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Sensor-Driven Detection of Social Isolation in Community-Dwelling Elderly

机译:社区居民老年人社交隔离的传感器驱动检测

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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 caregi ving. 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 room are associated with different social isolation dimensions. The average time spent outside home is associated with the social loneliness level, social network score and the overall social isolation level of the elderly and the time spent in the living room is positively associated with the emotional loneliness level. Further, elderly who perceived themselves as socially lonely tend to take more naps during the day time. The findings of this study provide implications on how a non-intrusive sensor-based monitoring system comprising of motion-sensors and a door contact sensor can be utilized to detect elderly who are at risk of social isolation.
机译:就地老龄化,即在社区中全面老龄化的能力,正日益得到认可,作为解决老年护理部门资源限制的一种解决方案。有效的老年人护理模式需要个性化且全面的护理方法。在这方面,传感器技术作为监视独居老人健康的有效手段而受到关注。在这项研究中,我们试图调查非侵入式传感器系统检测社会隔离的社区居住老年人的潜力。使用混合方法方法,我们的结果表明,传感器派生的功能(例如外出行为,白天打apping和在客厅花费的时间)与不同的社会隔离维度相关。在家外度过的平均时间与社会孤独感水平,社交网络得分和老年人的整体社会孤立感水平相关,而在客厅度过的时间与情感孤独感水平呈正相关。此外,自以为是社交孤独者的老年人在白天往往会小睡一会儿。这项研究的发现为如何使用基于非侵入式传感器的监视系统(包括运动传感器和门接触传感器)检测具有社会隔离风险的老年人提供了启示。

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