Integratable fast algorithm for denoising electrocardiosignal and identifying QRS waves

Abstract

The invention combines a wavelet lifting process and a difference process and provides an integratable fast algorithm for denoising electrocardiosignal and identifying QRS waves. The invention provides a method for denoising a weighted threshold value and solves the problem of signal distortion after denoising by using a global threshold value. The invention proposes to realize the lifting transformation of an electrocardiosignal by using a DB4 first-order derivative, avoid a wavelet lifting and re-decomposing process of the denoised signal and speed up the identification of QRS waves by combining the difference process in a DB4 wavelet lifting transformation process; meanwhile, an improved self-adaptive threshold updating method is adopted to improve the accuracy of QRS wave identification. In the invention, both the wavelet lifting process and a difference process, which are adopted, have the characteristics of high computing speed, low memory space occupation and capacity of realizing integer operation; therefore, the integrated application of the algorithm can be realized easily on the conventional hardware platform and can be realized easily in applications of computers and large processors.

Description

technical field

[0001] The invention belongs to the fields of information processing and medical signal processing, in particular to an integrated fast algorithm for denoising electrocardiogram signals and QRS wave identification. Background technique

[0002] Conventional ECG signals are mV-level signals. In the process of collecting the ECG signal, due to the interference of the outside world and the human body itself, the collected ECG signal is mixed with a large number of noise signals. Noise changes the own characteristics of ECG signal, which affects the analysis and diagnostic accuracy of ECG. Because the ECG signal has non-stationary characteristics and the pollution noise has a large distribution range, which limits the use of traditional linear filters, wavelet analysis has been widely used in the denoising of ECG signals in the past few years. The literatures A Wavelet-Based ECG Delineator Evaluation on Standard Databases, A New Wavelet Based Method for Denoisi...