Improving ECG signal denoising using wavelet transform for the prediction of malignant arrhythmias
by Agostino Giorgio; Cataldo Guaragnella; Domenico Andrea Giliberti
International Journal of Medical Engineering and Informatics (IJMEI), Vol. 12, No. 2, 2020

Abstract: This paper deals with the accuracy of algorithms for the detection of ventricular late potentials (VLP) in an electrocardiographic signal (ECG), being associated with malignant arrhytmias and possible cardiac death. VLP detection is strongly influenced by signal noise. The objective of this paper is to define a denoising algorithm improving the VLPs detection. The method uses wavelet denoising, subband coding, unfortunately introducing heavy linear distortions. Therefore, an equalisation filter has been properly designed, in order to cancel the distortions. The algorithm has been implemented and successfully verified using MATLAB. Then, it has been implemented on Altera's FPGA and then verified on the evaluation board DE1-SoC. On-board processed results and theoretical results are consistent, validating the algorithm. The results show that the algorithm capability to be implemented as programmable hardware. It also could be used for upgrading ECG devices reliability in the field of heart diseases prevention.

Online publication date: Mon, 27-Apr-2020

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