Title :
ECG denoising using modulus maxima of wavelet transform
Author :
Ayat, Mohammad ; Shamsollahi, Mohammad B. ; Mozaffari, Behrooz ; Kharabian, Shahrzad
Author_Institution :
Biomed. Signal & Image Process. Lab. (BiSIPL), Sharif Univ. of Technol., Tehran, Iran
Abstract :
ECG denoising has always been an important issue in medical engineering. The purposes of denoising are reducing noise level and improving signal to noise ratio (SNR) without distorting the signal. This paper proposes a method for removing white Gaussian noise from ECG signals. The concepts of singularity and local maxima of the wavelet transform modulus were used for analyzing singularity and reconstructing the ECG signal. Adaptive thresholding was used to remove white Gaussian noise modulus maximum of wavelet transform and then reconstruct the signal.
Keywords :
Gaussian noise; electrocardiography; medical signal processing; signal denoising; signal reconstruction; wavelet transforms; white noise; ECG denoising; ECG signal reconstruction; adaptive thresholding; medical engineering; modulus maxima of wavelet transform modulus; signal to noise ratio; white Gaussian noise removal; ECG Denoising; lipschitz exponents; singular points; wavelet transform; Algorithms; Artifacts; Diagnosis, Computer-Assisted; Electrocardiography; Humans; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted;
Conference_Titel :
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
Conference_Location :
Minneapolis, MN
Print_ISBN :
978-1-4244-3296-7
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2009.5332617