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Detection of Heart Abnormalities Using Signal Processing

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  • Robinson, Mbato

    (Ignatius Ajuru University of Education, Port Harcourt, Nigeria)

  • Kabari, Ledisi G.

    (Ignatius Ajuru University of Education, Port Harcourt, Nigeria)

Abstract

The heart is the center of life. It pumps and distributes blood to every other part of the body. Thus, it holds a strategic position in the body and must be in perfect condition at all times to perform these operations. The Electrocardiogram (ECG) is used to demonstrate the circuit activity of the heart. However, ECG signals can be difficult to interpret especially from non-health professionals. In this work, we developed a model that can detect and interpret the characteristics of an ECG signal, hence, identifying non-linearity of the heart. Fast Fourier Transform was used to filter our ECG readings dataset and remove unwanted signals, before the signals were used for classification and calculation of heart rate using peak values/intervals. The dataset contained about 218,000 ECG readings, including gender and age grades of the patients. Object Oriented Analysis and Design Methodology (OOADM) was adopted in this approach. The system was implemented using MATLAB software. The overall efficiency of the model is 95%, which outperforms other existing models. This system could be beneficial to the research community on signal processing.

Suggested Citation

  • Robinson, Mbato & Kabari, Ledisi G., 2021. "Detection of Heart Abnormalities Using Signal Processing," International Journal of Research and Innovation in Applied Science, International Journal of Research and Innovation in Applied Science (IJRIAS), vol. 6(11), pages 23-27, November.
    • Handle: RePEc:bjf:journl:v:6:y:2021:i:11:p:23-27
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