MEDITATION EEG INTERPRETATION BASED ON NOVEL FUZZY-MERGING STRATEGIES AND WAVELET FEATURES
Author(s) -
Kang-Ming Chang,
PeiChen Lo
Publication year - 2005
Publication title -
biomedical engineering applications basis and communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.171
H-Index - 22
eISSN - 1793-7132
pISSN - 1016-2372
DOI - 10.4015/s1016237205000263
Subject(s) - meditation , wavelet , electroencephalography , interpretation (philosophy) , artificial intelligence , computer science , pattern recognition (psychology) , fuzzy logic , chart , psychology , speech recognition , mathematics , statistics , psychiatry , philosophy , programming language , theology
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.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom