ArticlePloS one2020
Voice quality and speech fluency distinguish individuals with Mild Cognitive Impairment from Healthy Controls.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.
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Who cites it
55 citing papers in PubMed, 104 citations in OpenAlex.
- SpeechDETECT: an explainable automated speech processing pipeline for early detection of neurological and health changes.Health information science and systems · 2026Article
- Article
- Detecting cognitive impairment and psychological well-being among older adults.Machine learning. Health · 2026Article
- EEG-based biomarker for the identification of mild cognitive impairment via coherency analysis and iterative dynamic time warping.Scientific reports · 2026Article
- A framework of digital biomarkers for neurodegenerative diseases.Nature reviews bioengineering · 2026Article
- Database of Speech and Language Affected by Mild Cognitive Impairment.Scientific data · 2026Article
- Developing a Multimodal Screening Algorithm for Mild Cognitive Impairment and Early Dementia in Home Health Care: Protocol for a Cross-Sectional Case-Control Study Using Speech Analysis, Large Language Models, and Electronic Health Records.JMIR research protocols · 2026Article
- A Machine Learning Framework for Cognitive Impairment Screening from Speech with Multimodal Large Models.Bioengineering (Basel, Switzerland) · 2026Article
- Clinical validation of a voice-based AI tool for screening cognitive impairment: a prospective multicenter study.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Article
- Language biomarker screening using AI: a transdiagnostic approach to the brain.Scientific reports · 2026Article
- Integrating acoustic, prosodic, and phonological features for automatic Alzheimer's detection.Frontiers in aging neuroscience · 2026Article
- Script Generation as an Efficient Measure of Cognition and Everyday Function in Older Adults.medRxiv : the preprint server for health sciences · 2025Article
- Domain generalization for voice-based cognitive impairment detection.BMC medical informatics and decision making · 2025Article
- Listening to the Mind: Integrating Vocal Biomarkers into Digital Health.Brain sciences · 2025Article
- Obfuscation via pitch-shifting for balancing privacy and diagnostic utility in voice-based cognitive assessment.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Articulatory precision from connected speech as a marker of cognitive decline in Alzheimer's disease risk-enriched cohorts.Journal of Alzheimer's disease : JAD · 2025Article
- Protocol for detection and monitoring of post-stroke cognitive impairment through AI-powered speech analysis: a mixed methods pilot study.Frontiers in aging neuroscience · 2025Article
- Reaction time variations in normal aging and elderly MCI patients under various cognitive load conditions.Frontiers in human neuroscience · 2025Article
- Mild cognitive impairment prediction based on multi-stream convolutional neural networks.BMC bioinformatics · 2024Article
- High frequency post-pause word choices and task-dependent speech behavior characterize connected speech in individuals with mild cognitive impairment.medRxiv : the preprint server for health sciences · 2024Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mild Cognitive Impairment (MCI) is a syndrome characterized by cognitive decline greater than expected for an individual's age and education level. This study aims to determine whether voice quality and speech fluency distinguish patients with MCI from healthy individuals to improve diagnosis of patients with MCI. We analyzed recordings of the Cookie Theft picture description task produced by 26 patients with MCI and 29 healthy controls from Sweden and calculated measures of voice quality and speech fluency. The results show that patients with MCI differ significantly from HC with respect to acoustic aspects of voice quality, namely H1-A3, cepstral peak prominence, center of gravity, and shimmer; and speech fluency, namely articulation rate and averaged speaking time. The method proposed along with the obtainability of connected speech productions can enable quick and easy analysis of speech fluency and voice quality, providing accessible and objective diagnostic markers of patients with MCI.
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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.