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Cognitive Assessment Estimation from Behavioral Responses in Emotional Faces Evaluation Task -- AI Regression Approach for Dementia Onset Prediction in Aging Societies

Published 25 Nov 2019 in q-bio.NC, cs.HC, and stat.ML | (1911.12135v1)

Abstract: We present a practical health-theme ML application concerning AI for social good' domain forProducing 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 well as reaction times, together with self-reported education levels and ages, obtained from a group of twenty older adults taking part in the reported data collection project. The presented results showcase the potential social benefits of artificial intelligence application for elderly and establish a step forward to develop ML approaches, for the subsequent application of simple behavioral objective testing for dementia onset diagnostics replacing subjective MoCA.

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