Boosting based classification of event related potentials for early diagnosis of alzheimer's disease

Nicholas Stepenosky, Apostolos Topalis, Hussein Syed, Deborah Green, John Kounios, Christopher Clark, Robi Polikar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

With the number of the elderly population affected by Alzheimer's disease (AD) rising, the need to find an accurate, inexpensive and non-intrusive procedure that can be made available to community Healthcare providers for early diagnosis of Alzheimer's disease is becoming more and more urgent as a major health concern. Several recent studies have looked at analyzing electroencephalogram signals through the use of wavelets and neural networks. In this study, multiresolution wavelet analysis, coupled with the ensemble of classifiers based boosting algorithm is used on the P300 component of the event related potentials (ERP) to determine the feasibility of the approach as a diagnostic tool for early diagnosis of AD. The technique and its promising initial results are presented.

Original languageEnglish (US)
Title of host publicationProceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2494-2497
Number of pages4
ISBN (Print)0780387406, 9780780387409
DOIs
StatePublished - Jan 1 2005
Event2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 - Shanghai, China
Duration: Sep 1 2005Sep 4 2005

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume7 VOLS
ISSN (Print)0589-1019

Other

Other2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
Country/TerritoryChina
CityShanghai
Period9/1/059/4/05

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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