2016
DOI: 10.1051/matecconf/20164202004
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Mobile Phone Based Falling Detection Sensor and Computer-Aided Algorithm for Elderly People

Abstract: Abstract. Falls are dan gerous for the elderly population; therefore many fall detection systems have been developed. However, previous methods are bulky for elderly people or only use a single sensor to isolate falls from daily living activities, which makes a fall difficult to distinguish. In this paper, we present a cost -effective and easy-to-use portable fall-detection sensor and algorithm. Specifically, to detect human falls, we used a three-axis accelerator and a three-axis gyroscope in a mobile phone. … Show more

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“…Examples of such factors are physical symptoms, impairment records, and demographic details (Boardman andSasse 2004, Vieira, Freund-Heritage et al 2011). For this moment of COVID-19, it is difficult for caregivers to be fully aware of the real-time for the elderly to prevent accidents (Lee, Park et al 2016). Internet monitoring with materials communications about accidents involve information about an entity (e.g., smart home-connected light appliances) that is relevant to the relationship between accidents and the elderly and may help induce preferred behavior of the elderly in these internet monitoring materials contexts (Zhang, Adipat et al 2009).…”
Section: Introductionmentioning
confidence: 99%
“…Examples of such factors are physical symptoms, impairment records, and demographic details (Boardman andSasse 2004, Vieira, Freund-Heritage et al 2011). For this moment of COVID-19, it is difficult for caregivers to be fully aware of the real-time for the elderly to prevent accidents (Lee, Park et al 2016). Internet monitoring with materials communications about accidents involve information about an entity (e.g., smart home-connected light appliances) that is relevant to the relationship between accidents and the elderly and may help induce preferred behavior of the elderly in these internet monitoring materials contexts (Zhang, Adipat et al 2009).…”
Section: Introductionmentioning
confidence: 99%