DocumentCode
2333416
Title
Majority Vote and Decision Template Based Ensemble Classifiers Trained on Event Related Potentials for Early Diagnosis of Alzheimer´s Disease
Author
Stepenosky, Nicholas ; Green, Deborah ; Kounios, John ; Clark, Christopher M. ; Polika, Robi
Author_Institution
Dept. of Electr. Eng., Rowan Univ., Glassboro, NJ
Volume
5
fYear
2006
fDate
14-19 May 2006
Abstract
With the rapid increase in the population of elderly individuals affected by Alzheimer´s disease, the need for an accurate, inexpensive and non-intrusive diagnostic biomarker that can be made available to community healthcare providers presents itself as a major public health concern. The feasibility of EEG as such a biomarker has gained a renewed attention as several recent studies, including our previous efforts, reported promising results. In this paper we present our preliminary results on using wavelet coefficients of event related potentials along with an ensemble of classifiers combined with majority vote and decision templates
Keywords
diseases; electroencephalography; health care; patient diagnosis; signal classification; wavelet transforms; Alzheimer disease diagnosis; EEG; community healthcare providers; decision template based ensemble classifiers; event related potentials; majority vote; nonintrusive diagnostic biomarker; public health concern; wavelet coefficients; Aging; Alzheimer´s disease; Biomarkers; Delay; Dementia; Electroencephalography; Enterprise resource planning; Medical services; Senior citizens; Voting;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on
Conference_Location
Toulouse
ISSN
1520-6149
Print_ISBN
1-4244-0469-X
Type
conf
DOI
10.1109/ICASSP.2006.1661422
Filename
1661422
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