Quantifying the similarity of multiple point processes with application to early diagnosis of Alzheimer's disease from EEG

Justin Dauwels, Theophane Weber, François Vialatte, Andrzej Cichocki

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A novel approach is proposed to quantify the similarity (or "synchrony") of multiple multi-dimensional point processes. It is based on a generative stochastic model that describes how two or more point processes are related to each other. As an application, the problem of diagnosing Alzheimer's disease (AD) from multi-channel EEG recordings is considered. The proposed method seems to be more sensitive to AD induced perturbations in EEG synchrony than classical similarity measures.

Original languageEnglish
Title of host publicationProceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
PublisherIEEE Computer Society
Pages2657-2660
Number of pages4
ISBN (Print)9781424418152
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - Vancouver, BC, Canada
Duration: 20 Aug 200825 Aug 2008

Publication series

NameProceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"

Conference

Conference30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Country/TerritoryCanada
CityVancouver, BC
Period20/08/0825/08/08

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