Feature Extraction of ECG signal using Meyer Wavelet Transform
SK. Piramu Preethika1, R. Gobinath2
1SK. Piramu Preethika, 1Research Scholar, Department of Computer Science, VISTAS, Chennai.
2R. Gobinath, Assistant Professor, Department of Computer Science, VISTAS, Chennai.
Manuscript received on 02 October 2019 | Revised Manuscript received on 13 October 2019 | Manuscript Published on 29 June 2020 | PP: 175-179 | Volume-8 Issue-10S2 August 2019 | Retrieval Number: J103208810S19/2019©BEIESP | DOI: 10.35940/ijitee.J1032.08810S19
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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: Humans suffered with heart related issues in this century due to the poor and improper regular routines which causes a major damage to their entire life. This paper deals with cardiovascular arrhythmias prevention and control by the usage of Electrocardiogram. Cloud storage is utilized for storing the voluminous data of Electrocardiogram details of patients. The collected raw data is pre-processed using the Meyer wavelet transform. It is a kind of a continuous wavelet, which is applied in several cases especially in adaptive filters multi-fault classification. The features extracted are amplitude, age, sex,RR speed and Medicine.These are considered as the information of each data packets that are stored in cloud and later it is transmitted to healthcare centres and physicians for diagnosis and appropriate treatment.
Keywords: Electrocardiogram (ECG),Cardiovasculardiseases (CVD), Meyer Wavelet Transform (MVT)
Scope of the Article: Classification