(1) Background: This study compared manually-counted treadmill walking steps from the hip-worn DigiwalkerSW200 and OmronHJ720ITC, and hip and wrist-worn ActiGraph GT3X+ and GT9X; determined brand-specific acceleration amplitude (g) and/or frequency (Hz) step-detection thresholds; and quantified key features of the acceleration signal during walking. (2) Methods: Twenty participants (Age: 26.7 ± 4.9 years) performed treadmill walking between 0.89-to-1.79 m/s (2–4 mph) while wearing a hip-worn DigiwalkerSW200, OmronHJ720ITC, GT3X+ and GT9X, and a wrist-worn GT3X+ and GT9X. A DigiwalkerSW200 and OmronHJ720ITC underwent shaker testing to determine device-specific frequency and amplitude step-detection thresholds. Simulated signal testing was used to determine thresholds for the ActiGraph step algorithm. Steps during human testing were compared using bias and confidence intervals. (3) Results: The OmronHJ720ITC was most accurate during treadmill walking. Hip and wrist-worn ActiGraph outputs were significantly different from the criterion. The DigiwalkerSW200 records steps for movements with a total acceleration of ≥1.21 g. The OmronHJ720ITC detects a step when movement has an acceleration ≥0.10 g with a dominant frequency of ≥1 Hz. The step-threshold for the ActiLife algorithm is variable based on signal frequency. Acceleration signals at the hip and wrist have distinctive patterns during treadmill walking. (4) Conclusions: Three common research-grade physical activity monitors employ different step-detection strategies, which causes variability in step output.

Our study investigated the performance of proximity sensor-based wear-time detection using the GT9X under laboratory and free-living settings. Fifty-two volunteers (23.2 ± 3.8 y; 23.2 ± 3.7 kg/m) participated in either a laboratory or free-living protocol. Lab participants wore and removed a wrist-worn GT9X on 3-5 occasions during a 3-hour directly observed activity protocol. The 2-day free-living protocol used an independent temperature sensor and self-report as the reference to determine if wrist and hip-worn GT9X accurately determined wear (i.e., sensitivity) and non-wear (i.e., specificity). Free-living estimates of wear/non-wear were also compared to Troiano 2007 and Choi 2012 wear/non-wear algorithms. In lab, sensitivity and specificity of the wrist-worn GT9X in detecting total minutes of wear-on and off was 93% and 49%, respectively. The GT9X detected wear-off more often than wear-on, but with a greater margin of error (4.8 ± 11.6 vs. 1.4 ± 1.4 min). In the free-living protocol, wrist and hip-worn GT9X's yielded sensitivity and specificity of 72 and 90% and 84 and 92%, respectively. GT9X estimations had inferior sensitivity but superior specificity to Troiano 2007 and Choi 2012 algorithms. Due to inaccuracies, it may not be advisable to singularly use the proximity-sensor-based wear-time detection method to detect wear-time.

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