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Validity of Consumer Activity Monitors and an Algorithm Using Smartphone Data for Measuring Steps during Different Activity Types

机译:消费者活动监视器的有效性以及使用智能手机数据的算法用于在不同活动类型期间测量步骤

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摘要

Background: Consumer activity monitors and smartphones have gained relevance for the assessment and promotion of physical activity. The aim of this study was to determine the concurrent validity of various consumer activity monitor models and smartphone models for measuring steps. Methods: Participants completed three activity protocols: (1) overground walking with three different speeds (comfortable, slow, fast), (2) activities of daily living (ADLs) focusing on arm movements, and (3) intermittent walking. Participants wore 11 activity monitors (wrist: 8; hip: 2; ankle: 1) and four smartphones (hip: 3; calf: 1). Observed steps served as the criterion measure. The mean average percentage error (MAPE) was calculated for each device and protocol. Results: Eighteen healthy adults participated in the study (age: 28.8 ± 4.9 years). MAPEs ranged from 0.3–38.2% during overground walking, 48.2–861.2% during ADLs, and 11.2–47.3% during intermittent walking. Wrist-worn activity monitors tended to misclassify arm movements as steps. Smartphone data collected at the hip, analyzed with a separate algorithm, performed either equally or even superiorly to the research-grade ActiGraph. Conclusion: This study highlights the potential of smartphones for physical activity measurement. Measurement inaccuracies during intermittent walking and arm movements should be considered when interpreting study results and choosing activity monitors for evaluation purposes.
机译:背景:消费者活动监视器和智能手机对评估和促进体育活动进行了相关性。本研究的目的是确定各种消费者活动监视器模型和智能手机模型的并行有效性,用于测量步骤。方法:参与者完成了三项活动协议:(1)俯瞰三种不同的速度(舒适,缓慢,快),(2)日常生活(ADL)的活动,专注于ARM运动,(3)间歇性的行走。参与者佩戴11个活动监视器(手腕:8;臀部:2;脚踝:1)和四个智能手机(臀部:3;小腿:1)。观察到的步骤用作标准测量。为每个设备和协议计算平均百分比误差(MAPE)。结果:18名健康成年人参加了这项研究(年龄:28.8±4.9岁)。地图在间接步行期间的0.3-38.2%,在ADL期间48.2-861.2%,间歇性行走期间11.2-47.3%。腕带活动监视器倾向于将ARM运动分类为步骤。在HIP上收集的智能手机数据,用单独的算法进行分析,同样地或甚至优于研究级的Actigaph进行。结论:本研究突出了智能手机进行身体活动测量的潜力。在解释研究结果和选择活动监视器时,应考虑在间歇性行走和手臂运动期间的测量不准确性。

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