ArticleEuropean psychiatry : the journal of the Association of European Psychiatrists2021
Measuring neuropsychiatric symptoms in patients with early cognitive decline using speech analysis.
Article in European psychiatry : the journal of the Association of European Psychiatrists, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.
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Who cites it
20 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Speech analysis for detecting depression in older adults: a systematic review.Frontiers in psychology · 2025Pooled it
- Application of machine learning in measurement of ageing and geriatric diseases: a systematic review.BMC geriatrics · 2023Pooled it
- Adaptive pathways for multimodal community-based detection of cognitive impairment: the CogScreen I study.Scientific reports · 2026Trial
- Effectiveness of a Biofeedback Intervention Targeting Mental and Physical Health Among College Students Through Speech and Physiology as Biomarkers Using Machine Learning: A Randomized Controlled Trial.Applied psychophysiology and biofeedback · 2024Trial
- Speech-related parameters are sensitive measures of acetylcholinesterase inhibitor therapy in mild Alzheimer's disease.PloS one · 2024Trial
- Validating objective and scalable speech markers of depression across two independent psychiatric cohorts.Annals of general psychiatry · 2026Article
- Machine learning in mental health promotion for older adults: a scoping review.BMC geriatrics · 2026Article
- Clinical Decision Support Using Speech Signal Analysis: Systematic Scoping Review of Neurological Disorders.Journal of medical Internet research · 2025Article
- The voice of depression: speech features as biomarkers for major depressive disorder.BMC psychiatry · 2024Article
- Using AI-Based Technologies to Help Nurses Detect Behavioral Disorders: Narrative Literature Review.JMIR nursing · 2024Review
- Harnessing Speech-Derived Digital Biomarkers to Detect and Quantify Cognitive Decline Severity in Older Adults.Gerontology · 2024Article
- Article
- Detecting subtle signs of depression with automated speech analysis in a non-clinical sample.BMC psychiatry · 2022Article
- Many Changes in Speech through Aging Are Actually a Consequence of Cognitive Changes.International journal of environmental research and public health · 2022Article
- Broadened assessments, health education and cognitive aids in the remote memory clinic.Frontiers in public health · 2022Article
- AI-Based Prediction and Prevention of Psychological and Behavioral Changes in Ex-COVID-19 Patients.Frontiers in psychology · 2021Review
- Speech and language features as indicators of neuropsychiatric symptoms in a memory clinic population.Alzheimer's & dementia (Amsterdam, Netherlands)Article
- Natural language processing techniques for studying language in pathological ageing: A scoping review.International journal of language & communication disordersArticle
- Automated remote speech-based testing of individuals with cognitive decline: Bayesian agreement of transcription accuracy.Alzheimer's & dementia (Amsterdam, Netherlands)Article
- Speech markers of depression dimensions across cognitive status.Alzheimer's & dementia (Amsterdam, Netherlands)Article
Corrections and comments
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Authors and funding
7 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundCertain neuropsychiatric symptoms (NPS), namely apathy, depression, and anxiety demonstrated great value in predicting dementia progression, representing eventually an opportunity window for timely diagnosis and treatment. However, sensitive and objective markers of these symptoms are still missing. Therefore, the present study aims to investigate the association between automatically extracted speech features and NPS in patients with mild neurocognitive disorders.
methodsSpeech of 141 patients aged 65 or older with neurocognitive disorder was recorded while performing two short narrative speech tasks. NPS were assessed by the neuropsychiatric inventory. Paralinguistic markers relating to prosodic, formant, source, and temporal qualities of speech were automatically extracted, correlated with NPS. Machine learning experiments were carried out to validate the diagnostic power of extracted markers.
resultsDifferent speech variables are associated with specific NPS; apathy correlates with temporal aspects, and anxiety with voice quality-and this was mostly consistent between male and female after correction for cognitive impairment. Machine learning regressors are able to extract information from speech features and perform above baseline in predicting anxiety, apathy, and depression scores.
conclusionsDifferent NPS seem to be characterized by distinct speech features, which are easily extractable automatically from short vocal tasks. These findings support the use of speech analysis for detecting subtypes of NPS in patients with cognitive impairment. This could have great implications for the design of future clinical trials as this cost-effective method could allow more continuous and even remote monitoring of symptoms.
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