The National Research Centre for the Work Environment, Copenhagen, Denmark.
School of Public Health, Charles Perkins Centre Prevention Research Collaboration, University of Sydney, Sydney, Australia.
Int J Behav Nutr Phys Act. 2019 Aug 16;16(1):65. doi: 10.1186/s12966-019-0835-0.
Pooling data from thigh-worn accelerometers across multiple studies has great potential to advance evidence on the health benefits of physical activity. This requires harmonization of information on body postures, physical activity types, volumes and time patterns across different brands of devices. The aim of this study is to compare the physical behavior estimates provided by three different brands of thigh-worn accelerometers.
Twenty participants volunteered for a 7-day free-living measurement. Three accelerometers - ActiGraph GT3X+, Axivity AX3 and ActivPAL Micro4 - were randomly placed in a vertical line on the midsection of the right thigh. Raw data from each accelerometer was processed and classified into 8 physical activities and postures using the Acti4 software. Absolute differences between estimates and the respective coefficient of variation (CV) were calculated.
We observed very minor differences between physical behavior estimates from three different accelerometer brands. When averaged over 24 h (1,440 min), the absolute difference (CV) between accelerometers were: 1.2 mins (0.001) for lying/sitting, 3.4 mins (0.02) for standing, 3.5 mins (0.06) for moving, 1.9 mins (0.03) for walking, 0.1 mins (0.19) for running, 1.2 mins (0.19) for stair climbing, 1.9 mins (0.07) for cycling. Moreover, there was an average absolute difference of 282 steps (0.03) per 24 h.
Physical behaviors were classified with negligible difference between the accelerometer brands. These results support harmonization of data from different thigh-worn accelerometers across multiple cohorts when analyzed in an identical manner.
从多个研究中汇集大腿佩戴式加速度计的数据具有极大的潜力来推进关于身体活动健康益处的证据。这需要协调不同品牌设备的体位、活动类型、活动量和时间模式信息。本研究的目的是比较三种不同品牌的大腿佩戴式加速度计提供的身体活动估计值。
20 名参与者自愿进行为期 7 天的自由生活测量。将三个加速度计——ActiGraph GT3X+、Axivity AX3 和 ActivPAL Micro4——随机放置在右大腿中部的一条垂直线上。使用 Acti4 软件，对每个加速度计的原始数据进行处理并分类为 8 种身体活动和体位。计算了估计值之间的绝对差异和相应的变异系数 (CV)。
我们观察到三种不同加速度计品牌的身体行为估计值之间存在非常微小的差异。当平均在 24 小时（1440 分钟）内时，加速度计之间的绝对差异（CV）为：躺着/坐着为 1.2 分钟（0.001），站立为 3.4 分钟（0.02），活动为 3.5 分钟（0.06），步行为 1.9 分钟（0.03），跑步为 0.1 分钟（0.19），爬楼梯为 1.2 分钟（0.19），骑自行车为 1.9 分钟（0.07）。此外，平均每天有 282 步（0.03）的绝对差异。
在加速度计品牌之间，身体行为的分类差异可以忽略不计。这些结果支持在以相同方式分析时，来自不同大腿佩戴式加速度计的不同队列的数据的协调。
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