Abstract | ElectroCardioGram (ECG) signals are usually corrupted with various types of artifacts which degrade the signal quality and might lead to misdiagnosis. The wavelet denoising technique is widely studied in the artifact removal literature which employs conventional Finite Impulse Response (FIR) wavelet filter banks for decomposing, thresholding and reconstructing the noisy signal to obtain high fidelity and clean ECG signal. However, the use of high order FIR wavelet filters increases the hardware complexity and cost of the system. This paper presents novel hybrid Infinite Impulse Response (IIR)/FIR Discrete Wavelet Transform (DWT) filter banks that can be employed in ambulatory health monitoring applications for denoising purposes. The proposed systems are evaluated and compared to the conventional FIR based DWT systems in terms of the computational complexity as well as the denoising performance. 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. |
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