Unobtrusive monitoring to detect depression for elderly with chronic illnesses

• Main Authors: KIM, Jung-Yoon, LIU, Na, TAN, Hwee Xian, CHU, Chao-Hsien
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2017
• Subjects: Feature extraction; depression detection; smart homes; unobtrusive monitoring; sensor technologies; Communication Technology and New Media; Health Information Technology; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/3773; https://ink.library.smu.edu.sg/context/sis_research/article/4775/viewcontent/07986964__1_.pdf
• Institution: Singapore Management University

Mental health related disorders are common diseases, especially among the elder. Among the various mental health diseases, one potential threat to ageing-in-place is the risk of depression. In this paper, we propose a simple unobtrusive sensing system using passive infra-red motion sensors to monito...