Abstract
In this paper is presented, a computational tool, to generate (in a controlled way) multiple morphologies of quasi-artificial electrocardiogram (ECG) beats, starting from the configuration and concatenation of six (6) default segments of an ECG beat. The tool allows: to add noises and line base drifts, to convolve the signal with up to three mathematical functions, and to introduce artefacts in any time position of a beat. The tool could be used for the training and evaluation of ECG patterns classifiers such as neural networks (NN), support vector machines (SVM) and others based on Artificial Intelligence techniques.
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© 2013 Springer Berlin Heidelberg
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Suárez-León, A.A., Neto, J.E., Vázquez-Seisdedos, C.R., Romero-Paz, M., Limão-Oliveira, R.C. (2013). Generador de Señales Electrocardiográficas con Morfologías Múltiples. In: Folgueras Méndez, J., et al. V Latin American Congress on Biomedical Engineering CLAIB 2011 May 16-21, 2011, Habana, Cuba. IFMBE Proceedings, vol 33. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21198-0_69
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DOI: https://doi.org/10.1007/978-3-642-21198-0_69
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21197-3
Online ISBN: 978-3-642-21198-0
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