A monitoring, modeling, and interactive recommendation system for in-home caregivers: demo abstract

Family caregivers often report increased anxiety and depression. In order to improve the interactions between in-home patients and caregivers, and reduce strain on caregivers, we build a monitoring, modeling, and interactive recommendation system for caregivers for in-home dementia patient care. The system includes monitoring for mood by speech, building classifiers that work in realistic home settings, and supporting an adaptive recommendation system to reduce stress of the caregiver. This demo shows how our system supports caregivers in practice through several scenarios.

[1]  J C Adair,et al.  Is it Alzheimer's? , 1998, Hospital practice.

[2]  John A. Stankovic,et al.  M^2G: A Monitor of Monitoring Systems with Ground Truth Validation Features for Research-Oriented Residential Applications , 2017, 2017 IEEE 14th International Conference on Mobile Ad Hoc and Sensor Systems (MASS).

[3]  R. Schulz,et al.  Family caregiving of persons with dementia: prevalence, health effects, and support strategies. , 2004, The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry.

[4]  Wei Chu,et al.  A contextual-bandit approach to personalized news article recommendation , 2010, WWW '10.

[5]  J. Weuve,et al.  2016 Alzheimer's disease facts and figures , 2016 .

[6]  Qingyun Wu,et al.  Learning Contextual Bandits in a Non-stationary Environment , 2018, SIGIR.