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Dynamic respiratory modeling for non-contact live monitoring by particle filter approach

机译:通过粒子过滤器方法进行非接触式实时监测的动态呼吸建模

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Although a Doppler radar detects the respiratory motion in the non-contact way, there is a problem of the performance decrement in proportion to the distance between a radar and a human body due to the reduction of the reflected rate. A model-based method is proposed to evaluate the respiratory presence in such cases. This model expresses the chest-wall displacement. The expression is composed of the periodic function which has five parameters. This model has a new property that the inspiration and the expiration are given by each of the two independent parameters. Therefore the problem is solved by tracking the radar outputs using the particle filter framework. The experiment was carried out to the six subjects at the distance 3.25m. The result showed that there was the statistically significant difference between the evaluation value of the unattended state and that of the attended one. In addition, the estimated model was favorably compared with the reference data which was measured by the high-precision displacement sensor. Consequently, the efficacy of the proposed method for the long distance (>3.00m) and that of the proposed respiratory model are established.
机译:尽管多普勒雷达以非接触方式检测呼吸运动,但是由于反射率的降低,存在与雷达与人体之间的距离成比例地性能降低的问题。提出了一种基于模型的方法来评估这种情况下的呼吸存在。该模型表示胸壁位移。该表达式由具有五个参数的周期函数组成。该模型具有一个新的属性,即灵感和有效期由两个独立的参数中的每一个给出。因此,可以通过使用粒子滤波器框架跟踪雷达输出来解决该问题。在距离3.25m处对六个对象进行了实验。结果表明,无人值守状态的评估值与有人值守状态的评估值在统计上有显着差异。另外,将估计的模型与由高精度位移传感器测量的参考数据进行了比较。因此,确立了所提出的方法在长距离(> 3.00m)下的有效性以及所提出的呼吸模型的有效性。

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