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.
Highlights
Between 2019 and 2050, the number of people aged 65 years or over in the world will increase from 703 million to 1.5 billion people [1]
To construct the search protocol, the research question was structured in terms of the following topics: Affective Computing, digital phenotyping, late-life depression, dementia, Alzheimer’s disease, and ethical issues
Data suggest that 1 in 10 cases of dementia world-wide can be attributed to depression [18]
Summary
Between 2019 and 2050, the number of people aged 65 years or over in the world will increase from 703 million to 1.5 billion people [1]. Late-life mood and cognitive conditions are characterized by their complexity, multisystemic nature and broad societal impact, making them poorly suited to siloed approaches of thinking and innovation [2]. Issues such as overlapping symptoms, comorbidities, and misdiagnosis among mental health and neurological disorders represents only a small subset of the challenges facing late-life mood and cognitive conditions [2]. Affective Computing for Late-Life Disorders psychiatric symptoms often occur during prodromal stages of neurodegenerative diseases [3,4,5]. Affective computing has immense potential to benefit the treatment and care of late-life mood and cognitive disorders. It is a transdisciplinary field that combines engineering and computer science with psychology, cognitive science, neuroscience, sociology, education, psychophysiology, value-centered design, ethics, and more
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