1. Investigating Acoustic and Psycholinguistic Predictors of Cognitive Impairment in Older Adults: Modeling Study.
- Author
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Badal, Varsha, Reinen, Jenna, Twamley, Elizabeth, Lee, Ellen, Fellows, Robert, Bilal, Erhan, and Depp, Colin
- Subjects
AI ,Alzheimer ,CI ,MCI ,ML ,NLP ,acoustic ,algorithm ,algorithms ,artificial intelligence ,cognitive disability ,cognitive impairment ,cognitive limitation ,cognitive restriction ,dementia ,early detection ,early warning ,machine learning ,mild cognitive impairment ,natural language processing ,neurocognition ,neurocognitive disorder ,neurological decline ,practical model ,practical models ,predictive analytics ,predictive model ,predictive models ,predictive system ,psycholinguistic ,speech ,speech marker ,speech markers ,Humans ,Female ,Male ,Cognitive Dysfunction ,Aged ,80 and over ,Aged ,Psycholinguistics ,Neuropsychological Tests - Abstract
BACKGROUND: About one-third of older adults aged 65 years and older often have mild cognitive impairment or dementia. Acoustic and psycho-linguistic features derived from conversation may be of great diagnostic value because speech involves verbal memory and cognitive and neuromuscular processes. The relative decline in these processes, however, may not be linear and remains understudied. OBJECTIVE: This study aims to establish associations between cognitive abilities and various attributes of speech and natural language production. To date, the majority of research has been cross-sectional, relying mostly on data from structured interactions and restricted to textual versus acoustic analyses. METHODS: In a sample of 71 older (mean age 83.3, SD 7.0 years) community-dwelling adults who completed qualitative interviews and cognitive testing, we investigated the performance of both acoustic and psycholinguistic features associated with cognitive deficits contemporaneously and at a 1-2 years follow up (mean follow-up time 512.3, SD 84.5 days). RESULTS: Combined acoustic and psycholinguistic features achieved high performance (F1-scores 0.73-0.86) and sensitivity (up to 0.90) in estimating cognitive deficits across multiple domains. Performance remained high when acoustic and psycholinguistic features were used to predict follow-up cognitive performance. The psycholinguistic features that were most successful at classifying high cognitive impairment reflected vocabulary richness, the quantity of speech produced, and the fragmentation of speech, whereas the analogous top-ranked acoustic features reflected breathing and nonverbal vocalizations such as giggles or laughter. CONCLUSIONS: These results suggest that both acoustic and psycholinguistic features extracted from qualitative interviews may be reliable markers of cognitive deficits in late life.
- Published
- 2024