ATSA-ESI: Assistive Technology Supporting Aging with Emotional and Social Intelligence

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For the past twelve years I have been building sophisticated assistive technology (AT) designed to assist elderly persons with dementia (e.g. Alzheimer's). An increasingly elderly population is placing a significant strain on the healthcare system, and an unsustainable burden on informal caregivers (e.g. spouses/children caring for their spouse/parent at home). I develop technologies that can provide autonomy and independence in aging, thereby releasing informal carers from part of this burden, and decreasing healthcare costs. Much progress has been made, but there is a long way to go before these devices are effective and usable. This proposal is to build a unified operational model of engineering, psychological and sociological perspectives on assistive technology (AT) for elder care. Increasingly, the notions of social, emotional and affective intelligence are playing a key role in the pursuit of effective human-machine interaction, including AT. For AT development, these notions are known to have a major impact on the actions of persons with dementia. For example, as Alzheimer's disease interferes with memory, it can often result in a person enacting a past identity, and treating such a person otherwise creates dissonance leading to conflict, stress, and depression, and certainly to AT non-adoption. To handle this, I develop artificially intelligent systems that integrate social and emotional factors into human-interactive systems including AT. I develop these systems using a foundation of probabilistic and decision theoretic sequential dynamical models. The next five years of my research will focus on the theoretical and practical development of group process models, guided by social-psychological theory, with specific application to AT for aging. I will work along three key avenues: hierarchical modelling of sentiment in groups of individuals and applications to specific assistive technologies, machine learning of user and context models from sensor data of individual and group interactions, and development of models of group processes in general beyond AT, based on social-psychological principles, with application to social networks. My currently supported research looks specifically at socio-emotional issues at the level of individual interactions (e.g. a single individual engaged in a single activity), and with a user-evaluative focus. In this proposal, I tackle the problem of modelling groups of individuals, going beyond the person in need of care to include their informal caregiver, their doctor, professional carer, offspring, siblings, neighbours and community. Based on social-psychological theory, I will develop and test models of social networks of elderly persons to provide more effective and tailored care. This work will dovetail with the other, more individual-oriented work funded by my other grants.