Extraction of evoked related potentials by using the combination of independent component analysis and wavelet analysis
Zou, L.; Chen, S.; Sun, Y.; Ma, Z.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi 27(4): 741-745
2010
ISSN/ISBN: 1001-5515 PMID: 20842836 Document Number: 642608
In this paper we present a new method of combining Independent Component Analysis (ICA) and Wavelet de-noising algorithm to extract Evoked Related Potentials (ERPs). First, the extended Infomax-ICA algorithm is used to analyze EEG signals and obtain the independent components (Ics); Then, the Wave Shrink (WS) method is applied to the demixed Ics as an intermediate step; the EEG data were rebuilt by using the inverse ICA based on the new Ics; the ERPs were extracted by using de-noised EEG data after being averaged several trials. The experimental results showed that the combined method and ICA method could remove eye artifacts and muscle artifacts mixed in the ERPs, while the combined method could retain the brain neural activity mixed in the noise Ics and could extract the weak ERPs efficiently from strong background artifacts.