Division Sports and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320B, 4052, Basel, Switzerland.
BMC Public Health. 2019 Feb 28;19(1):244. doi: 10.1186/s12889-019-6568-9.
Wrist-worn accelerometers are increasingly used in epidemiological studies to record physical activity. The accelerometer data are usually only analyzed if the convention for compliant wear time is met (i.e. ≥ 10 h per day) but the algorithms to detect wear time have been developed based on data from hip-worn devices only and have not been tested in a free-living setting. The aim of this study was to validate the automatic wear time detection algorithms of one of the most frequently used devices in a free-living setting.
Sixty-eight adults wore one ActiGraph GT3X+ accelerometer on the wrist and one on the hip and additionally recorded wear times for each device separately in a diary. Monitoring phase was during three consecutive days in a free-living setting. Wear time was computed by the algorithms of Troiano and Choi and compared to the diary recordings.
Mean wear time was over 1420 min per day for both devices on all days. Lin's concordance correlation coefficient for the wrist-worn wear time was 0.73 (0.60; 0.82) when comparing the diary with Troiano and 0.78 (0.67; 0.86) when comparing the diary with Choi. For hip-worn devices the respective values were 0.23 (0.13; 0.33) for Troiano and 0.92 (0.88; 0.95) for Choi. Mean and standard deviation values for absolute percentage errors for wrist-worn devices were - 1.3 ± 8.1% in Troiano and 0.9 ± 7.7% in Choi. The respective values for hip-worn devices were - 17.5 ± 10% in Troiano and - 0.8 ± 4.6% in Choi.
Hip worn devices may be preferred due to their higher accuracy in physical activity measurement. Automatic wear-time detection can show high errors in individuals, but on a group level, type I, type II, and total errors are generally low when the Choi algorithm is used. In a real-life setting and participants with a high compliance, the algorithm by Choi is sufficient to distinguish wear time from non-wear time on a group level.
腕部佩戴的加速度计越来越多地用于记录体力活动的流行病学研究。只有当符合规定的佩戴时间(即每天≥10 小时)时,才会对加速度计数据进行分析,但检测佩戴时间的算法仅基于髋部佩戴设备的数据开发,并未在自由生活环境中进行过测试。本研究旨在验证最常用设备之一的自动佩戴时间检测算法在自由生活环境中的准确性。
68 名成年人在腕部和髋部分别佩戴一个 ActiGraph GT3X+ 加速度计,并在日记中分别记录每个设备的佩戴时间。监测阶段在连续三天的自由生活环境中进行。佩戴时间由 Troiano 和 Choi 的算法计算,并与日记记录进行比较。
两种设备在所有天的平均佩戴时间均超过 1420 分钟/天。当将日记与 Troiano 进行比较时,腕部佩戴时间的 Lin 一致性相关系数为 0.73(0.60;0.82),当与 Choi 进行比较时为 0.78(0.67;0.86)。对于髋部佩戴设备,Troiano 的相应值为 0.23(0.13;0.33),Choi 的相应值为 0.92(0.88;0.95)。腕部佩戴设备的平均和标准差绝对值百分比误差值分别为 Troiano 中的-1.3±8.1%和 Choi 中的 0.9±7.7%。髋部佩戴设备的相应值分别为 Troiano 中的-17.5±10%和 Choi 中的-0.8±4.6%。
由于髋部佩戴设备在体力活动测量方面具有更高的准确性,因此可能更受欢迎。自动佩戴时间检测在个体中可能会出现较大误差,但在群体水平上,当使用 Choi 算法时,I 型、II 型和总误差通常较低。在现实生活环境中,对于高依从性的参与者,Choi 算法足以在群体水平上区分佩戴时间和不佩戴时间。