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Sociology

Singapore Management University

Research Collection School Of Computing and Information Systems

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Social isolation

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Quantifying Activity Levels Of Community-Dwelling Seniors Through Beacon Monitoring, Jin Qiang Goh, Hwee-Pink Tan, Hwee Xian Tan Jan 2019

Quantifying Activity Levels Of Community-Dwelling Seniors Through Beacon Monitoring, Jin Qiang Goh, Hwee-Pink Tan, Hwee Xian Tan

Research Collection School Of Computing and Information Systems

The ageing population is rapidly increasing, both in Singapore and worldwide. Due to the shortage of healthcare professionals and institutionalized care, there is a pertinent need for seniors to age-in-place-safely and in the familiarity of their neighborhoods. In addition, changing family structures and rising divorce rates, coupled with the desire for more personal space and independence, have resulted in a significant proportion of seniors who live alone at home. In this paper, we describe a scalable and low-cost monitoring system that can help to identify community-dwelling seniors who are at risk of social isolation and/or frailty. This is achieved by …


Sensor-Driven Detection Of Social Isolation In Community-Dwelling Elderly, W K P Neranjana Nadee Rodrigo Goonawardene, Xiaoping Toh, Hwee-Pink Tan Jan 2017

Sensor-Driven Detection Of Social Isolation In Community-Dwelling Elderly, W K P Neranjana Nadee Rodrigo Goonawardene, Xiaoping Toh, Hwee-Pink Tan

Research Collection School Of Computing and Information Systems

Ageing-in-place, the ability to age holistically in the community, is increasingly gaining recognition as a solution to address resource limitations in the elderly care sector. Effective elderly care models require a personalised and all-encompassing approach to caregiving. In this regard, sensor technologies have gained attention as an effective means to monitor the wellbeing of elderly living alone. In this study, we seek to investigate the potential of non-intrusive sensor systems to detect socially isolated community dwelling elderly. Using a mixed method approach, our results showed that sensor-derived features such as going-out behavior, daytime napping and time spent in the living …