Intramuscular EMG-driven musculoskeletal modelling: towards implanted muscle interfacing in spinal cord injury patients
File(s)TBME-02406-2020-R1.pdf (2.22 MB)
Accepted version
OA Location
Author(s)
Type
Journal Article
Abstract
OBJECTIVE: Surface EMG-driven modelling has been proposed as a means to control assistive devices by estimating joint torques. Implanted EMG sensors have several advantages over wearable sensors but provide a more localized information on muscle activity, which may impact torque estimates. Here, we tested and compared the use of surface and intramuscular EMG measurements for the estimation of required assistive joint torques using EMG driven modelling. METHODS: Four healthy subjects and three incomplete spinal cord injury (SCI) patients performed walking trials at varying speeds. Motion capture marker trajectories, surface and intramuscular EMG, and ground reaction forces were measured concurrently. Subject-specific musculoskeletal models were developed for all subjects, and inverse dynamics analysis was performed for all individual trials. EMG-driven modelling based joint torque estimates were obtained from surface and intramuscular EMG. RESULTS: The correlation between the experimental and predicted joint torques was similar when using intramuscular or surface EMG as input to the EMG-driven modelling estimator in both healthy individuals and patients. CONCLUSION: We have provided the first comparison of non-invasive and implanted EMG sensors as input signals for torque estimates in healthy individuals and SCI patients. SIGNIFICANCE: Implanted EMG sensors have the potential to be used as a reliable input for assistive exoskeleton joint torque actuation.
Date Issued
2021-06-07
Date Acceptance
2021-05-31
Citation
IEEE Transactions on Biomedical Engineering, 2021, 69 (1), pp.63-74
ISSN
0018-9294
Publisher
Institute of Electrical and Electronics Engineers
Start Page
63
End Page
74
Journal / Book Title
IEEE Transactions on Biomedical Engineering
Volume
69
Issue
1
Copyright Statement
© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.
License URL
Sponsor
Commision of the European Communities
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/34097604
Grant Number
779982
Subjects
Science & Technology
Technology
Engineering, Biomedical
Engineering
EMG driven modelling
musculoskeletal model
electromyography
assistive technology
human-machine interface
spinal cord injury
JOINT MOMENTS
GAIT
RELIABILITY
MOVEMENTS
FORCES
Biomedical Engineering
0801 Artificial Intelligence and Image Processing
0903 Biomedical Engineering
0906 Electrical and Electronic Engineering
Publication Status
Published online
Coverage Spatial
United States
Date Publish Online
2021-06-07