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Using Fixed Point Arithmetic for Cardiac Pathologies Detection Based on Electrocardiogram

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 8112)


This paper proposes to implement an automatic detection system for the heart diseases over a Field Programmable Gate Array (FPGA). The system is able to process, analyze and classify the cardiac pathologies in real time from electrocardiogram (ECG). Firstly, the pulses of the ECG signals have been extracted from electrocardiographic registers. After that, digital signal processing, normalization and heart pulse features extraction algorithms have been used. These algorithms principally are based on Digital Wavelet Transform (DWT) techniques, and Principal Component Analysis (PCA). Finally, cardiac pulse detection and classification algorithms have been implemented in an Artificial Neural Network (ANN). In this way, the subjectivity problem in the heart disease diagnosis is solved, and the task of heart specialist is facilitated.


  • Cardio-Vascular Diseases
  • Electrocardiogram
  • QRS complex
  • Discrete Wavelet Transform
  • Artificial Neural Network
  • Field Programmable Gate Array
  • System Generator
  • Matlab
  • Simulink

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Travieso-González, C.M., Pérez-Suárez, S.T., Alonso, J.B. (2013). Using Fixed Point Arithmetic for Cardiac Pathologies Detection Based on Electrocardiogram. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory - EUROCAST 2013. EUROCAST 2013. Lecture Notes in Computer Science, vol 8112. Springer, Berlin, Heidelberg.

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-53861-2

  • Online ISBN: 978-3-642-53862-9

  • eBook Packages: Computer ScienceComputer Science (R0)