Publication Type

Conference Proceeding Article

Publication Date

6-2017

Abstract

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.

Keywords

Depression, Elderly, Loneliness, Monitoring system

Discipline

Experimental Analysis of Behavior | Mental and Social Health | Social Welfare

Research Areas

Software and Cyber-Physical Systems

Publication

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

Identifier

10.1145/3092305.3092311

Publisher

Harvard Business School Press

City or Country

Niagara Falls; United States

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org./10.1145/3092305.3092311

Share

COinS