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Technology and Dementia Preconference
Madeline R Hale1,2, Deling He3, Rebecca E Langhough4,5,6
1Department of Communication Sciences and Disorders, University of Wisconsin-Madison, Madison, WI, USA.
Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|December 23, 2025
Summary
Speech pause analysis in story recall can detect early Alzheimer's disease (AD). Mild cognitive impairment (MCI) patients exhibit longer pauses and shorter speech duration compared to cognitively unimpaired (CU) individuals, indicating potential as an AD biomarker.
Area of Science:
- Neurology
- Speech-Language Pathology
- Biomarkers
Background:
- Subtle speech features, including pauses, are sensitive to Alzheimer's disease (AD) PET biomarkers.
- Previous research indicated that silent pauses in Cookie Theft (CT) picture descriptions differentiated cognitively unimpaired (CU) from cognitively impaired individuals.
- The current study investigates the utility of pause detection in story recall (SR) tasks.
Purpose of the Study:
- To examine the effectiveness of acoustic-based silent pause analysis in differentiating between individuals with Mild Cognitive Impairment (MCI) and CU individuals using story recall tasks.
- To correlate speech pause metrics with PET biomarkers (amyloid/tau), neuropsychological test results, and overall cognitive status.
Main Methods:
- Fifty participants (25 MCI, 25 CU) from the Wisconsin Registry for Alzheimer's Prevention (WRAP) and Wisconsin Alzheimer's Disease Research Center (WADRC) were propensity score matched.
- Delayed story recall audio (Logical Memory/Craft Story) was processed to extract silent pauses (>80ms) using MATLAB Speech Pause Analysis.
- Statistical analyses included Wilcoxon signed rank tests, Spearman correlations, logistic regression, and ROC analyses to compare pause metrics and cognitive status.
Main Results:
- Cognitively unimpaired (CU) participants exhibited increased story recall (SR) duration (p=0.001, r=0.622).
- Mild Cognitive Impairment (MCI) participants showed longer mean pause duration (p=0.0317, r=0.374) and higher pause percentage (p=0.045, r=0.342).
- Total SR duration was a significant predictor of cognitive status (OR=0.93, CI=0.89-0.97, AUC=0.76), outperforming CT analysis (AUC=0.57).
Conclusions:
- Individuals with MCI produced shorter SR samples with a greater percentage and duration of pauses compared to CU participants.
- Shorter speech duration in SR correlated with higher amyloid-beta levels, suggesting a link to AD pathology.
- Automated acoustic-based pause analysis shows promise as an early diagnostic marker for AD, meriting further investigation in diverse populations.
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