详细信息
基于改进小波阈值算法的ECG肌电信号去噪研究 被引量:3
An improved wavelet threshold algorithm for cancelling EMG signal from ECG signal
文献类型:期刊文献
中文题名:基于改进小波阈值算法的ECG肌电信号去噪研究
英文题名:An improved wavelet threshold algorithm for cancelling EMG signal from ECG signal
作者:顾旋[1];张伟[1];吕珊珊[1];梁富娥[1];刘东华[1]
第一作者:顾旋
机构:[1]甘肃中医药大学信息工程学院,甘肃兰州730100
第一机构:甘肃中医药大学信息工程学院(教育技术中心)
年份:2023
卷号:40
期号:2
起止页码:212
中文期刊名:中国医学物理学杂志
外文期刊名:Chinese Journal of Medical Physics
收录:CSTPCD;;CSCD:【CSCD_E2023_2024】;
基金:甘肃省教育厅创新基金(2022B-113);甘肃中医药大学研究生创新基金(2022CX81)。
语种:中文
中文关键词:心电图信号;肌电信号;小波阈值算法去噪;阈值函数;Pearson相关系数
外文关键词:electrocardiogram signal;electromyogram signal;wavelet threshold algorithm denoising;threshold function;Pearson correlation coefficient
摘要:为了解决传统软、硬阈值算法对肌电信号去噪后心电图(ECG)信号幅值降低和存在局部异常尖峰,导致去噪效果较差的问题。通过研究小波阈值算法的去噪原理和优化规则,基于双曲正切函数构造出一种具有连续性、结构简单、灵活性较高的可调阈值函数和改进的分层阈值,并分析得到小波分解含噪ECG信号的最佳小波基函数和分解层数,提出了一种改进的小波阈值算法。将软、硬阈值算法、相关文献中的阈值算法和本文所提改进阈值算法对含有真实肌电信号噪声的ECG信号进行去噪对比研究。实验结果表明:本文改进阈值算法能较好地去除ECG信号中的肌电信号噪声,并能更好地保持ECG信号波形特征,且Pearson相关系数值大于其他阈值算法。定性和定量结果表明,本文所提改进阈值算法对ECG肌电信号噪声具有较好的去噪效果。
After removing the electromyogram(EMG) signal from electrocardiogram(ECG) signal with the traditional soft and hard threshold algorithms, the amplitude of ECG signal decreases and there are local abnormal peaks, leading to unsatisfactory denoising results. By studying the denoising principle and optimization rules of the wavelet threshold algorithm, based on the hyperbolic tangent function, an adjustable threshold function with continuity, simple structure and high flexibility, and an improved hierarchical threshold are constructed. The optimal wavelet basis function and wavelet decomposition level for noisy ECG signals are obtained through analysis. Finally, an improved wavelet threshold algorithm is proposed. The soft and hard threshold algorithms, the threshold algorithm in the relevant literatures, and the proposed algorithm are used to cancel the real EMG signal from ECG signal. The experimental results show that the improved threshold algorithm can better remove EMG signal from ECG signal and preserve the waveform characteristics of ECG signal, and has a greater Pearson correlation coefficient value than other threshold algorithms. Both qualitative and quantitative results confirm that the proposed threshold algorithm is effective in cancelling EMG signal from ECG signal.
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