小波熵在心电高频噪声处理和R波检测中应用  

Application of wavelet entropy in denoising processing and R wave detection of ECG signal

作　　者：侯宏花[1] 桂志国[1] 

机构地区：[1]中北大学信息与通信工程学院仪器科学与动态测试教育部重点实验室,太原030051

出　　处：《计算机工程与应用》2010年第9期116-119,共4页Computer Engineering and Applications

基　　金：山西省自然科学基金(No.2009011020-2);山西省高等学校科技项目(No.20081024)~~

摘　　要：为了在滤除噪声的同时不丢失信号有用信息,将小波熵理论与小波阈值去噪方法综合起来,提出一种基于小波熵的自适应阈值去噪和R波峰值定位方法,对心电信号高频噪声不同信噪比情况做了去噪处理,并同小波熵最优阈值法做了对比分析,结果表明,本算法可以自适应地确定小波系数阈值,不需要直接处理大量的小波系数,且具有良好的滤波性能,尤其在噪声严重时,去噪和R波检测效果更优。最后对实测和数据库中46例数据都做了应用分析,表明本算法具有快速性、有效性和稳定性的特点。For keeping the available information of a signal when removing noise,a novel adaptive threshold filter and R wave detection method based on wavelet entropy is proposed,which combines the wavelet entropy theory with the threshold wavelet denoising method.Then the high-frequency noise with different SNR in the ECG signal is analyzed by this method.And the analysis is done compared with the optimal threshold wavelet entropy denoising method.The results indicate that the arithmetic can adaptively confirm the wavelet coefficients threshold and it needn＇t dispose the large numbers of wavelet coefficients directly.At the same time,it has an excellent filter performance and especially more effective in serious noisy situations.At last,the proposed method is verified using the clinical data and the data from MIT-BIH arrhythmia database.It shows that this method is simple,effective and stable.

关 键 词：心电信号 小波熵 小波变换 去噪处理 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]