Related Experiment Video
Updated: Sep 13, 2025
Assessing the Accuracy of Fitness Smartwatch Data for Cardiovascular and Physical Activity Monitoring: A Validation Study in Digital Health
Published on: February 21, 2025
Agreement Between TDK Silmee W22 and ActiGraph wGT3X-BT for Estimating Daily Step Counts and Moderate to Vigorous
Hiroko Shimura1,2, Shinpei Okada3,4, Kazushi Maruo1,5
1Research Team for Promoting Independence and Mental Health, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo, Japan.
Background:
Wearable Internet of Things (IoT) devices are powerful tools for remotely collecting intensive longitudinal data. The TDK Silmee W22, a wristband-type wearable IoT device with a built-in 3-axis acceleration sensor, provides minute-by-minute physical activity data such as estimated metabolic equivalents (METs) and step counts. These measurements can be aggregated to daily estimates; however, their accuracies have not been fully explored in adults under free-living settings.
Objective:
This study aims to assess the agreement between the TDK Silmee W22 and the research-grade activity monitor, ActiGraph wGT3X-BT, in estimating daily steps and time spent in moderate to vigorous physical activity (MVPA ≥3 METs) in adults under free-living settings.
Methods:
A convenience sample of young to older adults was recruited from communities across several prefectures in Japan. Participants concurrently wore a TDK Silmee W22 on their nondominant wrist and an ActiGraph wGT3X-BT on the left side of the waist during waking hours for 7 consecutive days. Data were aggregated to daily steps and time spent in MVPA (≥1952 vertical axis counts/minute for ActiGraph) for each participant. A valid day was defined as having ≥ 10 hours of accumulated ActiGraph wear time with ≥100 and <50,000 accumulated steps from both devices. Each valid day was classified as either an active day (≥10,000 steps/day or ≥21.4 minutes MVPA per day) or an inactive day. Bland-Altman plots combined with multilevel analysis and κ statistics were used to assess the agreement between physical activity estimates from the devices.
Results:
A total of 129 participants (n=66, 51.2% women) aged 23-89 years provided the final dataset of 884 observations (5 to 7 daily observations/participant). The TDK Silmee W22 estimated an overall mean of 6369 (SE 242) steps/day and 40.3 (SE 1.9) minutes/day spent in MVPA. Although Bland-Altman plots suggested no obvious proportional bias, fixed biases were observed; the TDK Silmee W22 estimated -1203 steps/day (95% limits of agreement [LoA] -4202 to 1796) and +5 minutes/day (LoA-23 to 34) spent in MVPA compared with those estimated by the ActiGraph wGT3X-BT. TDK Silmee W22 and ActiGraph wGT3X-BT, respectively, classified 14% and 23.1% as active by daily step counts (κ=0.65, 95% CI 0.59-0.72), and 70.4% and 60.9% as active by daily time spent in MVPA (κ=0.64, 95% CI 0.59-0.69), both indicating moderate agreement.
Conclusions:
TDK Silmee W22 underestimated step counts and overestimated time spent in MVPA compared with the research-grade ActiGraph wGT3X-BT, which may lead to misclassification of active and inactive days. Caution is warranted when using TDK Silmee W22 data over relatively short periods, as discrepancies-particularly when compared with research-grade monitors-may affect feedback or goal setting.
