Open AccessRemoval of ocular artifacts from EEG signals using adaptive threshold PCA and Wavelet transforms
Author(s) -
P. Ashok Babu,
K. Rajendra Prasad
Publication year - 2011
Publication title -
international journal of electronic signal and systems
Language(s) - English
Resource type - Journals
ISSN - 2231-5969
DOI - 10.47893/ijess.2011.1009
Subject(s) - electroencephalography , principal component analysis , artificial intelligence , pattern recognition (psychology) , computer science , wavelet , threshold limit value , wavelet transform , computer vision , speech recognition , psychology , medicine , neuroscience , environmental health
It becomes more difficult to identify and analyze the Electroencephalogram (EEG) signals when it is corrupted by eye movements and eye blinks. This paper gives the different methods how to remove the artifacts in EEG signals. In this paper we proposed wavelet based threshold method and Principal Component Analysis (PCA) based adaptive threshold method to remove the ocular artifacts. Compared to the wavelet threshold method PCA based adaptive threshold method will gives the better PSNR value and it will decreases the elapsed time.