Mutual information entropy research on dementia EEG signals

Author

Qi, Hongzhi ; Wan, Baikun ; Zhao, Li

Author_Institution

Dept. of Biomed. Eng., Tianjin Univ., China

fYear

2004

fDate

14-16 Sept. 2004

Firstpage

885

Lastpage

889

Abstract

The aim of this study is to find new components from electroencephalogram (EEG) of Alzheimer´s disease patients. Three parameters based on information theory and nonlinear dynamic, information entropy, mutual entropy and approximate entropy, were computed and the results were analyzed. Compare with normal persons, there is an extensive and significant depression in information activity, transport intensity and complexity of AD patients EEG signals. This result indicates an important possibility to generate a rigorous measure of AD patients from EEG signals in clinical diagnosis.

Keywords

diseases; electroencephalography; entropy; medical signal processing; patient diagnosis; Alzheimer disease patients; approximate entropy; clinical diagnosis; dementia EEG signals; electroencephalogram; information activity; information theory; mutual information entropy; nonlinear dynamic entropy; transport intensity; Alzheimer´s disease; Clinical diagnosis; Dementia; Electroencephalography; Information analysis; Information entropy; Information theory; Mutual information; Signal generators;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Information Technology, 2004. CIT '04. The Fourth International Conference on

Print_ISBN

0-7695-2216-5

Type

conf

DOI

10.1109/CIT.2004.1357307

Filename

1357307