Publication:
Ten years of research on automatic voice and speech analysis of people with Alzheimer's disease and mild cognitive impairment : a systematic review article

Simple item page
dc.contributor.authorMartínez-Nicolás, Israel
dc.contributor.authorLlorente, Thide
dc.contributor.authorMartínez-Sánchez, Francisco
dc.contributor.authorGarcía Meilá, Juan José
dc.contributor.departmentPsicología Básica y Metodología
dc.date.accessioned2024-02-02T08:01:14Z
dc.date.available2024-02-02T08:01:14Z
dc.date.issued2021-03-23
dc.description©<2021>. This manuscript version is made available under the CC-BY license http://creativecommons.org/licenses/ccby/4.0/ This document is the Published, version of a Published Work that appeared in final form in [Frontiers in Psychology]. To access the final edited and published work see [https://doi.org/10.3389/fpsyg.2021.620251]
dc.description.abstractBackground: The field of voice and speech analysis has become increasingly popular over the last 10 years, and articles on its use in detecting neurodegenerative diseases have proliferated. Many studies have identified characteristic speech features that can be used to draw an accurate distinction between healthy aging among older people and those with mild cognitive impairment and Alzheimer’s disease. Speech analysis has been singled out as a cost-effective and reliable method for detecting the presence of both conditions. In this research, a systematic review was conducted to determine these features and their diagnostic accuracy. Methods: Peer-reviewed literature was located across multiple databases, involving studies that apply new procedures of automatic speech analysis to collect behavioral evidence of linguistic impairments along with their diagnostic accuracy on Alzheimer’s disease and mild cognitive impairment. The risk of bias was assessed by using JBI and QUADAS-2 checklists. Results: Thirty-five papers met the inclusion criteria; of these, 11 were descriptive studies that either identified voice features or explored their cognitive correlates, and the rest were diagnostic studies. Overall, the studies were of good quality and presented solid evidence of the usefulness of this technique. The distinctive acoustic and rhythmic features found are gathered. Most studies record a diagnostic accuracy over 88% for Alzheimer’s and 80% for mild cognitive impairment. Conclusion: Automatic speech analysis is a promising tool for diagnosing mild cognitive impairment and Alzheimer’s disease. The reported features seem to be indicators of the cognitive changes in older people. The specific features and the cognitive changes involved could be the subject of further research.es
dc.formatapplication/pdfes
dc.format.extent15es
dc.identifier.citationFrontiers in Psychology, 12:620251, 2021
dc.identifier.doihttps://doi.org/10.3389/fpsyg.2021.620251
dc.identifier.issn1664-1078 (electrónico)
dc.identifier.urihttp://hdl.handle.net/10201/138485
dc.languageenges
dc.publisherFrontiers Media
dc.relationSin financiación externa a la Universidades
dc.rightsinfo:eu-repo/semantics/openAccesses
dc.subjectAlzheimer’s disease
dc.subjectMild cognitive impairment
dc.subjectSpeech analysis
dc.subjectLanguage impairment
dc.subjectSpeech impairment
dc.titleTen years of research on automatic voice and speech analysis of people with Alzheimer's disease and mild cognitive impairment : a systematic review article
dc.typeinfo:eu-repo/semantics/articlees
dspace.entity.typePublicationes
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Ten Years of Research on Automatic Voice and Speech Analysis of People With Alzheimer’s Disease and Mild Cognitive Impairment A Systematic Review Article.pdf
Size:
2.35 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
2.26 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Artículos