Principal component analysis of wavelet variances of Chan-meditation and resting EEG

• Main Authors: Ciou, Wei-Syun, 邱偉勳
• Other Authors: Lo, Pei-Chen
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/jwd9xj

碩士 === 國立交通大學 === 電控工程研究所 === 101 === This thesis is aimed to investigate the high-frequency components in EEG signals by estimating the variance of wavelet coefficients and analyzing the principle components of variance matrix. EEG’s were recorded from two groups of volunteers. Experimental and control group involved respectively eight experienced Chan-Meditation practitioners and eight healthy control subjects within the same age range. First we decomposed the 2-minute EEG signals into one-second epochs. For each epoch, Maximal Overlap Discrete Wavelet Transform（MODWT）was employed to evaluate the wavelet coefficients and then estimate the variance of wavelet coefficients for all 30 channels. For each channel, seven variances were computed for seven wavelet scales corresponding to different EEG rhythms. Accordingly, each one-second epoch can be represented by a feature vector composed of 7 variances. Then, for the 30-channel EEGs, we constructed a 30-by-7 matrix and applied PCA (Principle Component Analysis) to obtain the mapping of the first principle component（PC1）. Brain mappings of different variances and PC1 allow us to identify the spatial focalization of particular EEG rhythms. In this study, we analyzed one-second epochs of EEG. After analyzing the whole signal, average mapping of PC1 was compared. Brain spatio-spectral characteristics of experimental/control volunteers under mental stress and meditation/rest were explored by dividing the brain cortex into five regions of local neural networks, frontal (F), parietal (P), right-temporal (R), left-temporal (L) and central (C) regions, defined by five clusters of nearby EEG channels. We focused on analyzing EEG of pre-mental-stress-test session and post-mental-stress-test session and compared the results. For control group, difference of the high-frequency components between these two sessions is not significant. For experimental group, after Chan-meditation practice, variation of the high-frequency components is more significant than control group.