Methodology of Filtering the Noise and Utilization of STEMI in the Myocardial Infarction
K. Manimekalai1, A.Kavitha2
1K.Manimekalai*, Research Scholar, Department of Computer Science, Kongunadu Arts and Science College, Coimbatore, India.
2Dr.A.Kavitha, Department of Computer Science, Kongunadu Arts and Science College, Coimbatore, India.
Manuscript received on September 23, 2019. | Revised Manuscript received on October 15, 2019. | Manuscript published on October 30, 2019. | PP: 4602-4606 | Volume-9 Issue-1, October 2019 | Retrieval Number: A9966109119/2019©BEIESP | DOI: 10.35940/ijeat.A9966.109119
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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: In order to detect the Myocardial Infarction from ECG records of the patients, the physicians study the electrical motion of the heart. A Myocardial Infarction is an illness condition related to the heart and it is recognized when the pathway to the heart is blocked. These blocks interrupt the regular functioning of the heart; which is spotted through the deviations in the readings of ECG signals. For the sake of detecting Myocardial Infarction, it is essential to detect ST-Elevation followed by the removal of noise in ECG signals with the help of the filtering process. ECG signals are getting affected by various noises with high and low frequencies that will originate the incorrect interpretation. The methodologies for ECG signal filtering using filtering algorithms and for STEMI feature selection from the resultant noise free ECG signals are presented in this paper by employing the MATLAB tool.
Keywords: ECG, Filtering, Feature Selection, Feature Extraction, Heart rate variability, Noise, STEMI.