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Physical Activity Trend eXtraction: A Framework for Extracting Moderate-Vigorous Physical Activity Trends From Wearable Fitness Tracker Data

机译:身体活动趋势提取:从可穿戴健身追踪器数据中提取中度剧烈运动趋势的框架

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Background Moderate-vigorous physical activity (MVPA) offers extensive health benefits but is neglected by many. As a result, a wide body of research investigating physical activity behavior change has been conducted. As many of these studies transition from paper-based methods of MVPA data collection to fitness trackers, a series of challenges arise in extracting insights from these new data. Objective The objective of this research was to develop a framework for preprocessing and extracting MVPA trends from wearable fitness tracker data to support MVPA behavior change studies. Methods Using heart rate data collected from fitness trackers, we propose Physical Activity Trend eXtraction (PATX), a framework that imputes missing data, recalculates personalized target heart zones, and extracts MVPA trends. We tested our framework on a dataset of 123 college study participants observed across 2 academic years (18 months) using Fitbit Charge HRs. To demonstrate the value of our frameworks’ output in supporting MVPA behavior change studies, we applied it to 2 case studies. Results Among the 123 participants analyzed, PATX labeled 41 participants as experiencing a significant increase in MVPA and 44 participants who experienced a significant decrease in MVPA, with significance defined as P .05. Our first case study was consistent with previous works investigating the associations between MVPA and mental health. Whereas the second, exploring how individuals perceive their own levels of MVPA relative to their friends, led to a novel observation that individuals were less likely to notice changes in their own MVPA when close ties in their social network mimicked their changes. Conclusions By providing meaningful and flexible outputs, PATX alleviates data concerns common with fitness trackers to support MVPA behavior change studies as they shift to more objective assessments of MVPA.
机译:背景进行剧烈运动(MVPA)可带来广泛的健康益处,但被许多人忽视。结果,进行了许多研究体育活动行为变化的研究。随着许多研究从基于纸张的MVPA数据收集方法过渡到健康追踪器,在从这些新数据中提取见解时会遇到一系列挑战。目的本研究的目的是开发一个框架,用于从可穿戴健身追踪器数据中预处理和提取MVPA趋势,以支持MVPA行为变化研究。方法我们使用从健身追踪器收集的心率数据,提出了体育活动趋势预测(PATX),该框架可估算缺失的数据,重新计算个性化的目标心脏区域并提取MVPA趋势。我们在使用Fitbit Charge HR在2个学年(18个月)中观察到的123名大学研究参与者的数据集上测试了我们的框架。为了展示我们框架的输出在支持MVPA行为变更研究中的价值,我们将其应用于2个案例研究。结果在分析的123名参与者中,PATX将41名参与者的MVPA显着提高,将44名参与者的MVPA显着降低,其显着性定义为P <.05。我们的第一个案例研究与先前研究MVPA与心理健康之间关系的研究一致。第二,探索个人如何相对于朋友如何看待自己的MVPA水平,得出了一个新颖的观察结果,即当社交网络中的亲密关系模仿他们的变化时,个人不太可能注意到自己的MVPA的变化。结论通过提供有意义且灵活的输出,PATX缓解了健身追踪器常见的数据问题,以支持MVPA行为改变研究,因为他们转向了更客观的MVPA评估。

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