TY - GEN
T1 - Multi-Direction Decoding of Both-Hand Movement Using EEG Signals
AU - Gao, Run
AU - Liu, Ying
AU - Wang, Jiarong
AU - Bi, Luzheng
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - In this paper, we propose a method to decode the both-hand movement multi-direction based on electroencephalogram (EEG) signals. We use two kinds of decoding features, which are the potential amplitudes and power sums of EEG signals. One-versus-rest and decision tree are adopted as classification strategies, and linear discriminant analysis (LDA) classifier is used for classification. We apply an experimental paradigm to demonstrate the proposed method. The best four-class classification performance using the power sums of EEG signals with the one-versus-rest classification strategy is close to 70%. The experimental results show the feasibility of decoding both-hand movement multi-directions based on EEG signals. This work can promote the development of brain-computer interfaces for the assistance of hand-impaired patients.
AB - In this paper, we propose a method to decode the both-hand movement multi-direction based on electroencephalogram (EEG) signals. We use two kinds of decoding features, which are the potential amplitudes and power sums of EEG signals. One-versus-rest and decision tree are adopted as classification strategies, and linear discriminant analysis (LDA) classifier is used for classification. We apply an experimental paradigm to demonstrate the proposed method. The best four-class classification performance using the power sums of EEG signals with the one-versus-rest classification strategy is close to 70%. The experimental results show the feasibility of decoding both-hand movement multi-directions based on EEG signals. This work can promote the development of brain-computer interfaces for the assistance of hand-impaired patients.
UR - http://www.scopus.com/inward/record.url?scp=85138736985&partnerID=8YFLogxK
U2 - 10.1109/RCAR54675.2022.9872187
DO - 10.1109/RCAR54675.2022.9872187
M3 - Conference contribution
AN - SCOPUS:85138736985
T3 - 2022 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2022
SP - 644
EP - 647
BT - 2022 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2022
Y2 - 17 July 2022 through 22 July 2022
ER -