ECG signal denoising algorithm based on wavelet transform

Le résumé fourni par la source

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.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.