Is EMG a viable alternative to BCI for detecting movement intention in severe stroke?
File(s)
Accepted version
Author(s)
Balasubramanian, Sivakumar
Garcia-Cossio, Eliana
Birbaumer, Niels
Burdet, Etienne
Ramos-Murguialday, Ander
Type
Journal Article
Abstract
Objective: In light of the shortcomings of current restorative brain-computer interfaces (BCI), this study investigated the possibility of using EMG to detect hand/wrist extension movement intention to trigger robot-assisted training in individuals without residual movements. Methods: We compared movement intention detection using an EMG detector with a sensorimotor rhythm based EEG-BCI using only ipsilesional activity. This was carried out on data of 30 severely affected chronic stroke patients from a randomized control trial using an EEG-BCI for robot-assisted training. Results: The results indicate the feasibility of using EMG to detect movement intention in this severely handicapped population; probability of detecting EMG when patients attempted to move was higher (p <; 0.001) than at rest. Interestingly, 22 out of 30 (or 73%) patients had sufficiently strong EMG in their finger/wrist extensors. Furthermore, in patients with detectable EMG, there was poor agreement between the EEG and EMG intent detectors, which indicates that these modalities may detect different processes. Conclusion : A substantial segment of severely affected stroke patients may benefit from EMG-based assisted therapy. When compared to EEG, a surface EMG interface requires less preparation time, which is easier to don/doff, and is more compact in size. Significance: This study shows that a large proportion of severely affected stroke patients have residual EMG, which yields a direct and practical way to trigger robot-assisted training.
Date Issued
2018-12-01
Date Acceptance
2018-03-04
Citation
IEEE Transactions on Biomedical Engineering, 2018, 65 (12), pp.2790-2797
ISSN
0018-9294
Publisher
Institute of Electrical and Electronics Engineers
Start Page
2790
End Page
2797
Journal / Book Title
IEEE Transactions on Biomedical Engineering
Volume
65
Issue
12
Copyright Statement
© 2018 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.
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000451253600014&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
Science & Technology
Technology
Engineering, Biomedical
Engineering
Stroke
EMG
BCI
neurorehabilitation
movement intention
BRAIN-COMPUTER INTERFACE
UPPER-EXTREMITY
MUSCLE-ACTIVITY
NEUROMUSCULAR STIMULATION
ELECTRICAL-STIMULATION
CORTICAL POTENTIALS
ASSOCIATIVE BRAIN
TIBIALIS ANTERIOR
ONSET
THERAPY
Publication Status
Published
Date Publish Online
2018-03-21