It is essential to proactively detect mental health problems such as loneliness and depression in the independently-living elderly for timely intervention by caregivers. In this paper, we introduce an unobtrusive sensor-enabled monitoring system that has been deployed to 50 government housing ats with the independent-living elderly for two years. Then, we also present our initial findings from the 6-month sensor data between August 2015 and April 2016 as well as the survey data to measure the subjective well-being indicator. Our study showed the promising results that "room-level movements within a house" and "going out" behavior captured by our simple sensor system has a potential to detect the cases of severe loneliness and depression with the precision of 10/16 and recall of 10/12.
Depression, Elderly, Loneliness, Monitoring system
Experimental Analysis of Behavior | Mental and Social Health | Social Welfare
Software and Cyber-Physical Systems
WPA 2017 - Proceedings of the 4th International Workshop on Physical Analytics, co-located with MobiSys 2017; 4th International Workshop on Physical Analytics, WPA 2017; Niagara Falls; United States; 2017 June 19
Harvard Business School Press
City or Country
Niagara Falls; United States
HUYNH, Nguyen Phan Sinh; TAN, Hwee-Pink; and LEE, Youngki.
Towards unobtrusive mental well-being monitoring for independent-living elderly. (2017). WPA 2017 - Proceedings of the 4th International Workshop on Physical Analytics, co-located with MobiSys 2017; 4th International Workshop on Physical Analytics, WPA 2017; Niagara Falls; United States; 2017 June 19. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/3673
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