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Spatial feature extraction from wrist pulse signals

机译:从腕部脉搏信号中提取空间特征

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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:脉冲诊断是中医重要的诊断方法。但是,它缺乏客观性。为了使脉冲诊断标准化,需要使用脉冲采集平台。这项研究实现了从带有二维压力传感器阵列的脉搏诊断仪获得的腕部脉搏信号的完整处理方法,以提取空间特征。首先,采用零相位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,该滤波器更好地提取脉冲趋势。接下来,在信号分析之前,去除不规则脉冲。然后,确定敲击峰值,并将其之间的间隔用于计算脉搏率。最后,使用多项式表面拟合方法从可视化的脉冲中计算脉冲特征,例如峰,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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