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dc.contributor.authorLo, Pei-Chenen_US
dc.contributor.authorZhu, Qiangen_US
dc.date.accessioned2014-12-08T15:20:10Z-
dc.date.available2014-12-08T15:20:10Z-
dc.date.issued2009en_US
dc.identifier.isbn978-1-4244-4705-3en_US
dc.identifier.urihttp://hdl.handle.net/11536/14300-
dc.description.abstractThis paper reports our preliminary result of microstate analysis for the spatiotemporal characteristics of Chan-meditation brain wave (electroencephalograph, EEG) based on time-varying dipolar-vector model of the alpha-map. Microstate behavior reveals subtle transience of focalized event. Multi-channel alpha-event epochs were identified by Wavelet decomposition and feature extraction. Global field power was adopted as the criterion to choose alpha-map candidates (normalized alpha-power vectors), that were further classified by Mahalanobis Fuzzy C-means into different region-focalization states. Transition between various alpha-event focalization states was ready to be explored via microstate analysis. Our findings reveal that Chan-meditation practitioners exhibit longer duration of frontal alpha-event microstate, reflecting sustained stability of the brain generators.en_US
dc.language.isoen_USen_US
dc.subjectMicrostate analysisen_US
dc.subjectelectroencephalograph (EEG)en_US
dc.subjectChan meditationen_US
dc.subjectwavelet decompositionen_US
dc.subjectMahalanobis Fuzzy C-means (M-FCM)en_US
dc.subjectbrain mappingen_US
dc.subjectfrontal alphaen_US
dc.titleMICROSTATE ANALYSIS OF ALPHA-EVENT BRAIN TOPOGRAPHY DURING CHAN MEDITATIONen_US
dc.typeArticleen_US
dc.identifier.journalPROCEEDINGS OF 2009 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-6en_US
dc.citation.spage717en_US
dc.citation.epage721en_US
dc.contributor.department電控工程研究所zh_TW
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.identifier.wosnumberWOS:000281720400133-
Appears in Collections:Conferences Paper