Application of Kalman Filtering in the Detection of Evoked Potentials
A method is proposed for de-noising and extracting non-stationary electroencephalogram (EEG) signals. Kalman filtering is an optimal recursive data processing algorithm. In this paper Kalman filtering is used to estimate evoked potentials (EP) from large background noise of electroencephalogram (EEG). The Waveforms of before filtering and after filtering is simulated and compared. The results show that the method can extract EP from the stationary random noise signals, and the filtering effect is more satisfied.
EEG EP Kalman Filternig
Shuping Hou Bai Yu
School of Information Engineering Tianjin University of Commerce Tianjin, China
国际会议
上海
英文
873-875
2008-05-16（万方平台首次上网日期，不代表论文的发表时间）