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The impact of Daubechies Wavelet performances on Ventricular Tachyarrhythmia Patients for determination of dominant frequency bands in HRV

机译:Daubechies小波表现对室性心律失常患者确定HRV主频的影响

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Heart rate variability is an important tool for cardiac diagnosis. In this work, the band analysis of very low frequency (VLF) is performed using wavelet packet transform (WPT) on VTA (ventricular tachyarrhythmia) patients. In order to determine the performance of Daubechies wavelets, the energy value of each nodes is computed using db4, db8, db12, db16 and db20 WPTs. The energy characteristic of main VLF band is estimated from sub-bands using multilayer perceptron neural network and dominant sub-bands of VLF are obtained. The dominant band is determined and the performance of Daubechies wavelets is compared in VLF band.
机译:心率变异性是进行心脏诊断的重要工具。在这项工作中,使用小波包变换(WPT)对VTA(室速性心律失常)患者进行了非常低频(VLF)的频带分析。为了确定Daubechies小波的性能,使用db4,db8,db12,db16和db20 WPT计算每个节点的能量值。使用多层感知器神经网络从子带估计主VLF频带的能量特性,并获得VLF的主要子带。确定主导频带,并在VLF频带中比较Daubechies小波的性能。

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