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Smith E, Storch EA, Vahia I, et al. Affective Computing for Late-Life Mood and Cognitive Disorders. Front Psychiatry. 2021;12:782183doi: 10.3389/fpsyt.2021.782183.
Smith, E., Storch, E. A., Vahia, I., Wong, S. T. C., Lavretsky, H., Cummings, J. L., & Eyre, H. A. (2021). Affective Computing for Late-Life Mood and Cognitive Disorders. Frontiers in psychiatry, 12782183. https://doi.org/10.3389/fpsyt.2021.782183
Smith, Erin, et al. "Affective Computing for Late-Life Mood and Cognitive Disorders." Frontiers in psychiatry vol. 12 (2021): 782183. doi: https://doi.org/10.3389/fpsyt.2021.782183
Smith E, Storch EA, Vahia I, Wong STC, Lavretsky H, Cummings JL, Eyre HA. Affective Computing for Late-Life Mood and Cognitive Disorders. Front Psychiatry. 2021 Dec 23;12:782183. doi: 10.3389/fpsyt.2021.782183. eCollection 2021. PMID: 35002802; PMCID: PMC8732874.
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Front Psychiatry. 2021 Dec 23;12:782183. doi: 10.3389/fpsyt.2021.782183. eCollection 2021.

Affective Computing for Late-Life Mood and Cognitive Disorders.

Frontiers in psychiatry

Erin Smith, Eric A Storch, Ipsit Vahia, Stephen T C Wong, Helen Lavretsky, Jeffrey L Cummings, Harris A Eyre

Affiliations

  1. The PRODEO Institute, San Francisco, CA, United States.
  2. Organisation for Economic Co-operation and Development (OECD), Paris, France.
  3. Department of Neurology & Neurological Sciences, Stanford University, Stanford, CA, United States.
  4. Global Brain Health Institute, University of California, San Francisco, San Francisco, CA, United States.
  5. Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland.
  6. Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, United States.
  7. Division of Geriatric Psychiatry, McLean Hospital, Boston, MA, United States.
  8. Division of Geriatric Psychiatry, Harvard Medical School, Boston, MA, United States.
  9. Systems Medicine and Biomedical Engineering Houston Methodist, Houston, TX, United States.
  10. Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States.
  11. Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences, University of Nevada, Las Vegas (UNLV), Las Vegas, NV, United States.
  12. IMPACT, The Institute for Mental and Physical Health and Clinical Translation, Deakin University, Geelong, VIC, Australia.

PMID: 35002802 PMCID: PMC8732874 DOI: 10.3389/fpsyt.2021.782183

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.

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

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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