Voice analysis results in individuals with Alzheimer's disease: How do age and cognitive status affect voice parameters?

Author:

Parlak Mümüne Merve1ORCID,Saylam Güleser2,Babademez Mehmet Ali3,Munis Özlem Bizpınar4,Tokgöz Sibel Alicura2

Affiliation:

1. Department of Speech and Language Therapy, Faculty of Health Sciences Ankara Yıldırım Beyazıt University Ankara Turkey

2. Department of Otolaryngology Etlik City Hospital Ankara Turkey

3. Department of Otolaryngology Ankara Bilkent City Hospital Ankara Turkey

4. Department of Neurology Etlik City Hospital Ankara Turkey

Abstract

AbstractBackgroundReports of acoustic changes in the voice in individuals with Alzheimer's disease (AD) and the relationship of acoustic changes with age and cognitive status are still limited.ObjectiveThis study aims to determine the changes in voice analysis results in AD, as well as the effects of age and cognitive status on voice parameters.MethodsThe study included 47 (AD: 30; healthy: 17) women with a mean age of 76.13 years. The acoustic voice parameters mean fundamental frequency (F0), relative average perturbation (RAP), jitter percent (Jitt), shimmer percent (Shim), and noise‐to‐harmonic ratio were detected. The mini‐mental state examination (MMSE) was utilized.ResultsF0, Shim, Jitt, and RAP values were found to be statistically significantly higher in individuals with AD compared to healthy individuals. There was a significant negative correlation between MMSE and F0, Jitt, RAP and Shim, and the MMSE score had a significant negative effect on F0, Jitt, and RAP (p < .05).ConclusionCognitive status was discovered to significantly impact the voice, with fundamental frequency and frequency and amplitude perturbations increasing as cognitive level decreases. In order to contribute to the therapy process for voice disorders, cognitive functions can be focused on in addition to voice therapy.

Publisher

Wiley

Subject

Behavioral Neuroscience

Reference33 articles.

1. Analysis of the consistency of information received from Alzheimer’s disease patients and their families in the quality of life and depression scales

2. Alzheimer Hastalığı'nda Evrelere Göre Hastaya Bakım Veren Kişi (Ler) nin Yükü;Elif K.;Archives of Neuropsychiatry,2017

3. Farrús M. &Codina‐Filbà J.(2020).Combining prosodic voice quality and lexical features to automatically detect Alzheimer's disease.arXiv preprint arXiv:2011.09272.

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