Meditation EEG Interpretation Based on Novel Fuzzy-Merging Strategies and Wavelet Features

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Title:	Meditation EEG Interpretation Based on Novel Fuzzy-Merging Strategies and Wavelet Features
Authors:	Kang-Ming Chang;Pei-Chen Lo
Keywords:	Meditation EEG (electroencephalogram) scoring;Wavelet analysis;Fuzzy c-means;clustering (FCM);meditation scenario
Date:	2005-08
Issue Date:	2010-05-12 01:12:14 (UTC+0)
Publisher:	Asia University
Abstract:	As the advantages of meditation have been outlined literally, scientific exploration of the meditation phenomena becomes significant. Meditation EEG may provide an access to the mental states beyond normal consciousness. It is the first attempt to score the meditation course by EEG. Wavelet analysis and fuzzy c-means (FCM) are applied in the automatic interpretation algorithm. However, FCM applied straightforward to quantitative feature vectors often results in an over-trifling interpretation. As a consequence, this paper presents novel cluster-managing strategies for achieving an interpretation closer to the result of naked-eye examination. The running gray-scale chart, derived by extracting, clustering, and coding the EEG features, reveals five different meditation scenarios differing from those of the controlled subjects.
Relation:	Journal of Biomedical Engineering-Applications, Basis & Communications 17: 167-175
Appears in Collections:	[Department of Photonics and Communication Engineering] Journal Article

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