louis, MO, USA; McKelvey School of Biomedical Engineering, Washington University in Saint Louis, Saint Louis, MO, USA.
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3
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Nanivadekar AC, Bose R, Petersen BA, Okorokova EV, Sarma D, Madonna TJ, Barra B, Farooqui J, Dalrymple AN, Levy I, Helm ER, Miele VJ, Boninger ML, Capogrosso M, Bensmaia SJ, Weber DJ, Fisher LE. Restoration of sensory feedback from the foot and reduction of phantom limb pain via closed-loop spinal cord stimulation. Nat Biomed Eng 2024; 8:992-1003. [PMID: 38097809 PMCID: PMC11404213 DOI: 10.1038/s41551-023-01153-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 10/27/2023] [Indexed: 12/30/2023]
Abstract
Restoring somatosensory feedback in individuals with lower-limb amputations would reduce the risk of falls and alleviate phantom limb pain. Here we show, in three individuals with transtibial amputation (one traumatic and two owing to diabetic peripheral neuropathy), that sensations from the missing foot, with control over their location and intensity, can be evoked via lateral lumbosacral spinal cord stimulation with commercially available electrodes and by modulating the intensity of stimulation in real time on the basis of signals from a wireless pressure-sensitive shoe insole. The restored somatosensation via closed-loop stimulation improved balance control (with a 19-point improvement in the composite score of the Sensory Organization Test in one individual) and gait stability (with a 5-point improvement in the Functional Gait Assessment in one individual). And over the implantation period of the stimulation leads, the three individuals experienced a clinically meaningful decrease in phantom limb pain (with an average reduction of nearly 70% on a visual analogue scale). Our findings support the further clinical assessment of lower-limb neuroprostheses providing somatosensory feedback.
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Affiliation(s)
- Ameya C Nanivadekar
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Rohit Bose
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Bailey A Petersen
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Elizaveta V Okorokova
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL, USA
| | - Devapratim Sarma
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Tyler J Madonna
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beatrice Barra
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Neuroscience and Movement Science, University of Fribourg, Fribourg, Switzerland
| | - Juhi Farooqui
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Ashley N Dalrymple
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA
- Department of Physical Medicine and Rehabilitation, University of Utah, Salt Lake City, UT, USA
| | - Isaiah Levy
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Eric R Helm
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Vincent J Miele
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Michael L Boninger
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Marco Capogrosso
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Sliman J Bensmaia
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL, USA
| | - Douglas J Weber
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Lee E Fisher
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA.
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA.
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4
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Malešević N, Antfolk C. Sensory feedback in upper limb prosthetics: advances and challenges. Nat Rev Neurol 2024; 20:449-450. [PMID: 38945981 DOI: 10.1038/s41582-024-00987-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Affiliation(s)
- Nebojša Malešević
- Department of Biomedical Engineering, Faculty of Engineering, Lund University, Lund, Sweden
| | - Christian Antfolk
- Department of Biomedical Engineering, Faculty of Engineering, Lund University, Lund, Sweden.
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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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6
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Erbaş İ, Güçlü B. Real-time vibrotactile pattern generation and identification using discrete event-driven feedback. Somatosens Mot Res 2024; 41:77-89. [PMID: 36751096 DOI: 10.1080/08990220.2023.2175811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Accepted: 01/30/2023] [Indexed: 02/09/2023]
Abstract
This study assesses human identification of vibrotactile patterns by using real-time discrete event-driven feedback. Previously acquired force and bend sensor data from a robotic hand were used to predict movement-type (stationary, flexion, contact, extension, release) and object-type (no object, hard object, soft object) states by using decision tree (DT) algorithms implemented in a field-programmable gate array (FPGA). Six able-bodied humans performed a 2- and 3-step sequential pattern recognition task in which state transitions were signaled as vibrotactile feedback. The stimuli were generated according to predicted classes represented by two frequencies (F1: 80 Hz, F2: 180 Hz) and two magnitudes (M1: low, M2: high) calibrated psychophysically for each participant; and they were applied by two actuators (Haptuators) placed on upper arms. A soft/hard object was mapped to F1/F2; and manipulating it with low/high force was assigned to M1/M2 in the left actuator. On the other hand, flexion/extension movement was mapped to F1/F2 in the right actuator, with movement in air as M1 and during object manipulation as M2. DT algorithm performed better for the object-type (97%) than the movement-type (88%) classification in real time. Participants could recognize feedback associated with 14 discrete-event sequences with low-to-medium accuracy. The performance was higher (76 ± 9% recall, 76 ± 17% precision, 78 ± 4% accuracy) for recognizing any one event in the sequences. The results show that FPGA implementation of classification for discrete event-driven vibrotactile feedback can be feasible in haptic devices with additional cues in the physical context.
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Affiliation(s)
- İsmail Erbaş
- Biomedical Engineering Department, Rensselaer Polytechnic Institute, Troy, NY, USA
| | - Burak Güçlü
- Institute of Biomedical Engineering, Boğaziçi University, İstanbul, Turkey
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7
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Kundu A, Patrick E, Currlin S, Madler R, Delgado F, Fahmy A, Verplancke R, Ballini M, Braeken D, de Beeck MO, Maghari N, Otto KJ, Bashirullah R. Using Compound Neural Action Potentials for Functional Validation of a High-Density Intraneural Interface: A Preliminary Study. MICROMACHINES 2024; 15:280. [PMID: 38399008 PMCID: PMC10891740 DOI: 10.3390/mi15020280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 02/14/2024] [Accepted: 02/15/2024] [Indexed: 02/25/2024]
Abstract
Compound nerve action potentials (CNAPs) were used as a metric to assess the stimulation performance of a novel high-density, transverse, intrafascicular electrode in rat models. We show characteristic CNAPs recorded from distally implanted cuff electrodes. Evaluation of the CNAPs as a function of stimulus current and calculation of recruitment plots were used to obtain a qualitative approximation of the neural interface's placement and orientation inside the nerve. This method avoids elaborate surgeries required for the implantation of EMG electrodes and thus minimizes surgical complications and may accelerate the healing process of the implanted subject.
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Affiliation(s)
- Aritra Kundu
- Department of Bioengineering, Imperial College London, SW7 2AZ London, UK
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, USA; (E.P.); (N.M.)
| | - Erin Patrick
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, USA; (E.P.); (N.M.)
| | - Seth Currlin
- Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA (K.J.O.)
| | - Ryan Madler
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, USA; (E.P.); (N.M.)
| | - Francisco Delgado
- Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA (K.J.O.)
| | - Ahmed Fahmy
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, USA; (E.P.); (N.M.)
| | - Rik Verplancke
- Centre for Microsystems Technology (CMST), IMEC and Ghent University, 9052 Zwijnaarde, Belgium (M.O.d.B.)
| | | | | | - Maaike Op de Beeck
- Centre for Microsystems Technology (CMST), IMEC and Ghent University, 9052 Zwijnaarde, Belgium (M.O.d.B.)
- IMEC, Kapeldreef 75, 3001 Leuven, Belgium;
| | - Nima Maghari
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, USA; (E.P.); (N.M.)
| | - Kevin J. Otto
- Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA (K.J.O.)
| | - Rizwan Bashirullah
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, USA; (E.P.); (N.M.)
- Galvani Bioelectronics, South San Francisco, CA 94080, USA
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8
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Morales AW, Du J, Warren DJ, Fernández-Jover E, Martinez-Navarrete G, Bouteiller JMC, McCreery DC, Lazzi G. Machine learning enables non-Gaussian investigation of changes to peripheral nerves related to electrical stimulation. Sci Rep 2024; 14:2795. [PMID: 38307915 PMCID: PMC10837107 DOI: 10.1038/s41598-024-53284-w] [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: 01/12/2023] [Accepted: 01/30/2024] [Indexed: 02/04/2024] Open
Abstract
Electrical stimulation of the peripheral nervous system (PNS) is becoming increasingly important for the therapeutic treatment of numerous disorders. Thus, as peripheral nerves are increasingly the target of electrical stimulation, it is critical to determine how, and when, electrical stimulation results in anatomical changes in neural tissue. We introduce here a convolutional neural network and support vector machines for cell segmentation and analysis of histological samples of the sciatic nerve of rats stimulated with varying current intensities. We describe the methodologies and present results that highlight the validity of the approach: machine learning enabled highly efficient nerve measurement collection, while multivariate analysis revealed notable changes to nerves' anatomy, even when subjected to levels of stimulation thought to be safe according to the Shannon current limits.
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Affiliation(s)
- Andres W Morales
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, 90089, USA.
| | - Jinze Du
- Department of Electrical Engineering, University of Southern California, Los Angeles, CA, 90089, USA
| | - David J Warren
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, 84112, USA
| | | | | | - Jean-Marie C Bouteiller
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, 90089, USA
- Institute for Technology and Medical Systems (ITEMS), Keck School of Medicine, University of Southern California, Los Angeles, CA, 90089, USA
| | | | - Gianluca Lazzi
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, 90089, USA
- Department of Electrical Engineering, University of Southern California, Los Angeles, CA, 90089, USA
- Department of Ophthalmology, University of Southern California, Los Angeles, CA, 90089, USA
- Institute for Technology and Medical Systems (ITEMS), Keck School of Medicine, University of Southern California, Los Angeles, CA, 90089, USA
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9
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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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10
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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: 3] [Impact Index Per Article: 3.0] [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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11
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Ionescu ON, Franti E, Carbunaru V, Moldovan C, Dinulescu S, Ion M, Dragomir DC, Mihailescu CM, Lascar I, Oproiu AM, Neagu TP, Costea R, Dascalu M, Teleanu MD, Ionescu G, Teleanu R. System of Implantable Electrodes for Neural Signal Acquisition and Stimulation for Wirelessly Connected Forearm Prosthesis. BIOSENSORS 2024; 14:31. [PMID: 38248408 PMCID: PMC10813559 DOI: 10.3390/bios14010031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 12/31/2023] [Accepted: 01/02/2024] [Indexed: 01/23/2024]
Abstract
There is great interest in the development of prosthetic limbs capable of complex activities that are wirelessly connected to the patient's neural system. Although some progress has been achieved in this area, one of the main problems encountered is the selective acquisition of nerve impulses and the closing of the automation loop through the selective stimulation of the sensitive branches of the patient. Large-scale research and development have achieved so-called "cuff electrodes"; however, they present a big disadvantage: they are not selective. In this article, we present the progress made in the development of an implantable system of plug neural microelectrodes that relate to the biological nerve tissue and can be used for the selective acquisition of neuronal signals and for the stimulation of specific nerve fascicles. The developed plug electrodes are also advantageous due to their small thickness, as they do not trigger nerve inflammation. In addition, the results of the conducted tests on a sous scrofa subject are presented.
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Affiliation(s)
- Octavian Narcis Ionescu
- Faculty of Mechanical and Electrical Engineering, Petroleum and Gas University from Ploiesti, 100680 Ploiesti, Romania; (O.N.I.); (G.I.)
- National Institute for Research and Development for Microtechnology Bucharest, 077190 Bucharest, Romania; (C.M.); (S.D.); (M.I.); (D.C.D.); (C.M.M.)
| | - Eduard Franti
- National Institute for Research and Development for Microtechnology Bucharest, 077190 Bucharest, Romania; (C.M.); (S.D.); (M.I.); (D.C.D.); (C.M.M.)
- ICIA, Centre of New Electronic Architectures, 061071 Bucharest, Romania;
| | - Vlad Carbunaru
- Emergency Clinic Hospital Bucharest, 014461 Bucharest, Romania; (V.C.); (I.L.); (A.M.O.); (T.P.N.)
- University of Medicine and Pharmacy UMF Carol Davila, 050474 Bucharest, Romania; (M.D.T.); (R.T.)
| | - Carmen Moldovan
- National Institute for Research and Development for Microtechnology Bucharest, 077190 Bucharest, Romania; (C.M.); (S.D.); (M.I.); (D.C.D.); (C.M.M.)
| | - Silviu Dinulescu
- National Institute for Research and Development for Microtechnology Bucharest, 077190 Bucharest, Romania; (C.M.); (S.D.); (M.I.); (D.C.D.); (C.M.M.)
| | - Marian Ion
- National Institute for Research and Development for Microtechnology Bucharest, 077190 Bucharest, Romania; (C.M.); (S.D.); (M.I.); (D.C.D.); (C.M.M.)
| | - David Catalin Dragomir
- National Institute for Research and Development for Microtechnology Bucharest, 077190 Bucharest, Romania; (C.M.); (S.D.); (M.I.); (D.C.D.); (C.M.M.)
| | - Carmen Marinela Mihailescu
- National Institute for Research and Development for Microtechnology Bucharest, 077190 Bucharest, Romania; (C.M.); (S.D.); (M.I.); (D.C.D.); (C.M.M.)
| | - Ioan Lascar
- Emergency Clinic Hospital Bucharest, 014461 Bucharest, Romania; (V.C.); (I.L.); (A.M.O.); (T.P.N.)
- University of Medicine and Pharmacy UMF Carol Davila, 050474 Bucharest, Romania; (M.D.T.); (R.T.)
| | - Ana Maria Oproiu
- Emergency Clinic Hospital Bucharest, 014461 Bucharest, Romania; (V.C.); (I.L.); (A.M.O.); (T.P.N.)
- University of Medicine and Pharmacy UMF Carol Davila, 050474 Bucharest, Romania; (M.D.T.); (R.T.)
| | - Tiberiu Paul Neagu
- Emergency Clinic Hospital Bucharest, 014461 Bucharest, Romania; (V.C.); (I.L.); (A.M.O.); (T.P.N.)
- University of Medicine and Pharmacy UMF Carol Davila, 050474 Bucharest, Romania; (M.D.T.); (R.T.)
| | - Ruxandra Costea
- Faculty of Veterinary Medicine, University of Agricultural Sciences and Veterinary Medicine of Bucharest, 011464 Bucharest, Romania;
| | - Monica Dascalu
- ICIA, Centre of New Electronic Architectures, 061071 Bucharest, Romania;
- Faculty of Electronics, Telecommunications and Information Technology, National University of Science and Technology Politehnica of Bucharest, 060042 Bucharest, Romania
| | - Mihai Daniel Teleanu
- University of Medicine and Pharmacy UMF Carol Davila, 050474 Bucharest, Romania; (M.D.T.); (R.T.)
| | - Gabriela Ionescu
- Faculty of Mechanical and Electrical Engineering, Petroleum and Gas University from Ploiesti, 100680 Ploiesti, Romania; (O.N.I.); (G.I.)
| | - Raluca Teleanu
- University of Medicine and Pharmacy UMF Carol Davila, 050474 Bucharest, Romania; (M.D.T.); (R.T.)
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12
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Zhang J, Chou CH, Hao M, Li Y, Yu Y, Lan N. Fusion of dual modalities of non-invasive sensory feedback for object profiling with prosthetic hands. Front Neurorobot 2023; 17:1298176. [PMID: 38162892 PMCID: PMC10757719 DOI: 10.3389/fnbot.2023.1298176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 11/24/2023] [Indexed: 01/03/2024] Open
Abstract
Introduction Either non-invasive somatotopic or substitute sensory feedback is capable of conveying a single modality of sensory information from prosthetic hands to amputees. However, the neurocognitive ability of amputees to integrate multi-modality sensory information for functional discrimination is unclear. The purpose of this study was to assess the fusion of non-invasive somatotopic tactile and substitute aperture feedbacks for profile perception of multiple physical features during grasping objects. Methods Two left transradial amputees with somatotopic evoked tactile sensation (ETS) of five fingers participated in the study. The tactile information of prosthetic hand was provided to amputees by the ETS feedback elicited on the stump projected finger map. Hand aperture information was conveyed to amputees with substitute electrotactile stimulation on the forearm or upper arm. Two types of sensory feedback were integrated to a commercial prosthetic hand. The efficacy of somatotopic ETS feedback on object length identification task was assessed with or without substitute aperture stimulation. The object size identification task was utilized to assess how ETS stimulation at the stump may affect aperture perception with stimulation on the ipsilateral upper arm or forearm. Finally, the task of identifying combined length and size was conducted to evaluate the ability of amputees to integrate the dual modalities of sensory feedback for perceiving profile features. Results The study revealed that amputee subjects can effectively integrate the ETS feedback with electrotactile substitutive feedback for object profile discrimination. Specifically, ETS was robust to provide object length information with electrotactile stimulation at either the forearm or upper arm. However, electrotactile stimulation at the upper arm for aperture perception was less susceptible to the interference of ETS stimulation than at the forearm. Discussion Amputee subjects are able to combine somatotopic ETS and aperture feedbacks for identifying multi-dimensional features in object profiling. The two sensory streams of information can be fused effectively without mutual interference for functional discrimination.
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Affiliation(s)
- Jie Zhang
- Laboratory of NeuroRehabilitation Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Chih-Hong Chou
- Laboratory of NeuroRehabilitation Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
- Institute of Medical Robotics, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Manzhao Hao
- Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yan Li
- Laboratory of NeuroRehabilitation Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yashuo Yu
- Laboratory of NeuroRehabilitation Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Ning Lan
- Laboratory of NeuroRehabilitation Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
- Institute of Medical Robotics, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
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13
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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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14
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Leach GA, Dean RA, Kumar NG, Tsai C, Chiarappa FE, Cederna PS, Kung TA, Reid CM. Regenerative Peripheral Nerve Interface Surgery: Anatomic and Technical Guide. PLASTIC AND RECONSTRUCTIVE SURGERY-GLOBAL OPEN 2023; 11:e5127. [PMID: 37465283 PMCID: PMC10351954 DOI: 10.1097/gox.0000000000005127] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 06/06/2023] [Indexed: 07/20/2023]
Abstract
Regenerative peripheral nerve interface (RPNI) surgery has been demonstrated to be an effective tool as an interface for neuroprosthetics. Additionally, it has been shown to be a reproducible and reliable strategy for the active treatment and for prevention of neuromas. The purpose of this article is to provide a comprehensive review of RPNI surgery to demonstrate its simplicity and empower reconstructive surgeons to add this to their armamentarium. This article discusses the basic science of neuroma formation and prevention, as well as the theory of RPNI. An anatomic review and discussion of surgical technique for each level of amputation and considerations for other etiologies of traumatic neuromas are included. Lastly, the authors discuss the future of RPNI surgery and compare this with other active techniques for the treatment of neuromas.
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Affiliation(s)
- Garrison A. Leach
- From the Department of General Surgery, Division of Plastic Surgery, University of California San Diego, La Jolla, Calif
| | - Riley A. Dean
- From the Department of General Surgery, Division of Plastic Surgery, University of California San Diego, La Jolla, Calif
| | - Nishant Ganesh Kumar
- Section of Plastic and Reconstructive Surgery and the Department of Biomedical Engineering, University of Michigan, Ann Arbor, Mich
| | - Catherine Tsai
- From the Department of General Surgery, Division of Plastic Surgery, University of California San Diego, La Jolla, Calif
| | - Frank E. Chiarappa
- Department of Orthopedic Surgery, University of California San Diego, La Jolla, Calif
| | - Paul S. Cederna
- Section of Plastic and Reconstructive Surgery and the Department of Biomedical Engineering, University of Michigan, Ann Arbor, Mich
| | - Theodore A. Kung
- Section of Plastic and Reconstructive Surgery and the Department of Biomedical Engineering, University of Michigan, Ann Arbor, Mich
| | - Chris M. Reid
- From the Department of General Surgery, Division of Plastic Surgery, University of California San Diego, La Jolla, Calif
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15
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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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16
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Tanner J, Keefer E, Cheng J, Helms Tillery S. Dynamic peripheral nerve stimulation can produce cortical activation similar to punctate mechanical stimuli. Front Hum Neurosci 2023; 17:1083307. [PMID: 37033904 PMCID: PMC10079952 DOI: 10.3389/fnhum.2023.1083307] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 02/28/2023] [Indexed: 04/11/2023] Open
Abstract
During contact, phasic and tonic responses provide feedback that is used for task performance and perceptual processes. These disparate temporal dynamics are carried in peripheral nerves, and produce overlapping signals in cortex. Using longitudinal intrafascicular electrodes inserted into the median nerve of a nonhuman primate, we delivered composite stimulation consisting of onset and release bursts to capture rapidly adapting responses and sustained stochastic stimulation to capture the ongoing response of slowly adapting receptors. To measure the stimulation's effectiveness in producing natural responses, we monitored the local field potential in somatosensory cortex. We compared the cortical responses to peripheral nerve stimulation and vibrotactile/punctate stimulation of the fingertip, with particular focus on gamma band (30-65 Hz) responses. We found that vibrotactile stimulation produces consistently phase locked gamma throughout the duration of the stimulation. By contrast, punctate stimulation responses were phase locked at the onset and release of stimulation, but activity maintained through the stimulation was not phase locked. Using these responses as guideposts for assessing the response to the peripheral nerve stimulation, we found that constant frequency stimulation produced continual phase locking, whereas composite stimulation produced gamma enhancement throughout the stimulus, phase locked only at the onset and release of the stimulus. We describe this response as an "Appropriate Response in the gamma band" (ARγ), a trend seen in other sensory systems. Our demonstration is the first shown for intracortical somatosensory local field potentials. We argue that this stimulation paradigm produces a more biomimetic response in somatosensory cortex and is more likely to produce naturalistic sensations for readily usable neuroprosthetic feedback.
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Affiliation(s)
- Justin Tanner
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, United States
| | | | - Jonathan Cheng
- University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Stephen Helms Tillery
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, United States
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17
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Abstract
The generation of an internal body model and its continuous update is essential in sensorimotor control. Although known to rely on proprioceptive sensory feedback, the underlying mechanism that transforms this sensory feedback into a dynamic body percept remains poorly understood. However, advances in the development of genetic tools for proprioceptive circuit elements, including the sensory receptors, are beginning to offer new and unprecedented leverage to dissect the central pathways responsible for proprioceptive encoding. Simultaneously, new data derived through emerging bionic neural machine-interface technologies reveal clues regarding the relative importance of kinesthetic sensory feedback and insights into the functional proprioceptive substrates that underlie natural motor behaviors.
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Affiliation(s)
- Paul D Marasco
- Laboratory for Bionic Integration, Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA;
- Charles Shor Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, USA
- Advanced Platform Technology Center, Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, Ohio, USA
| | - Joriene C de Nooij
- Department of Neurology and the Columbia University Motor Neuron Center, Columbia University Medical Center, New York, NY, USA;
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18
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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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19
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Opinions on noninvasive sensory feedback of upper limb prosthetic users. Prosthet Orthot Int 2022; 46:591-600. [PMID: 36515904 DOI: 10.1097/pxr.0000000000000160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 03/14/2022] [Indexed: 02/03/2023]
Abstract
BACKGROUND Restoring touch perception for individuals with upper extremity limb loss is an ambitious task. It is important to understand how persons with upper limb loss think this would be best achieved. METHODS An anonymous online survey was developed to obtain data from prosthetic users. Participants ranked the perceived acceptability and effectiveness of noninvasive sensory feedback to areas of intact sensation not typically involved in sensory feedback (i.e., the arm). The focus was on 4 main types of haptic information-object contact, proprioception, surface texture, and grasp force-as well as how best to convey those senses with various stimuli. The users were asked to grade themselves in certain tasks and then analyze which tasks would be improved with sensory feedback. Associations were explored between demographic characteristics and interest in sensory feedback. RESULTS Nationally, prostheses providers sent more than 2000 email invitations to the online survey and received 142 unique responses. Responses indicated interest in sensory feedback through prosthetic limbs by individuals with upper limb loss. The most popular pairing of haptic information with sensory substitution was grasp force paired with gentle vibration. Tasks that most persons taking the survey agreed would benefit from sensory feedback were zipping a jacket, tying shoes, buttoning a shirt, and using a cup. No difference was observed in interest between sex and employment status, but a significant decrease (P = .004) was seen in interest among participants with more years of prosthetic use. DISCUSSION The results from this national survey of upper extremity prosthetic users can be used to help guide the development of noninvasive sensory feedback options.
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20
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Schlichenmeyer TC, Zellmer ER, Burton H, Ray WZ, Moran DW. Detection and discrimination of electrical stimuli from an upper limb cuff electrode in M. Mulatta. J Neural Eng 2022; 19. [PMID: 36317300 DOI: 10.1088/1741-2552/ac9e76] [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: 04/22/2022] [Accepted: 10/28/2022] [Indexed: 11/07/2022]
Abstract
Objective.Peripheral nerve interfaces seek to restore nervous system function through electrical stimulation of peripheral nerves. In clinical use, these devices should function reliably for years or decades. In this study, we assessed evoked sensations from multi-channel cuff electrode stimulation in macaque monkeys up to 711 d post-implantation.Approach.Three trained macaque monkeys received multi-channel cuff electrode implants at the median or ulnar nerves in the upper arm. Electrical stimuli from the cuff interfaces evoked sensations, which we measured via standard psychophysical tasks. We adjusted pulse amplitude or pulse width for each block with various electrode channel configurations to examine the effects of stimulus parameterization on sensation. We measured detection thresholds and just-noticeable differences (JNDs) at irregular, near-daily intervals for several months using Bayesian inferencing from trial data. We examined data trends using classical models such as Weber's Law and the strength-duration relationship using linear regression.Main results.Detection thresholds were similar between blocks with pulse width modulation and blocks with pulse amplitude modulation when represented as charge per pulse, the product of the amplitude and the pulse width. Conversely, Weber fractions-calculated as the slope of the regression between JND charge values and reference stimulus charge-were significantly different between pulse width and pulse amplitude modulation blocks for the discrimination task.Significance.Weber fractions were lower in blocks with amplitude modulation than in blocks with pulse width modulation, suggesting that pulse amplitude modulation allows finer resolution of sensory encoding above threshold. Consequently, amplitude modulation may enable a greater dynamic range for sensory perception with neuroprosthetic devices.
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Affiliation(s)
- T C Schlichenmeyer
- Washington University in St Louis, 1 Brookings Dr, St Louis, MO 63118, United States of America
| | - E R Zellmer
- Washington University in St Louis, 1 Brookings Dr, St Louis, MO 63118, United States of America
| | - H Burton
- Washington University in St Louis, 1 Brookings Dr, St Louis, MO 63118, United States of America
| | - W Z Ray
- Washington University in St Louis, 1 Brookings Dr, St Louis, MO 63118, United States of America
| | - D W Moran
- Washington University in St Louis, 1 Brookings Dr, St Louis, MO 63118, United States of America
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21
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Dong M, Coleman HA, Tonta MA, Xiong Z, Li D, Thomas S, Liu M, Fallon JB, Parkington HC, Forsythe JS. Rapid electrophoretic deposition of biocompatible graphene coatings for high-performance recording neural electrodes. NANOSCALE 2022; 14:15845-15858. [PMID: 36259692 DOI: 10.1039/d2nr04421h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
The electrical and biological interfacial properties of invasive electrodes have a significant impact on the performance and longevity of neural recordings in the brain. In this study, we demonstrated rapid electrophoretic deposition and electrochemical reduction of graphene oxide (GO) on metal-based neural electrodes. Scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS) and other characterizations confirmed the existence of a uniform and effectively reduced graphene oxide coating. Electrochemically reduced graphene oxide (ErGO) coated Pt/Ir neural electrodes exhibited 15.2-fold increase in charge storage capacity (CSC) and 90% decrease in impedance with only 3.8% increase in electrode diameter. Patch clamp electrophysiology and calcium imaging of primary rat hippocampus neurons cultured on ErGO demonstrated that there was no adverse impact on the functional development of neurons. Immunostaining showed a balanced growth of excitatory and inhibitory neurons, and astrocytes. Acute recordings from the auditory cortex and chronic recordings (19 days) from the somatosensory cortex found ErGO coating improved the performance of neural electrodes in signal-to-noise ratio (SNR) and amplitude of signals. The proposed approach not only provides an in-depth evaluation of the effect of ErGO coating on neural electrodes but also widens the coating methods of commercial neural electrodes.
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Affiliation(s)
- Miheng Dong
- Department of Materials Science and Engineering, Monash Institute of Medical Engineering, Monash University, Clayton, VIC 3800, Australia.
- Monash Suzhou Research Institute, Monash University, Suzhou SIP 250000, China
| | - Harold A Coleman
- Department of Physiology, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia
| | - Mary A Tonta
- Department of Physiology, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia
| | - Zhiyuan Xiong
- Department of Chemical Engineering, University of Melbourne, Parkville, Victoria, Australia
| | - Dan Li
- Department of Chemical Engineering, University of Melbourne, Parkville, Victoria, Australia
| | - Sebastian Thomas
- Department of Materials Science and Engineering, Monash Institute of Medical Engineering, Monash University, Clayton, VIC 3800, Australia.
| | - Minsu Liu
- Department of Materials Science and Engineering, Monash Institute of Medical Engineering, Monash University, Clayton, VIC 3800, Australia.
- Monash Suzhou Research Institute, Monash University, Suzhou SIP 250000, China
- Foshan (Southern China) Institute for New Materials, Foshan 528200, China
| | - James B Fallon
- The Bionics Institute, East Melbourne, Victoria 3002, Australia
- Medical Bionics Department, University of Melbourne, Parkville, Victoria 3010, Australia
| | - Helena C Parkington
- Department of Physiology, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia
| | - John S Forsythe
- Department of Materials Science and Engineering, Monash Institute of Medical Engineering, Monash University, Clayton, VIC 3800, Australia.
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22
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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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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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24
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Lee H, Kim D, Park YL. Explainable Deep Learning Model for EMG-Based Finger Angle Estimation Using Attention. IEEE Trans Neural Syst Rehabil Eng 2022; 30:1877-1886. [PMID: 35834448 DOI: 10.1109/tnsre.2022.3188275] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Electromyography (EMG) is one of the most common methods to detect muscle activities and intentions. However, it has been difficult to estimate accurate hand motions represented by the finger joint angles using EMG signals. We propose an encoder-decoder network with an attention mechanism, an explainable deep learning model that estimates 14 finger joint angles from forearm EMG signals. This study demonstrates that the model trained by the single-finger motion data can be generalized to estimate complex motions of random fingers. The color map result of the after-training attention matrix shows that the proposed attention algorithm enables the model to learn the nonlinear relationship between the EMG signals and the finger joint angles, which is explainable. The highly activated entries in the color map of the attention matrix derived from model training are consistent with the experimental observations in which certain EMG sensors are highly activated when a particular finger moves. In summary, this study proposes an explainable deep learning model that estimates finger joint angles based on EMG signals of the forearm using the attention mechanism.
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25
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Koh RGL, Zariffa J, Jabban L, Yen SC, Donaldson N, Metcalfe BW. Tutorial: A guide to techniques for analysing recordings from the peripheral nervous system. J Neural Eng 2022; 19. [PMID: 35772397 DOI: 10.1088/1741-2552/ac7d74] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 06/30/2022] [Indexed: 11/11/2022]
Abstract
The nervous system, through a combination of conscious and automatic processes, enables the regulation of the body and its interactions with the environment. The peripheral nervous system is an excellent target for technologies that seek to modulate, restore or enhance these abilities as it carries sensory and motor information that most directly relates to a target organ or function. However, many applications require a combination of both an effective peripheral nerve interface and effective signal processing techniques to provide selective and stable recordings. While there are many reviews on the design of peripheral nerve interfaces, reviews of data analysis techniques and translational considerations are limited. Thus, this tutorial aims to support new and existing researchers in the understanding of the general guiding principles, and introduces a taxonomy for electrode configurations, techniques and translational models to consider.
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Affiliation(s)
- Ryan G L Koh
- IBBME, University of Toronto, Rosebrugh Bldg, 164 College St Room 407, Toronto, Ontario, M5S 3G9, CANADA
| | - Jose Zariffa
- Research, Toronto Rehabilitation Institute - University Health Network, 550 University Ave, #12-102, Toronto, Ontario, M5G 2A2, CANADA
| | - Leen Jabban
- Electronic and Electrical Engineering, University of Bath, Electronic and Electrical Engineering, Claverton Down, Bath, Bath, BA2 7AY, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Shih-Cheng Yen
- Engineering Design and Innovation Centre, National University of Singapore, 21 Lower Kent Ridge Road, Singapore, 119077, SINGAPORE
| | - Nick Donaldson
- Medical Physics and Bioengineering, University College London, Gower Street, London, WC1E 6BT, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Benjamin W Metcalfe
- Electronics & Electrical Engineering, University of Bath, Claverton Down, Bath, Somerset, BA2 7JY, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
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Guémann M, Halgand C, Bastier A, Lansade C, Borrini L, Lapeyre É, Cattaert D, de Rugy A. Sensory substitution of elbow proprioception to improve myoelectric control of upper limb prosthesis: experiment on healthy subjects and amputees. J Neuroeng Rehabil 2022; 19:59. [PMID: 35690860 PMCID: PMC9188052 DOI: 10.1186/s12984-022-01038-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 05/31/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Current myoelectric prostheses lack proprioceptive information and rely on vision for their control. Sensory substitution is increasingly developed with non-invasive vibrotactile or electrotactile feedback, but most systems are designed for grasping or object discriminations, and few were tested for online control in amputees. The objective of this work was evaluate the effect of a novel vibrotactile feedback on the accuracy of myoelectric control of a virtual elbow by healthy subjects and participants with an upper-limb amputation at humeral level. METHODS Sixteen, healthy participants and 7 transhumeral amputees performed myoelectric control of a virtual arm under different feedback conditions: vision alone (VIS), vibration alone (VIB), vision plus vibration (VIS + VIB), or no feedback at all (NO). Reach accuracy was evaluated by angular errors during discrete as well as back and forth movements. Healthy participants' workloads were assessed with the NASA-TLX questionnaire, and feedback conditions were ranked according to preference at the end of the experiment. RESULTS Reach errors were higher in NO than in VIB, indicating that our vibrotactile feedback improved performance as compared to no feedback. Conditions VIS and VIS+VIB display similar levels of performance and produced lower errors than in VIB. Vision remains therefore critical to maintain good performance, which is not ameliorated nor deteriorated by the addition of vibrotactile feedback. The workload associated with VIB was higher than for VIS and VIS+VIB, which did not differ from each other. 62.5% of healthy subjects preferred the VIS+VIB condition, and ranked VIS and VIB second and third, respectively. CONCLUSION Our novel vibrotactile feedback improved myoelectric control of a virtual elbow as compared to no feedback. Although vision remained critical, the addition of vibrotactile feedback did not improve nor deteriorate the control and was preferred by participants. Longer training should improve performances with VIB alone and reduce the need of vision for close-loop prosthesis control.
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Affiliation(s)
- Matthieu Guémann
- HYBRID Team, INCIA, CNRS, UMR 5287, Bordeaux, France. .,Unité de Physiologie de l'Exercice et des Activités en Conditions Extrêmes,Département Environnements Opérationnels, Institut de Recherche Biomédicale des Armées, Brétigny, France.
| | | | | | | | - Léo Borrini
- Physical and Rehabilitation Medicine Department, Percy Military Hospital, Clamart, France
| | - Éric Lapeyre
- Physical and Rehabilitation Medicine Department, Percy Military Hospital, Clamart, France
| | | | - Aymar de Rugy
- HYBRID Team, INCIA, CNRS, UMR 5287, Bordeaux, France
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27
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Sevcencu C. Single-interface bioelectronic medicines - concept, clinical applications and preclinical data. J Neural Eng 2022; 19. [PMID: 35533654 DOI: 10.1088/1741-2552/ac6e08] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Accepted: 05/08/2022] [Indexed: 11/12/2022]
Abstract
Presently, large groups of patients with various diseases are either intolerant, or irresponsive to drug therapies and also intractable by surgery. For several diseases, one option which is available for such patients is the implantable neurostimulation therapy. However, lacking closed-loop control and selective stimulation capabilities, the present neurostimulation therapies are not optimal and are therefore used as only "third" therapeutic options when a disease cannot be treated by drugs or surgery. Addressing those limitations, a next generation class of closed-loop controlled and selective neurostimulators generically named bioelectronic medicines seems within reach. A sub-class of such devices is meant to monitor and treat impaired functions by intercepting, analyzing and modulating neural signals involved in the regulation of such functions using just one neural interface for those purposes. The primary objective of this review is to provide a first broad perspective on this type of single-interface devices for bioelectronic therapies. For this purpose, the concept, clinical applications and preclinical studies for further developments with such devices are here analyzed in a narrative manner.
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Affiliation(s)
- Cristian Sevcencu
- National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donat Street, Cluj-Napoca, 400293, ROMANIA
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28
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Klinisches Update zu Phantomschmerz. Schmerz 2022; 37:195-214. [DOI: 10.1007/s00482-022-00629-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/02/2022] [Indexed: 10/18/2022]
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29
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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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30
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Graczyk EL, Christie BP, He Q, Tyler DJ, Bensmaia SJ. Frequency Shapes the Quality of Tactile Percepts Evoked through Electrical Stimulation of the Nerves. J Neurosci 2022; 42:2052-2064. [PMID: 35074865 PMCID: PMC8916769 DOI: 10.1523/jneurosci.1494-21.2021] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 09/29/2021] [Accepted: 11/22/2021] [Indexed: 11/21/2022] Open
Abstract
Electrical stimulation of the peripheral nerves of human participants provides a unique opportunity to study the neural determinants of perceptual quality using a causal manipulation. A major challenge in the study of neural coding of touch has been to isolate the role of spike timing-at the scale of milliseconds or tens of milliseconds-in shaping the sensory experience. In the present study, we address this question by systematically varying the pulse frequency (PF) of electrical stimulation pulse trains delivered to the peripheral nerves of seven participants with upper and lower extremity limb loss via chronically implanted neural interfaces. We find that increases in PF lead to systematic increases in perceived frequency, up to ∼50 Hz, at which point further changes in PF have little to no impact on sensory quality. Above this transition frequency, ratings of perceived frequency level off, the ability to discriminate changes in PF is abolished, and verbal descriptors selected to characterize the sensation change abruptly. We conclude that sensation quality is shaped by temporal patterns of neural activation, even if these patterns are imposed on a fixed neural population, but this temporal patterning can only be resolved up to ∼50 Hz. These findings highlight the importance of spike timing in shaping the quality of a sensation and will contribute to the development of encoding strategies for conveying touch feedback through bionic hands and feet.SIGNIFICANCE STATEMENT A major challenge in the study of neural coding of touch has been to understand how temporal patterns in neuronal responses shape the sensory experience. We address this question by varying the pulse frequency (PF) of electrical pulse trains delivered through implanted nerve interfaces in seven amputees. We concomitantly vary pulse width to separate the effect of changing PF on sensory quality from its effect on perceived magnitude. We find that increases in PF lead to increases in perceived frequency, a qualitative dimension, up to ∼50 Hz, beyond which changes in PF have little impact on quality. We conclude that temporal patterning in the neuronal response can shape quality and discuss the implications for restoring touch via neural interfaces.
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Affiliation(s)
- Emily L Graczyk
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106
- Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, Ohio 44106
| | - Breanne P Christie
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106
- Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland 20723
| | - Qinpu He
- Committee on Computational Neuroscience, University of Chicago, Chicago, Illinois 60637
| | - Dustin J Tyler
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106
- Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, Ohio 44106
| | - Sliman J Bensmaia
- Committee on Computational Neuroscience, University of Chicago, Chicago, Illinois 60637
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, Illinois 60637
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31
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Amoruso E, Dowdall L, Kollamkulam MT, Ukaegbu O, Kieliba P, Ng T, Dempsey-Jones H, Clode D, Makin TR. Intrinsic somatosensory feedback supports motor control and learning to operate artificial body parts. J Neural Eng 2022; 19:016006. [PMID: 34983040 PMCID: PMC10431236 DOI: 10.1088/1741-2552/ac47d9] [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: 10/05/2021] [Revised: 12/09/2021] [Accepted: 01/04/2022] [Indexed: 11/11/2022]
Abstract
Objective.Considerable resources are being invested to enhance the control and usability of artificial limbs through the delivery of unnatural forms of somatosensory feedback. Here, we investigated whether intrinsic somatosensory information from the body part(s) remotely controlling an artificial limb can be leveraged by the motor system to support control and skill learning.Approach.We used local anaesthetic to attenuate somatosensory inputs to the big toes while participants learned to operate through pressure sensors a toe-controlled and hand-worn robotic extra finger. Motor learning outcomes were compared against a control group who received sham anaesthetic and quantified in three different task scenarios: while operating in isolation from, in synchronous coordination, and collaboration with, the biological fingers.Main results.Both groups were able to learn to operate the robotic extra finger, presumably due to abundance of visual feedback and other relevant sensory cues. Importantly, the availability of displaced somatosensory cues from the distal bodily controllers facilitated the acquisition of isolated robotic finger movements, the retention and transfer of synchronous hand-robot coordination skills, and performance under cognitive load. Motor performance was not impaired by toes anaesthesia when tasks involved close collaboration with the biological fingers, indicating that the motor system can close the sensory feedback gap by dynamically integrating task-intrinsic somatosensory signals from multiple, and even distal, body-parts.Significance.Together, our findings demonstrate that there are multiple natural avenues to provide intrinsic surrogate somatosensory information to support motor control of an artificial body part, beyond artificial stimulation.
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Affiliation(s)
- E Amoruso
- Institute of Cognitive Neuroscience, University College London, London, United Kingdom
| | - L Dowdall
- Institute of Cognitive Neuroscience, University College London, London, United Kingdom
| | - M T Kollamkulam
- Institute of Cognitive Neuroscience, University College London, London, United Kingdom
| | - O Ukaegbu
- Institute of Cognitive Neuroscience, University College London, London, United Kingdom
- East London NHS Foundation Trust, London, United Kingdom
| | - P Kieliba
- Institute of Cognitive Neuroscience, University College London, London, United Kingdom
| | - T Ng
- Royal Free London NHS Foundation Trust, London, United Kingdom
| | - H Dempsey-Jones
- Institute of Cognitive Neuroscience, University College London, London, United Kingdom
| | - D Clode
- Institute of Cognitive Neuroscience, University College London, London, United Kingdom
| | - T R Makin
- Institute of Cognitive Neuroscience, University College London, London, United Kingdom
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32
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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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Objective neuromodulation basis for intrafascicular artificial somatosensation through carbon nanotube yarn electrodes. J Neurosci Methods 2022; 369:109481. [PMID: 35032498 DOI: 10.1016/j.jneumeth.2022.109481] [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: 08/17/2021] [Revised: 12/13/2021] [Accepted: 01/10/2022] [Indexed: 11/20/2022]
Abstract
BACKGROUND Intrafascicular electrical stimulation has been extensively adopted to achieve sensory feedback for limb amputees. Axon-like carbon nanotube yarn (CNTy) electrodes with both promising flexibility and spatial selectivity index (SSI) can be fascinating alternatives to generate artificial somatosensation. NEW METHOD Here we systematically disclose objective neuromodulation basis for artificial somatosensation through intrafascicular CNTy electrodes. CNTy electrodes with different exposed lengths were utilized for electrically stimulating tibial nerves in twelve rats. Somatosensory evoked potentials (SEPs) were recorded synchronously using an epidural thirty-channel electrode array. Spatiotemporal characteristics of SEPs were analyzed as current pulse amplitude (PA), pulse width (PW) and pulse frequency (PF) varied. RESULTS The current thresholds at 1Hz exhibit the lowest means when compared with those at 4 and 8Hz for most CNTy electrodes (20/28). For all the electrodes, amplitudes of SEPs and activated areas of perceptive fields increase with PWs and PAs rising, and decrease remarkably with PFs from 1 to 8Hz. Latencies of P1 and N1 of SEP peaks gradually reduced with PWs and PAs advancing. Considering high SSIs, relatively stable current thresholds, wider variation ranges of sensory magnitudes and optimal stability of perceptive fields, the L-200 μm electrodes are preferable for neuromodulation with PFs of 1 - 8Hz, PWs of 100 - 800 μs and PAs of 2 - 64 μA. COMPARISON WITH EXISTING METHODS New-type CNTy electrodes possess both promising flexibility and SSI when compared with other neural interfaces. We systematically explore objective neuromodulation basis for artificial somatosensation through CNTy electrodes for the first time. CONCLUSIONS Significantly higher SSIs, lower current and charge thresholds exist for CNTy electrodes in comparison with other peripheral-nerve interfaces. This study can, for the first time, lay a solid neuromodulation foundation for CNTy electrodes to achieve fine sensory feedback.
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Chakraborty B, Joshi-Imre A, Cogan SF. Charge injection characteristics of sputtered ruthenium oxide electrodes for neural stimulation and recording. J Biomed Mater Res B Appl Biomater 2022; 110:229-238. [PMID: 34259381 PMCID: PMC8608743 DOI: 10.1002/jbm.b.34906] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 06/23/2021] [Accepted: 06/27/2021] [Indexed: 01/03/2023]
Abstract
We have studied the charge-injection characteristics and electrochemical impedance of sputtered ruthenium oxide (RuOx ) films as electrode coatings for neural stimulation and recording electrodes. RuOx films were deposited by reactive DC magnetron sputtering, using a combination of water vapor and oxygen gas as reactive plasma constituents. The cathodal charge storage capacity of planar RuOx electrodes was found to be 54.6 ± 9.5 mC/cm2 (mean ± SD, n = 12), and the charge-injection capacity in a 0.2-ms cathodal current pulse was found to be 7.1 ± 0.3 mC/cm2 (mean ± SD, n = 15) at 0.6 V positive bias versus Ag|AgCl, in phosphate buffer saline at room temperature for ~250 nm thick films. In general, the RuOx films exhibited high charge-injection capacities, with or without a positive interpulse bias, comparable to sputtered iridium oxide (SIROF) coatings. The charge-injection capacity increased monotonically with film thickness from 120 to 630 nm, and reached 11.30 ± 0.34 mC/cm2 (mean ± SD, n = 5) at 0.6 V bias versus Ag|AgCl at 630 nm film thickness. In addition, RuOx films showed minimal changes in electrochemical characteristics over 1.5 billion cycles of constant current pulsing at a charge density of 408 μC/cm2 (8 nC/phase, 200 μs pulse width). The findings of low-impedance, high charge-injection capacity, and long-term pulsing stability suggest the suitability of RuOx as a comparatively inexpensive and favorable choice of electrode material for neural stimulation and recording.
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Affiliation(s)
- Bitan Chakraborty
- Department of Materials Science and Engineering, The University of Texas at Dallas, Richardson, Texas, USA
| | - Alexandra Joshi-Imre
- Department of Research, The University of Texas at Dallas, Richardson, Texas, USA
| | - Stuart F. Cogan
- Department of Bioengineering, The University of Texas at Dallas, Richardson, Texas, USA
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35
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Ahmadi-Dastgerdi N, Hosseini-Nejad H, Amiri H, Shoeibi A, Gorriz JM. A Vector Quantization-Based Spike Compression Approach Dedicated to Multichannel Neural Recording Microsystems. Int J Neural Syst 2021; 32:2250001. [PMID: 34931938 DOI: 10.1142/s0129065722500010] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Implantable high-density multichannel neural recording microsystems provide simultaneous recording of brain activities. Wireless transmission of the entire recorded data causes high bandwidth usage, which is not tolerable for implantable applications. As a result, a hardware-friendly compression module is required to reduce the amount of data before it is transmitted. This paper presents a novel compression approach that utilizes a spike extractor and a vector quantization (VQ)-based spike compressor. In this approach, extracted spikes are vector quantized using an unsupervised learning process providing a high spike compression ratio (CR) of 10-80. A combination of extracting and compressing neural spikes results in a significant data reduction as well as preserving the spike waveshapes. The compression performance of the proposed approach was evaluated under variant conditions. We also developed new architectures such that the hardware blocks of our approach can be implemented more efficiently. The compression module was implemented in a 180-nm standard CMOS process achieving a SNDR of 14.49[Formula: see text]dB and a classification accuracy (CA) of 99.62% at a CR of 20, while consuming 4[Formula: see text][Formula: see text]W power and 0.16[Formula: see text]mm2 chip area per channel.
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Affiliation(s)
| | | | - Hadi Amiri
- School of Engineering Science, College of Engineering, University of Tehran, Tehran, Iran
| | - Afshin Shoeibi
- Faculty of Electrical Engineering, FPGA Research Lab K. N. Toosi, University of Technology, Tehran, Iran
| | - Juan Manuel Gorriz
- Department of Signal Processing Networking and Communications, University of Granada, Granada, Spain.,Department of Psychiatry, University of Cambridge, Cambridge, UK
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36
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Marasco PD, Hebert JS, Sensinger JW, Beckler DT, Thumser ZC, Shehata AW, Williams HE, Wilson KR. Neurorobotic fusion of prosthetic touch, kinesthesia, and movement in bionic upper limbs promotes intrinsic brain behaviors. Sci Robot 2021; 6:eabf3368. [PMID: 34516746 DOI: 10.1126/scirobotics.abf3368] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
[Figure: see text].
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Affiliation(s)
- Paul D Marasco
- Laboratory for Bionic Integration, Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, ND20, Cleveland, OH 44195, USA.,Advanced Platform Technology Center, Louis Stokes Cleveland Department of Veterans Affairs Medical Center, 10701 East Boulevard 151 W/APT, Cleveland, OH 44106, USA
| | - Jacqueline S Hebert
- Division of Physical Medicine and Rehabilitation, Department of Medicine, University of Alberta, Edmonton, Alberta T6G 2E1, Canada.,Glenrose Rehabilitation Hospital, Alberta Health Services, 10230-111 Avenue, Edmonton, Alberta T5G 0B7, Canada
| | - Jonathon W Sensinger
- Institute of Biomedical Engineering, University of New Brunswick, 25 Dineen Drive, Fredericton, New Brunswick E3B 5A3, Canada
| | - Dylan T Beckler
- Laboratory for Bionic Integration, Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, ND20, Cleveland, OH 44195, USA
| | - Zachary C Thumser
- Laboratory for Bionic Integration, Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, ND20, Cleveland, OH 44195, USA.,Research Service, Louis Stokes Cleveland Department of Veterans Affairs Medical Center, 10701 East Boulevard, Research 151, Cleveland, OH 44106, USA
| | - Ahmed W Shehata
- Division of Physical Medicine and Rehabilitation, Department of Medicine, University of Alberta, Edmonton, Alberta T6G 2E1, Canada
| | - Heather E Williams
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta T6G 2E1, Canada
| | - Kathleen R Wilson
- Institute of Biomedical Engineering, University of New Brunswick, 25 Dineen Drive, Fredericton, New Brunswick E3B 5A3, Canada
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37
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Shokur S, Mazzoni A, Schiavone G, Weber DJ, Micera S. A modular strategy for next-generation upper-limb sensory-motor neuroprostheses. MED 2021; 2:912-937. [DOI: 10.1016/j.medj.2021.05.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Revised: 04/28/2021] [Accepted: 05/10/2021] [Indexed: 02/06/2023]
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38
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Veith A, Li X, Modi H, Abbaspour A, Luan L, Xie C, Baker AB. Optimized design of a hyperflexible sieve electrode to enhance neurovascular regeneration for a peripheral neural interface. Biomaterials 2021; 275:120924. [PMID: 34147716 PMCID: PMC9939235 DOI: 10.1016/j.biomaterials.2021.120924] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 05/13/2021] [Accepted: 05/23/2021] [Indexed: 11/24/2022]
Abstract
One in 190 Americans is currently living with the loss of a limb resulted from injury, amputation, or neurodegenerative disease. Advanced neuroprosthetic devices combine peripheral neural interfaces with sophisticated prosthetics and hold great potential for the rehabilitation of impaired motor and sensory functions. While robotic prosthetics have advanced very rapidly, peripheral neural interfaces have long been limited by the capability of interfacing with the peripheral nervous system. In this work, we developed a hyperflexible regenerative sieve electrode to serve as a peripheral neural interface. We examined tissue neurovascular integration through this novel device. We demonstrated that we could enhance the neurovascular invasion through the device with directional growth factor delivery. Furthermore, we demonstrated that we could reduce the tissue reaction to the device often seen in peripheral neural interfaces. Finally, we show that we can create a stable tissue device interface in a long-term implantation that does not impede the normal regenerative processes of the nerve. Our study developed an optimal platform for the continued development of hyperflexible sieve electrode peripheral neural interfaces.
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Affiliation(s)
- Austin Veith
- The University of Texas at Austin, Department of Biomedical Engineering, Austin, TX, USA
| | - Xue Li
- Rice University, Department of Electrical and Computer Engineering, Houston, TX, USA
| | - Hailey Modi
- The University of Texas at Austin, Department of Biomedical Engineering, Austin, TX, USA
| | - Ali Abbaspour
- The University of Texas at Austin, Department of Biomedical Engineering, Austin, TX, USA
| | - Lan Luan
- Rice University, Department of Electrical and Computer Engineering, Houston, TX, USA
| | - Chong Xie
- Rice University, Department of Electrical and Computer Engineering, Houston, TX, USA
| | - Aaron B Baker
- The University of Texas at Austin, Department of Biomedical Engineering, Austin, TX, USA; Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, TX, USA; Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX, USA; Institute for Biomaterials, Drug Delivery and Regenerative Medicine, The University of Texas at Austin, Austin, TX, USA.
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39
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Karczewski AM, Dingle AM, Poore SO. The Need to Work Arm in Arm: Calling for Collaboration in Delivering Neuroprosthetic Limb Replacements. Front Neurorobot 2021; 15:711028. [PMID: 34366820 PMCID: PMC8334559 DOI: 10.3389/fnbot.2021.711028] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 06/22/2021] [Indexed: 11/21/2022] Open
Abstract
Over the last few decades there has been a push to enhance the use of advanced prosthetics within the fields of biomedical engineering, neuroscience, and surgery. Through the development of peripheral neural interfaces and invasive electrodes, an individual's own nervous system can be used to control a prosthesis. With novel improvements in neural recording and signal decoding, this intimate communication has paved the way for bidirectional and intuitive control of prostheses. While various collaborations between engineers and surgeons have led to considerable success with motor control and pain management, it has been significantly more challenging to restore sensation. Many of the existing peripheral neural interfaces have demonstrated success in one of these modalities; however, none are currently able to fully restore limb function. Though this is in part due to the complexity of the human somatosensory system and stability of bioelectronics, the fragmentary and as-yet uncoordinated nature of the neuroprosthetic industry further complicates this advancement. In this review, we provide a comprehensive overview of the current field of neuroprosthetics and explore potential strategies to address its unique challenges. These include exploration of electrodes, surgical techniques, control methods, and prosthetic technology. Additionally, we propose a new approach to optimizing prosthetic limb function and facilitating clinical application by capitalizing on available resources. It is incumbent upon academia and industry to encourage collaboration and utilization of different peripheral neural interfaces in combination with each other to create versatile limbs that not only improve function but quality of life. Despite the rapidly evolving technology, if the field continues to work in divided "silos," we will delay achieving the critical, valuable outcome: creating a prosthetic limb that is right for the patient and positively affects their life.
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Affiliation(s)
| | - Aaron M. Dingle
- Division of Plastic Surgery, Department of Surgery, University of Wisconsin–Madison, Madison, WI, United States
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40
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Raspopovic S, Valle G, Petrini FM. Sensory feedback for limb prostheses in amputees. NATURE MATERIALS 2021; 20:925-939. [PMID: 33859381 DOI: 10.1038/s41563-021-00966-9] [Citation(s) in RCA: 87] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Accepted: 02/22/2021] [Indexed: 06/12/2023]
Abstract
Commercial prosthetic devices currently do not provide natural sensory information on the interaction with objects or movements. The subsequent disadvantages include unphysiological walking with a prosthetic leg and difficulty in controlling the force exerted with a prosthetic hand, thus creating health issues. Restoring natural sensory feedback from the prosthesis to amputees is an unmet clinical need. An optimal device should be able to elicit natural sensations of touch or proprioception, by delivering the complex signals to the nervous system that would be produced by skin, muscles and joints receptors. This Review covers the various neurotechnological approaches that have been proposed for the development of the optimal sensory feedback restoration device for arm and leg amputees.
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Affiliation(s)
- Stanisa Raspopovic
- Laboratory for Neuroengineering, Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, Zurich, Switzerland.
| | - Giacomo Valle
- Laboratory for Neuroengineering, Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, Zurich, Switzerland
| | - Francesco Maria Petrini
- Laboratory for Neuroengineering, Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, Zurich, Switzerland
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41
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Current Stimulation of the Midbrain Nucleus in Pigeons for Avian Flight Control. MICROMACHINES 2021; 12:mi12070788. [PMID: 34209448 PMCID: PMC8305299 DOI: 10.3390/mi12070788] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 06/18/2021] [Accepted: 06/28/2021] [Indexed: 11/17/2022]
Abstract
A number of research attempts to understand and modulate sensory and motor skills that are beyond the capability of humans have been underway. They have mainly been expounded in rodent models, where numerous reports of controlling movement to reach target locations by brain stimulation have been achieved. However, in the case of birds, although basic research on movement control has been conducted, the brain nuclei that are triggering these movements have yet to be established. In order to fully control flight navigation in birds, the basic central nervous system involved in flight behavior should be understood comprehensively, and functional maps of the birds’ brains to study the possibility of flight control need to be clarified. Here, we established a stable stereotactic surgery to implant multi-wire electrode arrays and electrically stimulated several nuclei of the pigeon’s brain. A multi-channel electrode array and a wireless stimulation system were implanted in thirteen pigeons. The pigeons’ flight trajectories on electrical stimulation of the cerebral nuclei were monitored and analyzed by a 3D motion tracking program to evaluate the behavioral change, and the exact stimulation site in the brain was confirmed by the postmortem histological examination. Among them, five pigeons were able to induce right and left body turns by stimulating the nuclei of the tractus occipito-mesencephalicus (OM), nucleus taeniae (TN), or nucleus rotundus (RT); the nuclei of tractus septo-mesencephalicus (TSM) or archistriatum ventrale (AV) were stimulated to induce flight aviation for flapping and take-off with five pigeons.
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42
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Gamal M, Mousa MH, Eldawlatly S, Elbasiouny SM. In-silico development and assessment of a Kalman filter motor decoder for prosthetic hand control. Comput Biol Med 2021; 132:104353. [PMID: 33831814 PMCID: PMC9887730 DOI: 10.1016/j.compbiomed.2021.104353] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Revised: 03/14/2021] [Accepted: 03/17/2021] [Indexed: 02/02/2023]
Abstract
Up to 50% of amputees abandon their prostheses, partly due to rapid degradation of the control systems, which require frequent recalibration. The goal of this study was to develop a Kalman filter-based approach to decoding motoneuron activity to identify movement kinematics and thereby provide stable, long-term, accurate, real-time decoding. The Kalman filter-based decoder was examined via biologically varied datasets generated from a high-fidelity computational model of the spinal motoneuron pool. The estimated movement kinematics controlled a simulated MuJoCo prosthetic hand. This clear-box approach showed successful estimation of hand movements under eight varied physiological conditions with no retraining. The mean correlation coefficient of 0.98 and mean normalized root mean square error of 0.06 over these eight datasets provide proof of concept that this decoder would improve long-term integrity of performance while performing new, untrained movements. Additionally, the decoder operated in real-time (~0.3 ms). Further results include robust performance of the Kalman filter when re-trained to more severe post-amputation limitations in the type and number of motoneurons remaining. An additional analysis shows that the decoder achieves better accuracy when using the firing of individual motoneurons as input, compared to using aggregate pool firing. Moreover, the decoder demonstrated robustness to noise affecting both the trained decoder parameters and the decoded motoneuron activity. These results demonstrate the utility of a proof of concept Kalman filter decoder that can support prosthetics' control systems to maintain accurate and stable real-time movement performance.
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Affiliation(s)
- Mai Gamal
- Center for Informatics Science, Nile University, Giza, Egypt,Computer Science and Engineering Department, Faculty of Media Engineering and Technology, German University in Cairo, Cairo, Egypt
| | - Mohamed H. Mousa
- Department of Biomedical, Industrial, and Human Factors Engineering, Wright State University, Dayton, OH, USA
| | - Seif Eldawlatly
- Computer Science and Engineering Department, Faculty of Media Engineering and Technology, German University in Cairo, Cairo, Egypt,Computer and Systems Engineering Department, Faculty of Engineering, Ain Shams University, Cairo, Egypt
| | - Sherif M. Elbasiouny
- Department of Biomedical, Industrial, and Human Factors Engineering, Wright State University, Dayton, OH, USA,Department of Neuroscience, Cell Biology, and Physiology, Wright State University, Dayton, OH, USA,Corresponding author. 3640 Colonel Glenn Hwy, Dayton, OH, 45435, USA., (S.M. Elbasiouny)
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43
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Kundu A, Fahmy A, Madler R, Otto K, Patrick E, Principe J, Maghari N, Bashirullah R. A multi-channel peripheral nerve stimulator with integrate-and-fire encoding. J Med Eng Technol 2021; 45:187-196. [PMID: 33729074 DOI: 10.1080/03091902.2021.1891311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Activation of peripheral nervous system (PNS) fibres to produce variable tactile and proprioceptive sensations in advanced bidirectional prosthetic limbs relies on neural stimulators with high spatial selectivity, dynamic range and resolution. A multi-channel application-specific integrated circuit (ASIC) is developed for PNS fibre activation using a wide dynamic range (10 nA-5 mA), high-resolution (30 nA step, 100 ns pulse accuracy) current stimulator, dissipating 0.73-2.75 mW at 3 V. The ASIC also enables encoding of external pressure signals via an integrate-and-fire methodology. Electrophysiological data of compound nerve action potentials were recorded for a range of stimulus amplitudes and pulse widths. This data was used to benchmark the performance of the ASIC with a known neural stimulator.
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Affiliation(s)
- Aritra Kundu
- Department of Neurology, Dell Medical School, The University of Texas at Austin, Austin, TX, USA
| | - Ahmed Fahmy
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, USA
| | - Ryan Madler
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, USA
| | - Kevin Otto
- Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
| | - Erin Patrick
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, USA
| | - Jose Principe
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, USA
| | - Nima Maghari
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, USA
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44
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Zheng Y, Hu X. Concurrent Prediction of Finger Forces Based on Source Separation and Classification of Neuron Discharge Information. Int J Neural Syst 2021; 31:2150010. [PMID: 33541251 DOI: 10.1142/s0129065721500106] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
A reliable neural-machine interface is essential for humans to intuitively interact with advanced robotic hands in an unconstrained environment. Existing neural decoding approaches utilize either discrete hand gesture-based pattern recognition or continuous force decoding with one finger at a time. We developed a neural decoding technique that allowed continuous and concurrent prediction of forces of different fingers based on spinal motoneuron firing information. High-density skin-surface electromyogram (HD-EMG) signals of finger extensor muscle were recorded, while human participants produced isometric flexion forces in a dexterous manner (i.e. produced varying forces using either a single finger or multiple fingers concurrently). Motoneuron firing information was extracted from the EMG signals using a blind source separation technique, and each identified neuron was further classified to be associated with a given finger. The forces of individual fingers were then predicted concurrently by utilizing the corresponding motoneuron pool firing frequency of individual fingers. Compared with conventional approaches, our technique led to better prediction performances, i.e. a higher correlation ([Formula: see text] versus [Formula: see text]), a lower prediction error ([Formula: see text]% MVC versus [Formula: see text]% MVC), and a higher accuracy in finger state (rest/active) prediction ([Formula: see text]% versus [Formula: see text]%). Our decoding method demonstrated the possibility of classifying motoneurons for different fingers, which significantly alleviated the cross-talk issue of EMG recordings from neighboring hand muscles, and allowed the decoding of finger forces individually and concurrently. The outcomes offered a robust neural-machine interface that could allow users to intuitively control robotic hands in a dexterous manner.
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Affiliation(s)
- Yang Zheng
- Joint Department of Biomedical Engineering, University of North Carolina - Chapel Hill and North Carolina State University, Raleigh, NC, USA
| | - Xiaogang Hu
- Joint Department of Biomedical Engineering, University of North Carolina - Chapel Hill and North Carolina State University, Raleigh, NC, USA
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45
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Nsugbe E. Brain-machine and muscle-machine bio-sensing methods for gesture intent acquisition in upper-limb prosthesis control: a review. J Med Eng Technol 2021; 45:115-128. [PMID: 33475039 DOI: 10.1080/03091902.2020.1854357] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2020] [Revised: 10/10/2020] [Accepted: 11/15/2020] [Indexed: 01/11/2023]
Abstract
This paper presents a review of a number of bio-sensing methods for gesture intent signal acquisition in control tasks for upper-limb prosthesis. The paper specifically provides a breakdown of the control task in myoelectric prosthesis, and in addition, highlights and describes the importance of the acquisition of a high-quality bio-signal. The paper also describes commonly used invasive and non-invasive brain and muscle machine interfaces such as electroencephalography, electrocorticography, electroneurography, surface electromyography, sonomyography, mechanomyography, near infra-red, force sensitive resistance/pressure, and magnetoencephalography. Each modality is reviewed based on its operating principle and limitations in gesture recognition, followed by respective advantages and disadvantages. Also described within this paper, are multimodal sensing approaches, which involve data fusion of information from various sensing modalities for an enhanced neuromuscular bio-sensing source. Using a semi-systematic review methodology, we are able to derive a novel tabular approach towards contrasting the various strengths and weaknesses of the reviewed bio-sensing methods towards gesture recognition in a prosthesis interface. This would allow for a streamlined method of down selection of an appropriate bio-sensor given specific prosthesis design criteria and requirements. The paper concludes by highlighting a number of research areas that require more work for strides to be made towards improving and enhancing the connection between man and machine as it concerns upper-limb prosthesis. Such areas include classifier augmentation for gesture recognition, filtering techniques for sensor disturbance rejection, feeling of tactile sensations with an artificial limb.
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Affiliation(s)
- Ejay Nsugbe
- University of Bristol, Bristol, United Kingdom
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46
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Page DM, George JA, Wendelken SM, Davis TS, Kluger DT, Hutchinson DT, Clark GA. Discriminability of multiple cutaneous and proprioceptive hand percepts evoked by intraneural stimulation with Utah slanted electrode arrays in human amputees. J Neuroeng Rehabil 2021; 18:12. [PMID: 33478534 PMCID: PMC7819250 DOI: 10.1186/s12984-021-00808-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Accepted: 01/11/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Electrical stimulation of residual afferent nerve fibers can evoke sensations from a missing limb after amputation, and bionic arms endowed with artificial sensory feedback have been shown to confer functional and psychological benefits. Here we explore the extent to which artificial sensations can be discriminated based on location, quality, and intensity. METHODS We implanted Utah Slanted Electrode Arrays (USEAs) in the arm nerves of three transradial amputees and delivered electrical stimulation via different electrodes and frequencies to produce sensations on the missing hand with various locations, qualities, and intensities. Participants performed blind discrimination trials to discriminate among these artificial sensations. RESULTS Participants successfully discriminated cutaneous and proprioceptive sensations ranging in location, quality and intensity. Performance was significantly greater than chance for all discrimination tasks, including discrimination among up to ten different cutaneous location-intensity combinations (15/30 successes, p < 0.0001) and seven different proprioceptive location-intensity combinations (21/40 successes, p < 0.0001). Variations in the site of stimulation within the nerve, via electrode selection, enabled discrimination among up to five locations and qualities (35/35 successes, p < 0.0001). Variations in the stimulation frequency enabled discrimination among four different intensities at the same location (13/20 successes, p < 0.0005). One participant also discriminated among individual stimulation of two different USEA electrodes, simultaneous stimulation on both electrodes, and interleaved stimulation on both electrodes (20/24 successes, p < 0.0001). CONCLUSION Electrode location, stimulation frequency, and stimulation pattern can be modulated to evoke functionally discriminable sensations with a range of locations, qualities, and intensities. This rich source of artificial sensory feedback may enhance functional performance and embodiment of bionic arms endowed with a sense of touch.
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Affiliation(s)
| | - Jacob A George
- Division of Physical Medicine and Rehabilitation, University of Utah, Salt Lake City, UT, 84112, USA.
| | - Suzanne M Wendelken
- Department of Anesthesiology, Maine Medical Center, Portland, ME, 04102, USA
| | - Tyler S Davis
- Department of Neurosurgery, University of Utah, Salt Lake City, UT, 84112, USA
| | | | | | - Gregory A Clark
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, 84112, USA
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47
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Abstract
Phantom limb pain is highly prevalent after amputation. Treatment results will probably benefit from an interdisciplinary team and individually adapted surgical, prosthetic and pain medicine approaches. Introduction: Most patients with amputation (up to 80%) suffer from phantom limb pain postsurgery. These are often multimorbid patients who also have multiple risk factors for the development of chronic pain from a pain medicine perspective. Surgical removal of the body part and sectioning of peripheral nerves result in a lack of afferent feedback, followed by neuroplastic changes in the sensorimotor cortex. The experience of severe pain, peripheral, spinal, and cortical sensitization mechanisms, and changes in the body scheme contribute to chronic phantom limb pain. Psychosocial factors may also affect the course and the severity of the pain. Modern amputation medicine is an interdisciplinary responsibility. Methods: This review aims to provide an interdisciplinary overview of recent evidence-based and clinical knowledge. Results: The scientific evidence for best practice is weak and contrasted by various clinical reports describing the polypragmatic use of drugs and interventional techniques. Approaches to restore the body scheme and integration of sensorimotor input are of importance. Modern techniques, including apps and virtual reality, offer an exciting supplement to already established approaches based on mirror therapy. Targeted prosthesis care helps to obtain or restore limb function and at the same time plays an important role reshaping the body scheme. Discussion: Consequent prevention and treatment of severe postoperative pain and early integration of pharmacological and nonpharmacological interventions are required to reduce severe phantom limb pain. To obtain or restore body function, foresighted surgical planning and technique as well as an appropriate interdisciplinary management is needed.
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48
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Srinivasan SS, Carty MJ, Calvaresi PW, Clites TR, Maimon BE, Taylor CR, Zorzos AN, Herr H. On prosthetic control: A regenerative agonist-antagonist myoneural interface. Sci Robot 2021; 2:2/6/eaan2971. [PMID: 33157872 DOI: 10.1126/scirobotics.aan2971] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2017] [Accepted: 05/10/2017] [Indexed: 01/25/2023]
Abstract
Prosthetic limb control is fundamentally constrained by the current amputation procedure. Since the U.S. Civil War, the external prosthesis has benefited from a pronounced level of innovation, but amputation technique has not significantly changed. During a standard amputation, nerves are transected without the reintroduction of proper neural targets, causing painful neuromas and rendering efferent recordings infeasible. Furthermore, the physiological agonist-antagonist muscle relationships are severed, precluding the generation of musculotendinous proprioception, an afferent feedback modality critical for joint stability, trajectory planning, and fine motor control. We establish an agonist-antagonist myoneural interface (AMI), a unique surgical paradigm for amputation. Regenerated free muscle grafts innervated with transected nerves are linked in agonist-antagonist relationships, emulating the dynamic interactions found within an intact limb. Using biomechanical, electrophysiological, and histological evaluations, we demonstrate a viable architecture for bidirectional signaling with transected motor nerves. Upon neural activation, the agonist muscle contracts, generating electromyographic signal. This contraction in the agonist creates a stretch in the mechanically linked antagonist muscle, producing afferent feedback, which is transmitted through its motor nerve. Histological results demonstrate regeneration and the presence of the spindle fibers responsible for afferent signal generation. These results suggest that the AMI will not only produce robust signals for the efferent control of an external prosthesis but also provide an amputee's central nervous system with critical musculotendinous proprioception, offering the potential for an enhanced prosthetic controllability and sensation.
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Affiliation(s)
- S S Srinivasan
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.,Center for Extreme Bionics, MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - M J Carty
- Center for Extreme Bionics, MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.,Department of Plastic and Reconstructive Surgery, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - P W Calvaresi
- Center for Extreme Bionics, MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - T R Clites
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.,Center for Extreme Bionics, MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - B E Maimon
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.,Center for Extreme Bionics, MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - C R Taylor
- Center for Extreme Bionics, MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.,Department of Media Arts and Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - A N Zorzos
- Center for Extreme Bionics, MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - H Herr
- Center for Extreme Bionics, MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
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49
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D'Anna E, Valle G, Mazzoni A, Strauss I, Iberite F, Patton J, Petrini FM, Raspopovic S, Granata G, Di Iorio R, Controzzi M, Cipriani C, Stieglitz T, Rossini PM, Micera S. A closed-loop hand prosthesis with simultaneous intraneural tactile and position feedback. Sci Robot 2021; 4:4/27/eaau8892. [PMID: 33137741 DOI: 10.1126/scirobotics.aau8892] [Citation(s) in RCA: 139] [Impact Index Per Article: 46.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2018] [Accepted: 12/18/2018] [Indexed: 01/09/2023]
Abstract
Current myoelectric prostheses allow transradial amputees to regain voluntary motor control of their artificial limb by exploiting residual muscle function in the forearm. However, the overreliance on visual cues resulting from a lack of sensory feedback is a common complaint. Recently, several groups have provided tactile feedback in upper limb amputees using implanted electrodes, surface nerve stimulation, or sensory substitution. These approaches have led to improved function and prosthesis embodiment. Nevertheless, the provided information remains limited to a subset of the rich sensory cues available to healthy individuals. More specifically, proprioception, the sense of limb position and movement, is predominantly absent from current systems. Here, we show that sensory substitution based on intraneural stimulation can deliver position feedback in real time and in conjunction with somatotopic tactile feedback. This approach allowed two transradial amputees to regain high and close-to-natural remapped proprioceptive acuity, with a median joint angle reproduction precision of 9.1° and a median threshold to detection of passive movements of 9.5°, which was comparable with results obtained in healthy participants. The simultaneous delivery of position information and somatotopic tactile feedback allowed both amputees to discriminate the size and compliance of four objects with high levels of performance (75.5%). These results demonstrate that tactile information delivered via somatotopic neural stimulation and position information delivered via sensory substitution can be exploited simultaneously and efficiently by transradial amputees. This study paves a way to more sophisticated bidirectional bionic limbs conveying richer, multimodal sensations.
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Affiliation(s)
- Edoardo D'Anna
- Bertarelli Foundation Chair in Translational Neuroengineering, Centre for Neuroprosthetics and Institute of Bioengineering, School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
| | - Giacomo Valle
- Bertarelli Foundation Chair in Translational Neuroengineering, Centre for Neuroprosthetics and Institute of Bioengineering, School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.,The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Alberto Mazzoni
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Ivo Strauss
- Bertarelli Foundation Chair in Translational Neuroengineering, Centre for Neuroprosthetics and Institute of Bioengineering, School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.,The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
| | | | - Jérémy Patton
- Bertarelli Foundation Chair in Translational Neuroengineering, Centre for Neuroprosthetics and Institute of Bioengineering, School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Francesco M Petrini
- Bertarelli Foundation Chair in Translational Neuroengineering, Centre for Neuroprosthetics and Institute of Bioengineering, School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Stanisa Raspopovic
- Laboratory for Neuroengineering, Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, 8092 Zürich, Switzerland
| | | | - Riccardo Di Iorio
- Institute of Neurology, Catholic University of The Sacred Heart, Policlinic A. Gemelli Foundation, Roma, Italy
| | - Marco Controzzi
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
| | | | - Thomas Stieglitz
- Laboratory for Biomedical Microtechnology, Department of Microsystems Engineering-IMTEK, University of Freiburg, Freiburg D-79110, Germany
| | - Paolo M Rossini
- Institute of Neurology, Catholic University of The Sacred Heart, Policlinic A. Gemelli Foundation, Roma, Italy.,Brain Connectivity Laboratory, IRCCS San Raffaele Pisana, Roma, Italy
| | - Silvestro Micera
- Bertarelli Foundation Chair in Translational Neuroengineering, Centre for Neuroprosthetics and Institute of Bioengineering, School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. .,The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
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50
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Wu Y, Liu Y, Zhou Y, Man Q, Hu C, Asghar W, Li F, Yu Z, Shang J, Liu G, Liao M, Li RW. A skin-inspired tactile sensor for smart prosthetics. Sci Robot 2021; 3:3/22/eaat0429. [PMID: 33141753 DOI: 10.1126/scirobotics.aat0429] [Citation(s) in RCA: 94] [Impact Index Per Article: 31.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2018] [Accepted: 08/06/2018] [Indexed: 12/11/2022]
Abstract
Recent achievements in the field of electronic skin have provided promising technology for prosthetic systems. However, the development of a bionic tactile-perception system that exhibits integrated stimuli sensing and neuron-like information-processing functionalities in a low-pressure regime remains a challenge. Here, we demonstrate a tactile sensor for smart prosthetics based on giant magneto-impedance (GMI) material embedded with an air gap. The sensor exhibits a high sensitivity of 120 newton-1 (or 4.4 kilopascal-1) and a very low detection limit of 10 micronewtons (or 0.3 pascals). The integration of the tactile sensor with an inductance-capacitance (LC) oscillation circuit enabled direct transduction of force stimuli into digital-frequency signals. The frequency increased with the force stimuli, consistent with the relationship between stimuli and human responses. The minimum loading of 50 micronewtons (or 1.25 pascals), which is less than the sensing threshold value of human skin, was also encoded into the frequency, similar to the pulse waveform of humans. The proposed tactile sensor not only showed desirable sensitivity and low detection limit but also exhibited transduction of digital-frequency signals like human stimuli responses. These features of the GMI-based tactile sensor show potential for its applications in smart prosthetics, especially prosthetic limbs that can functionally replace natural limbs.
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Affiliation(s)
- Yuanzhao Wu
- CAS Key Laboratory of Magnetic Materials and Devices, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, P. R. China.,Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, P. R. China.,University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Yiwei Liu
- CAS Key Laboratory of Magnetic Materials and Devices, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, P. R. China. .,Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, P. R. China
| | - Youlin Zhou
- CAS Key Laboratory of Magnetic Materials and Devices, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, P. R. China.,Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, P. R. China
| | - Qikui Man
- CAS Key Laboratory of Magnetic Materials and Devices, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, P. R. China.,Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, P. R. China
| | - Chao Hu
- CAS Key Laboratory of Magnetic Materials and Devices, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, P. R. China.,Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, P. R. China
| | - Waqas Asghar
- CAS Key Laboratory of Magnetic Materials and Devices, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, P. R. China.,Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, P. R. China.,University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Fali Li
- CAS Key Laboratory of Magnetic Materials and Devices, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, P. R. China.,Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, P. R. China.,University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Zhe Yu
- CAS Key Laboratory of Magnetic Materials and Devices, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, P. R. China.,Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, P. R. China.,University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Jie Shang
- CAS Key Laboratory of Magnetic Materials and Devices, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, P. R. China.,Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, P. R. China
| | - Gang Liu
- CAS Key Laboratory of Magnetic Materials and Devices, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, P. R. China.,Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, P. R. China
| | - Meiyong Liao
- National Institute for Materials Science, 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan
| | - Run-Wei Li
- CAS Key Laboratory of Magnetic Materials and Devices, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, P. R. China. .,Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, P. R. China
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