Validity of activity trackers, smartphones, and phone applications to measure steps in various walking conditions

TLDR

Count non-empty: all three have content. So output 3 sentences in order: Purpose, Mechanism, Findings. Purpose: "To examine the validity of popular smartphone accelerometer applications and a consumer activity wristband compared to a widely used research accelerometer while assessing the impact of the phone's position on the accuracy of step detection." We can shorten: "The study examined the validity of popular smartphone accelerometer apps and a consumer wristband against a research accelerometer, evaluating how phone position affects step‑count accuracy." That is one sentence.

Abstract

To examine the validity of popular smartphone accelerometer applications and a consumer activity wristband compared to a widely used research accelerometer while assessing the impact of the phone's position on the accuracy of step detection. Twenty volunteers from 2 different age groups (Group A: 18‐25 years, n = 10; Group B 45‐70 years, n = 10) were equipped with 3 iP hone SE smartphones (placed in pants pocket, shoulder bag, and backpack), 1 Samsung Galaxy S6 Edge (pants pocket), 1 Garmin Vivofit 2 wristband, and 2 ActiGraph wGTX + devices (worn at wrist and hip) while walking on a treadmill (1.6, 3.2, 4.8, and 6.0 km/h) and completing a walking course. All smartphones included 6 accelerometer applications. Video observation was used as gold standard. Validity was evaluated by comparing each device with the gold standard using mean absolute percentage errors ( MAPE ). The MAPE of the iP hone SE (all positions) and the Garmin Vivofit was small (<3) for treadmill walking ≥3.2 km/h and for free walking. The Samsung Galaxy and hip‐worn ActiGraph showed small MAPE only for treadmill walking at 4.8 and 6.0 km/h and for free walking. The wrist‐worn ActiGraph showed high MAPE (17‐47) for all walking conditions. The iP hone SE and the Garmin Vivofit 2 are accurate tools for step counting in different age groups and during various walking conditions, even during slow walking. The phone's position does not impact the accuracy of step detection, which substantially improves the versatility for physical activity assessment in clinical and research settings.