The Finger Movement Identification Based on Fuzzy Clustering and BP Neural Network

摘要：

The classification and identification technology plays an important role in the research of Brain-computer interface (BCI) systems. In this paper, we do fuzzy clustering disposal for the multi-channel electroencephalogram (ERG) during finger movement at first according to event-related desynchronization phenomena (ERD) in the event-related EEC Then we classify signal-trial EEC with the feature extracted from EEG based on common spatial subspace decomposition (CSSD) algorithm. The averaged classification accuracy achieves 94.58％ in the course of testing on the data from four subjects. Experiment results show that the combination of fuzzy clustering and neural network can greatly improve the rate of identification for finger movement.

关键词： fuzzy clustering BP network finger movement identification

作者: Lanlan Yu Tianxing Meng Jian Hu

作者单位: School of Electric and Electronic Engineering, Shandong University of Technology Zibo, 255091, China

会议类型: 国际会议

会议名称: The Second International Conference on Business Intelligence and Financial Engineering(BIFE 2009)(第二届商务智能与金融工程国际会议)

会议地点: 北京

会议语种:英文

页码: 29-33

在线出版日期: 2009-07-24（万方平台首次上网日期，不代表论文的发表时间）