Literature DB >> 24481220

Speech in Alzheimer's disease: can temporal and acoustic parameters discriminate dementia?

Juan José G Meilán1, Francisco Martínez-Sánchez, Juan Carro, Dolores E López, Lymarie Millian-Morell, José M Arana.   

Abstract

AIMS: The study explores how speech measures may be linked to language profiles in participants with Alzheimer's disease (AD) and how these profiles could distinguish AD from changes associated with normal aging.
METHODS: We analysed simple sentences spoken by older adults with and without AD. Spectrographic analysis of temporal and acoustic characteristics was carried out using the Praat software.
RESULTS: We found that measures of speech, such as variations in the percentage of voice breaks, number of periods of voice, number of voice breaks, shimmer (amplitude perturbation quotient), and noise-to-harmonics ratio, characterise people with AD with an accuracy of 84.8%. DISCUSSION: These measures offer a sensitive method of assessing spontaneous speech output in AD, and they discriminate well between people with AD and healthy older adults. This method of evaluation is a promising tool for AD diagnosis and prognosis, and it could be used as a dependent measure in clinical trials.
© 2014 S. Karger AG, Basel.

Entities:  

Mesh:

Year:  2014        PMID: 24481220     DOI: 10.1159/000356726

Source DB:  PubMed          Journal:  Dement Geriatr Cogn Disord        ISSN: 1420-8008            Impact factor:   2.959


  14 in total

1.  Voice biomarkers as indicators of cognitive changes in middle and later adulthood.

Authors:  Elizabeth Mahon; Margie E Lachman
Journal:  Neurobiol Aging       Date:  2022-07-01       Impact factor: 5.133

2.  Cognitive and Structural Correlates of Conversational Speech Timing in Mild Cognitive Impairment and Mild-to-Moderate Alzheimer's Disease: Relevance for Early Detection Approaches.

Authors:  Céline De Looze; Amir Dehsarvi; Lisa Crosby; Aisling Vourdanou; Robert F Coen; Brian A Lawlor; Richard B Reilly
Journal:  Front Aging Neurosci       Date:  2021-04-27       Impact factor: 5.750

3.  Automated assessment of speech production and prediction of MCI in older adults.

Authors:  Victoria Sanborn; Rachel Ostrand; Jeffrey Ciesla; John Gunstad
Journal:  Appl Neuropsychol Adult       Date:  2020-12-30       Impact factor: 2.050

4.  Automatic speech analysis for the assessment of patients with predementia and Alzheimer's disease.

Authors:  Alexandra König; Aharon Satt; Alexander Sorin; Ron Hoory; Orith Toledo-Ronen; Alexandre Derreumaux; Valeria Manera; Frans Verhey; Pauline Aalten; Phillipe H Robert; Renaud David
Journal:  Alzheimers Dement (Amst)       Date:  2015-03-29

5.  Speech Analysis by Natural Language Processing Techniques: A Possible Tool for Very Early Detection of Cognitive Decline?

Authors:  Daniela Beltrami; Gloria Gagliardi; Rema Rossini Favretti; Enrico Ghidoni; Fabio Tamburini; Laura Calzà
Journal:  Front Aging Neurosci       Date:  2018-11-13       Impact factor: 5.750

6.  Talk2Me: Automated linguistic data collection for personal assessment.

Authors:  Majid Komeili; Chloé Pou-Prom; Daniyal Liaqat; Kathleen C Fraser; Maria Yancheva; Frank Rudzicz
Journal:  PLoS One       Date:  2019-03-27       Impact factor: 3.240

7.  A new diagnostic approach for the identification of patients with neurodegenerative cognitive complaints.

Authors:  Sabah Al-Hameed; Mohammed Benaissa; Heidi Christensen; Bahman Mirheidari; Daniel Blackburn; Markus Reuber
Journal:  PLoS One       Date:  2019-05-24       Impact factor: 3.240

8.  Predicting MCI Status From Multimodal Language Data Using Cascaded Classifiers.

Authors:  Kathleen C Fraser; Kristina Lundholm Fors; Marie Eckerström; Fredrik Öhman; Dimitrios Kokkinakis
Journal:  Front Aging Neurosci       Date:  2019-08-02       Impact factor: 5.750

9.  Transformer-based deep neural network language models for Alzheimer's disease risk assessment from targeted speech.

Authors:  Alireza Roshanzamir; Hamid Aghajan; Mahdieh Soleymani Baghshah
Journal:  BMC Med Inform Decis Mak       Date:  2021-03-09       Impact factor: 2.796

10.  Detecting Dementia Through Interactive Computer Avatars.

Authors:  Hiroki Tanaka; Hiroyoshi Adachi; Norimichi Ukita; Manabu Ikeda; Hiroaki Kazui; Takashi Kudo; Satoshi Nakamura
Journal:  IEEE J Transl Eng Health Med       Date:  2017-09-15       Impact factor: 3.316

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.