ECG signal denoising algorithm based on wavelet transform

Zijian Ren; Hai Zhao

doi:10.1117/12.2673787

6 April 2023 ECG signal denoising algorithm based on wavelet transform

Zijian Ren, Hai Zhao

Proceedings Volume 12615, International Conference on Signal Processing and Communication Technology (SPCT 2022); 126150G (2023) https://doi.org/10.1117/12.2673787
Event: International Conference on Signal Processing and Communication Technology (SPCT 2022), 2022, Harbin, China

Abstract

This paper introduces an optimized de-noising method based on the wavelet transform hard and soft threshold de-noising method, which is used to remove noise from electrocardiogram signals to achieve clinical high-precision diagnosis. An appropriate threshold processing method is required in the process of denoising and restoring the electrocardiogram signals carrying a certain degree of noise. However, the traditional hard and soft thresholds have serious problems such as distortion and oscillation. By using the optimized new threshold algorithm, the problem of hard and soft threshold processing can be improved to a certain extent under the condition of higher degree of signal restoration and better denoising effect. The experimental results show that with the help of the optimized algorithm in Python, the denoising and restoration of noisy electrocardiogram signals have indeed achieved better results than the traditional methods.

Citation Download Citation

Zijian Ren and Hai Zhao "ECG signal denoising algorithm based on wavelet transform", Proc. SPIE 12615, International Conference on Signal Processing and Communication Technology (SPCT 2022), 126150G (6 April 2023); https://doi.org/10.1117/12.2673787

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available