A nonlinear method for ERP signal processing using nonextensive entropy analysis

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 micro...

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Bibliographic Details
Main Authors: Minfen Shen, Qianhua Zhang, Lihua Tian, Chan, F.H.Y.
Format: Conference Proceeding
Language:English
Subjects:
Applied sciences
Biological and medical sciences
Brain
Computerized, statistical medical data processing and models in biomedicine
Electroencephalography
Enterprise resource planning
Entropy
Exact sciences and technology
Information, signal and communications theory
Medical management aid. Diagnosis aid
Medical sciences
Miscellaneous
Pathology
Signal analysis
Signal processing
Signal resolution
Statistical analysis
Statistics
Telecommunications and information theory
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Summary: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.
DOI:10.1109/ICOSP.2004.1442223