Development of Graphical User Interface to Classify Cardiac Abnormalities using ECG Signal

  • Sharanya S Department of Electronics and Instrumentation Engineering, SRM Institute of Science and Technology, Kattankulathur, Kancheepuram-603203 India.
  • Sridhar PA Department of Electronics and Instrumentation Engineering, SRM Institute of Science and Technology, Kattankulathur, Kancheepuram-603203 India.
  • Suresh MP Department of Electronics and Instrumentation Engineering, SRM Institute of Science and Technology, Kattankulathur, Kancheepuram-603203 India.
  • Poorana Mary Monisha W Department of Electronics and Instrumentation Engineering, SRM Institute of Science and Technology, Kattankulathur, Kancheepuram-603203 India.
  • Tharadevi R Department of Electronics and Instrumentation Engineering, SRM Institute of Science and Technology, Kattankulathur, Kancheepuram-603203 India.

Abstract

Analysis of Electrocardiogram (ECG) signal can lead to better detection of cardiac arrhythmia. The important steps involved in the ECG signal analysis include acquisition of data, pre-processing of signal to remove artefacts, feature extraction of attributes and finally identifying abnormalities. This work proposes an efficient implementation of the R-R interval-based ECG classification technique for detecting abnormalities in heart functioning. ECG signals from an online database (PhysioNet.org) was analysed after noise removal for R-R interval, as R peak has the maximum prominent amplitude in ECG wave. Deviation in the R-R interval values obtained from unhealthy was observed and compared with healthy subjects. This observation of cardiac activity can be visualised in our developed Graphical User Interface (GUI). The GUI platform requires only the input of the ECG signal that is to be analysed for abnormalities, which can provide the clinician with the result of cardiac abnormality classification and can help in diagnosis.

 

Keywords: Artifacts, Cardiac Arrhythmia, Electrocardiogram (ECG), Graphical User Interface (GUI)

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Published
2019-07-12
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How to Cite
Sharanya S, Sridhar PA, Suresh MP, Poorana Mary Monisha W, & Tharadevi R. (2019). Development of Graphical User Interface to Classify Cardiac Abnormalities using ECG Signal. International Journal of Research in Pharmaceutical Sciences, 10(3), 1621-1625. https://doi.org/10.26452/ijrps.v10i3.1326
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Original Articles
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