Abstract Details

Title Remote Assessment of Cognitive Frailty in Older Adults via Speech and Video Analysis

Topic Aging, Dementia, and Behavioral Neurology

Presentation(s) P5 - Poster Session 5 (5:30 PM-6:30 PM)

Poster/Presentation
Number 9-009

Objective

To develop and validate a video-based tool for assessment of cognitive frailty.

Background Cognitive frailty is a complex and multifaceted condition characterized by the coexistence of physical frailty and cognitive impairment and is prevalent in older adults. Traditional clinical assessments for frailty can be time-consuming and costly. There is a need for a robust solution that can be administered more frequently than traditional assessments.

Design/Methods

Participants aged 20-85 performed 20-second elbow extension-flexion tasks under both single-task (ST) and dual-task (DT) conditions. During DT, participants counted backward while performing the task, video-recorded via webcam. Frailty-related measurements were derived from video-based motion tracking algorithms which detect and analyze hand movements with high fidelity. The speech features were analyzed using BioDigit Speech (BioSensics LLC, Newton, MA USA), which enables measurement of over 40 speech outcomes by leveraging information in the audio waveform, spectrum, and cepstrum to capture phonatory, articulatory, prosody, and intelligibility features of speech.

Results Eighty-two participants were categorized into four groups: Robust (CI+/PF+, n=28), High Cognition (CI+/PF-, n=17), High Physical (CI-/PF+, n=21), and Worst (CI-/PF-, n=16). A machine learning model, employing a random forest approach with 5-fold cross-validation, was developed with both video and speech features as the input features. The model achieved an accuracy and precision of more than 75% along with an area under the curve (AUC) value of more than 0.80. Notably, the contribution of video features collected during the dual-task (DT) condition was found to be more significant compared to the single-task (ST) condition.

Conclusions The study validated the capacity of the proposed solution to evaluate cognitive frailty remotely using the video and speech biomarkers. The development of a video-based assessment for cognitive frailty offers a cost-effective, remote, and scalable solution that can be administered more frequently than traditional clinical assessments.

Authors/Disclosures
Ram Kinker Mishra, PhD (Biosensics) PRESENTER	Dr. Mishra has received personal compensation for serving as an employee of BioSensics LLC.
Mohammad Dehghan Rouzi (Baylor College of Medicine)	No disclosure on file
Adonay Nunes (Biosensics)	Adonay Nunes has nothing to disclose.
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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