Research on Various Enhancing Algorithms for ECG
Vallem Sharmila1, Komalla Ashoka Reddy2
1Vallem Sharmila, Department of Electronics & Communication Engineering, JNTU, Hyderabad (Telangana), India.
2Komalla Ashoka Reddy, Department of Electronics & Instrumentation Engineering, Kakatiya University, Warangal (Telangana), India.
Manuscript received on 03 June 2019 | Revised Manuscript received on 28 June 2019 | Manuscript Published on 04 July 2019 | PP: 332-338 | Volume-8 Issue-1S4 June 2019 | Retrieval Number: A10590681S419/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Electrocardiogram (ECG) is an electrical signal used for measuring activity of the heart on the body surface via electrodes (leads). It is a primary diagnostic tool for analysis of cardio vascular problems. As ECG signal gets corrupted by different artefacts like power line interference, baseline drift and muscle contraction, diagnosis becomes a difficult task. To get an artefact free ECG signal various techniques employed for de-noising are wavelet transforms, (MSPCA) Multi scale Principal Component Analysis, (HOSA) Higher Order Spectral Analysis and Empirical mode of Decomposition (EMD). Performance comparison of these techniques is achieved by calculating the statistical parameters such as (RMSE) Root mean square error, (RMSV) Root mean square variance and (RMSD)Root mean square deviation.
Keywords: Algorithms Various Signal Power.
Scope of the Article: Low-power design