Abstract Details

Title Speech Biomarkers of Cognitive Decline in Older Adults

Topic Aging, Dementia, and Behavioral Neurology

Presentation(s) P2 - Poster Session 2 (11:45 AM-12:45 PM)

Poster/Presentation
Number 9-011

Objective To demonstrate the efficacy of digital speech analysis as a tool for identifying and gauging cognitive impairment in older adults by focusing on speech biomarkers.

Background

Current cognitive assessments face challenges such as floor/ceiling and practice effects, insufficient psychometric performance in milder cases, and repeated assessment effects. Digital speech analysis presents an opportunity to overcome these issues, especially in the field of detecting cognitive decline.

Design/Methods Older adults with varied cognitive states were recruited. Speech data was recorded as participants read a standard passage aloud, and then processed with BioDigit Speech to derive digital biomarkers, including timing, pitch, and intelligibility. Group differences were measured using Cohen's d, and correlations were established with the Montreal Cognitive Assessment (MoCA). A stepwise approach employing a Random Forest model was utilized to classify cognitive decline vs cognitive intact individuals through speech features.

Results The study involved 59 participants: 36 with cognitive impairment and 23 cognitively intact controls. Among all parameters, similarity determined by Dynamic Time Warping (DTW) displayed the strongest positive correlation (rho=0.529, p<0.001) with MoCA scores, while timing parameters, specifically the ratio of extra words, exhibited the most potent negative correlation (rho=-0.441, p<0.001). Discriminative performance peaked using a combination of four speech parameters: total pause time, speech to pause ratio, similarity DTW, and the ratio of extra words. The precision and balanced accuracy scores recorded were 84.3 ± 1.5% and 75.0 ± 1.4%, respectively.

Conclusions

Speech data analysis effectively distinguishes between cognitively impaired and cognitively intact older adults. Such digital speech analysis holds promise as a biomarker for early detection and continual monitoring of cognitive decline, paving the way for innovative strategies in dementia care.

Authors/Disclosures
Adonay Nunes (Biosensics) PRESENTER	Adonay Nunes has nothing to disclose.
Ram Kinker Mishra, PhD (Biosensics)	Dr. Mishra has received personal compensation for serving as an employee of BioSensics LLC.
Jose Casado (BioSensics LLC)	Jose Casado has received personal compensation for serving as an employee of Biosensics.
Gozde Cay	No disclosure on file
Mohammad Dehghan Rouzi (Baylor College of Medicine)	No disclosure on file
Myeounggon Lee (Baylor College of Medicine)	No disclosure on file
Ashkan Vaziri, PhD (Biosensics LLC)	Dr. Vaziri has received personal compensation for serving as an employee of Biosensics.
Bijan Najafi (University of California, Los Angeles)	Bijan Najafi has received personal compensation in the range of $10,000-$49,999 for serving as a Consultant for BioSensics LLC. The institution of Bijan Najafi has received research support from NIH. The institution of Bijan Najafi has received research support from NSF. Bijan Najafi has received intellectual property interests from a discovery or technology relating to health care. Bijan Najafi has received intellectual property interests from a discovery or technology relating to health care. Bijan Najafi has received intellectual property interests from a discovery or technology relating to health care. Bijan Najafi has received personal compensation in the range of $500-$4,999 for serving as a Reviewer with NIH. Bijan Najafi has received personal compensation in the range of $500-$4,999 for serving as a Reviewer with DEPARTMENT OF VETERANS AFFAIRS.

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