Publication Type

Conference Proceeding Article

Version

publishedVersion

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

Databases and Information Systems | Experimental Analysis of Behavior | Mental and Social Health | Social Welfare | Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

WPA '17: Proceedings of the 4th International on Workshop on Physical Analytics, Niagara Falls, June 19

First Page

1

Last Page

6

ISBN

9781450349581

Identifier

10.1145/3092305.3092311

Publisher

ACM

City or Country

New York

Copyright Owner and License

Publisher

Additional URL

https://doi.org/10.1145/3092305.3092311

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