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Study on Pulse-Signal Detection Methods Using Wavelet Transform and Hilbert Huang Transform

机译:使用小波变换和Hilbert Huang变换的脉冲信号检测方法研究

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The practical wrist pulse of the healthy person and the coronary heart disease patient were analyzed by wavelet transform (WT) and hilbert huang transform ( HHT), and the characteristic information(percentage of energy density) of the pulse signal was discussed. The simulation results show that both WT and HHT are efficient ways in analyzing and processing pulse signal, and can draw main characteristic information from pulse signal. However the basis function is preselected in WT, it doesn't need to be preselected in HHT. In HHT the intrinsic mode function(EVIF) is obtained by empirical mode decomposition(EMD), it can reflect the instantaneous frequency of pulse signal, and has the actual physical meaning. The resolving power of time and frequency in WT is restricted by Heisenberg uncertainty principle, and is restricted by each other. While the resolving power of time and frequency in HHT is adaptively changed according to signal intrinsic characteristics. The HHT is more adaptive than WT in analyzing pulse signal. The HHT can offer a new idea to diagnose cardiovascular disease by wrist pulse signal.
机译:通过小波变换(WT)和Hilbert Huang变换(HHT)分析了健康人和冠心病患者的实际手腕脉冲,并且讨论了脉冲信号的特征信息(能量密度的百分比)。仿真结果表明,WT和HHT都是分析和处理脉冲信号的有效方法,并且可以从脉冲信号绘制主要特征信息。然而,在WT中预先选择基本函数,不需要在HHT中预选。在HHT中,内在模式功能(EVIF)通过经验模式分解(EMD)获得,它可以反映脉冲信号的瞬时频率,并且具有实际的物理含义。 WT中的时间和频率的分辨率受到Heisenberg不确定性原理的限制,并且彼此限制。虽然时间和HHT中的时间和频率的分辨率自适应地改变,但是根据信号固有特征自适应地改变。在分析脉冲信号时,HHT比WT更自适应。 HHT可以通过手腕脉冲信号提供诊断心血管疾病的新想法。

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