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评估可穿戴设备在养老院环境中用于接触者追踪的性能。

Evaluating the performance of wearable devices for contact tracing in care home environments.

机构信息

School of Electronic and Electrical Engineering, University of Leeds, Leeds, UK.

School of Civil Engineering, University of Leeds, Leeds, UK.

出版信息

J Occup Environ Hyg. 2023 Oct;20(10):468-479. doi: 10.1080/15459624.2023.2241522. Epub 2023 Sep 8.

Abstract

COVID-19 has had a devastating impact worldwide, including in care homes where there have been substantial numbers of cases among a very vulnerable population. A key mechanism for managing exposure to the virus and targeting interventions is contact tracing. Unfortunately, environments such as care homes that were most catastrophically impacted by COVID-19 are also those least amenable to traditional contact tracing. A promising alternative to recall and smartphone-based contact tracing approaches is the use of discrete wearable devices that exploit Bluetooth Low Energy (BLE) and Long-Range Wide Area Network (LoRaWAN) technologies. However, the real-world performance of these devices in the context of contact tracing is uncertain. A series of experiments were conducted to evaluate the performance of a wearables system that is based on BLE and LoRaWAN technologies. In each experiment, the number of successful contacts was recorded and the physical distance between two contacts was compared to a calculated distance using the Received Signal Strength Indication (RSSI) to determine the precision, error rate, and duration of proximity. The overall average system contact detection success rate was measured as 75.5%; when wearables were used as per the manufacturer's guidelines the contact detection success rate increased to 81.5%, but when obstructed by everyday objects such as clothing or inside a bag the contact detection success rate was only 64.2%. The calculated distance using RSSI was close to the physical distance in the absence of obstacles. However, in the presence of typical obstacles found in care home settings, the reliability of detection decreased, and the calculated distance usually appeared far from the actual contact point. The results suggest that under real-world conditions there may be a large proportion of contacts that are underestimated or undetected.

摘要

新冠疫情在全球范围内造成了毁灭性的影响,包括在养老院中,那里有大量非常脆弱的人群感染了这种病毒。管理接触病毒和有针对性地进行干预的一个关键机制是接触者追踪。不幸的是,像养老院这样受到新冠疫情严重影响的环境也是最不适合传统接触者追踪的环境。一种有前途的替代回忆和基于智能手机的接触者追踪方法是使用离散的可穿戴设备,这些设备利用蓝牙低能(BLE)和远距离广域网(LoRaWAN)技术。然而,这些设备在接触者追踪方面的实际性能尚不确定。进行了一系列实验来评估一种基于 BLE 和 LoRaWAN 技术的可穿戴系统的性能。在每个实验中,记录成功接触的次数,并将两个接触点之间的物理距离与使用接收信号强度指示(RSSI)计算的距离进行比较,以确定精度、错误率和接近度的持续时间。总体平均系统接触检测成功率为 75.5%;当可穿戴设备按照制造商的指南使用时,接触检测成功率增加到 81.5%,但当被日常物品(如衣物或包内)阻挡时,接触检测成功率仅为 64.2%。使用 RSSI 计算的距离在没有障碍物的情况下接近物理距离。然而,在养老院环境中常见的障碍物存在的情况下,检测的可靠性降低,计算的距离通常与实际接触点相差甚远。结果表明,在实际情况下,可能有很大一部分接触被低估或未被检测到。

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