Division of Sport and Exercise, School of Health and Life Sciences, University of the West of Scotland, Scotland, UK.
J Sports Sci. 2024 Sep;42(17):1664-1672. doi: 10.1080/02640414.2024.2404784. Epub 2024 Oct 6.
Step counts can be estimated from wrist-worn accelerometers through the Verisense Step Count Algorithm. No study has assessed agreement between stepping metrics from ActiGraph accelerometers during free-living. Thirty-four participants (age: 22.9 ± 3.4 years) provided 24 h accelerometer data (non-dominant wrist) and waist. Agreement of two Verisense Algorithms (Verisense 1 & 2) for estimating daily steps, moderate-to-vigorous physical activity (MVPA), peak 1-min and 30-min accumulated steps, against the waist and ActiLife step-count Algorithm was assessed. Mean bias ± 95% limits of agreement (LoA) for daily steps was +1255 ± 3780 steps/day (mean absolute percent error (MAPE): 21%) (Verisense 1) and +1357 ± 3434 steps/day (MAPE: 20%) (Verisense 2). For peak 1-min accumulated steps, mean bias and 95% LoA was -17 ± 23 steps/min (MAPE: 17%) (Verisense 1) and -6 ± 5 steps/min (MAPE: 9%) with Verisense 2. For peak 30-min accumulated steps, mean bias and 95% LoA was -12 ± 45 steps/min (MAPE: 25%) (Verisense 1) and -2 ± 38 steps/min (MAPE: 13%) (Verisense 2). For MVPA steps/day, mean bias and 95% LoA was -1450 ± 3194 steps/day (MAPE: 420%) (Verisense 1) and -844 ± 2571 steps/day (MAPE: 211%) (Verisense 2). For MVPA min/day, mean bias and 95% LoA was -13 ± 27 min/day (MAPE: 368%) (Verisense 1) and -8 ± 24 min/day (MAPE: 209%) (Verisense 2). The Verisense 2 algorithm enhanced agreement for stepping intensity metrics but further refinement is needed to enhance agreement for MVPA against the waist.
可以通过 Verisense 计步算法从佩戴在手腕上的加速度计估算步数。目前尚无研究评估在自由活动期间，ActiGraph 加速度计的计步指标是否具有一致性。34 名参与者（年龄：22.9±3.4 岁）提供了 24 小时加速度计数据（非优势手腕）和腰部数据。评估了两种 Verisense 算法（Verisense 1 和 2）估计每日步数、中高强度体力活动（MVPA）、1 分钟和 30 分钟峰值累计步数、与腰部和 ActiLife 计步算法的一致性。每日步数的平均偏差（bias）±95%一致性界限（LoA）分别为+1255±3780 步/天（平均绝对百分比误差（MAPE）：21%）（Verisense 1）和+1357±3434 步/天（MAPE：20%）（Verisense 2）。对于 1 分钟峰值累计步数，平均偏差和 95% LoA 为-17±23 步/分钟（MAPE：17%）（Verisense 1）和-6±5 步/分钟（MAPE：9%），而 Verisense 2 的值分别为-6±5 步/分钟（MAPE：9%）。对于 30 分钟峰值累计步数，平均偏差和 95% LoA 为-12±45 步/分钟（MAPE：25%）（Verisense 1）和-2±38 步/分钟（MAPE：13%）（Verisense 2）。对于 MVPA 每日步数，平均偏差和 95% LoA 为-1450±3194 步/天（MAPE：420%）（Verisense 1）和-844±2571 步/天（MAPE：211%）（Verisense 2）。对于 MVPA 每日分钟数，平均偏差和 95% LoA 为-13±27 分钟/天（MAPE：368%）（Verisense 1）和-8±24 分钟/天（MAPE：209%）（Verisense 2）。Verisense 2 算法提高了计步强度指标的一致性，但需要进一步改进以提高与腰部相比的 MVPA 一致性。
