Abstract
The purpose of the present study was to evaluate the performance of a low-cost commercial smartwatch, the Xiaomi Mi Band (MB), in extracting physical activity and sleep-related measures and show its potential use in addressing questions that require large-scale real-time data and/or intercultural data including low-income countries. We evaluated physical activity and sleep-related measures and discussed the potential application of such devices for large-scale step and sleep data acquisition. To that end, we conducted two separate studies. In Study 1, we evaluated the performance of MB by comparing it to the GT3X (ActiGraph, wGT3X-BT), a scientific actigraph used in research, as well as subjective sleep reports. In Study 2, we distributed the MB across four countries (Austria, Germany, Cuba, and Ukraine) and investigated physical activity and sleep among these countries. The results of Study 1 indicated that MB step counts correlated highly with the scientific GT3X device, but did display biases. In addition, the MB-derived wake-up and total-sleep-times showed high agreement with subjective reports, but partly deviated from GT3X predictions. Study 2 revealed similar MB step counts across countries, but significant later wake-up and bedtimes for Ukraine than the other countries. We hope that our studies will stimulate future large-scale sensor-based physical activity and sleep research studies, including various cultures.
Highlights
In the past three years, the number of wearable devices worldwide has more than doubled, increasing from 325 million in 2016 to 722 million in 2019, while the number of these devices is forecast to reach more than one billion by 2022 [1]
Data and statistical analysis: Firstly, we examined whether the actigraph position relative to the wrist had an effect on the movement and sleep parameters by running a two-sample t-test for Mi Band (MB) and the GT3X separately
Total-sleep-times were significantly affected for MB (t(140) = 2.07, p = 0.04), with a closer MB wrist position resulting in shorter total-sleep-times (M = 7.58, SD = 1.17 vs. M = 7.98, SD = 1.21)
Summary
In the past three years, the number of wearable devices worldwide has more than doubled, increasing from 325 million in 2016 to 722 million in 2019, while the number of these devices is forecast to reach more than one billion by 2022 [1]. The availability of reliable, accurate, and low-cost commercial smartwatches is expected to rapidly increase their use in scientific endeavors for addressing rest- and activity-related questions in large samples. Following this line of reasoning, we here aimed at (i) directly evaluating the performance of a common and low-cost commercial smartwatch, namely the Xiaomi Mi Band (MB), and (ii) using it for a first cultural study investigating potential cultural differences in physical activity and sleep. We hope that our studies will guide and stimulate future large-scale sensor-based physical activity and sleep research projects using and evaluating similar consumer devices
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