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Cognitive Neurodynamics
Erschienen in: Cognitive Neurodynamics 6/2016

01.12.2016 | Research Article

A novel method for early diagnosis of Alzheimer’s disease based on higher-order spectral estimation of spontaneous speech signals

verfasst von: Mahda Nasrolahzadeh, Zeynab Mohammadpoory, Javad Haddadnia

Erschienen in: Cognitive Neurodynamics | Ausgabe 6/2016

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Abstract

One main challenge for medical investigators is the early diagnosis of Alzheimer’s disease (AD) because it provides greater opportunities for patients to be eligible for more clinical trials. In this study, higher order spectra of human speech signals during AD were explored to analyze and compare the quadratic phase coupling of spontaneous speech signals for healthy and AD subjects using bispectrum and bicoherence. The results showed that the quadratic phase couplings of spontaneous speech signal of persons with Alzheimer’s were reduced compared to healthy subject. However, the speech phase coupled harmonics shifted to the higher frequencies in Alzheimer’s than healthy subjects. In addition, it was shown not only are there significant differences between Alzheimer’s and control subjects in parameters estimated, but also the speech patterns appeared to have fluctuated in both types of spontaneous speech.
Vorheriger Artikel The oscillation-like activity in bullfrog ON–OFF retinal ganglion cell
Nächster Artikel Robust frequency recognition for SSVEP-based BCI with temporally local multivariate synchronization index

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Metadaten
Titel
A novel method for early diagnosis of Alzheimer’s disease based on higher-order spectral estimation of spontaneous speech signals
verfasst von
Mahda Nasrolahzadeh
Zeynab Mohammadpoory
Javad Haddadnia
Publikationsdatum
01.12.2016
Verlag
Springer Netherlands
Erschienen in
Cognitive Neurodynamics / Ausgabe 6/2016
Print ISSN: 1871-4080
Elektronische ISSN: 1871-4099
DOI
https://doi.org/10.1007/s11571-016-9406-0

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