IIR Wavelet Filter Banks for ECG Signal Denoising

Abstract

ElectroCardioGram (ECG) signals are widely used for diagnostic purposes. However, it is well known that these recordings are usually corrupted with different type of noise/artifacts which might lead to misdiagnosis of the patient. This paper presents the design and novel use of Infinite Impulse Response (IIR) filter based Discrete Wavelet Transform (DWT) for ECG denoising that can be employed in ambulatory health monitoring applications. The proposed system is evaluated and compared in terms of denoising performance as well as the computational complexity with the conventional Finite Impulse Response (FIR) based DWT systems. For this purpose, raw ECG data from MIT-BIH arrhythmia database are contaminated with synthetic noise and denoised with the aforementioned filter banks. The results from 100 Monte Carlo simulations demonstrated that the proposed filter banks provide better denoising performance with fewer arithmetic operations than those reported in the open literature.