Abstract
The possibility of using a smartwatch as a rehabilitation tool to monitor patients’ heart rates during exercise has gained the attention of many researchers. This study aimed to evaluate the accuracy and precision of the HR measurement performed by two wrist monitors: the Fitbit Charge 4 and the Xiaomi Mi Band 5. Thirty-one healthy volunteers were asked to perform a stress test on a treadmill. Their heart rates were recorded simultaneously by the wristbands and an electrocardiogram (ECG) at 1 min intervals. The mean absolute error percentage (MAPE), Lin’s concordance correlation coefficient (LCCC), and Bland–Altman analysis were calculated to compare the precision and accuracy of heart rate measurements. The estimated validation criteria were MAPE < 10% and LCCC < 0.8. The overall MAPE and LCCC of the Fitbit were 10.19% (±11.79%) and 0.753 (95% CI: 0.717–0.785), respectively. The MAPE and LCCC of the Xiaomi were 6.89% (±9.75) and 0.903 (0.886–0.917), respectively. The precision and accuracy of both devices decreased with the increased exercise intensity. The accuracy of wearable wrist-worn heart rate monitors varies and depends on the intensity of training. Therefore, the decision to use such a device as a heart rate monitor during in-home rehabilitation should be made with caution.
Highlights
Academic Editor: Yvonne TranRecent advances in mobile sensor technology have increased the popularity of wristworn fitness trackers
This study aimed to evaluate the accuracy and precision of heart rate (HR) measurement performed by two popular wrist-worn monitors, the Fitbit Charge 4 (Fitbit) and Xiaomi Mi
A total of 556 pairs of data were obtained for Fitbit, and 509 pairs were obtained for Xiaomi
Summary
Academic Editor: Yvonne TranRecent advances in mobile sensor technology have increased the popularity of wristworn fitness trackers (wristbands, smart bands, and smartwatches). More advanced medical algorithms include detecting atrial fibrillation, estimating heart rate variability to assess the autonomic nervous system, and continuous glucose monitoring [1]. The newest models may have a one-lead ECG option. The popularity of such devices gives a unique opportunity to acquire a large amount of data about the patients, which can be analyzed in medical research. The data are collected in the natural setting of the patient, which allows the patient to assess their lifestyle habits. Making it possible to find connections between behavior, physical activity, sleep quality, and diseases
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