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Review
. 2021 Dec 23:12:782183.
doi: 10.3389/fpsyt.2021.782183. eCollection 2021.

Affective Computing for Late-Life Mood and Cognitive Disorders

Erin Smith  1   2   3   4   5 , Eric A Storch  6 , Ipsit Vahia  7   8 , Stephen T C Wong  9 , Helen Lavretsky  10 , Jeffrey L Cummings  11 , Harris A Eyre  1   2   4   5   6   12
Affiliations
Review

Affective Computing for Late-Life Mood and Cognitive Disorders

Erin Smith et al. Front Psychiatry. .

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.

Keywords: Alzheimer's disease; affective computing; dementia; digital phenotyping; late-life depression.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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References

    1. UN . World Population Ageing. (2019). United Nations Department of Economic and Social Affairs (2019).
    1. Smith E, Au R, Mossé M, Lavretsky H, Forbes M, Eyre HA. Rebooting late-life mental health innovation and entrepreneurship with convergence science. Am J Geriatr Psychiatry. (2020) 28:591–6. 10.1016/j.jagp.2020.03.003 - DOI - PubMed
    1. Fujishiro H, Nakamura S, Sato K, Iseki E. Prodromal dementia with L ewy bodies. Geriatr Gerontol Int. (2015) 15:817–26. 10.1111/ggi.12466 - DOI - PubMed
    1. Woolley JD, Khan BK, Murthy NK, Miller BL, Rankin KP. The diagnostic challenge of psychiatric symptoms in neurodegenerative disease: rates of and risk factors for prior psychiatric diagnosis in patients with early neurodegenerative disease. J Clin Psychiatry. (2011) 72: 126–33. 10.4088/JCP.10m06382oli - DOI - PMC - PubMed
    1. Pellicano C, Benincasa D, Pisani V, Buttarelli FR, Giovannelli M, Pontieri FE. Prodromal non-motor symptoms of Parkinson's disease. Neuropsychiatr Dis Treat. (2007) 3:145. 10.2147/nedt.2007.3.1.145 - DOI - PMC - PubMed