MRC Unit for Lifelong Health and Ageing, UCL, 5th Floor, 1-19 Torrington Place, London, WC1E 7HB, UK.
Department of Biomedical Engineering, King's College London, London, UK.
Sci Rep. 2024 Oct 3;14(1):22994. doi: 10.1038/s41598-024-74140-x.
Exercise capacity is a strong independent predictor of cardiovascular and all-cause mortality. The utilization of well-established submaximal tests of exercise capacity such as the 6-min walk test (6MWT), 3-min step test (3MST) and 10-chair rise test (10CRT) in the community would improve patient care but requires remote monitoring technology. Consumer grade smartwatches provide such an opportunity, however, their accuracy in measuring physiological responses to these tests is unclear. The aim of this study was to determine the accuracy of consumer grade smartwatches in assessing exercise capacity to develop a framework for remote, unsupervised testing. 16 healthy adults (7 male (44%), age median 27 [interquartile range (IQR) 26,29] years) performed 6MWTs using two protocols: (1) standard-straight 30 m laps (6MWT-standard) and 2) continuous lap-circular 240 m laps around a park (6MWT-continuous lap), 3MSTs and 10CRTs. Each one of these four tests was performed three times across two clinic visits. Each participant was fitted with a Garmin Vivoactive4 and Fitbit Sense smartwatch to measure three parameters: distance, step counts and heart rate (HR) response. Reference measures were a meter-wheel, hand tally counter and ECG, respectively. Mean HR was measured at rest, peak exercise and recovery. Agreement was measured using Bland-Altman analysis for repeated measures and summarized as median absolute percentage errors (MAPE). Distance during 6MWT-continuous lap had better agreement than during 6MWT-standard for both Garmin (MAPE: 6.4% [3.0, 10.4%] versus 20.1% [13.9, 28.4%], p < 0.001) and Fitbit (8.0% [2.9, 10.1% versus 18.8% [15.2, 28.1%], p < 0.001). Garmin measured step count more accurately than Fitbit (MAPE: 1.8% [0.9, 2.9%] versus 8.0% [2.6, 12.3%], p < 0.001). Irrespective of test, both devices showed excellent accuracy in measuring HR at rest and recovery (≤ 3%), while accuracy decreased during peak exercise (Fitbit: ~ 12% and Garmin: ~ 7%). In young adults without mobility difficulties, exercise capacity can be measured remotely using standardized tests and consumer grade smartwatches.
运动能力是心血管和全因死亡率的强有力的独立预测因素。在社区中利用经过充分验证的亚极量运动能力测试，如 6 分钟步行测试（6MWT）、3 分钟台阶测试（3MST）和 10 次椅子站立测试（10CRT），可以改善患者的护理，但需要远程监测技术。消费级智能手表提供了这样的机会，然而，它们在测量这些测试对生理反应的准确性尚不清楚。本研究旨在确定消费级智能手表评估运动能力的准确性，以开发远程、无人监督测试的框架。16 名健康成年人（7 名男性（44%），年龄中位数为 27 [四分位距（IQR）26,29]岁）使用两种方案进行 6MWT：（1）标准直 30 m 跑道（6MWT-标准）和 2）连续跑道 240 m 环绕公园（6MWT-连续跑道），3MST 和 10CRT。每个参与者在两次就诊中进行了三次这四项测试。每位参与者都配备了 Garmin Vivoactive4 和 Fitbit Sense 智能手表，以测量三个参数：距离、步数和心率（HR）反应。参考测量值分别为米轮、手动计数器和心电图。分别在休息、运动峰值和恢复时测量平均 HR。采用重复测量的 Bland-Altman 分析来衡量一致性，并以中位数绝对百分比误差（MAPE）进行总结。Garmin 和 Fitbit 对 6MWT-连续跑道的测量距离比 6MWT-标准的一致性更好（Garmin：MAPE：6.4%[3.0，10.4%]比 20.1%[13.9，28.4%]，p<0.001；Fitbit：8.0%[2.9，10.1%比 18.8%[15.2，28.1%]，p<0.001）。Garmin 比 Fitbit 更准确地测量步数（MAPE：1.8%[0.9，2.9%]比 8.0%[2.6，12.3%]，p<0.001）。无论测试如何，这两种设备在测量休息和恢复时的 HR 方面都表现出出色的准确性（≤3%），而在运动峰值时准确性下降（Fitbit：12%，Garmin：7%）。在没有运动障碍的年轻成年人中，可以使用标准化测试和消费级智能手表远程测量运动能力。
