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SVM Based Life Threatening Arrhythmias Detection

Author(s): B. Sivachandra Mahalingam*, P. Ajai Rai, J. K. Prasanth Singh and U. M. Kavin Karthikeyan

Electrocardiogram (ECG) is the most important and widely used method to study the diseases related to heart. The detailed study of ECG graph helps the medical practitioner to diagnose the condition of the heart. Based on the information provided by ECG graph, an appropriate treatment can be given to the patient. The patient with the medical history of heart alignments should maintain a record of ECG papers for timely analysis and diagnosis of the diseases, which requires large storage space and extensive manual effort. The visual technique of analyzing the ECG signals is tedious and time consuming. In order to overcome this problem, an automatic system which involves digital signal integration and analysis tool is developed using MATLAB. This provides an effective strategy for analog to digital conversion of legated paper biomedical map, equipped with a plottingter. The conversion of electrocardiography (ECG) information from charts into digital ECG signals is designed using MATLAB. This method is cost effective, efficient paper work conversion, provides convenient storage and retrieval of ECG information and does not require dedicated hardware. In addition, this tool can be used to potentially integrate ECG information with the patient’s disease analysis.

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Google Scholar citation report
Citations : 4955

International Journal of Chemical Sciences received 4955 citations as per Google Scholar report

Indexed In

  • Google Scholar
  • Open J Gate
  • China National Knowledge Infrastructure (CNKI)
  • Cosmos IF
  • Geneva Foundation for Medical Education and Research

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