Artificial Intelligence for Gerontechnology: Papers from the AAAI Symposium
Diane J. Cook, Narayanan C. Krishnan, Parisa Rashidi, Marjorie Skubic, Alex Mihailidis, Cochairs
The aging population, the increasing cost of formal health care, caregiver burden and the importance that older adults place on living independently in their own homes motivate the need for the development of patient-centric technologies that promote safe independent living. These patient-centric technologies need to address various aging related physical and cognitive health problems such as heart disease, diabetes, deterioration of physical function, falling, wandering, strokes, and memory problems, lack of medication adherence, cognitive decline and loneliness. Advances in the sensor and computing technology that allow for ambient unobtrusive and continuous home monitoring have opened new vistas for the development of such technologies. AI is central to such systems as it deals with the process of transforming raw sensor data into human interpretable abstractions and innovating new human computer interfaces for the older adults. AI can help in decision making and analyzing the sheer volume of captured data from a variety of sensing technologies for understanding the physical activities, nighttime behaviors, medication taking, socialization and ongoing physiological changes in the older adults. As the availability of longitudinal data increases, we have an unprecedented opportunity to discover new early predictors of clinically significant events. This is a challenging research area that has seen increasing interest among the research community due to the need of the hour.