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

Bibliographic Details
Title: An Approach for Pattern Recognition of EEG Applied in Prosthetic Hand Drive
Authors: Xiao-Dong Zhang, Yun-Xia Wang, Yao-Nan Li, Jin-Jin Zhang
Source: Journal of Systemics, Cybernetics and Informatics, Vol 9, Iss 6, Pp 51-56 (2011)
Publisher Information: International Institute of Informatics and Cybernetics, 2011.
Publication Year: 2011
Collection: LCC:Information technology
LCC:Communication. Mass media
Subject Terms: Prosthesis Hand, pattern recognition, Brain-Computer Interface, Eeg, Information technology, T58.5-58.64, Communication. Mass media, P87-96
More Details: 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.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 1690-4524
Relation: http://www.iiisci.org/Journal/CV$/sci/pdfs/RO865CT.pdf; https://doaj.org/toc/1690-4524
Access URL: https://doaj.org/article/bc178b215966420b858ab50e9a41af01
Accession Number: edsdoj.bc178b215966420b858ab50e9a41af01
Database: Directory of Open Access Journals