Discriminating Power of an Sample Entropy and a Nonlinear Association Index in Prediction of a Preterm Labor Based on Electrohysterographical Signals

Author:

Radomski Dariusz,Małkiewicz Agnieszka

Publisher

Springer Berlin Heidelberg

Reference8 articles.

1. Leistritz, L., Galicki, M., Kochs, E., Zwick, E.B., Fitzek, C., Reichenbach, J.R., Witte, H.: Application of generalized dynamic neural networks to biomedical data. IEEE Trans. Biomed Eng. 53(11), 2289–2299 (2006)

2. Rossi, J., Gondry, J., Baaklini, N., Naepels, P., Marque, C.: Wavelet analysis of electrohysterography of women exhibiting clinical signs of high-risk pregnancy. Proceedings of the Engineering in Medicine and Biology Society 2, 1059–1060 (1995)

3. Graczyk, S., Jezewski, J., Horoba, K.: Analysis of abdominal electrical activity of uterus-approximate entropy approach. In: Proceedings of the 22nd Annual International

4. Radomski, D.: Sensitivity Analysis of a Sample Entropy Estimator on its Parameters in Application to Electrohysterographical Signals. Biocybernetics and Biomedical Engineering

5. Radomski, D., MaÅĆkiewicz, A.: Identification of a Nonlinear Association Between Components of the Electrohysterographical Signal. Int. J. Electron. Telecom. 56(3), 287–290 (2010)

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