基于时频联合分析的弹道心图伪周期段

Jingjing Jin, Xu Wang, Yingnan Wu, Yanbo Yu
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引用次数: 4

摘要

心跳引起同步的身体振动,这可以通过称为balllisto心动图的灵敏力传感器在脊柱轴上测量。心电图是一种非平稳的生理信号,传统的信号处理方法无法对其进行分析和处理。介绍了心电图的生成和采集方法。以双线性时频分布和线性时频分布为例,讨论了Cohen类分布和小波变换,并将其应用于弹心图伪周期段。此外,球心图的频率范围和小波分解的层次由Cohen类分布决定,但指数分布的性能优于Wigner-Ville分布,并且与实际球心图的时域波有很好的对应关系。实验结果表明,双线性时频分布和线性时频分布均能将心电图划分为与心动周期相对应的伪周期,但小波分解的分段性能优于Cohen类分布,且后者更易于实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pseudo-period segment of ballistocardiogram based on joint time-frequency analysis
Heart beat causes the synchronous body vibration, which can be measured on the spine axis by sensitive force sensor called ballistocardiogram. Ballistocardiogram was a kind of nonstationary physiological signal, which couldn't be analyzed and processed by traditional signal processing method. The generation and acquisition method of ballistocardiogram were explained. As examples of bilinear and linear time-frequency distribution, the Cohen class distribution and wavelet transform were discussed and used in ballistocardigram pseudo-period segment. In addition, the frequency range of ballistocardiogram and the levels of wavelet decomposition were determined by Cohen class distribution, but the performance of exponential distribution is better than that of Wigner-Ville distribution and has a fine correspondence to time domain wave of actual ballistocardigram. The experiment results show that, bilinear and linear time-frequency distribution are both able to divide ballistocardiogram into pseudo-periods corresponding to cardiac cycle, but the segment performance of wavelet decomposition is better than that of Cohen class distribution, and the latter one is terser to realize.
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