VLSI Implementation of Systolic Architecture for Removing Noise From ECG Signal

Abstract

Electrocardiogram (ECG) signals are affected by various types of noises that are differed based on frequency content. In order to improve accuracy and reliability, it is essential to remove such a disturbance. The denoising of ECG signals is challenging as it is difficult to apply filters with fixed coefficients. Adaptive filtering techniques can be used, in which the filter coefficients can be modified to record the dynamic changes of the signal. The system changes with a sparsity level such as non- sparse, semi sparse and sparse. The Convex combination of Least Mean Square (LMS) and Zero Attractor LMS (ZA-LMS) filter is suitable for both Sparse and also for non-sparse environments. The Systolic Architecture is implemented in the proposed design in order to improve the performance of the system and to reduce combinational delay path. Systolic architectures  are designed for normal Least Mean Square filter (LMS), Zero Attractor LMS filter (ZA- LMS) and the Convex combination of Least Mean Square (LMS) and Zero Attractor LMS (ZA-LMS) filter using Xilinx system generator tool.