Identifying elderlies at risk of becoming more depressed with Internet-of-Things

Identifying elderlies at risk of becoming more depressed with Internet-of-Things

Depression in the elderly is common and dangerous. Current methods to monitor elderly depression, however, are costly, time-consuming and inefficient. In this paper, we present a novel depression-monitoring system that infers an elderly’s changes in depression level based on his/her activity pattern...

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Bibliographic Details
Main Authors: OU, Jiajue, LIANG, Huiguang, TAN, Hwee Xian
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2018
Subjects:
Depression
Elderly
IoT
Machine learning
Gerontology
Software Engineering
Online Access:https://ink.library.smu.edu.sg/sis_research/4096
https://ink.library.smu.edu.sg/context/sis_research/article/5099/viewcontent/Ou2018_Chapter_IdentifyingElderliesAtRiskOfBe.pdf
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Institution: Singapore Management University
Language: English

Internet

https://ink.library.smu.edu.sg/sis_research/4096
https://ink.library.smu.edu.sg/context/sis_research/article/5099/viewcontent/Ou2018_Chapter_IdentifyingElderliesAtRiskOfBe.pdf

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