Osoba


Současná pozice:
External teacher
Současné projekty:
2005 - 2009: member of research team solving project num. 1ET101210512 "Intelligent methods for evaluation of long-term EEG recordings".
2007 - 2008: project IG CTU, CTU0712513 "Recognition and automated classification of significant areas in EEG signal".
2009 - 2011: member of research team solving project num. MSM 6840770012, "Transdisciplinary Biomedical Engineering Research II".


Výuka:
A0B33BMI - Introduction to Biomedical Engineering and Informatics

Vzdělání:
- 2012 -
Doctoral Degree in Artificial Intelligence and Biocybernetics
Faculty of Electrical Engineering
Czech Technical University in Prague
Czech Republic

- 2005 -
Master Degree in Biomedical Engineering
Faculty of Electrical Engineering
Czech Technical University in Prague
Czech Republic

Vedoucí prací:
Diploma Thesis:

[2010] Bc. Robin Horniak: Analýza EEG signálu
[2011] Bc. Radek Novák: Hodnocení EEG signálu v reálném čase
[2011] Bc. Pavel Poláček: SW modul pro realizaci neurofeedback terapie

Bachelor Thesis:

[2007] Nguyen quang Huy: Metody pro zpracování EEG signálu
[2007] Radek Novák: Hardwarové řešení pro klasifikaci spánkových fází
[2007] Jakub Hrebeňár: Analýza novorozeneckých polysomnografických záznamů
[2008] Jan Franc: Korelační a koherentní analýza v EEG
[2009] Vojtěch Červený: Analýza EOG signálu
[2009] Milan Kostílek: Vliv emočních podnětů na charakteristiku EEG signálu
[2009] Michael Kantůrek: Adaptivní segmentace EEG signálu
[2011] Ludmila Dohnalová: Systém pro selekci příznaků z EEG signálu
[2012] Tomáš Kaiser: Analýza epileptických EEG signálů
[2012] Radek Procházka: Designing DB for Neurofeedback Lab Management
[2013] Václav Příhoda: Anotátor dlouhodobých EEG záznamů
[2013] Petr Štěpánek: Modulární systém pro zpracování PSG záznamů
[2013] Matej Murgaš: Incremental Learning in the Task of EEG Signal Classification
[2013] Jakub Kahoun: Využití znalostí experta při zpracování EEG signálů

Publikace:
Related publication in journals:
  1. V. Gerla, K. Paul, L. Lhotska, and V. Krajca. Multivariate analysis of full-term neonatal polysomnographic data. IEEE Transactions on Information Technology in Biomedicine, 13(1):104-110, January 2009.

  2. M. Vavrecka, V. Gerla, L. Lhotska, M. Brunovsky. Frames of reference and their neural correlates within navigation in a 3D environment, Visual Neuroscience, pages 183-191, 2012.

  3. V. Gerla, M. Bursa, L. Lhotska, K. Paul, and V. Krajca. Newborn sleep stage classification using hybrid evolutionary approach. International Journal of Bioelectromagnetism-Special Issue on Recent Trends in Bioelectromagnetism, 9(1):28-29, 2007.

  4. V. Djordjevic, V. Gerla, M. Huptych, L. Lhotska, and V. Krajca. The development of modules for the support of education in the field of biomedical engineering. Elektronika ir Elektrotechnika, 102(6):47-50, 2010.

Related publication in proceedings:
  1. V. Gerla, V. D. Radisavljevic, L. Lhotska, and V. Krajca. Feature Selection for Adults Sleep and Neonatal Polysomnographic Data. In IFMBE Proceedings: World Congress on Medical Physics and Biomedical Engineering. Heidelberg: Springer, vol. 39, pages 538-541, 2012.

  2. V. Gerla, V. Djordjevic, L. Lhotska, and V. Krajča. PSGlab Matlab toolbox for polysomnographic data processing: development and practical application. In 10th International Conference on Information Technology and Applications in Biomedicine, Crete, 2010. IEEE Control Syst Soc.

  3. V. Gerla, V. Djordjevic, M. Vavrecka, L. Lhotska, and V. Krajca. Application of clustering for increasing the evaluation objectivity of electroencephalographic recordings. In Proceedings of Biosignal 2010: Analysis of Biomedical Signals and Images, pages 398-404, Brno, 2010. Brno University of Technology.

  4. V. Gerla, V. Djordjevic, L. Lhotska, and V. Krajca. System approach to complex signal processing task. In Computer Aided Systems Theory - Revised Selected Papers, pages 579-586, Heidelberg, 2009. Springer.

  5. V. Gerla, V. Djordjevic, L. Lhotska, and V. Krajca. Visualization methods used for evaluation of neonatal polysomnographic data. In Proceedings of 9th Intrenational Conference on Information Technology and Applications in Biomedicine, Piscataway, 2009. IEEE.

  6. V. Gerla, M. Macas, L. Lhotska, V. Djordjevic, V. Krajca, and K. Paul. Ward's clustering method for distinction between neonatal sleep stages. In World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany, pages 786-789, Berlin, 2009. Springer Science+Business Media.

  7. V. Gerla, M. Burša, L. Lhotska, P. Kordik, K. Paul, and V. Krajca. Inductive modeling in newborn sleep stage recognition. In IWIM 2007 - International Workshop on Inductive Modelling, pages 312-317, Prague, 2007. Czech Technical University in Prague.

  8. V. Gerla, L. Lhotska, V. Krajca, and K. Paul. Multichannel analysis of the newborn EEG data. In International Special Topics Conference on Information Technology in Biomedicine, Piscataway, 2006. IEEE.

Authorized software:
  1. V. Gerla, V. D. Radisavljevic, and L. Lhotska. Polysomnographic Data Processing Toolbox for Matlab, 2011.



Další odkazy:
Automated Analysis of Long-Term EEG Signals - Ph.D. thesis

Biodat - Biomedical Data and Signal Processing Group
PSGlab - Polysomnographic Data Processing Matlab Toolbox

Za obsah zodpovídá: Kristina Lukešová