ECG Denoising Methodology using Intrinsic Time Scale Decomposition and Adaptive Switching Mean Filter
Open Access
- 10 May 2021
- journal article
- Published by Lattice Science Publication (LSP) in Indian Journal of Signal Processing
- Vol. 1 (2), 7-12
- https://doi.org/10.54105/ijsp.b1005.051221
Abstract
Electrocardiogram (ECG) is a widely employed tool for the analysis of cardiac disorders. A clean ECG is often desired for proper treatment of cardiac ailments. However, in the real scenario, ECG signals are corrupted with various noises during acquisition and transmission. In this article, an efficient ECG de-noising methodology using combined intrinsic time scale decomposition (ITD) and adaptive switching mean filter (ASMF) is proposed. The standard performance metric namely output SNR improvement measure the efficacy of the proposed technique at various signal to noise ratio (SNR). The proposed de-noising methodology is compared with other existing ECG de-noising approaches. A detail qualitative and quantitative study and analysis indicate that the proposed technique can be used as an effective tool for de-noising of ECG signals and hence can serve for better diagnostic in computer-based automated medical system. The performance of the proposed work is compared with existing ECG de-noising techniques namely wavelet soft thresholding based filter (DWT) [16], EMD with DWT technique [18], DWT with ADTF technique [19]. The effectiveness of the presented work has been evaluated in both qualitative and quantitative analysis. All the simulations are carried out using MATLAB software environment.Keywords
This publication has 34 references indexed in Scilit:
- An adaptive filtering approach for electrocardiogram (ECG) signal noise reduction using neural networksNeurocomputing, 2013
- ECG Signal Denoising By Wavelet Transform ThresholdingAmerican Journal of Applied Sciences, 2008
- Wavelet-based denoising using subband dependent threshold for ECG signalsDigital Signal Processing, 2008
- Time-varying vibration decomposition and analysis based on the Hilbert transformJournal of Sound and Vibration, 2006
- Optimal selection of wavelet basis function applied to ECG signal denoisingDigital Signal Processing, 2006
- Application of independent component analysis in removing artefacts from the electrocardiogramNeural Computing & Applications, 2005
- Application of the Empirical Mode Decomposition to the Analysis of Esophageal Manometric Data in Gastroesophageal Reflux DiseaseIEEE Transactions on Biomedical Engineering, 2005
- The impact of the MIT-BIH Arrhythmia DatabaseIEEE Engineering in Medicine and Biology Magazine, 2001
- Comparing stress ECG enhancement algorithmsIEEE Engineering in Medicine and Biology Magazine, 1996
- De-noising by soft-thresholdingIEEE Transactions on Information Theory, 1995