基于消费者的可穿戴设备测量慢性阻塞性肺病患者和健康对照者临床参数的有效性:观察研究。

IF 5.4 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Fien Hermans, Eva Arents, Astrid Blondeel, Wim Janssens, Nina Cardinaels, Patrick Calders, Thierry Troosters, Eric Derom, Heleen Demeyer
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引用次数: 0

摘要

背景:基于消费者的可穿戴设备越来越受欢迎,为远程跟踪个人临床参数提供了机会。然而,有关其标准有效性和已知群体有效性的文献却很少:本研究旨在评估 Fitbit Charge 4(一种腕戴式消费类可穿戴设备)与医疗级设备进行比较的有效性,以测量比利时慢性阻塞性肺病(COPD)患者和健康对照者在自由生活条件下的临床参数(即每日步数、静息心率[RHR]、心率变异性[HRV]、呼吸频率[RR]和血氧饱和度):参与者在佩戴 Fitbit Charge 4 的同时还佩戴了三种医疗级设备:(1)Dynaport MoveMonitor,持续 7 天,获取每日步数;(2)Polar H10,持续 5 天,获取 RHR、HRV 和 RR;(3)Nonin WristOX2 3150,持续 4 晚,获取血氧饱和度。标准有效性是通过调查 Fitbit Charge 4 和相应参考设备逐日测量值之间的一致性来评估的。通过比较慢性阻塞性肺病患者和健康对照组来评估已知组的有效性:30 名慢性阻塞性肺病患者和 25 名年龄和性别匹配的健康对照者的数据显示,Fitbit Charge 4 和相应的参考设备在测量每日步数(类内相关系数 [ICC2,1]=0.79 和 ICC2,1=0.85 分别为 0.79 和 0.85)、RHR(ICC2,1=0.80 和 ICC2,1=0.79 分别为 0.80 和 0.79)和 RR(ICC2,1=0.84 和 ICC2,1=0.77 分别为 0.84 和 0.77)方面具有良好的一致性。心率变异的一致性为中度(健康对照组:ICC2,1=0.69)至高度(慢性阻塞性肺病:ICC2,1=0.87)。慢性阻塞性肺病患者血氧饱和度测量的一致性较差(ICC2,1=0.32)。Fitbit设备高估了两组患者的每日步数,低估了心率变异。健康对照组的 RHR 和 RR 被高估,而慢性阻塞性肺病患者则无差异。慢性阻塞性肺病患者的血氧饱和度被高估。Fitbit Charge 4 检测出慢性阻塞性肺病患者和健康对照组在每日步数、RHR 和 RR 方面存在显著差异,这与参考设备发现的差异相似,支持已知组的有效性:尽管 Fitbit Charge 4 主要显示出中等到良好的一致性,但临床参数的测量结果与参考设备存在偏差,这表明远程监测患者和解释参数需要谨慎。Fitbit Charge 4能检测出参考设备测量的慢性阻塞性肺病患者与健康对照组之间的临床参数差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Validity of a Consumer-Based Wearable to Measure Clinical Parameters in Patients With Chronic Obstructive Pulmonary Disease and Healthy Controls: Observational Study.

Background: Consumer-based wearables are becoming more popular and provide opportunities to track individual's clinical parameters remotely. However, literature about their criterion and known-groups validity is scarce.

Objective: This study aimed to assess the validity of the Fitbit Charge 4, a wrist-worn consumer-based wearable, to measure clinical parameters (ie, daily step count, resting heart rate [RHR], heart rate variability [HRV], respiratory rate [RR], and oxygen saturation) in patients with chronic obstructive pulmonary disease (COPD) and healthy controls in free-living conditions in Belgium by comparing it with medical-grade devices.

Methods: Participants wore the Fitbit Charge 4 along with three medical-grade devices: (1) Dynaport MoveMonitor for 7 days, retrieving daily step count; (2) Polar H10 for 5 days, retrieving RHR, HRV, and RR; and (3) Nonin WristOX2 3150 for 4 nights, retrieving oxygen saturation. Criterion validity was assessed by investigating the agreement between day-by-day measures of the Fitbit Charge 4 and the corresponding reference devices. Known-groups validity was assessed by comparing patients with COPD and healthy controls.

Results: Data of 30 patients with COPD and 25 age- and gender-matched healthy controls resulted in good agreement between the Fitbit Charge 4 and the corresponding reference device for measuring daily step count (intraclass correlation coefficient [ICC2,1]=0.79 and ICC2,1=0.85, respectively), RHR (ICC2,1=0.80 and ICC2,1=0.79, respectively), and RR (ICC2,1=0.84 and ICC2,1=0.77, respectively). The agreement for HRV was moderate (healthy controls: ICC2,1=0.69) to strong (COPD: ICC2,1=0.87). The agreement in measuring oxygen saturation in patients with COPD was poor (ICC2,1=0.32). The Fitbit device overestimated the daily step count and underestimated HRV in both groups. While RHR and RR were overestimated in healthy controls, no difference was observed in patients with COPD. Oxygen saturation was overestimated in patients with COPD. The Fitbit Charge 4 detected significant differences in daily step count, RHR, and RR between patients with COPD and healthy controls, similar to those identified by the reference devices, supporting known-groups validity.

Conclusions: Although the Fitbit Charge 4 shows mainly moderate to good agreement, measures of clinical parameters deviated from the reference devices, indicating that monitoring patients remotely and interpreting parameters requires caution. Differences in clinical parameters between patients with COPD and healthy controls that were measured by the reference devices were all detected by the Fitbit Charge 4.

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来源期刊
JMIR mHealth and uHealth
JMIR mHealth and uHealth Medicine-Health Informatics
CiteScore
12.60
自引率
4.00%
发文量
159
审稿时长
10 weeks
期刊介绍: JMIR mHealth and uHealth (JMU, ISSN 2291-5222) is a spin-off journal of JMIR, the leading eHealth journal (Impact Factor 2016: 5.175). JMIR mHealth and uHealth is indexed in PubMed, PubMed Central, and Science Citation Index Expanded (SCIE), and in June 2017 received a stunning inaugural Impact Factor of 4.636. The journal focusses on health and biomedical applications in mobile and tablet computing, pervasive and ubiquitous computing, wearable computing and domotics. JMIR mHealth and uHealth publishes since 2013 and was the first mhealth journal in Pubmed. It publishes even faster and has a broader scope with including papers which are more technical or more formative/developmental than what would be published in the Journal of Medical Internet Research.
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