Study on EEG Signal Processing for Visual P300-Speller
In recent years,the patients with motor dysfunction have become a special social group with increasing number that needs more concerns and cares.Aimed at designing a new brain-computer interface for such patients,this paper proposed a visual P300-speller system with a matrix containing letters and numbers and developed its EEG signal processing algorithm.ABSVM-RFE method was used for channel selection to shorten time of calculations.The proposed system has been validated through offline and online experiments.The highest accuracy of the offline experiments was 99%.In the online tests,EEG data were analysed using only one channel with three subjects and the system achieved a data transfer rate of 7.27 bits/min with a highest accuracy of 80%.It may provide technique support for the effective exploration of voluntary information output channels for those severe disables.
motor dysfunction brain-controlled virtual keyboard visual P300-speller
Long Chen Dong Ming Min-Peng Xu Yu-Feng Ke Nan-Nan Li Hong-Zhi Qi Bai-Kun Wan
College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
国际会议
天津
英文
227-230
2012-10-16（万方平台首次上网日期，不代表论文的发表时间）