Evaluación de calidad de los ECG adquiridos mediante teléfonos móviles usando tres algoritmos de clasificación

Authors

  • Edgar Muñóz Universidad de Cuenca
  • Juan Narváez Universidad de Cuenca
  • Raúl Suquinagua Universidad de Cuenca
  • Fabian Astudillo Universidad de Cuenca https://orcid.org/0000-0001-7644-0270

Keywords:

Quality of ECGs, computing in cardiology, PhysioNet, mobile phone

Abstract

Computing in Cardiology 2011 proposed to develop an efficient algorithm to classify the quality of electrocardiograms (ECG) recorded by mobile phones; the ECGs are classified as acceptable and unacceptable. Within the framework of the final project of the optional Biomedical Signal Processing, the present work evaluates the performance of a combination of several parameters and proposed during the competition three classification schemes: Logic Rules, Vector Support Machines and Neural Network. For the training of the neural network different inputs are combined, according to the classification parameters and relevant characteristics of each ECG signal extracted through eigenvalues. The best performance was obtained using SVM with certain specific parameters, while using the multilayer neural network and logic rules presented smaller performances.

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References

Chudáček, V., Zach, L., Kužílek, J., Spilka, J., Lhotská, L. (2011). Simple scoring system for ECG quality assessment on Android platform. 2011 Computing in Cardiology, 38, 449-451.

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Silva, I., Moody, G. B., Celi, L. (2011). Improving the quality of ECGs collected using mobile phones: The PhysioNet/Computing in Cardiology Challenge 2011. 2011 Computing in Cardiology, 38, 273-276.

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Published

2017-12-30

How to Cite

Muñóz, E., Narváez, J., Suquinagua, R., & Astudillo, F. (2017). Evaluación de calidad de los ECG adquiridos mediante teléfonos móviles usando tres algoritmos de clasificación. Maskana, 8(1), 385–390. Retrieved from https://publicaciones.ucuenca.edu.ec/ojs/index.php/maskana/article/view/1998

Issue

Vol. 8 (2017): PROCEEDINGS: R+D+Engineering

Section

Second Congress of Signal Processing, Communications and Pattern Recognition

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