Improving ECG signal denoising using wavelet transform for the prediction of malignant arrhythmias

Objective: This paper deals with the accuracy of algorithms for the detection of cardiac Ventricular Late Potentials (VLP). The presence of VLP in an electrocardiographic signal (ECG) is associated with possible sudden cardiac death, because of malignant arrhythmias. VLP detection is strongly influenced by signal noise, thus the ECG needs to be denoised before VLP detection. The objective of this paper is to define a denoising algorithm improving the VLPs detection in ECG signal, and to describe its hardware implementation on a Field Programmable Gate Array device (FPGA). Methods: The method described uses wavelet denoising, implemented as subband coding. The drawbacks of this method are heavy linear distortions undergone by the analyzed signal. This disadvantage is overcome by using an equalization filter properly designed by the authors for canceling the introduced distortions. Results: The algorithm (equalizer filter + wavelet denoising) has been firstly implemented and successfully verified using MATLAB. Then, it has been implemented as programmable hardware on Alteras FPGA. The synthesized hardware has been verified on the evaluation board DE1-SoC, mounting a Cyclone V 5CSEMA5F31C6 FPGA chip. Conclusions: On board processed results and theoretical results are consistent, validating the effectiveness of the algorithm and of the designed hardware. Significance: Results show that the algorithm accuracy and its capability to be implemented as programmable hardware also could be used for upgrading ECG devices reliability in the field of heart diseases prevention.