ECG Signal Analysis Using Temporary Dynamic Sequence Alignment

Análisis de Señales ECG empleando Alineación Secuencial Dinámica Temporal

Authors

  • Valentín Molina Universidad ECCI
  • Gerardo Ceballo Ceballo Universidad de los Andes, Mérida
  • Hermann Davila Universidad ECCI

Keywords:

ECG, Denoising, Dynamic Programming, Local Alignment, Template Classification

Abstract

This paper shows a feature extraction method for electrocardiographic signals (ECG) based on dynamic
programming algorithms. Specifically, we applied local alignment technique for recognition of template in
continuous ECG signals. First, we encoded the signal to characters based on the sign and magnitude of first
derivative, then we applied local alignment algorithm to search for a complex PQRST template in target
continuous ECG signal. Finally, we arrange the data for direct measurement of morphological features in all
PQRST segment detected. To validate these algorithms, we contrasted them with conventional analysis by
measuring QT segments in the Massachusetts Institute of Technology (MIT) data base. We obtained processing
time at least 100 times lower than those obtained via conventional manual analysis and error rates in QT
measurement below 5%. The automated massive analysis of ECG presented in this work is suitable for postprocessing methods like data mining, classification, and assisted diagnosis of cardiac pathologies.

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Published

2013-06-04

How to Cite

Molina, V. ., Ceballo, G. C., & Davila, H. . (2013). ECG Signal Analysis Using Temporary Dynamic Sequence Alignment: Análisis de Señales ECG empleando Alineación Secuencial Dinámica Temporal. Tecciencia, 14(7), 9–13. Retrieved from https://tecciencia.ecci.edu.co/index.php/TECCIENCIA/article/view/61