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Assessing blood-pressure measurement in tablet-based mHealth apps

机译:在基于平板电脑的mHealth应用程序中评估血压测量

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We propose a new method to record contextual information associated with a blood-pressure reading using a tablet's touchscreen and accelerometer. This contextual information can be used to verify that a patient's lower arm remained well-supported and stationary during her blood-pressure measurement. We found that a binary support vector machine classifier could be used to distinguish different types of lower-arm movements from stationary arms with 90% accuracy overall. Predetermined thresholds for the accelerometer readings suffice to determine whether the tablet, and therefore the arm that rested on it, remained supported. Together, these two methods can allow mHealth applications to guide untrained patients (or health workers) in measuring blood pressure correctly.
机译:我们提出了一种使用平板电脑的触摸屏和加速度计来记录与血压读数相关的上下文信息的新方法。此上下文信息可用于验证患者的下臂在血压测量过程中保持良好支撑和静止。我们发现,二进制支持向量机分类器可用于区分固定臂的不同类型的下臂运动,整体精度为90%。加速度计读数的预定阈值足以确定平板电脑以及放置在其上的手臂是否仍受支撑。这两种方法结合在一起,可以使mHealth应用程序指导未经训练的患者(或卫生工作者)正确测量血压。

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