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Analysis and classification of wrist pulse using sample entropy

机译:基于样本熵的手腕脉搏分析与分类

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The cardiovascular system is complex system containing many nonlinearities. Pulse signals are nonlinear reflecting the status of the heart and the vascular system. Sample entropy analysis can quantify signal regularity or the system complexity generating the signal. In this paper the wrist pulse signals of healthy group and coronary heart disease group are analyzed and studied with sample entropy analysis, and the selection of parameters is discussed. The pulse signals of two groups are classified using support vector machine (SVM), the classification results are analyzed. The results indicate there was difference between the sample entropy of two groups of wrist pulse signals; SVM classifiers have good performance for classification of the two groups. Sample entropy analysis of wrist pulse was helpful for non-destructive inspection of coronary heart disease.
机译:心血管系统是包含许多非线性的复杂系统。脉冲信号是非线性的,反映了心脏和血管系统的状态。样本熵分析可以量化信号的规律性或生成信号的系统复杂性。本文采用样本熵分析法对健康人群和冠心病人群的手腕脉搏信号进行了分析和研究,并对参数的选择进行了探讨。使用支持向量机(SVM)对两组脉冲信号进行分类,并对分类结果进行分析。结果表明两组手腕脉搏信号的样本熵之间存在差异。 SVM分类器对两组分类具有良好的性能。腕脉的样本熵分析有助于冠状动脉心脏疾病的无损检查。

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