Using Fixed Point Arithmetic for Cardiac Pathologies Detection Based on Electrocardiogram

  • Carlos M. Travieso-González
  • Santiago T. Pérez-Suárez
  • Jesús B. Alonso
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, 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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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Carlos M. Travieso-González
    • 1
  • Santiago T. Pérez-Suárez
    • 1
  • Jesús B. Alonso
    • 1
  1. 1.Signal and Communication Department (DSC), Institute for Technological Development and Innovation in Communications (IDeTIC)Universidad de Las Palmas de Gran Canaria, Campus of TafiraLas Palmas de Gran CanariaSpain

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