Improvement of Threshold Function Based on Wavelet Transform for Denoising ECG Signals

Cardiovascular disease is a major threat to human health, and the study of electrocardiogram signals is crucial for analyzing and exploring this disease. Based on a summary and analysis of previous work, this paper collects electrocardiogram data from the MIT-BIH database and uses a combination of wavelet transform algorithm and Mallet algorithm to analyze and study the classic soft and hard threshold functions. A new threshold function is proposed to address the shortcomings of these functions in denoising electrocardiogram signals. Finally, experimental results in MATLAB demonstrate that the new threshold function can better denoise and obtain pure electrocardiogram signals.