Liu Xiuling, Qiao Lei, Yang Jianli, Dong Bin, Wang Hongrui
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2014 Jun;31(3):511-5.
Due to the characteristics and environmental factors, electrocardiogram (ECG) signals are usually interfered by noises in the course of signal acquisition, so it is crucial for ECG intelligent analysis to eliminate noises in ECG signals. On the basis of wavelet transform, threshold parameters were improved and a more appropriate threshold expression was proposed. The discrete wavelet coefficients were processed using the improved threshold parameters, the accurate wavelet coefficients without noises were gained through inverse discrete wavelet transform, and then more original signal coefficients could be preserved. MIT-BIH arrythmia database was used to validate the method. Simulation results showed that the improved method could achieve better denoising effect than the traditional ones.
由于心电图(ECG)信号的特性和环境因素,在信号采集过程中,心电图信号通常会受到噪声干扰,因此消除心电图信号中的噪声对于心电图智能分析至关重要。在小波变换的基础上,对阈值参数进行了改进,并提出了更合适的阈值表达式。利用改进后的阈值参数对离散小波系数进行处理,通过离散小波逆变换得到无噪声的准确小波系数,进而可以保留更多的原始信号系数。使用麻省理工学院 - 贝斯以色列女执事医疗中心(MIT - BIH)心律失常数据库对该方法进行验证。仿真结果表明,改进后的方法比传统方法能取得更好的去噪效果。