Mutual Information Entropy Research on Dementia EEG Signals

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Fourth International Conference on Computer and Information Technology (CIT'04)

Wuhan, China

September 14-September 16

ISBN: 0-7695-2216-5

	ASCII Text	x
	Hongzhi Qi, Baikun Wan, Li Zhao, "Mutual Information Entropy Research on Dementia EEG Signals," Computer and Information Technology, International Conference on, pp. 885-889, Fourth International Conference on Computer and Information Technology (CIT'04), 2004.

	BibTex	x
	@article{ 10.1109/CIT.2004.1357307, author = {Hongzhi Qi and Baikun Wan and Li Zhao}, title = {Mutual Information Entropy Research on Dementia EEG Signals}, journal ={Computer and Information Technology, International Conference on}, volume = {0}, year = {2004}, isbn = {0-7695-2216-5}, pages = {885-889}, doi = {http://doi.ieeecomputersociety.org/10.1109/CIT.2004.1357307}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Computer and Information Technology, International Conference on TI - Mutual Information Entropy Research on Dementia EEG Signals SN - 0-7695-2216-5 SP885 EP889 A1 - Hongzhi Qi, A1 - Baikun Wan, A1 - Li Zhao, PY - 2004 KW - EEG KW - information entropy KW - mutual entropy KW - approximate entropy KW - Alzheimer's disease VL - 0 JA - Computer and Information Technology, International Conference on ER -

Hongzhi Qi, Tianjin University

Baikun Wan, Tianjin University

Li Zhao, Tianjin University

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CIT.2004.1357307

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.

Index Terms:

EEG, information entropy, mutual entropy, approximate entropy, Alzheimer's disease

Citation:

Hongzhi Qi, Baikun Wan, Li Zhao, "Mutual Information Entropy Research on Dementia EEG Signals," cit, pp.885-889, Fourth International Conference on Computer and Information Technology (CIT'04), 2004

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