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Jiří Spilka.

You can find updated information at this web page.

Researcher at Czech Institute of Informatics, Robotics and Cybernetics (CIIRC)
Czech Technical University in Prague

Curriculum vitae

full CV

Research interest

biomedical signal processing, machine learning, classification, fetal heart rate analysis and classification, cardiotocography

Past research projects:
(Grant IGA) – Cardiotocography evaluation by means of artificial intelligence
(Eniac-MAS) – One part of the project: mCTG – Mobile CardiTocoGraphy – telemedicine application for risk pregnancies at home.

Selected Publications


Abry2018bpex P. Abry, J. Spilka, R. Leonarduzzi, V. Chudáček, N. Pustelnik, M. Doret Sparse learning for Intrapartum fetal heart rate analysis In Biomedical Physics Engineering Express 4(3) 034002, 2018.
web | .pdf | .bib | paper results
Spilka2017jbhi J. Spilka, J. Frecon, R. Leonarduzzi, N. Pustelnik, P. Abry, M. Doret Sparse Support Vector Machine for Intrapartum Fetal Heart Rate Classification In IEEE Journal of Biomedical and Health Informatics, 21(3), 664 - 671, 2017.
web | .pdf | .bib
Doret2015plosone M. Doret, J. Spilka, V. Chudáček, P. Goncalves, P. Abry Fractal Analysis and Hurst Parameter for Intrapartum Fetal Heart Rate Variability Analysis: A Versatile Alternative to Frequency Bands and LF/HF Ratio In PLoS ONE, vol. 10, no. 8, p. e0136661, 08 2015.
web | .pdf | .bib
highlights image J. Spilka, J. Frecon, R. Leonarduzzi, N. Pustelnik, P. Abry, M. Doret Intrapartum Fetal Heart Rate Classification from Trajectory in Sparse SVM feature space In Ann Int Conf IEEE Eng Med Biol Soc (EMBC), Milan, Italy, August 2015, pp. 2335--2338.
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highlights image L. Hruban, J. Spilka, V. Chudáček, P. Janků, et al. Agreement on intrapartum cardiotocogram recordings between expert obstetricians In Journal of Evaluation in Clinical Practice, 21(4): 694-702, 2015.
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highlights image P. Karvelis, J. Spilka, G. Georgoulas, V. Chudáček, C. Stylios, L. Lhotská Combining Latent Class Analysis Labeling with Multiclass Approach for Fetal Heart Rate Categorization In Physiological Measurement 36, 1001-1024, 2015.
web | .pdf | .bib
highlights image J. Spilka, S.G. Roux, N.B. Garnier, P. Abry, P. Goncalves, and M. Doret Nearest-neighbor based wavelet entropy rate measures for intrapartum fetal heart rate variability In Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE, 2813–2816, IEEE, 2014.
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highlights image J. Spilka, V. Chudáček, P. Janků, L. Hruban, M. Burša, M. Huptych, L. Zach, L. Lhotská. Analysis of obstetricians’ decision making on CTG recordings. Journal of Biomedical Informatics 2014, 51:72-79, 2014
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highlights image V. Chudáček, J. Spilka, M. Burša, P. Janků, L. Hruban, M. Huptych, L. Lhotská. Open access intrapartum CTG database. BMC Pregnancy and Childbirth 2014 14(1):16, 2014.
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highlights image J. Spilka, V. Chudáček, M. Koucký, L. Lhotská, M. Huptych, P. Janků, G. Georgoulas, C. Stylios. Using nonlinear features for fetal heart rate classification. Biomedical Signal Processing and Control 7(4):350–357, 2012.
web | .pdf | .bib
highlights image V. Chudáček, J. Spilka, P. Janků, M. Koucký, L. Lhotská, and M. Huptych. Automatic evaluation of intrapartum fetal heart rate recordings: A comprehensive analysis of useful features. Physiological Measurement 32:1347–1360, 2011.
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highlights image J. Spilka, V. Chudáček, V. Kužílek, L. Lhotská, and M. Hanuliak. Detection of Inferior Myocardial Infarction: A Comparison of Various Decision Systems and Learning Algorithms. In Computers in Cardiology volume 37, 2010
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Teaching

present: Artificial Intelligence
past: Medical Informatics, Introduction to Biomedical Engineering, eHealth and telemedicine