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待选:使用可穿戴设备测量老年人的取货时间。

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

作者信息

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

机构信息

Dept. of Computer Science, William & Mary, Williamsburg, VA.

Dept. of Kinesiology, William & Mary, Williamsburg, VA.

出版信息

IEEE Int Conf Connect Health Appl Syst Eng Technol. 2024 Jun;2024:152-156. doi: 10.1109/chase60773.2024.00025. Epub 2024 Aug 5.

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.

摘要

随着年龄增长,老年人从地上捡起物品的能力会逐渐下降,这会导致生活质量下降以及跌倒风险增加。医疗保健专业人员对长期监测受试者捡起物品能力的下降情况并在其对受试者健康构成危险时进行干预表示出兴趣。目前通过门诊患者就诊来评估捡起物品能力的方法既耗时又费钱。显然需要一种经济高效的远程捡起物品评估方法,以减轻患者和医生的负担。为应对这些挑战,我们推出了一种称为ToPick的捡起时间(ToP)解决方案,旨在随时间自动评估捡起物品的能力。ToPick的实际性能很明显,在对10名老年人的20次捡起事件进行评估时,其中位数误差最小约为100毫秒。此外,ToPick具有很高的可靠性,在捡起事件检测方面达到了完美的准确率、精确率和召回率。我们通过设计一款供医疗从业者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财务成本,同时为用户提供移动治疗。

相似文献

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ToPick: Time-of-Pickup Measurement for the Elderly using Wearables.待选:使用可穿戴设备测量老年人的取货时间。
IEEE Int Conf Connect Health Appl Syst Eng Technol. 2024 Jun;2024:152-156. doi: 10.1109/chase60773.2024.00025. Epub 2024 Aug 5.

本文引用的文献

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A wearable multi-sensor system for real world gait analysis.一种可穿戴多传感器系统,用于现实世界中的步态分析。
Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:7020-7023. doi: 10.1109/EMBC46164.2021.9630392.
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Falls in Older Adults are Serious.老年人跌倒问题严重。
Indian J Orthop. 2020 Jan 24;54(1):69-74. doi: 10.1007/s43465-019-00037-x. eCollection 2020 Feb.
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Predictive Walking-Age Health Analyzer.预测行走年龄健康分析仪。
IEEE J Biomed Health Inform. 2018 Mar;22(2):363-374. doi: 10.1109/JBHI.2017.2666603. Epub 2017 Feb 9.

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