ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2019
Using Tablet-Based Assessment to Characterize Speech for Individuals with Dementia and Mild Cognitive Impairment: Preliminary Results.
Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.
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Who cites it
8 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Ten Years of Research on Automatic Voice and Speech Analysis of People With Alzheimer's Disease and Mild Cognitive Impairment: A Systematic Review Article.Frontiers in psychology · 2021Pooled it
- Speech changes in old age: Methodological considerations for speech-based discrimination of healthy ageing and Alzheimer's disease.International journal of language & communication disordersPooled it
- Reading and lexical-semantic retrieval tasks outperforms single task speech analysis in the screening of mild cognitive impairment and Alzheimer's disease.Scientific reports · 2023Article
- Screening of Mild Cognitive Impairment Through Conversations With Humanoid Robots: Exploratory Pilot Study.JMIR formative research · 2023Article
- Automated Analysis of Drawing Process to Estimate Global Cognition in Older Adults: Preliminary International Validation on the US and Japan Data Sets.JMIR formative research · 2022Article
- Using Speech Data From Interactions With a Voice Assistant to Predict the Risk of Future Accidents for Older Drivers: Prospective Cohort Study.Journal of medical Internet research · 2021Article
- Automatic Assessment of Loneliness in Older Adults Using Speech Analysis on Responses to Daily Life Questions.Frontiers in psychiatry · 2021Article
- Tablet-Based Automatic Assessment for Early Detection of Alzheimer's Disease Using Speech Responses to Daily Life Questions.Frontiers in digital health · 2021Article
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Authors and funding
14 authors.
Funding
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Abstract
Early detection of dementia as well as improvement in diagnosis coverage has been increasingly important. Previous studies involved extracting speech features during neuropsychological assessments by humans, such as medical pro- fessionals, and succeeded in detecting patients with dementia and mild cognitive impairment (MCI). Enabling such assessment in an automated fashion by using computer devices would extend the range of application. In this study, we developed a tablet-based application for neuropsychological assessments and collected speech data from 44 Japanese native speakers including healthy controls (HCs) and those with MCI and dementia. We first extracted acoustic and phonetic features and showed that several features exhibited significant difference between HC vs. MCI and HC vs. dementia. We then constructed classification models by using these features and demonstrated that these models could differentiate MCI and dementia from HC with up to 82.4 and 92.6% accuracy, respectively.
Identifiers
31258954PMC6568131What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.