An Approach for Pattern Recognition of EEG Applied in Prosthetic Hand Drive

Journal of Systemics, Cybernetics and Informatics

Xiao-Dong Zhang¹  Yao-Nan Li²  Jin-Jin Zhang²  Yun-Xia Wang² 

[1] Shenyang Institute of automation Chinese Academy of Sciences;Xi’an Jiaotong University;

关键词: Prosthesis Hand;    pattern recognition;    Brain-Computer Interface;    Eeg;   

DOI  :  

来源: DOAJ

【 摘 要 】

For controlling the prosthetic hand by only electroencephalogram (EEG), it has become the hot spot in robotics research to set up a direct communication and control channel between human brain and prosthetic hand. In this paper, the EEG signal is analyzed based on multi-complicated hand activities. And then, two methods of EEG pattern recognition are investigated, a neural prosthesis hand system driven by BCI is set up, which can complete four kinds of actions (arm’s free state, arm movement, hand crawl, hand open). Through several times of off-line and on-line experiments, the result shows that the neural prosthesis hand system driven by BCI is reasonable and feasible, the C-support vector classifiers-based method is better than BP neural network on the EEG pattern recognition for multi-complicated hand activities.

【 授权许可】

Unknown