基于Hilbert-Huang变换的心音信号时频分析

Tzu-Hsun Hung, Chia-Ching Chou, W. Fang, A. Li, Yu-Ching Chang, Bai-Kuang Hwang, Y. Shau
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引用次数: 14

摘要

本文提出了一种基于Hilbert-Huang变换(HHT)的心音时频分析方法。由于大多数生物医学信号,如脑电图(EEG)、心电图(ECG)和心音信号都是非平稳信号,因此采用HHT。在实际情况下,心音信号记录经常受到前端电路或测量仪器产生的尖峰噪声的污染。首先采用数字中值滤波器去除心音信号中的尖峰噪声。然后,利用经验模态分解(EMD)算法将时间序列数据分解为若干个内禀模态函数(IMFs)。利用希尔伯特变换算法获取每个IMF的瞬时频率。仿真结果表明,基于HHT算法的心音信号时频域分析能够提供更高的频率分辨率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Time-frequency analysis of heart sound signals based on Hilbert-Huang Transformation
In this study, a method based on Hilbert-Huang Transformation (HHT) for time-frequency analysis of heart sound signals is presented. HHT is employed because most biomedical signals such as Electroencephalogram (EEG), Electrocardiogram (ECG) and heart sound signals are non-stationary signals. Heart sound signals recordings are often contaminated with the spike noise caused by the front-end circuits or measurement instruments in the real situations. A digital median filter is firstly employed to remove the spike noise of the heart sound signals. Then, the time series data are decomposed into several IMFs (Intrinsic Mode Function) using Empirical Mode Decomposition (EMD) algorithm. Hilbert transformation algorithm is utilized to acquire the instantaneous frequency for every IMF. Simulation results show that time-frequency domain analysis of heart sounds signals based on HHT algorithm is able to offer higher frequency resolution.
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