The non-stationary of evoked potential tracked by ICA and WT

Author

Ding, Haiyan ; Ye, Datian

Author_Institution

Dept. of Biomedical Eng., Tsinghua Univ., Beijing

fYear

0

fDate

0-0 0

Firstpage

74

Lastpage

76

Abstract

This paper promotes a method to track the non-stationary of evoked potential´s amplitude during the electroencephalograph recording by the application of independent component analysis and wavelet transform. With the aid of the spatial information and multi-trial recording, the signal-to-noise ratio is improved greatly enough to quantitatively evaluate how the evoked potential´s amplitude varies across the trials. The result on real auditory evoked potential shows a drop of about 40% on the amplitude of evoked potential during 10 minutes recording. The present work is helpful to study the uncertainty and singularity of evoked potential. Furthermore, it will put forward the reasonable experiment design of evoked potential extraction

Keywords

auditory evoked potentials; electroencephalography; independent component analysis; medical signal processing; wavelet transforms; ICA; WT; auditory evoked potential; electroencephalography; evoked potential extraction; independent component analysis; nonstationary evoked potential; signal-to-noise ratio; wavelet transform; Biomedical engineering; Brain modeling; Data mining; Electroencephalography; Independent component analysis; Principal component analysis; Signal to noise ratio; Uncertainty; Wavelet analysis; Wavelet transforms; Evoked potential (EP); Independent component analysis (ICA); Wavelet transform (WT);

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Architectures for Machine Perception, 2003 IEEE International Workshop on

Conference_Location

Hong Kong

Print_ISBN

0-7803-8612-4

Type

conf

DOI

10.1109/ISSMD.2004.1689564

Filename

1689564