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

机译:传感器驱动的社区住宅老年人社会隔离检测

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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 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 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:老化,在社区全面增长的能力越来越多地获得认可,作为解决老年护理部门资源限制的解决方案。有效的老年护理模型需要个性化和全部包含的护理方法。在这方面,传感器技术已经受到关注,作为监测老年人居住的福祉的有效手段。在这项研究中,我们寻求调查非侵入式传感器系统的潜力,以检测社交孤立的社区住宅老年人。使用混合方法方法,我们的结果表明,传感器导出的特征,如外出行为,日间时间敲击和起居室所花费的时间与不同的社会隔离尺寸相关联。房屋外的平均时间与社会孤独水平,社会网络得分和老年人的整体社会隔离水平以及在客厅所花费的时间与情绪孤独水平正相关。此外,在白天的时候认为自己是社会孤独的老年人倾向于需要更多的小睡。本研究的发现提供了对如何利用运动传感器和门接触传感器的非侵入式传感器的监测系统的影响,以检测有人具有社会隔离风险的老年人。

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