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Spatial feature extraction from wrist pulse signals

机译:手腕脉冲信号的空间特征提取

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Pulse diagnosis is an important diagnostic method in traditional Chinese medicine. However, it lacks objectivity. To standardize pulse diagnosis, pulse-taking platforms are required. This study implements a complete processing method for wrist pulse signals obtained from a pulse diagnosis instrument with a two-dimensional pressure sensor array to extract the spatial features. First, a zero-phase filter is adopted for acquiring the appropriate frequency band for bio-signals and removing noise. The filter is better to extract the pulse trend due to no phase shift distortion. Next, irregular pulses are removed prior to signal analysis. Then, percussion peaks are identified and the interval between them is used to calculate the pulse rate. Finally, a polynomial surface fitting method is used to compute pulse features, such as the peak, length, width, and surface curvature, from a visualized pulse, which is helpful for the study of pulse classification or even pulse diagnosis.
机译:脉冲诊断是中医药中的重要诊断方法。但是,它缺乏客观性。为了标准化脉冲诊断,需要脉冲平台。该研究实现了一种完整的处理方法,用于从具有二维压力传感器阵列的脉冲诊断仪器获得的腕脉冲信号,以提取空间特征。首先,采用零相滤波器来获取用于生物信号的适当频带并去除噪声。由于没有相移失真,过滤器更好地提取脉冲趋势。接下来,在信号分析之前被移除不规则脉冲。然后,识别打击峰,并且它们之间的间隔用于计算脉冲率。最后,使用多项式表面拟合方法来计算脉冲特征,例如从可视化脉冲计算脉冲特征,例如峰值,长度,宽度和表面曲率,这有助于研究脉冲分类甚至脉冲诊断。

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