Electrocardiogram Signal Denoising Using Discrete Wavelet Transform
Electrocardiogram Signal Denoising Using Discrete Wavelet Transform
摘要
The most common noises in ECG （electrocardiogram） signal processing are BW （baseline wandering） and the 50 or 60 Hz PLI （power line interferences）. In order to remove these two major source of noises, we have used the recent powerful DWT （discrete wavelet transform） signal processing in ECG signals which are obtained from MIT-BIH Arrhythmia Database. The results indicate that DWT is a good method for filtering noises without changing the morphology of ECG, and can be applied to all types of ECG signals, whether normal or presenting arrhythmias.
参考文献14
-
1Addison, S.P. 2005. "Wavelet Transforms and the ECG." Physiol. Meas. 26:R155-99.
-
2Thakor, N.V., Webster, J.G., and Tbompkins, W.J. 1984. "Estimation of QRS Complex Power Spectra for Design ofa QRS Filter." IEEE Trans. Biomed. Eng. 31: 702-5.
-
3Thakor, N.V.,and Zhu, Y.S. 1991. "Applications of Adaptive Filtering to ECG Analysis: Noise Cancellation and Arrhythmia Detection." IEEE Trans. Biomed. Eng. 38 (8): 785-94.
-
4Weng, B., Blanco-Velasco,M.,and Barrier, K.E. 2006. "Baseline Wander Correction in ECG by the Empirical Mode Decomposition." lnProceedings of the 1EEE 32nd Annual Northeast Bioengineering Conference, 135-5.
-
5Taouli, S.A.,and Reguig, F.B. 2010. "Noise and Baseline Wandering Suppression of ECG Signals by Morphological Filter." Journal of Medical Engineering & Technology34 (2): 87-96.
-
6Zahhad, M.A., Ahmed, S. M.,and Zakaria, A. 2011. "ECG Signal Compression Technique Based on Discrete Wavelet Transform and QRS-Complex Estimation." Signal Processing : An International Journal (SPIJ) 4 (2): 138-60.
-
7Mallat, S. 1989. "A Theory for Multiresolution Signal Decomposition: The Wavelet Representation." IEEE Trans. on Patt. Anal.and Maeh. lntell.11 (7): 674-93.
-
8M1T-B1Hd://www.physionet.org/physiobank/database/mi tdb/.
-
9Zidelmal, Z., Amirou, A., Adnaneb, M., and Belouchranib, A. 2012. "QRS Detection Based on Wavelet Coefficients." Computer Methods and Programs in Biomedicine 107(2012):490-6.
-
10Pan, J.,and Tompkins, W. J. 1985. "A Real Time QRS Detection Algorithm." IEEE Trans. Biomed. Eng. 32: 230--6.
-
1王振力,张雄伟,郑翔,杨剑.一种新的子波域语音增强方法[J].信号处理,2006,22(3):325-328. 被引量：9
-
2殷瑞祥,马维祯.有限长度离散子波变换的快速算法[J].华南理工大学学报（自然科学版）,1994,22(5):58-65.
-
3苏静,刘跃军.一种基于离散小波变换的信息隐藏算法的实现[J].安阳师范学院学报,2010(2):43-46.
-
4余越,柯有安.离散子波变换计算子波级数变换的预滤波器结构[J].北京理工大学学报,1996,16(3):303-309.
-
5张志明,梅文博,周思永.基于DSP的正交离散子波变换系统的设计与实现[J].信号处理,1999,15(2):121-124.
-
6殷瑞祥,马维祯.用于图象压缩的子波变换的算法结构[J].数据采集与处理,1995,10(4):261-268. 被引量：3
-
7梅文博,周闰,周思永.正交离散子波变换有限字长效应分析[J].电子测量与仪器学报,1998,12(3):1-6.
-
8林子明,梁利平.HEVC静态图像压缩与JPEG 2000性能比较与分析[J].电视技术,2015,39(13):20-23. 被引量：5
-
9微波集成电路、毫米波集成电路[J].电子科技文摘,2000(10):28-28.
-
10Liu Xiaofeng Qin Shuren Bo Lin.NON-STATIONARY SIGNAL DENOISING USING TIME-FREQUENCY CURVE SURFACE FITTING[J].Journal of Electronics(China),2007,24(6):776-781.
