Low-Cost Consumer-Based Trackers to Measure Physical Activity and Sleep Duration Among Adults in Free-Living Conditions: Validation Study
Low-Cost Consumer-Based Trackers to Measure Physical Activity and Sleep Duration Among Adults in Free-Living Conditions: Validation Study
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DOI：
10.2196/16674
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发表时间：
2020-05-19
影响因子：
5
通讯作者：
DeSmet, Ann
中科院分区：
文献类型：
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作者：
Degroote, Laurent;Hamerlinck, Gilles;DeSmet, Ann
背景：用于监测体力活动(PA)和总睡眠时间(TST)的可穿戴跟踪器越来越受欢迎。这些设备不仅被消费者用来监控他们的行为，也被研究人员用来跟踪大样本的行为，被卫生专业人员用来实施旨在促进健康的干预措施，并远程监控患者。然而，高成本和准确性问题可能是广泛采用的障碍。目的：本研究旨在调查6种低成本活动跟踪器测量步数、中到高强度体力活动(MVPA)和TST的同时效度：GeAert on Coach、iWown i5 Plus、MyKronoz ZeFit4、Nokia Go、VeryFit 2.0和小米MiBand 2。方法：对20名成年人进行日常活动和睡眠的自由生活方案。在3天3夜的时间里，他们同时在非优势手腕上佩戴低成本跟踪器和高成本跟踪器(Fitbit Charge HR)。参与者白天在臀部佩戴Actigraph GT3X+加速度计，晚上在非优势上臂佩戴BodyMedia SenseWear设备。使用IBM SPSS240中的平均绝对百分比误差分数、相关性和Bland-Altman图，将每个跟踪器与Actigraph GT3X+和BodyMedia SenseWear进行比较，以评估其有效性。低成本追踪器在测量步骤方面显示出中到强的相关性(Spearman r=0.53-0.91)和低到好的一致性(组内相关系数[ICC]=0.51-0.90)。测量MVPA显示出弱到中等的相关性(Spearman r=0.24-0.56)和低一致性(ICC=0.18-0.56)。对于测量TST，低成本追踪器显示出弱到强的相关性(Spearman r=0.04-0.73)和低一致性(ICC=0.05-0.52)。Bland-Altman图显示，根据所使用的低成本跟踪器，测量步骤、MVPA和TST的计数过多和计数不足之间存在差异。包括Fitbit(一种高成本跟踪器)在内的所有跟踪器都没有显示出测量MVPA的高效度。结论：本研究首次考察了低成本跟踪器的并发效度。测量步数的有效性最强；在一些跟踪器中有证据表明测量睡眠的有效性，而测量MVPA时间的有效性在所有设备中都很弱。不同设备的有效性不同，小米在测量步数方面的有效性最高，VeryFit在睡眠和步数领域的表现相对较强。低成本跟踪器在监控和测量运动和睡眠行为方面前景光明，无论是对消费者还是研究人员。
Background: Wearable trackers for monitoring physical activity (PA) and total sleep time (TST) are increasingly popular. These devices are used not only by consumers to monitor their behavior but also by researchers to track the behavior of large samples and by health professionals to implement interventions aimed at health promotion and to remotely monitor patients. However, high costs and accuracy concerns may be barriers to widespread adoption.Objective: This study aimed to investigate the concurrent validity of 6 low-cost activity trackers for measuring steps, moderate-to-vigorous physical activity (MVPA), and TST: Geonaut On Coach, iWown i5 Plus, MyKronoz ZeFit4, Nokia GO, VeryFit 2.0, and Xiaomi MiBand 2.Methods: A free-living protocol was used in which 20 adults engaged in their usual daily activities and sleep. For 3 days and 3 nights, they simultaneously wore a low-cost tracker and a high-cost tracker (Fitbit Charge HR) on the nondominant wrist. Participants wore an ActiGraph GT3X+ accelerometer on the hip at daytime and a BodyMedia SenseWear device on the nondominant upper arm at nighttime. Validity was assessed by comparing each tracker with the ActiGraph GT3X+ and BodyMedia SenseWear using mean absolute percentage error scores, correlations, and Bland-Altman plots in IBM SPSS 24.0.Results: Large variations were shown between trackers. Low-cost trackers showed moderate-to-strong correlations (Spearman r=0.53-0.91) and low-to-good agreement (intraclass correlation coefficient [ICC]=0.51-0.90) for measuring steps. Weak-to-moderate correlations (Spearman r=0.24-0.56) and low agreement (ICC=0.18-0.56) were shown for measuring MVPA. For measuring TST, the low-cost trackers showed weak-to-strong correlations (Spearman r=0.04-0.73) and low agreement (ICC=0.05-0.52). The Bland-Altman plot revealed a variation between overcounting and undercounting for measuring steps, MVPA, and TST, depending on the used low-cost tracker. None of the trackers, including Fitbit (a high-cost tracker), showed high validity to measure MVPA.Conclusions: This study was the first to examine the concurrent validity of low-cost trackers. Validity was strongest for the measurement of steps; there was evidence of validity for measurement of sleep in some trackers, and validity for measurement of MVPA time was weak throughout all devices. Validity ranged between devices, with Xiaomi having the highest validity for measurement of steps and VeryFit performing relatively strong across both sleep and steps domains Low-cost trackers hold promise for monitoring and measurement of movement and sleep behaviors, both for consumers and researchers.