Cognitive Assessment Estimation from Behavioral Responses in Emotional Faces Evaluation Task -- AI Regression Approach for Dementia Onset Prediction in Aging Societies
Tomasz M. Rutkowski, Masato S. Abe, Marcin Koculak, Mihoko, Otake-Matsuura

TL;DR
This paper explores an AI regression approach using behavioral responses in emotional face evaluation tasks to predict dementia onset in elderly individuals, aiming to replace subjective assessments with objective digital biomarkers.
Contribution
It introduces a novel AI-based regression method utilizing emotional and reaction data to estimate cognitive scores, advancing dementia detection techniques in aging societies.
Findings
Encouraging preliminary results in MoCA score prediction
Behavioral responses correlate with cognitive assessment scores
Potential for replacing subjective dementia diagnostics
Abstract
We present a practical health-theme machine learning (ML) application concerning `AI for social good' domain for `Producing Good Outcomes' track. In particular, the solution is concerning the problem of a potential elderly adult dementia onset prediction in aging societies. The paper discusses our attempt and encouraging preliminary study results of behavioral responses analysis in a working memory-based emotional evaluation experiment. We focus on the development of digital biomarkers for dementia progress detection and monitoring. We present a behavioral data collection concept for a subsequent AI-based application together with a range of regression encouraging results of Montreal Cognitive Assessment (MoCA) scores in the leave-one-subject-out cross-validation setup. The regressor input variables include experimental subject's emotional valence and arousal recognition responses, as…
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Taxonomy
TopicsDementia and Cognitive Impairment Research · Face recognition and analysis · Brain Tumor Detection and Classification
