Hurst Exponents and Linear Regression with an Application to Low-Power Beta Characterization in meditation EEG

ASIA unversity > 資訊學院 > 光電與通訊學系 > 期刊論文 > Item 310904400/9552

Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/9552

Title:	Hurst Exponents and Linear Regression with an Application to Low-Power Beta Characterization in meditation EEG
Authors:	Kang-Ming Chang;Pei-Chen Lo
Keywords:	Beta rhythm EEG;Hurst exponent;meditation;regression-fitting;wavelet
Date:	2005-06
Issue Date:	2010-05-12 01:12:13 (UTC+0)
Publisher:	Asia University
Abstract:	A lever-like EEG feature-extraction method based on the Hurst exponent and regression-fitting errors is proposed for identifying beta rhythms. The proposed method is superior to most methods using the time- and frequency-domain feature extraction parameters for identifying beta rhythms.
Relation:	American Journal of Electroneurodiagnostic Technology 45(2): 130-138
Appears in Collections:	[光電與通訊學系] 期刊論文

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