Citation

Smith E, Storch EA, Vahia I, Wong STC, Lavretsky H, Cummings JL, Eyre HA. Front. Psychiatry 2021; 12.

Copyright

(Copyright © 2021, Frontiers Media)

DOI

10.3389/fpsyt.2021.782183

PMID

unavailable

Abstract

Affective computing (also referred to as artificial emotion intelligence or emotion AI) is the study and development of systems and devices that can recognize, interpret, process, and simulate emotion or other affective phenomena. With the rapid growth in the aging population around the world, affective computing has immense potential to benefit the treatment and care of late-life mood and cognitive disorders. For late-life depression, affective computing ranging from vocal biomarkers to facial expressions to social media behavioral analysis can be used to address inadequacies of current screening and diagnostic approaches, mitigate loneliness and isolation, provide more personalized treatment approaches, and detect risk of suicide. Similarly, for Alzheimer's disease, eye movement analysis, vocal biomarkers, and driving and behavior can provide objective biomarkers for early identification and monitoring, allow more comprehensive understanding of daily life and disease fluctuations, and facilitate an understanding of behavioral and psychological symptoms such as agitation. To optimize the utility of affective computing while mitigating potential risks and ensure responsible development, ethical development of affective computing applications for late-life mood and cognitive disorders is needed. Copyright © 2021 Smith, Storch, Vahia, Wong, Lavretsky, Cummings and Eyre.

Language: en

Keywords

human; suicide; Review; dementia; aging; artificial intelligence; screening; loneliness; risk assessment; disease association; cognitive defect; patient care; Alzheimer disease; diagnostic test; agitation; Alzheimer's disease; facial expression; ethical theory; process development; eye movement; late-life depression; personalized medicine; social media; late life depression; cognition assessment; emotion assessment; mood disorder assessment; isolation; affective computing; digital phenotyping