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Communication Dans Un Congrès Année : 2017

Alzheimer's disease diagnosis using synchrony and disorder measures

Résumé

This study tackles the issue of Alzheimer's disease diagnosis with electroencephalography based on the quantification of the brain functional connectivity. In this work, we evaluated two measures of functional connectivity, namely Phase Synchrony largely used in the literature and Epoch-based entropy, to distinguish between Mild Alzheimer's disease patients (AD patients) and patients with Subjective Cognitive Impairment (SCI subjects). A Linear Discriminate Analysis was used to discriminate the two groups of subjects with a leave-one-out procedure. The obtained results indicated that the accuracy reached 98.33% with Epoch-based entropy and 52.33% with Phase synchrony in θ band
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Dates et versions

hal-01701329 , version 1 (05-02-2018)

Identifiants

  • HAL Id : hal-01701329 , version 1

Citer

Amira Aljane, Nesma Houmani. Alzheimer's disease diagnosis using synchrony and disorder measures. JDSE 2017 : 2nd Junior Conference on Data Science and Engineering, Sep 2017, Orsay, France. pp.117 - 119. ⟨hal-01701329⟩
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