Title :
Application of Kalman Filtering in the Detection of Evoked Potentials
Author :
Hou, Shuping ; Yu, Bai
Author_Institution :
Sch. of Inf. Eng., Tianjin Univ. of Commerce, Tianjin
Abstract :
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.
Keywords :
Kalman filters; bioelectric potentials; electroencephalography; medical signal detection; medical signal processing; signal denoising; EEG; Kalman filtering; electroencephalogram; evoked potentials detection; recursive data processing algorithm; signal denoising; signal extraction; Business; Data mining; Difference equations; Digital signal processing; Electroencephalography; Filtering; Kalman filters; Scalp; Signal processing; Wiener filter;
Conference_Titel :
Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-1747-6
Electronic_ISBN :
978-1-4244-1748-3
DOI :
10.1109/ICBBE.2008.214
