Just Walk的系统识别:促进身体活动的行为移动健康干预

Mohammad T. Freigoun, César A. Martín, Alicia B. Magann, D. Rivera, Sayali S. Phatak, E. Korinek, E. Hekler
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引用次数: 21

摘要

有重要证据表明,体育活动可以降低许多慢性疾病的风险。随着移动医疗(mHealth)技术的兴起,一种有希望的方法是设计针对个人不断变化的需求的干预措施。这是Just Walk的首要目标,这是一种基于系统识别和控制工程原理设计的高适应性身体活动干预。该干预措施的特点包括使用多正弦信号作为伪随机输入,为参与者提供每日步骤目标和奖励目标,以及应用于明智选择的数据段的非常规ARX估计验证程序,该程序旨在平衡验证数据段的预测能力和总体拟合优度。对估计模型的分析提供了影响身体活动的个体参与者特征的重要线索。从黑盒建模中获得的见解对于建立基于社会认知理论动态扩展的半物理模型至关重要。
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System identification of Just Walk: A behavioral mHealth intervention for promoting physical activity
There is significant evidence to show that physical activity reduces the risk of many chronic diseases. With the rise of mobile health (mHealth) technologies, one promising approach is to design interventions that are responsive to an individual's changing needs. This is the overarching goal of Just Walk, an intensively adaptive physical activity intervention that has been designed on the basis of system identification and control engineering principles. Features of this intervention include the use of multisine signals as pseudo-random inputs for providing daily step goals and reward targets for participants, and an unconventional ARX estimation-validation procedure applied to judiciously-selected data segments that seeks to balance predictive ability over validation data segments with overall goodness of fit. Analysis of the estimated models provides important clues to individual participant characteristics that influence physical activity. The insights gained from black-box modeling are critical to building semi-physical models based on a dynamic extension of Social Cognitive Theory.
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