【摘要】 目的:在心电信号(ECG)的采集过程中,常常会受到噪声的影响,为了正确进行心电参数测量、波形识别和病情诊断,在低信噪微弱信号检测中必须要进行噪声抑制,提高信噪比。噪声的滤波处理是心电图分析的一个重要步骤。方法:本文提出了一种基于小波包变换及与分解层次相关的自适应阈值的去噪方法,利用小波包对心电信号进行分解,可以同时对信号的低频和高频部分进行分解,可以更好的保留原信号信息,减少噪声对信号的影响,同时对小波包树系数用自适应阈值进行软阈值处理,可以明显提高信噪比。结果:用本文提出的算法对心电信号进行滤波,确实提高了信噪比。得到比较优秀的去噪效果。结论:仿真实验表明,本文提出的算法滤噪效果优于小波去噪效果。更多还原

【Abstract】 Objective:ECG(ECG) acquisition process,often subject to noise,in order to correctly measure the ECG parameters,waveform identification and disease diagnosis,in the low noise of weak signal detection in noise reduction must be carried out to improve the signal to noise ratio.Noise filtering is an important step in ECG analysis.Methods:This paper presents a wavelet packet transform and decomposition level associated with the adaptive threshold denoising method.The use of wavelet packet decomposition of ECG signal,signal can be low and high frequency part of the decomposition as well.We can be to better reserve the original signal information,to reduce the impact of noise on the signal,while the wavelet packet tree coefficients of adaptive threshold soft threshold can significantly improve signal to noise ratio.Results:The proposed algorithm with the ECG signal filtering,improves the signal to noise ratio.Conclusions:Simulation results show that the proposed denoising algorithm is better than the wavelet denoising.更多还原