Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/4016
Title: Design and FPGA Implementation of an Efficient Architecture for Noise Removal in ECG Signals Using Lifting-Based Wavelet Denoising
Authors: Gon, Anusaka
Mukherjee, Atin
Keywords: Field programming gate array
wearable ECG devices
ECG noise removal
lifting-based discrete wavelet transform
soft thresholding
Issue Date: May-2023
Citation: 11th International Conference on ESDC, IIIT, Sri City, India, 4-6 May 2023
Abstract: Noise removal is the most crucial pre-processing step for present-generation biomedical wearable electrocardiogram (ECG) patches and devices to provide efficient detection and monitoring of cardiac arrhythmias. This paper proposes a hardware-efficient and multiplier-less FPGAbased ECG noise removal architecture based on lifting-based wavelet denoising that employs a universal threshold leveldependent function in combination with soft thresholding to produce a noise-free ECG signal. The paper also proposes a modified lifting-based discrete wavelet transform (DWT) algorithm that is multiplier-less and provides a one-step equation for the calculation of the forward output coefficients and the inverse output coefficients. Since a comparator circuit is a very complicated circuitry in VLSI implementation, an optimized median calculation and soft thresholding block with no compare operations for wavelet-based thresholding is proposed. The ECG data is collected from the MIT-BIH arrhythmia database and the ECG noises from the MIT-BIH noise stress database. The proposed denoising technique for the ECG signal is tested on MATLAB which achieves an average improvement in SNR of 7.4 dB and an MSE of 0.0206. The FPGA implementation is performed on the Nexys 4 DDR board, and the proposed wavelet-based denoising architecture results in lower hardware utilization and a relatively high operating frequency of 166 MHz when compared to existing ECG denoising architectures.
Description: Copyright belongs to proceeding publisher
URI: http://hdl.handle.net/2080/4016
Appears in Collections:Conference Papers

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