Physiological Sensors Equipped in Wearable Devices for Management of Long COVID Persisting Symptoms: Scoping Review.

IF 5.8 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Shikha Kukreti, Meng-Ting Lu, Chun-Yin Yeh, Nai-Ying Ko
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引用次数: 0

Abstract

Background: Wearable technology has evolved in managing COVID-19, offering early monitoring of key physiological parameters. However, the role of wearables in tracking and managing long COVID is less understood and requires further exploration of their potential.

Objective: This review assessed the application and effectiveness of wearable devices in managing long COVID symptoms, focusing on commonly used sensors and their potential for improving long-term patient care.

Methods: A literature search was conducted across databases including PubMed, Embase, Web of Science, and Cochrane Central, adhering to PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) reporting guidelines. The search was updated regularly throughout 2024. Abstract and full-text screening and selection were facilitated using Rayyan software developed by Qatar Computing Research Institute. Quality appraisal was conducted using the Joanna Briggs Institute (JBI) critical appraisal tool to ensure the methodological rigor of the included studies. Data were extracted on study characteristics, wearable devices, sensors used, and monitored physiological parameters, and the results were synthesized in a narrative format.

Results: A total of 1186 articles were identified, and after duplicate removal and screening, 15 studies were initially included, with 11 studies meeting the criteria for final data synthesis. The included studies varied in design, ranging from observational to interventional trials, and involved sample sizes from 3 to 17,667 participants across different countries. In total, 10 different wearable devices were used to monitor long COVID symptoms, capturing key metrics such as heart rate variability, body temperature, sleep, and physical activity. Smartwatches were the most used wearable devices and fitness trackers with electrocardiography and photoplethysmography sensors were used to monitor heart rate, oxygen saturation, and respiratory rate. Of the 10 devices, 4 were Food and Drug Administration-approved, emphasizing the reliability and validation of the physiological data collected. Studies were primarily conducted in the United States and Europe, reflecting significant regional research interest in wearable technology for long COVID management.

Conclusions: This review highlights the potential of wearable technology in providing continuous and personalized monitoring for long COVID patients. Although wearables show promise in tracking persistent symptoms, further research is needed to improve usability, validate long-term efficacy, and enhance patient engagement.

可穿戴设备中配备的生理传感器用于管理COVID - 19长期持续症状:范围审查
背景:可穿戴技术在COVID-19管理中不断发展,提供关键生理参数的早期监测。然而,可穿戴设备在跟踪和管理长期COVID方面的作用尚不清楚,需要进一步探索其潜力。目的:本综述评估可穿戴设备在管理COVID - 19长期症状中的应用和有效性,重点关注常用传感器及其改善患者长期护理的潜力。方法:在PubMed、Embase、Web of Science和Cochrane Central等数据库中进行文献检索,遵循PRISMA-ScR (Systematic Reviews and meta - analysis extension for Scoping Reviews)报告指南。整个2024年,搜索都在定期更新。使用卡塔尔计算研究所开发的Rayyan软件进行摘要和全文筛选。质量评估采用乔安娜布里格斯研究所(JBI)的关键评估工具进行,以确保纳入研究的方法严谨性。从研究特征、可穿戴设备、使用的传感器和监测的生理参数等方面提取数据,并将结果以叙述的形式进行综合。结果:共纳入1186篇文献,剔除重复和筛选后,最初纳入15项研究,其中11项研究符合最终数据合成的标准。纳入的研究在设计上各不相同,从观察性试验到干预性试验,涉及的样本量从3到17667名来自不同国家的参与者。总共使用了10种不同的可穿戴设备来监测长期的COVID症状,捕捉心率变异性、体温、睡眠和身体活动等关键指标。智能手表是最常用的可穿戴设备,带有心电图和光电容积脉搏波传感器的健身追踪器被用来监测心率、氧饱和度和呼吸频率。在这10台设备中,有4台获得了美国食品和药物管理局的批准,强调了所收集生理数据的可靠性和有效性。研究主要在美国和欧洲进行,反映了该地区对长期COVID管理可穿戴技术的重大研究兴趣。结论:本综述强调了可穿戴技术在为长期COVID患者提供持续和个性化监测方面的潜力。尽管可穿戴设备有望追踪持续症状,但仍需进一步研究以提高可用性,验证长期疗效,并提高患者参与度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
14.40
自引率
5.40%
发文量
654
审稿时长
1 months
期刊介绍: The Journal of Medical Internet Research (JMIR) is a highly respected publication in the field of health informatics and health services. With a founding date in 1999, JMIR has been a pioneer in the field for over two decades. As a leader in the industry, the journal focuses on digital health, data science, health informatics, and emerging technologies for health, medicine, and biomedical research. It is recognized as a top publication in these disciplines, ranking in the first quartile (Q1) by Impact Factor. Notably, JMIR holds the prestigious position of being ranked #1 on Google Scholar within the "Medical Informatics" discipline.
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