Validity of four low-cost smartwatches in estimating energy expenditure during cycling in Chinese untrained women - Yongfu Liu; Fei Liu; Wenjun Yu; Yuxin Xiao; Di Liu; Zhi Li; Weiwei Chen; Feng Gao; Shenglong Le (PLoS ONE, 2025)
Wrist-worn activity monitors, such as smartwatches, are frequently used to monitor energy expenditure (EE) of physical activity, but there is a high degree of heterogeneity in their accuracy. The purpose of this study was to evaluate the validity of four affordable, low-price smartwatches, including HONOR Band 7 (HNB7), HUAWEI Band 8 (HWB8), XIAOMI Smart Band 8 (XMB8), and KEEP Smart Band B4 Lite (KPB4L), for estimating EE during ergometer cycling in untrained Chinese women. Twenty Chinese women who exercised ≤3 times per week simultaneously wore two smartwatches, randomly assigned to each wrist, during cycling at 30W, 40W, 50W and 60W on the ergometer. As the golden standard, indirect calorimetry (CORTEX METAMAX 3B, MM3B) was used to evaluate EE at the same time. For all loads, EE values were significantly overestimated by XMB8 and KPB4L, compared to the golden standard (all p < 0.001), but not by HNB7 and HWB8. The mean absolute percentage error (MAPE) was 49.5–57.4% for the KPB4L, 30.5–41.0% for the XMB8, 12.5–18.6% for the HWB8, and 15.0–23.0% for the HNB7, respectively. A lower MAPE value indicates that smartwatch estimates are closer to the golden standard. Bland–Altman plots indicated a trend of increasing positive bias as EE increased across all devices, with the XMB8 and KPB4L showing this pattern most clearly. The results clearly show that although HNB7 and HWB8 demonstrated moderate accuracy, there were significant differences in EE estimation accuracy across the tested devices. These findings suggest caution in using low-price smartwatches for energy balance management in untrained female populations. However, the findings of this study are subject to limitations, such as a small and homogeneous sample size, and the occasional missing of data across multiple load levels. Future studies should increase the sample size and include more diverse participants to validate these findings.