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Losanno E, Badi M, Roussinova E, Bogaard A, Delacombaz M, Shokur S, Micera S. An Investigation of Manifold-Based Direct Control for a Brain-to-Body Neural Bypass. IEEE OPEN JOURNAL OF ENGINEERING IN MEDICINE AND BIOLOGY 2024; 5:271-280. [PMID: 38766541 PMCID: PMC11100864 DOI: 10.1109/ojemb.2024.3381475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 02/06/2024] [Accepted: 03/11/2024] [Indexed: 05/22/2024] Open
Abstract
Objective: Brain-body interfaces (BBIs) have emerged as a very promising solution for restoring voluntary hand control in people with upper-limb paralysis. The BBI module decoding motor commands from brain signals should provide the user with intuitive, accurate, and stable control. Here, we present a preliminary investigation in a monkey of a brain decoding strategy based on the direct coupling between the activity of intrinsic neural ensembles and output variables, aiming at achieving ease of learning and long-term robustness. Results: We identified an intrinsic low-dimensional space (called manifold) capturing the co-variation patterns of the monkey's neural activity associated to reach-to-grasp movements. We then tested the animal's ability to directly control a computer cursor using cortical activation along the manifold axes. By daily recalibrating only scaling factors, we achieved rapid learning and stable high performance in simple, incremental 2D tasks over more than 12 weeks of experiments. Finally, we showed that this brain decoding strategy can be effectively coupled to peripheral nerve stimulation to trigger voluntary hand movements. Conclusions: These results represent a proof of concept of manifold-based direct control for BBI applications.
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Affiliation(s)
- E. Losanno
- The Biorobotics Institute and Department of Excellence in Robotics and AIScuola Superiore Sant'Anna56025PisaItaly
- Modular Implantable Neuroprostheses (MINE) LaboratoryUniversità Vita-Salute San Raffaele and Scuola Superiore Sant'AnnaMilanItaly
| | - M. Badi
- Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics and Institute of BioengineeringÉcole Polytechnique Fédérale de Lausanne (EPFL)1015LausanneSwitzerland
| | - E. Roussinova
- Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics and Institute of BioengineeringÉcole Polytechnique Fédérale de Lausanne (EPFL)1015LausanneSwitzerland
| | - A. Bogaard
- Department of Neuroscience and Movement Sciences, Platform of Translational Neurosciences, Section of Medicine, Faculty of Sciences and MedicineUniversity of Fribourg1700FribourgSwitzerland
| | - M. Delacombaz
- Department of Neuroscience and Movement Sciences, Platform of Translational Neurosciences, Section of Medicine, Faculty of Sciences and MedicineUniversity of Fribourg1700FribourgSwitzerland
| | - S. Shokur
- Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics and Institute of BioengineeringÉcole Polytechnique Fédérale de Lausanne (EPFL)1015LausanneSwitzerland
| | - S. Micera
- The Biorobotics Institute and Department of Excellence in Robotics and AIScuola Superiore Sant'Anna56025PisaItaly
- Modular Implantable Neuroprostheses (MINE) LaboratoryUniversità Vita-Salute San Raffaele and Scuola Superiore Sant'AnnaMilanItaly
- Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics and Institute of BioengineeringÉcole Polytechnique Fédérale de Lausanne (EPFL)1015LausanneSwitzerland
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Lorach H, Galvez A, Spagnolo V, Martel F, Karakas S, Intering N, Vat M, Faivre O, Harte C, Komi S, Ravier J, Collin T, Coquoz L, Sakr I, Baaklini E, Hernandez-Charpak SD, Dumont G, Buschman R, Buse N, Denison T, van Nes I, Asboth L, Watrin A, Struber L, Sauter-Starace F, Langar L, Auboiroux V, Carda S, Chabardes S, Aksenova T, Demesmaeker R, Charvet G, Bloch J, Courtine G. Walking naturally after spinal cord injury using a brain-spine interface. Nature 2023; 618:126-133. [PMID: 37225984 PMCID: PMC10232367 DOI: 10.1038/s41586-023-06094-5] [Citation(s) in RCA: 88] [Impact Index Per Article: 88.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 04/17/2023] [Indexed: 05/26/2023]
Abstract
A spinal cord injury interrupts the communication between the brain and the region of the spinal cord that produces walking, leading to paralysis1,2. Here, we restored this communication with a digital bridge between the brain and spinal cord that enabled an individual with chronic tetraplegia to stand and walk naturally in community settings. This brain-spine interface (BSI) consists of fully implanted recording and stimulation systems that establish a direct link between cortical signals3 and the analogue modulation of epidural electrical stimulation targeting the spinal cord regions involved in the production of walking4-6. A highly reliable BSI is calibrated within a few minutes. This reliability has remained stable over one year, including during independent use at home. The participant reports that the BSI enables natural control over the movements of his legs to stand, walk, climb stairs and even traverse complex terrains. Moreover, neurorehabilitation supported by the BSI improved neurological recovery. The participant regained the ability to walk with crutches overground even when the BSI was switched off. This digital bridge establishes a framework to restore natural control of movement after paralysis.
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Affiliation(s)
- Henri Lorach
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Andrea Galvez
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Valeria Spagnolo
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Felix Martel
- Univ. Grenoble Alpes, CEA, LETI, Clinatec, Grenoble, France
| | - Serpil Karakas
- Univ. Grenoble Alpes, CEA, LETI, Clinatec, Grenoble, France
| | - Nadine Intering
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Molywan Vat
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Olivier Faivre
- Univ. Grenoble Alpes, CEA, LETI, Clinatec, Grenoble, France
| | - Cathal Harte
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Salif Komi
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Jimmy Ravier
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Thibault Collin
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Laure Coquoz
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Icare Sakr
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Edeny Baaklini
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Sergio Daniel Hernandez-Charpak
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Gregory Dumont
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | | | | | - Tim Denison
- Medtronic, Minneapolis, MN, USA
- Department of Engineering Science, University of Oxford, Oxford, UK
| | - Ilse van Nes
- Department of Rehabilitation, Sint Maartenskliniek, Nijmegen, the Netherlands
| | - Leonie Asboth
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | | | - Lucas Struber
- Univ. Grenoble Alpes, CEA, LETI, Clinatec, Grenoble, France
| | | | - Lilia Langar
- Univ. Grenoble Alpes, CHU Grenoble Alpes, Clinatec, Grenoble, France
| | | | - Stefano Carda
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Stephan Chabardes
- Univ. Grenoble Alpes, CEA, LETI, Clinatec, Grenoble, France
- Univ. Grenoble Alpes, CHU Grenoble Alpes, Clinatec, Grenoble, France
| | | | - Robin Demesmaeker
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | | | - Jocelyne Bloch
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland.
| | - Grégoire Courtine
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland.
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Zuccaroli I, Lucke-Wold B, Palla A, Eremiev A, Sorrentino Z, Zakare-Fagbamila R, McNulty J, Christie C, Chandra V, Mampre D. Neural Bypasses: Literature Review and Future Directions in Developing Artificial Neural Connections. OBM NEUROBIOLOGY 2023; 7:158. [PMID: 36908763 PMCID: PMC9997488 DOI: 10.21926/obm.neurobiol.2301158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/24/2023]
Abstract
Reported neuro-modulation schemes in the literature are typically classified as closed-loop or open-loop. A novel group of recently developed neuro-modulation devices may be better described as a neural bypass, which attempts to transmit neural data from one location of the nervous system to another. The most common form of neural bypasses in the literature utilize EEG recordings of cortical information paired with functional electrical stimulation for effector muscle output, most commonly for assistive applications and rehabilitation in spinal cord injury or stroke. Other neural bypass locations that have also been described, or may soon be in development, include cortical-spinal bypasses, cortical-cortical bypasses, autonomic bypasses, peripheral-central bypasses, and inter-subject bypasses. The most common recording devices include EEG, ECoG, and microelectrode arrays, while stimulation devices include both invasive and noninvasive electrodes. Several devices are in development to improve the temporal and spatial resolution and biocompatibility for neuronal recording and stimulation. A major barrier to entry includes neuroplasticity and current decoding mechanisms that regularly require retraining. Neural bypasses are a unique class of neuro-modulation. Continued advancement of neural recording and stimulating devices with high spatial and temporal resolution, combined with decoding mechanisms uninhibited by neuroplasticity, can expand the therapeutic capability of neural bypassing. Overall, neural bypasses are a promising modality to improve the treatment of common neurologic disorders, including stroke, spinal cord injury, peripheral nerve injury, brain injury and more.
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Affiliation(s)
| | | | | | - Alexander Eremiev
- Department of Neurosurgery, New York University School of Medicine, New York, USA
| | | | | | - Jack McNulty
- Department of Neurosurgery, University of Iowa, Iowa City, IA, USA
| | - Carlton Christie
- Department of Neurosurgery, University of Florida, Gainesville, USA
| | - Vyshak Chandra
- Department of Neurosurgery, University of Florida, Gainesville, USA
| | - David Mampre
- Johns Hopkins University, Baltimore, USA
- Department of Neurosurgery, University of Florida, Gainesville, USA
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Kruppa C, Benner S, Brinkemper A, Aach M, Reimertz C, Schildhauer TA. [New technologies and robotics]. UNFALLCHIRURGIE (HEIDELBERG, GERMANY) 2023; 126:9-18. [PMID: 36515725 DOI: 10.1007/s00113-022-01270-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 11/22/2022] [Indexed: 12/15/2022]
Abstract
The development of increasingly more complex computer and electromotor technologies enables the increasing use and expansion of robot-assisted systems in trauma surgery rehabilitation; however, the currently available devices are rarely comprehensively applied but are often used within pilot projects and studies. Different technological approaches, such as exoskeletal systems, functional electrical stimulation, soft robotics, neurorobotics and brain-machine interfaces are used and combined to read and process the communication between, e.g., residual musculature or brain waves, to transfer them to the executing device and to enable the desired execution.Currently, the greatest amount of evidence exists for the use of exoskeletal systems with different modes of action in the context of gait and stance rehabilitation in paraplegic patients; however, their use also plays a role in the rehabilitation of fractures close to the hip joint and endoprosthetic care. So-called single joint systems are also being tested in the rehabilitation of functionally impaired extremities, e.g., after knee prosthesis implantation. At this point, however, the current data situation is still too limited to be able to make a clear statement about the use of these technologies in the trauma surgery "core business" of rehabilitation after fractures and other joint injuries.For rehabilitation after limb amputation, in addition to the further development of myoelectric prostheses, the current development of "sentient" prostheses is of great interest. The use of 3D printing also plays a role in the production of individualized devices.Due to the current progress of artificial intelligence in all fields, ground-breaking further developments and widespread application possibilities in the rehabilitation of trauma patients are to be expected.
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Affiliation(s)
- Christiane Kruppa
- Chirurgische Klinik und Poliklinik, Berufsgenossenschaftliches Universitätsklinikum Bergmannsheil Bochum, Ruhr-Universität Bochum, Bochum, Deutschland.
| | - Sebastian Benner
- BG Service- und Rehabilitationszentrum, BG Unfallklinik Frankfurt am Main gGmbH, Frankfurt am Main, Deutschland
| | - Alexis Brinkemper
- Chirurgische Klinik und Poliklinik, Berufsgenossenschaftliches Universitätsklinikum Bergmannsheil Bochum, Ruhr-Universität Bochum, Bochum, Deutschland
| | - Mirko Aach
- Chirurgische Klinik und Poliklinik, Abteilung für Rückenmarkverletzte, Berufsgenossenschaftliches Universitätsklinikum Bergmannsheil Bochum, Ruhr-Universität Bochum, Bochum, Deutschland
| | - Christoph Reimertz
- BG Service- und Rehabilitationszentrum, BG Unfallklinik Frankfurt am Main gGmbH, Frankfurt am Main, Deutschland
| | - Thomas A Schildhauer
- Chirurgische Klinik und Poliklinik, Berufsgenossenschaftliches Universitätsklinikum Bergmannsheil Bochum, Ruhr-Universität Bochum, Bochum, Deutschland
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5
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Chaikho L, Clark E, Raison M. Transcutaneous Functional Electrical Stimulation Controlled by a System of Sensors for the Lower Limbs: A Systematic Review. SENSORS (BASEL, SWITZERLAND) 2022; 22:9812. [PMID: 36560179 PMCID: PMC9780889 DOI: 10.3390/s22249812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Revised: 11/30/2022] [Accepted: 12/11/2022] [Indexed: 06/17/2023]
Abstract
In the field of transcutaneous functional electrical stimulation (FES), open-loop and closed-loop control strategies have been developed to restore functions of the lower limbs: walking, standing up, maintaining posture, and cycling. These strategies require sensors that provide feedback information on muscle activity or biomechanics of movement. Since muscle response induced by transcutaneous FES is nonlinear, time-varying, and dependent on muscle fatigue evolution, the choice of sensor type and control strategy becomes critical. The main objective of this review is to provide state-of-the-art, emerging, current, and previous solutions in terms of control strategies. Focus is given on transcutaneous FES systems for the lower limbs. Using Compendex and Inspec databases, a total of 135 review and conference articles were included in this review. Recent studies mainly use inertial sensors, although the use of electromyograms for lower limbs has become more frequent. Currently, several researchers are opting for nonlinear controllers to overcome the nonlinear and time-varying effects of FES. More development is needed in the field of systems using inertial sensors for nonlinear control. Further studies are needed to validate nonlinear control systems in patients with neuromuscular disorders.
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Affiliation(s)
- Layal Chaikho
- Lab of Intelligent Biomechanics, Robotics, and Rehab Technology (LIBRTy), Department of Mechanical Engineering, Polytechnique Montréal, P.O. Box 6079 Station Centre-Ville, Montréal, QC H3C 3A7, Canada
- Institute of Biomedical Engineering, Polytechnique Montreal, P.O. Box 6079 Station Centre-Ville, Montréal, QC H3C 3A7, Canada
| | | | - Maxime Raison
- Lab of Intelligent Biomechanics, Robotics, and Rehab Technology (LIBRTy), Department of Mechanical Engineering, Polytechnique Montréal, P.O. Box 6079 Station Centre-Ville, Montréal, QC H3C 3A7, Canada
- Institute of Biomedical Engineering, Polytechnique Montreal, P.O. Box 6079 Station Centre-Ville, Montréal, QC H3C 3A7, Canada
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6
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Zhang Q, Fragnito N, Franz JR, Sharma N. Fused ultrasound and electromyography-driven neuromuscular model to improve plantarflexion moment prediction across walking speeds. J Neuroeng Rehabil 2022; 19:86. [PMID: 35945600 PMCID: PMC9361708 DOI: 10.1186/s12984-022-01061-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 07/21/2022] [Indexed: 11/28/2022] Open
Abstract
Background Improving the prediction ability of a human-machine interface (HMI) is critical to accomplish a bio-inspired or model-based control strategy for rehabilitation interventions, which are of increased interest to assist limb function post neurological injuries. A fundamental role of the HMI is to accurately predict human intent by mapping signals from a mechanical sensor or surface electromyography (sEMG) sensor. These sensors are limited to measuring the resulting limb force or movement or the neural signal evoking the force. As the intermediate mapping in the HMI also depends on muscle contractility, a motivation exists to include architectural features of the muscle as surrogates of dynamic muscle movement, thus further improving the HMI’s prediction accuracy. Objective The purpose of this study is to investigate a non-invasive sEMG and ultrasound (US) imaging-driven Hill-type neuromuscular model (HNM) for net ankle joint plantarflexion moment prediction. We hypothesize that the fusion of signals from sEMG and US imaging results in a more accurate net plantarflexion moment prediction than sole sEMG or US imaging. Methods Ten young non-disabled participants walked on a treadmill at speeds of 0.50, 0.75, 1.00, 1.25, and 1.50 m/s. The proposed HNM consists of two muscle-tendon units. The muscle activation for each unit was calculated as a weighted summation of the normalized sEMG signal and normalized muscle thickness signal from US imaging. The HNM calibration was performed under both single-speed mode and inter-speed mode, and then the calibrated HNM was validated across all walking speeds. Results On average, the normalized moment prediction root mean square error was reduced by 14.58 % (\documentclass[12pt]{minimal}
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\begin{document}$$p<0.001$$\end{document}p<0.001) with the proposed HNM when compared to sEMG-driven and US imaging-driven HNMs, respectively. Also, the calibrated models with data from the inter-speed mode were more robust than those from single-speed modes for the moment prediction. Conclusions The proposed sEMG-US imaging-driven HNM can significantly improve the net plantarflexion moment prediction accuracy across multiple walking speeds. The findings imply that the proposed HNM can be potentially used in bio-inspired control strategies for rehabilitative devices due to its superior prediction. Supplementary Information The online version contains supplementary material available at 10.1186/s12984-022-01061-z.
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Affiliation(s)
- Qiang Zhang
- Joint Department of Biomedical Engineering at the University of North Carolina-Chapel Hill and North Carolina State University, 1840 Entrepreneur Dr., 27695, Raleigh, NC, USA.,Joint Department of Biomedical Engineering at the University of North Carolina-Chapel Hill and North Carolina State University, 333 S Columbia St., 27514, Chapel Hill, NC, USA
| | - Natalie Fragnito
- Joint Department of Biomedical Engineering at the University of North Carolina-Chapel Hill and North Carolina State University, 1840 Entrepreneur Dr., 27695, Raleigh, NC, USA.,Joint Department of Biomedical Engineering at the University of North Carolina-Chapel Hill and North Carolina State University, 333 S Columbia St., 27514, Chapel Hill, NC, USA
| | - Jason R Franz
- Joint Department of Biomedical Engineering at the University of North Carolina-Chapel Hill and North Carolina State University, 1840 Entrepreneur Dr., 27695, Raleigh, NC, USA.,Joint Department of Biomedical Engineering at the University of North Carolina-Chapel Hill and North Carolina State University, 333 S Columbia St., 27514, Chapel Hill, NC, USA
| | - Nitin Sharma
- Joint Department of Biomedical Engineering at the University of North Carolina-Chapel Hill and North Carolina State University, 1840 Entrepreneur Dr., 27695, Raleigh, NC, USA. .,Joint Department of Biomedical Engineering at the University of North Carolina-Chapel Hill and North Carolina State University, 333 S Columbia St., 27514, Chapel Hill, NC, USA.
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7
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Gadot R, Smith DN, Prablek M, Grochmal JK, Fuentes A, Ropper AE. Established and Emerging Therapies in Acute Spinal Cord Injury. Neurospine 2022; 19:283-296. [PMID: 35793931 PMCID: PMC9260540 DOI: 10.14245/ns.2244176.088] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 05/05/2022] [Indexed: 12/11/2022] Open
Abstract
Acute spinal cord injury (SCI) is devastating for patients and their caretakers and has an annual incidence of 20–50 per million people. Following initial assessment with appropriate physical examination and imaging, patients who are deemed surgical candidates should undergo decompression with stabilization. Earlier intervention can improve neurological recovery in the post-operative period while allowing earlier mobilization. Optimized medical management is paramount to improve outcomes. Emerging strategies for managing SCI in the acute period stem from an evolving understanding of the pathophysiology of the injury. General areas of focus include ischemia prevention, reduction of secondary injury due to inflammation, modulation of the cytotoxic and immune response, and promotion of cellular regeneration. In this article, we review established, emerging, and novel experimental therapies. Continued translational research on these methods will improve the feasibility of bench-to-bedside innovations in treating patients with acute SCI.
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Affiliation(s)
- Ron Gadot
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - David N. Smith
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Marc Prablek
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Joey K. Grochmal
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Alfonso Fuentes
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Alexander E. Ropper
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
- Corresponding Author Alexander E. Ropper Department of Neurosurgery, Baylor College of Medicine, 7200 Cambridge St. Suite 9A, Houston, TX, USA
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8
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Steele AG, Manson GA, Horner PJ, Sayenko DG, Contreras-Vidal JL. Effects of transcutaneous spinal stimulation on spatiotemporal cortical activation patterns: A proof-of-concept EEG study. J Neural Eng 2022; 19. [PMID: 35732141 DOI: 10.1088/1741-2552/ac7b4b] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Accepted: 06/22/2022] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Transcutaneous spinal cord stimulation (TSS) has been shown to be a promising non-invasive alternative to epidural spinal cord stimulation (ESS) for improving outcomes of people with spinal cord injury (SCI). However, studies on the effects of TSS on cortical activation are limited. Our objectives were to evaluate the spatiotemporal effects of TSS on brain activity, and determine changes in functional connectivity under several different stimulation conditions. As a control, we also assessed the effects of functional electrical stimulation (FES) on cortical activity. APPROACH Non-invasive scalp electroencephalography (EEG) was recorded during TSS or FES while five neurologically intact participants performed one of three lower-limb tasks while in the supine position: (1) A no contraction control task, (2) a rhythmic contraction task, or (3) a tonic contraction task. After EEG denoising and segmentation, independent components were clustered across subjects to characterize sensorimotor networks in the time and frequency domains. Independent components of the event related potentials (ERPs) were calculated for each cluster and condition. Next, a Generalized Partial Directed Coherence (gPDC) analysis was performed on each cluster to compare the functional connectivity between conditions and tasks. RESULTS Independent Component analysis of EEG during TSS resulted in three clusters identified at Brodmann areas (BA) 9, BA 6, and BA 4, which are areas associated with working memory, planning, and movement control. Lastly, we found significant (p < 0.05, adjusted for multiple comparisons) increases and decreases in functional connectivity of clusters during TSS, but not during FES when compared to the no stimulation conditions. SIGNIFICANCE The findings from this study provide evidence of how TSS recruits cortical networks during tonic and rhythmic lower limb movements. These results have implications for the development of spinal cord-based computer interfaces, and the design of neural stimulation devices for the treatment of pain and sensorimotor deficit.
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Affiliation(s)
- Alexander G Steele
- Department of Neurosurgery, Houston Methodist Research Institute, 6670 Bertner Ave, Houston, Texas, 77030-2707, UNITED STATES
| | - Gerome A Manson
- Department of Neurosurgery, Houston Methodist Research Institute, 6670 Bertner Ave, Houston, Texas, 77030-2707, UNITED STATES
| | - Philip J Horner
- Department of Neurosurgery, Houston Methodist Research Institute, 6670 Bertner Ave, Houston, Texas, 77030-2707, UNITED STATES
| | - Dimitry G Sayenko
- Department of Neurosurgery, Houston Methodist Research Institute, 6670 Bertner Ave, Houston, Texas, 77030-2707, UNITED STATES
| | - Jose L Contreras-Vidal
- Electrical and Computer Engineering, University of Houston, N308 Engineering Building I, Houston, Texas, 77204-4005, UNITED STATES
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9
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Pais-Vieira C, Gaspar P, Matos D, Alves LP, da Cruz BM, Azevedo MJ, Gago M, Poleri T, Perrotta A, Pais-Vieira M. Embodiment Comfort Levels During Motor Imagery Training Combined With Immersive Virtual Reality in a Spinal Cord Injury Patient. Front Hum Neurosci 2022; 16:909112. [PMID: 35669203 PMCID: PMC9163805 DOI: 10.3389/fnhum.2022.909112] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 04/28/2022] [Indexed: 02/02/2023] Open
Abstract
Brain-machine interfaces combining visual, auditory, and tactile feedback have been previously used to generate embodiment experiences during spinal cord injury (SCI) rehabilitation. It is not known if adding temperature to these modalities can result in discomfort with embodiment experiences. Here, comfort levels with the embodiment experiences were investigated in an intervention that required a chronic pain SCI patient to generate lower limb motor imagery commands in an immersive environment combining visual (virtual reality -VR), auditory, tactile, and thermal feedback. Assessments were made pre-/ post-, throughout the intervention (Weeks 0-5), and at 7 weeks follow up. Overall, high levels of embodiment in the adapted three-domain scale of embodiment were found throughout the sessions. No significant adverse effects of VR were reported. Although sessions induced only a modest reduction in pain levels, an overall reduction occurred in all pain scales (Faces, Intensity, and Verbal) at follow up. A high degree of comfort in the comfort scale for the thermal-tactile sleeve, in both the thermal and tactile feedback components of the sleeve was reported. This study supports the feasibility of combining multimodal stimulation involving visual (VR), auditory, tactile, and thermal feedback to generate embodiment experiences in neurorehabilitation programs.
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Affiliation(s)
- Carla Pais-Vieira
- Centro de Investigação Interdisciplinar em Saúde (CIIS), Instituto de Ciências da Saúde (ICS), Universidade Católica Portuguesa, Porto, Portugal
| | - Pedro Gaspar
- Centro de Investigação em Ciência e Tecnologia das Artes (CITAR), Universidade Católica Portuguesa, Porto, Portugal
| | - Demétrio Matos
- ID+ (Instituto de Investigação em Design, Média e Cultura), Instituto Politécnico do Cávado e do Ave, Vila Frescainha, Portugal
| | - Leonor Palminha Alves
- Human Robotics Group, Centro de Sistemas Inteligentes do IDMEC - Instituto de Engenharia Mecânica, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Bárbara Moreira da Cruz
- Serviço de Medicina Física e Reabilitação, Hospital Senhora da Oliveira, Guimarães, Portugal
| | - Maria João Azevedo
- Serviço de Medicina Física e Reabilitação, Hospital Senhora da Oliveira, Guimarães, Portugal
| | - Miguel Gago
- Serviço de Neurologia, Hospital Senhora da Oliveira, Guimarães, Portugal
| | - Tânia Poleri
- Plano de Ação para Apoio aos Deficientes Militares, Porto, Portugal
| | - André Perrotta
- Centre for Informatics and Systems of the University of Coimbra (CISUC), Coimbra, Portugal
| | - Miguel Pais-Vieira
- Institute of Biomedicine (iBiMED), Department of Medical Sciences, Universidade de Aveiro, Aveiro, Portugal
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10
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De Almeida TF, Borges LHB, Dantas AFODA. Development of an IoT Electrostimulator with Closed-Loop Control. SENSORS (BASEL, SWITZERLAND) 2022; 22:3551. [PMID: 35591243 PMCID: PMC9104803 DOI: 10.3390/s22093551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 05/02/2022] [Accepted: 05/04/2022] [Indexed: 02/05/2023]
Abstract
The most used approach in the motor rehabilitation of spinal cord injury is functional electrical stimulation. However, current devices do not provide real-time feedback, work in the closed-loop, and became remotely operable. In this scenario, this paper presents the development of an open access 4-channel IoT electrostimulator device with an inertial sensor. The electrostimulator circuit was designed with four modules: Boost Converter, H-bridge, Inertial Measurement Unit, and Processing Module. The firmware was implemented in the processing module to manage the modules to perform closed-loop stimulation (using PID controller). To perform the proof of concept of the device, a closed loop test was performed to control the ankle joint, performing the movements of dorsiflexion, plantar flexion, inversion, and eversion. The designed hardware allowed one to freely change the boost converter voltage and modulate the signal with 200 μs of pulse duration and 50 Hz of period in a safe and stable way. Furthermore, the controller was able to move the ankle joint in all desired directions following the reference values and respecting the imposed constraints. In general, the developed hardware was able to safely control a closed-loop joint.
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Affiliation(s)
| | | | - André Felipe Oliveira de Azevedo Dantas
- Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Av. Alberto Santos Dumont, 1560, Zona Rural, Macaiba 59280-000, RN, Brazil; (T.F.D.A.); (L.H.B.B.)
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11
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Kiang L, Woodington B, Carnicer-Lombarte A, Malliaras G, Barone DG. Spinal cord bioelectronic interfaces: opportunities in neural recording and clinical challenges. J Neural Eng 2022; 19. [PMID: 35320780 DOI: 10.1088/1741-2552/ac605f] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 03/23/2022] [Indexed: 11/11/2022]
Abstract
Bioelectronic stimulation of the spinal cord has demonstrated significant progress in restoration of motor function in spinal cord injury (SCI). The proximal, uninjured spinal cord presents a viable target for the recording and generation of control signals to drive targeted stimulation. Signals have been directly recorded from the spinal cord in behaving animals and correlated with limb kinematics. Advances in flexible materials, electrode impedance and signal analysis will allow SCR to be used in next-generation neuroprosthetics. In this review, we summarize the technological advances enabling progress in SCR and describe systematically the clinical challenges facing spinal cord bioelectronic interfaces and potential solutions, from device manufacture, surgical implantation to chronic effects of foreign body reaction and stress-strain mismatches between electrodes and neural tissue. Finally, we establish our vision of bi-directional closed-loop spinal cord bioelectronic bypass interfaces that enable the communication of disrupted sensory signals and restoration of motor function in SCI.
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Affiliation(s)
- Lei Kiang
- Orthopaedic Surgery, Singapore General Hospital, Outram Road, Singapore, Singapore, 169608, SINGAPORE
| | - Ben Woodington
- Department of Engineering, University of Cambridge, Electrical Engineering Division, 9 JJ Thomson Ave, Cambridge, Cambridge, CB2 1TN, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Alejandro Carnicer-Lombarte
- Clinical Neurosciences, University of Cambridge, Bioelectronics Laboratory, Cambridge, CB2 0PY, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - George Malliaras
- University of Cambridge, University of Cambridge, Cambridge, CB2 1TN, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Damiano G Barone
- Department of Engineering, University of Cambridge, Electrical Engineering Division, 9 JJ Thomson Ave, Cambridge, Cambridge, Cambridgeshire, CB2 1TN, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
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12
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Wang TY, Park C, Zhang H, Rahimpour S, Murphy KR, Goodwin CR, Karikari IO, Than KD, Shaffrey CI, Foster N, Abd-El-Barr MM. Management of Acute Traumatic Spinal Cord Injury: A Review of the Literature. Front Surg 2021; 8:698736. [PMID: 34966774 PMCID: PMC8710452 DOI: 10.3389/fsurg.2021.698736] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 11/19/2021] [Indexed: 11/27/2022] Open
Abstract
Traumatic spinal cord injury (TSCI) is a debilitating disease that poses significant functional and economic burden on both the individual and societal levels. Prognosis is dependent on the extent of the spinal injury and the severity of neurological dysfunction. If not treated rapidly, patients with TSCI can suffer further secondary damage and experience escalating disability and complications. It is important to quickly assess the patient to identify the location and severity of injury to make a decision to pursue a surgical and/or conservative management. However, there are many conditions that factor into the management of TSCI patients, ranging from the initial presentation of the patient to long-term care for optimal recovery. Here, we provide a comprehensive review of the etiologies of spinal cord injury and the complications that may arise, and present an algorithm to aid in the management of TSCI.
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Affiliation(s)
- Timothy Y Wang
- Department of Neurological Surgery, Duke University Medical Center, Durham, NC, United States
| | - Christine Park
- Department of Neurological Surgery, Duke University Medical Center, Durham, NC, United States
| | - Hanci Zhang
- Department of Orthopedic Surgery, Duke University Medical Center, Durham, NC, United States
| | - Shervin Rahimpour
- Department of Neurological Surgery, Duke University Medical Center, Durham, NC, United States
| | - Kelly R Murphy
- Department of Neurological Surgery, Duke University Medical Center, Durham, NC, United States
| | - C Rory Goodwin
- Department of Neurological Surgery, Duke University Medical Center, Durham, NC, United States
| | - Isaac O Karikari
- Department of Neurological Surgery, Duke University Medical Center, Durham, NC, United States
| | - Khoi D Than
- Department of Neurological Surgery, Duke University Medical Center, Durham, NC, United States
| | - Christopher I Shaffrey
- Department of Neurological Surgery, Duke University Medical Center, Durham, NC, United States
| | - Norah Foster
- Premier Orthopedics, Centerville, OH, United States
| | - Muhammad M Abd-El-Barr
- Department of Neurological Surgery, Duke University Medical Center, Durham, NC, United States
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13
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Liu JT, Wang SY, Xiao HP, Gu B, Li HN. Effects of methylprednisolone and treadmill training on spinal cord injury in experimental rats. Exp Ther Med 2021; 22:1413. [PMID: 34676006 DOI: 10.3892/etm.2021.10849] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Accepted: 07/01/2021] [Indexed: 01/26/2023] Open
Abstract
Methylprednisolone (MP) is widely used to treat clinical spinal cord injury (SCI). Treadmill training is also considered an important treatment after SCI to improve motor function in patients, resulting in an evident improvement. Therefore, the present study was designed to evaluate and contrast the effects of MP and treadmill training administered in combination or alone after SCI in adult rats. A rat spinal cord T10 contusion model was induced in Sprague-Dawley rats using an impact device. A total of 40 rats were divided into four groups (n=10 rats/group): the MP, MP + treadmill training, SCI and sham group. At 30 min after injury, MP sodium succinate was injected into the rats of the MP and MP + treadmill training groups. Treadmill training began on the second week post-trauma and was performed for 8 weeks. The results showed that MP therapy combined with treadmill training significantly ameliorated several parameters of hind limb function compared with those by MP treatment alone (all P<0.05). A significantly reduced immunopositive area of Nogo receptor and chondroitin sulfate proteoglycans and reduced relative expression of these mRNAs were found in the MP + treadmill training group (P<0.05) compared with the findings in the MP group. In conclusion, the present study indicated that combined MP and treadmill training treatment improved the recovery of hind limb function in rats with SCI, thus potentially representing a promising strategy to cure SCI.
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Affiliation(s)
- Jian-Tao Liu
- School of Life Sciences, Jiangxi Science and Technology Normal University, Nanchang, Jiangxi 330013, P.R. China
| | - Shuo-Yu Wang
- School of Life Sciences, Jiangxi Science and Technology Normal University, Nanchang, Jiangxi 330013, P.R. China
| | - Han-Ping Xiao
- School of Life Sciences, Jiangxi Science and Technology Normal University, Nanchang, Jiangxi 330013, P.R. China
| | - Bing Gu
- School of Life Sciences, Jiangxi Science and Technology Normal University, Nanchang, Jiangxi 330013, P.R. China
| | - Hua-Nan Li
- Department of Spine Surgery, The Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Nanchang, Jiangxi 330006, P.R. China
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14
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de Sousa ACC, Bó AP. Simulation studies on hybrid neuroprosthesis control strategies for gait at low speeds. Biomed Signal Process Control 2021. [DOI: 10.1016/j.bspc.2021.102970] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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15
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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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16
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Bonizzato M, Martinez M. An intracortical neuroprosthesis immediately alleviates walking deficits and improves recovery of leg control after spinal cord injury. Sci Transl Med 2021; 13:13/586/eabb4422. [PMID: 33762436 DOI: 10.1126/scitranslmed.abb4422] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Accepted: 01/09/2021] [Indexed: 12/18/2022]
Abstract
Most rehabilitation interventions after spinal cord injury (SCI) only target the sublesional spinal networks, peripheral nerves, and muscles. However, mammalian locomotion is not a mere act of rhythmic pattern generation. Recovery of cortical control is essential for voluntary movement and modulation of gait. We developed an intracortical neuroprosthetic intervention to SCI, with the goal to condition cortical locomotor control. Neurostimulation delivered in phase coherence with ongoing locomotion immediately alleviated primary SCI deficits, such as leg dragging, in rats with incomplete SCI. Cortical neurostimulation achieved high fidelity and markedly proportional online control of leg trajectories in both healthy and SCI rats. Long-term neuroprosthetic training lastingly improved cortical control of locomotion, whereas short training held transient improvements. We performed longitudinal awake cortical motor mapping, unveiling that recovery of cortico-spinal transmission tightly parallels return of locomotor function in rats. These results advocate directly targeting the motor cortex in clinical neuroprosthetic approaches.
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Affiliation(s)
- Marco Bonizzato
- Department of Neurosciences and Groupe de recherche sur le système nerveux central (GRSNC), Université de Montréal, Montréal, Québec H3T 1N8, Canada.,CIUSSS du Nord-de-l'Île-de-Montréal, Montréal, Québec H4J 1C5, Canada
| | - Marina Martinez
- Department of Neurosciences and Groupe de recherche sur le système nerveux central (GRSNC), Université de Montréal, Montréal, Québec H3T 1N8, Canada. .,CIUSSS du Nord-de-l'Île-de-Montréal, Montréal, Québec H4J 1C5, Canada
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17
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Yokoyama H, Kaneko N, Watanabe K, Nakazawa K. Neural decoding of gait phases during motor imagery and improvement of the decoding accuracy by concurrent action observation. J Neural Eng 2021; 18. [PMID: 34082405 DOI: 10.1088/1741-2552/ac07bd] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 06/03/2021] [Indexed: 12/20/2022]
Abstract
Objective. Brain decoding of motor imagery (MI) not only is crucial for the control of neuroprosthesis but also provides insights into the underlying neural mechanisms. Walking consists of stance and swing phases, which are associated with different biomechanical and neural control features. However, previous knowledge on decoding the MI of gait is limited to simple information (e.g. the classification of 'walking' and 'rest').Approach. Here, we investigated the feasibility of electroencephalogram (EEG) decoding of the two gait phases during the MI of walking and whether the combined use of MI and action observation (AO) would improve decoding accuracy.Main results. We demonstrated that the stance and swing phases could be decoded from EEGs during MI or AO alone. We also demonstrated the decoding accuracy during MI was improved by concurrent AO. The decoding models indicated that the improved decoding accuracy following the combined use of MI and AO was facilitated by the additional information resulting from the concurrent cortical activations related to sensorimotor, visual, and action understanding systems associated with MI and AO.Significance. This study is the first to show that decoding the stance versus swing phases during MI is feasible. The current findings provide fundamental knowledge for neuroprosthetic design and gait rehabilitation, and they expand our understanding of the neural activity underlying AO, MI, and AO + MI of walking.Novelty and significanceBrain decoding of detailed gait-related information during motor imagery (MI) is important for brain-computer interfaces (BCIs) for gait rehabilitation. This study is the first to show the feasibility of EEG decoding of the stance versus swing phases during MI. We also demonstrated that the combined use of MI and action observation (AO) improves decoding accuracy, which is facilitated by the concurrent and synergistic involvement of the cortical activations for MI and AO. These findings extend the current understanding of neural activity and the combined effects of AO and MI and provide a basis for effective techniques for walking rehabilitation.
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Affiliation(s)
- Hikaru Yokoyama
- Department of Electrical and Electronic Engineering, Tokyo University of Agriculture and Technology, Tokyo, Japan.,Japan Society for the Promotion of Science, Tokyo 102-0083, Japan.,Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo 153-8902, Japan
| | - Naotsugu Kaneko
- Japan Society for the Promotion of Science, Tokyo 102-0083, Japan.,Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo 153-8902, Japan
| | - Katsumi Watanabe
- Faculty of Science and Engineering, Waseda University, Tokyo 169-8555, Japan.,Faculty of Arts, Design, and Architecture, University of New South Wales, Sydney, NSW 2021, Australia
| | - Kimitaka Nakazawa
- Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo 153-8902, Japan
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18
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Pizzolato C, Gunduz MA, Palipana D, Wu J, Grant G, Hall S, Dennison R, Zafonte RD, Lloyd DG, Teng YD. Non-invasive approaches to functional recovery after spinal cord injury: Therapeutic targets and multimodal device interventions. Exp Neurol 2021; 339:113612. [DOI: 10.1016/j.expneurol.2021.113612] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 12/24/2020] [Accepted: 01/11/2021] [Indexed: 12/16/2022]
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19
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Converging Robotic Technologies in Targeted Neural Rehabilitation: A Review of Emerging Solutions and Challenges. SENSORS 2021; 21:s21062084. [PMID: 33809721 PMCID: PMC8002299 DOI: 10.3390/s21062084] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 03/05/2021] [Accepted: 03/11/2021] [Indexed: 11/17/2022]
Abstract
Recent advances in the field of neural rehabilitation, facilitated through technological innovation and improved neurophysiological knowledge of impaired motor control, have opened up new research directions. Such advances increase the relevance of existing interventions, as well as allow novel methodologies and technological synergies. New approaches attempt to partially overcome long-term disability caused by spinal cord injury, using either invasive bridging technologies or noninvasive human-machine interfaces. Muscular dystrophies benefit from electromyography and novel sensors that shed light on underlying neuromotor mechanisms in people with Duchenne. Novel wearable robotics devices are being tailored to specific patient populations, such as traumatic brain injury, stroke, and amputated individuals. In addition, developments in robot-assisted rehabilitation may enhance motor learning and generate movement repetitions by decoding the brain activity of patients during therapy. This is further facilitated by artificial intelligence algorithms coupled with faster electronics. The practical impact of integrating such technologies with neural rehabilitation treatment can be substantial. They can potentially empower nontechnically trained individuals-namely, family members and professional carers-to alter the programming of neural rehabilitation robotic setups, to actively get involved and intervene promptly at the point of care. This narrative review considers existing and emerging neural rehabilitation technologies through the perspective of replacing or restoring functions, enhancing, or improving natural neural output, as well as promoting or recruiting dormant neuroplasticity. Upon conclusion, we discuss the future directions for neural rehabilitation research, diagnosis, and treatment based on the discussed technologies and their major roadblocks. This future may eventually become possible through technological evolution and convergence of mutually beneficial technologies to create hybrid solutions.
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20
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Zulauf-Czaja A, Al-Taleb MKH, Purcell M, Petric-Gray N, Cloughley J, Vuckovic A. On the way home: a BCI-FES hand therapy self-managed by sub-acute SCI participants and their caregivers: a usability study. J Neuroeng Rehabil 2021; 18:44. [PMID: 33632262 PMCID: PMC7905902 DOI: 10.1186/s12984-021-00838-y] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 02/10/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Regaining hand function is the top priority for people with tetraplegia, however access to specialised therapy outwith clinics is limited. Here we present a system for hand therapy based on brain-computer interface (BCI) which uses a consumer grade electroencephalography (EEG) device combined with functional electrical stimulation (FES), and evaluate its usability among occupational therapists (OTs) and people with spinal cord injury (SCI) and their family members. METHODS Users: Eight people with sub-acute SCI (6 M, 2F, age 55.4 ± 15.6) and their caregivers (3 M, 5F, age 45.3 ± 14.3); four OTs (4F, age 42.3 ± 9.8). User Activity: Researchers trained OTs; OTs subsequently taught caregivers to set up the system for the people with SCI to perform hand therapy. Hand therapy consisted of attempted movement (AM) of one hand to lower the power of EEG sensory-motor rhythm in the 8-12 Hz band and thereby activate FES which induced wrist flexion and extension. Technology: Consumer grade wearable EEG, multichannel FES, custom made BCI application. LOCATION Research space within hospital. Evaluation: donning times, BCI accuracy, BCI and FES parameter repeatability, questionnaires, focus groups and interviews. RESULTS Effectiveness: The BCI accuracy was 70-90%. Efficiency: Median donning times decreased from 40.5 min for initial session to 27 min during last training session (N = 7), dropping to 14 min on the last self-managed session (N = 3). BCI and FES parameters were stable from session to session. Satisfaction: Mean satisfaction with the system among SCI users and caregivers was 3.68 ± 0.81 (max 5) as measured by QUEST questionnaire. Main facilitators for implementing BCI-FES technology were "seeing hand moving", "doing something useful for the loved ones", good level of computer literacy (people with SCI and caregivers), "active engagement in therapy" (OT), while main barriers were technical complexity of setup (all groups) and "lack of clinical evidence" (OT). CONCLUSION BCI-FES has potential to be used as at home hand therapy by people with SCI or stroke, provided it is easy to use and support is provided. Transfer of knowledge of operating BCI is possible from researchers to therapists to users and caregivers. Trial registration Registered with NHS GG&C on December 6th 2017; clinicaltrials.gov reference number NCT03257982, url: https://clinicaltrials.gov/ct2/show/NCT03257982 .
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Affiliation(s)
- Anna Zulauf-Czaja
- Biomedical Engineering Research Division, University of Glasgow, Glasgow, UK.
| | - Manaf K H Al-Taleb
- Biomedical Engineering Research Division, University of Glasgow, Glasgow, UK.,Wasit University, Wasit, Iraq
| | - Mariel Purcell
- Queen Elizabeth National Spinal Injuries Unit, Elizabeth University Hospital, Glasgow, Queen, UK
| | - Nina Petric-Gray
- Biomedical Engineering Research Division, University of Glasgow, Glasgow, UK
| | - Jennifer Cloughley
- Queen Elizabeth National Spinal Injuries Unit, Elizabeth University Hospital, Glasgow, Queen, UK
| | - Aleksandra Vuckovic
- Biomedical Engineering Research Division, University of Glasgow, Glasgow, UK
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21
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Wahlgren C, Levi R, Amezcua S, Thorell O, Thordstein M. Prevalence of discomplete sensorimotor spinal cord injury as evidenced by neurophysiological methods: A cross-sectional study. J Rehabil Med 2021; 53:jrm00156. [PMID: 33284352 PMCID: PMC8814834 DOI: 10.2340/16501977-2774] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/17/2020] [Indexed: 11/16/2022] Open
Abstract
OBJECTIVES To assess the prevalence of residual trans-lesion connectivity in persons with chronic clinically complete spinal cord injury (discompleteness) by neurophysiological methods. PARTICIPANTS A total of 23 adults with chronic sensorimotor complete spinal cord injury, identified through regional registries the regional spinal cord registry of Östergötland, Sweden. METHODS Diagnosis of clinically complete spinal cord injury was verified by standardized neurological examination. Then, a neurophysiological examination was performed, comprising electroneurography, electromyography, sympathetic skin response and evoked potentials (sensory, laser and motor). Based on this assessment, a composite outcome measure, indicating either strong, possible or no evidence of discomplete spinal cord injury, was formed. RESULTS Strong neurophysiological evidence of discomplete spinal cord injury was found in 17% (4/23) of participants. If also accepting "possible evidence", the discomplete group comprised 39% (9/23). The remaining 61% showed no neurophysiological evidence of discompleteness. However, if also counting reports of subjective sensation elicited during neurophysiological testing in the absence of objective findings, 52% (12/23) showed indication of discomplete spinal cord injury. CONCLUSION Evidence of discomplete spinal cord injury can be demonstrated using standard neurophysiological techniques in a substantial subset of individuals with clinically complete spinal cord injury. This study adds to the evidence base indicating the potential of various modes of cross-lesional sensorimotor functional restoration in some cases of chronic clinically complete spinal cord injury.
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Affiliation(s)
- Carl Wahlgren
- Department of Rehabilitation Medicine, and Department of Health, Medicine and Caring Sciences, Division of Prevention, Rehabilitation and Community Medicine, Linköping, Sweden. E-mail:
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Nakatani S, Araki N, Hoshino T, Fukayama O, Mabuchi K. Brain-controlled cycling system for rehabilitation following paraplegia with delay-time prediction. J Neural Eng 2020; 18. [PMID: 33291086 DOI: 10.1088/1741-2552/abd1bf] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 12/08/2020] [Indexed: 11/11/2022]
Abstract
Objective.Robotic rehabilitation systems have been investigated to assist with motor dysfunction recovery in patients with lower-extremity paralysis caused by central nervous system lesions. These systems are intended to provide appropriate sensory feedback associated with locomotion. Appropriate feedback is thought to cause synchronous neuron firing, resulting in the recovery of function.Approach.In this study, we designed and evaluated an ergometric cycling wheelchair, with a brain-machine interface (BMI), that can force the legs to move by including normal stepping speeds and quick responses. Experiments were conducted in five healthy subjects and one patient with spinal cord injury (SCI), who experienced the complete paralysis of the lower limbs. Event-related desynchronization (ERD) in the β band (18-28 Hz) was used to detect lower-limb motor images.Main results.An ergometer-based BMI system was able to safely and easily force patients to perform leg movements, at a rate of approximately 1.6 seconds/step (19 rpm), with an online accuracy rate of 73.1% for the SCI participant. Mean detection time from the cue to pedaling onset was 0.83±0.31 s.Significance.This system can easily and safely maintain a normal walking speed during the experiment and be designed to accommodate the expected delay between the intentional onset and physical movement, to achieve rehabilitation effects for each participant. Similar BMI systems, implemented with rehabilitation systems, may be applicable to a wide range of patients.
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Affiliation(s)
- Shintaro Nakatani
- School of engineering, Tottori University, 101, 4 cho-me, Koyama-cho Minami School of Engineering Tottori university, Tottori, Tottori, 680-8550, JAPAN
| | - Nozomu Araki
- Graduate school of engineering, University of Hyogo, 2167, Shosha, Himeji, Hyogo, 671-2280, JAPAN
| | - Takayuki Hoshino
- Department of Mechanical Science, Hirosaki University, 3, Bunkyo, Hirosaki, Aomori, 036-8561, JAPAN
| | - Osamu Fukayama
- National Institute of Information and Communications Technology Center for Information and Neural Networks, 1-4 Yamadaoka, Suita, Osaka, 565-0871, JAPAN
| | - Kunihiko Mabuchi
- The University of Tokyo Graduate School of Information Science and Technology, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, JAPAN
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Kimura M, Nakatani S, Nishida SI, Taketoshi D, Araki N. 3D Printable Dry EEG Electrodes with Coiled-Spring Prongs. SENSORS 2020; 20:s20174733. [PMID: 32825762 PMCID: PMC7506718 DOI: 10.3390/s20174733] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 08/18/2020] [Accepted: 08/18/2020] [Indexed: 11/20/2022]
Abstract
Various dry electroencephalography (EEG) electrodes have been developed. Dry EEG electrodes need to be pressed onto the scalp; therefore, there is a tradeoff between keeping the contact impedance low and maintaining comfort. We propose an approach to solve this tradeoff through the printing of complex-shaped electrodes by using a stereolithography 3D printer. To show the feasibility of our approach, we fabricated electrodes that have flexible fingers (prongs) with springs. Although dry electrodes with flexible prongs have been proposed, a suitable spring constant has not been obtained. In this study, the spring constant of our electrodes was determined from a contact model between the electrodes and the scalp. The mechanical properties and reproductivity of the electrodes were found to be sufficient. Finally, we measured the alpha waves when a participant opened/closed his eyes by using our electrodes.
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Affiliation(s)
- Masaya Kimura
- Graduate School of Sustainability Science, Tottori University, 4-101, Koyama-cho Minami, Tottori 680-8552, Japan; (M.K.); (S.-I.N.)
| | - Shintaro Nakatani
- Graduate School of Sustainability Science, Tottori University, 4-101, Koyama-cho Minami, Tottori 680-8552, Japan; (M.K.); (S.-I.N.)
- Advanced Mechanical and Electronic System Research Center, Faculty of Engineering, Tottori University, 4-101, Koyama-cho Minami, Tottori 680-8552, Japan
- Correspondence:
| | - Shin-Ichiro Nishida
- Graduate School of Sustainability Science, Tottori University, 4-101, Koyama-cho Minami, Tottori 680-8552, Japan; (M.K.); (S.-I.N.)
- Advanced Mechanical and Electronic System Research Center, Faculty of Engineering, Tottori University, 4-101, Koyama-cho Minami, Tottori 680-8552, Japan
| | - Daiju Taketoshi
- Technical Department, Tottori University, 4-101, Koyama-cho Minami, Tottori 680-8552, Japan;
| | - Nozomu Araki
- Graduate School of Engineering, University of Hyogo, 2167 Shosha, Himeji, Hyogo 671-2201, Japan;
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Foldes ST, Boninger ML, Weber DJ, Collinger JL. Effects of MEG-based neurofeedback for hand rehabilitation after tetraplegia: preliminary findings in cortical modulations and grip strength. J Neural Eng 2020; 17:026019. [PMID: 32135525 DOI: 10.1088/1741-2552/ab7cfb] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
OBJECTIVE Neurofeedback (NF) trains people to volitionally modulate their cortical activity to affect a behavioral outcome. We evaluated the feasibility of using NF to improve hand function after chronic cervical-level spinal cord injury (SCI) using biologically-relevant visual feedback of motor-related brain activity and an intuitive control scheme. APPROACH The NF system acquired magnetoencephalography (MEG) data in real-time to provide feedback of event-related desynchronization (ERD) measured over the sensorimotor cortex during attempted hand grasping. During brain control, stronger ERD resulting from attempted grasping drove the virtual hand towards a more closed grasp, while less ERD drove the hand more open. MAIN RESULTS Eight individuals with partial or complete hand impairment due to chronic SCI controlled the NF to perform a grasping task that increased in difficulty as the participants achieved success. During their first NF session, participants achieved an average success rate of 63.7 ± 6.4% (chance level of 13.9%). After as few as one intervention session, four of the seven individuals evaluated for ERD changes had significantly strengthened ERD and three of the four participants with measurable grip strength prior to NF had increased grip strength. Interestingly, both individuals who participated in a longer-term study (i.e. >8 NF sessions) had improved grip strength and significantly strengthened ERD. SIGNIFICANCE This study demonstrates that MEG-based NF training can change brain activity in individuals with hand impairment due to SCI and has the potential to induce acute changes in grip strength. Future studies will evaluate whether neuroplasticity induced with long term NF can improve hand function for those with moderate impairment.
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Affiliation(s)
- Stephen T Foldes
- VA Pittsburgh Healthcare System, Pittsburgh, PA, United States of America. Rehab Neural Engineering Labs, Departments of Physical Medicine and Rehabilitation and Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America. Center for the Neural Basis of Cognition, Pittsburgh, PA, United States of America. Barrow Neurological Institute, Phoenix Children's Hospital, Phoenix, AZ, United States of America
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Saha S, Baumert M. Intra- and Inter-subject Variability in EEG-Based Sensorimotor Brain Computer Interface: A Review. Front Comput Neurosci 2020; 13:87. [PMID: 32038208 PMCID: PMC6985367 DOI: 10.3389/fncom.2019.00087] [Citation(s) in RCA: 78] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Accepted: 12/16/2019] [Indexed: 12/05/2022] Open
Abstract
Brain computer interfaces (BCI) for the rehabilitation of motor impairments exploit sensorimotor rhythms (SMR) in the electroencephalogram (EEG). However, the neurophysiological processes underpinning the SMR often vary over time and across subjects. Inherent intra- and inter-subject variability causes covariate shift in data distributions that impede the transferability of model parameters amongst sessions/subjects. Transfer learning includes machine learning-based methods to compensate for inter-subject and inter-session (intra-subject) variability manifested in EEG-derived feature distributions as a covariate shift for BCI. Besides transfer learning approaches, recent studies have explored psychological and neurophysiological predictors as well as inter-subject associativity assessment, which may augment transfer learning in EEG-based BCI. Here, we highlight the importance of measuring inter-session/subject performance predictors for generalized BCI frameworks for both normal and motor-impaired people, reducing the necessity for tedious and annoying calibration sessions and BCI training.
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Affiliation(s)
- Simanto Saha
- School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA, Australia
| | - Mathias Baumert
- School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA, Australia
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