Chowdhury, Anirban and Raza, Haider and Meena, Yogesh Kumar and Dutta, Ashish and Prasad, Girijesh (2019) An EEG-EMG Correlation-based Brain-Computer Interface for Hand Orthosis Supported Neuro-Rehabilitation. Journal of Neuroscience Methods, 312. pp. 1-11. DOI https://doi.org/10.1016/j.jneumeth.2018.11.010
Chowdhury, Anirban and Raza, Haider and Meena, Yogesh Kumar and Dutta, Ashish and Prasad, Girijesh (2019) An EEG-EMG Correlation-based Brain-Computer Interface for Hand Orthosis Supported Neuro-Rehabilitation. Journal of Neuroscience Methods, 312. pp. 1-11. DOI https://doi.org/10.1016/j.jneumeth.2018.11.010
Chowdhury, Anirban and Raza, Haider and Meena, Yogesh Kumar and Dutta, Ashish and Prasad, Girijesh (2019) An EEG-EMG Correlation-based Brain-Computer Interface for Hand Orthosis Supported Neuro-Rehabilitation. Journal of Neuroscience Methods, 312. pp. 1-11. DOI https://doi.org/10.1016/j.jneumeth.2018.11.010
Abstract
Background Corticomuscular coupling has been investigated for long, to find out the underlying mechanisms behind cortical drives to produce different motor tasks. Although important in rehabilitation perspective, the use of corticomuscular coupling for driving brain-computer interface (BCI)-based neurorehabilitation is much ignored. This is primarily due to the fact that the EEG-EMG coherence popularly used to compute corticomuscular coupling, fails to produce sufficient accuracy in single-trial based prediction of motor tasks in a BCI system. New Method In this study, we have introduced a new corticomuscular feature extraction method based on the correlation between band-limited power time-courses (CBPT) associated with EEG and EMG. 16 healthy individuals and 8 hemiplegic patients participated in a BCI-based hand orthosis triggering task, to test the performance of the CBPT method. The healthy population was equally divided into two groups; one experimental group for CBPT-based BCI experiment and another control group for EEG-EMG coherence based BCI experiment. Results The classification accuracy of the CBPT-based BCI system was found to be 92.81±2.09% for the healthy experimental group and 84.53±4.58% for the patients’ group. Comparison with existing method The CBPT method significantly (p−value < 0.05) outperformed the conventional EEG-EMG coherence method in terms of classification accuracy. Conclusions The experimental results clearly indicate that the EEG-EMG CBPT is a better alternative as a corticomuscular feature to drive a BCI system. Additionally, it is also feasible to use the proposed method to design BCI-based robotic neurorehabilitation paradigms.
Item Type: | Article |
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Uncontrolled Keywords: | Corticomuscular-Coherence (CMC); Correlation between band-limited power time-courses (CBPT); Electroencephalogram (EEG); Electromyogram (EMG); Hybrid Brain-computer interface (h-BCI); Hand Orthosis; Neurorehabilitation |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 19 Nov 2018 09:56 |
Last Modified: | 07 Aug 2024 19:04 |
URI: | http://repository.essex.ac.uk/id/eprint/23487 |
Available files
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