Evaluación de la calidad de registros de ECG mediante el uso de algoritmos de clasificación

Authors

Keywords:

Quality of ECGs, ECGs in mobile phones, computing in cardiology, PhysioNet challenge 2011

Abstract

This paper presents a proposal to improve the performance of a solution proposed in the 2011 challenge of PhysioNet/Computing in Cardiology. The later consists in the use of mobile phones as a tool to help people with different levels of experience in ECGs in the process of determining the quality and validity of the ECG performed on patients living in rural areas as basis in the diagnosis of possible diseases. The research challenge focuses on improvement of the classification of the features extracted from the signals. In this context, in addition to the features already discussed in previous works, three new features are proposed to enhance the performance of the classification algorithms.

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References

Clifford, G. D., Lopez, D., Li, Q., Rezek, I. (2011). Signal quality indices and data fusion for determining acceptability of electrocardiograms collected in noisy ambulatory environments. 2011 Computing in Cardiology, 38, 285-288.

Goldberger, A. L., Amaral, L. A., Glass, L., Hausdorff, J. M., Ivanov, P. C., Mark, R. G., … Stanley, H. E. (2000). PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation, 101(23), E215-220.

Liu, C., Li, P., Zhao, L., Liu, F., Wang, R. (2011). Real-time signal quality assessment for ECGs collected using mobile phones. 2011 Computing in Cardiology, 38, 357-360.

Moody, B. E. (2011). Rule-based methods for ECG quality control. 2011 Computing in Cardiology, 38, 361-363.

Osowski, S., Siwek, K., Markiewicz, T. (2004). MLP and SVM networks - a comparative study. Proceedings of the 6th Nordic Signal Processing Symposium, NORSIG 2004, pp. 37-40.

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.

Silva, I., Moody, G. B. (2014). An open-source toolbox for analysing and processing PhysioNet databases in MATLAB and Octave. Journal of Open Research Software, 2(1). https://doi.org/10.5334/jors.bi

Zaunseder, S., Huhle, R., Malberg, H. (2011). CinC challenge #x2014 - Assessing the usability of ECG by ensemble decision trees. 2011 Computing in Cardiology, 38, 277-280.

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Published

2017-12-30

How to Cite

Enderica, S., López, F., Astudillo, F., & Wong, S. (2017). Evaluación de la calidad de registros de ECG mediante el uso de algoritmos de clasificación. Maskana, 8(1), 391–396. Retrieved from https://publicaciones.ucuenca.edu.ec/ojs/index.php/maskana/article/view/1999

Issue

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

Section

Second Congress of Signal Processing, Communications and Pattern Recognition

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