A nonlinear method for ERP signal processing using nonextensive entropy analysis

Author

Shen, Minfen ; Zhang, Qianhua ; Tian, Lihua ; Chan, Francis H Y

Author_Institution

Sci. Res. Center, Shantou Univ., Guangdong, China

Volume

3

fYear

2004

fDate

31 Aug.-4 Sept. 2004

Firstpage

2233

Abstract

Nonextensive time-dependent entropy (TDE) is presented for analysis of event-related potential (ERP). Entropy method is effective in describing the transition of clinical electroencephalogram (EEG) signals. TDE is used to characterize in a quantitative way functional dynamics of order/disorder microstates in EEG signals. In this work TDE is computed for ERPs recorded from 14 healthy subjects in a cognitive task. From the experimental results, the dynamic characteristics of clinical brain electrical activities can be demonstrated by using nonextensive entropy method.

Keywords

electroencephalography; entropy; medical signal processing; ERP signal processing; clinical brain electrical activity; clinical electroencephalogram signal; disorder microstates; event-related potential; nonextensive entropy analysis; nonextensive time-dependent entropy; Brain; Electroencephalography; Enterprise resource planning; Entropy; Pathology; Signal analysis; Signal processing; Signal resolution; Statistical analysis; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on

Print_ISBN

0-7803-8406-7

Type

conf

DOI

10.1109/ICOSP.2004.1442223

Filename

1442223