Decoding Coordinated Directions of Bimanual Movements from EEG Signals
Bimanual coordination is common in human daily life, whereas current research focused mainly on decoding unimanual movement from electroencephalogram (EEG) signals. Here we developed a brain-computer interface (BCI) paradigm of task-oriented bimanual movements to decode coordinated directions from movement-related cortical potentials (MRCPs) of EEG. Eight healthy subjects participated in the target-reaching task, including (1) performing leftward, midward, and rightward bimanual movements, and (2) performing leftward and rightward unimanual movements. A combined deep learning model of convolution neural network and bidirectional long short-term memory network was proposed to classify movement directions from EEG. Results showed that the average peak classification accuracy for three coordinated directions of bimanual movements reached 73.39 ± 6.35%. The binary classification accuracies achieved 80.24 ± 6.25, 82.62 ± 7.82, and 86.28 ± 5.50% for leftward versus midward, rightward versus midward and leftward versus rightward, respectively. We also compared the binary classification (leftward versus rightward) of bimanual, left-hand, and right-hand movements, and accuracies achieved 86.28 ± 5.50%, 75.67 ± 7.18%, and 77.79 ± 5.65%, respectively. The results indicated the feasibility of decoding human coordinated directions of task-oriented bimanual movements from EEG.
|EI Accession Number|
Bandpass filters ; Biomedical signal processing ; Brain ; Decoding ; Deep learning ; Electroencephalography ; Electrophysiology ; Interfaces (computer) ; Job analysis
|ESI Classification Code|
Biomedical Engineering:461.1 ; Ergonomics and Human Factors Engineering:461.4 ; Medicine and Pharmacology:461.6 ; Electric Filters:703.2 ; Information Theory and Signal Processing:716.1 ; Computer Peripheral Equipment:722.2 ; Data Processing and Image Processing:723.2
|ESI Research Field|
Cited Times [WOS]:1
|Document Type||Journal Article|
|Department||Department of Biomedical Engineering|
Department of Biomedical Engineering, Shenzhen Key Laboratory of Smart Healthcare Engineering, Guangdong Provincial Key Laboratory of Advanced Biomaterials, Southern University of Science and Technology, Shenzhen, China
|First Author Affilication||Department of Biomedical Engineering|
|First Author's First Affilication||Department of Biomedical Engineering|
Zhang，Mingming,Wu，Junde,Song，Jongbin,et al. Decoding Coordinated Directions of Bimanual Movements from EEG Signals[J]. IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING,2022,PP(99):1-1.
Zhang，Mingming.,Wu，Junde.,Song，Jongbin.,Fu，Ruiqi.,Ma，Rui.,...&Chen，Yi Feng.(2022).Decoding Coordinated Directions of Bimanual Movements from EEG Signals.IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING,PP(99),1-1.
Zhang，Mingming,et al."Decoding Coordinated Directions of Bimanual Movements from EEG Signals".IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING PP.99(2022):1-1.
|Files in This Item:||There are no files associated with this item.|
|Recommend this item|
|Export to Endnote|
|Export to Excel|
|Export to Csv|
|Similar articles in Google Scholar|
|Similar articles in Baidu Scholar|
|Similar articles in Bing Scholar|
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.