ToPick: Time-of-Pickup Measurement for the Elderly using Wearables.

John Clapham, Kenneth Koltermann, Xinyu Chen, Minglong Sun, Gang Zhou, Evie N Burnet
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Abstract

The ability to pick up objects off the floor can degrade over time with elderly individuals, leading to a reduced quality of life and an increase in the risk of falling. Healthcare professionals have expressed an interest in monitoring the decline in pickup ability of a subject over extended periods of time and intervening when it becomes hazardous to the subject's health. The current means of evaluating pickup ability involving in-clinic patient visits is both time and financially expensive. There is a clear need for a cost-effective, remote means of pickup evaluation to ease the burden on both patients and physicians. To address these challenges, we introduce a Time-of-Pickup (ToP) solution, called ToPick, designed for the automatic assessment of pickup ability over time. The practical performance of ToPick is evident, demonstrated by a minimal median error of approximately 100 milliseconds in evaluating 20 pickup events among 10 elderly individuals. Furthermore, ToPick exhibits a high level of reliability, achieving perfect accuracy, precision, and recall scores for pickup event detection. We actualize our research findings by designing an application intended for adoption by both healthcare practitioners and elderly individuals. The app aims to reduce both time and financial costs while enabling mobile treatment for users.

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ToPick:利用可穿戴设备测量老年人的拾物时间。
随着时间的推移,老年人拾起地上物品的能力会逐渐下降,从而导致生活质量下降和跌倒风险增加。医疗保健专业人员表示有兴趣监测受试者长时间拾取能力下降的情况,并在对受试者健康造成危害时进行干预。目前评估拾起能力的方法涉及到门诊病人就诊,既费时又费钱。显然,我们需要一种经济高效的远程拾取能力评估方法,以减轻患者和医生的负担。为了应对这些挑战,我们推出了一种名为 ToPick 的拾取时间(ToP)解决方案,旨在随时间推移自动评估拾取能力。ToPick 的实用性能是显而易见的,在评估 10 位老人的 20 次拾取事件时,中位误差最小约为 100 毫秒。此外,ToPick 还表现出很高的可靠性,在拾取事件检测方面达到了完美的准确度、精确度和召回分数。我们通过设计一款供医疗从业人员和老年人使用的应用程序来实现我们的研究成果。该应用程序旨在减少时间和经济成本,同时为用户提供移动治疗。
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