Brain-Computer Interface Channel-Selection Strategy Based on Analysis of Event-Related Desynchronization Topography in Stroke Patients
Joint Authors
Li, Chong
Ji, Linhong
Jia, Tianyu
Xu, Quan
Pan, Yu
Source
Journal of Healthcare Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-08-28
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
In the last decade, technology-assisted stroke rehabilitation has been the focus of research.
Electroencephalogram- (EEG-) based brain-computer interface (BCI) has a great potential for motor rehabilitation in stroke patients since the closed loop between motor intention and the actual movement established by BCI can stimulate the neural pathways of motor control.
Due to the deficits in the brain, motor intention expression may shift to other brain regions during and even after neural reorganization.
The objective of this paper was to study the event-related desynchronization (ERD) topography during motor attempt tasks of the paretic hand in stroke patients and compare the classification performance using different channel-selection strategies in EEG-based BCI.
Fifteen stroke patients were recruited in this study.
A cue-based experimental paradigm was applied in the experiment, in which each patient was required to open the palm of the paretic or the unaffected hand.
EEG was recorded and analyzed to measure the motor intention and indicate the activated brain regions.
Support vector machine (SVM) combined with common spatial pattern (CSP) algorithm was used to calculate the offline classification accuracy between the motor attempt of the paretic hand and the resting state applying different channel-selection strategies.
Results showed individualized ERD topography during the motor attempt of the paretic hand due to the deficits caused by stroke.
Statistical analysis showed a significant increase in the classification accuracy by analyzing the channels showing ERD than analyzing the channels from the contralateral sensorimotor cortex (SM1).
The results indicated that for stroke patients whose affected motor cortex is extensively damaged, the compensated brain regions should be considered for implementing EEG-based BCI for motor rehabilitation as the closed loop between the altered activated brain regions and the paretic hand can be stimulated more accurately using the individualized channel-selection strategy.
American Psychological Association (APA)
Li, Chong& Jia, Tianyu& Xu, Quan& Ji, Linhong& Pan, Yu. 2019. Brain-Computer Interface Channel-Selection Strategy Based on Analysis of Event-Related Desynchronization Topography in Stroke Patients. Journal of Healthcare Engineering،Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1175146
Modern Language Association (MLA)
Li, Chong…[et al.]. Brain-Computer Interface Channel-Selection Strategy Based on Analysis of Event-Related Desynchronization Topography in Stroke Patients. Journal of Healthcare Engineering No. 2019 (2019), pp.1-12.
https://search.emarefa.net/detail/BIM-1175146
American Medical Association (AMA)
Li, Chong& Jia, Tianyu& Xu, Quan& Ji, Linhong& Pan, Yu. Brain-Computer Interface Channel-Selection Strategy Based on Analysis of Event-Related Desynchronization Topography in Stroke Patients. Journal of Healthcare Engineering. 2019. Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1175146
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1175146