Model of Syntactic Compatibility in Workflows for Electrophysiology

Jan Štebeták, Roman Moucek

Abstract

Large amounts of EEG/ERP (electroencephalography, event-related potential) data are produced by scientific laboratories. For complex analysis, data are processed by a set of methods sequentially or in parallel. These processes are known as workflows. However, various input/output formats of used methods involve difficulties while putting methods in a pipe. Simple syntactic rules comparing formats of input/output are already used by workflow engines. In electrophysiology, it is necessary to extend these rules due to variety of methods. Therefore, extension of syntactic rules between subsequent methods in a workflow is presented in this paper. The proposed solution allows creating more complex workflows in the domain of electrophysiology.

References

  1. (CARMEN) Development of a workflow system for the CARMEN Neuroscience Portal (2013)
  2. http://neuroinformatics2012.org/abstracts/development-ofa-workflow-system-for-the-carmen-neuroscienceportal
  3. Taverna (2013), http://www.taverna.org.uk/
  4. eScience Central (2013) http:// www.esciencecentral.co.uk/?p=151
  5. Watson, P., Hiden, H., Woodman, S., 2010, “e-Science Central for CARMEN: Science as a Service.” Concurrency and Computation: Practice and Experience, Volume 22, Issue 17, pages 2369-2380, 10 December.
  6. Rondik, T. 2012, “Methods for Detection of ERP Waveforms in BCI Systems” State of the Art and Concept of Ph.D. Thesis, Pilsen.
  7. Vidal, J. J., 1977, Real-time detection of brain events in EEG. Proceedings of the IEEE, Volume 65, Issue 5, pp. 633 - 641.
  8. Ciniburk, J., Moucek, R., Mautner, P., Rondík, T., 2010, ERP components detection using wavelet transform and matching pursuit algorithm, DCII,Prague (2010)
  9. Vareka, L., 2012, Matching Pursuit for P300-based Brain Computer Interfaces, Prague.
  10. Hyvärinen, A., Karhunen, J., and Oja, E., 2001, “Independent Component Analysis” Adaptive and Learning Systems for Signal Processing, Communications and Control. J. Wiley,.
  11. Rondik, T., 2010, “Použití matching pursuit s vlastním slovníkem funkcí pri detekci ERP v EEG signálu (Using matching pursuit algorithm with its own dictionary for ERP in EEG signal detection)”. Proceedings of the 10th Conference Kognice a umelý život (Cognition and Artificial Life), Opava: Slezská univerzita, pp. 329-332,.
  12. Ciniburk, J., 2011, “Hilbert-Huang transform for ERP detection“, Ph.D. Thesis, University of West Bohemia, Pilsen, Czech Republic.
  13. Stebetak, J., 2013, “Analytic Methods and Workflows for EEG/ERP Domain” State of the Art and Concept of Ph.D. Thesis, Pilsen.
  14. Littauer, R., Ram, K., Ludäscher, B., Michener, W. Koskela, R., 2012, “Trends in Use of Scientific Workflows: Insights from a PublicRepository and Recommendations for Best Practice“, The International Journal of Digital Curation, Volume 7, Issue 2.
Download


Paper Citation


in Harvard Style

Štebeták J. and Moucek R. (2014). Model of Syntactic Compatibility in Workflows for Electrophysiology . In Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2014) ISBN 978-989-758-010-9, pages 442-446. DOI: 10.5220/0004909304420446


in Bibtex Style

@conference{healthinf14,
author={Jan Štebeták and Roman Moucek},
title={Model of Syntactic Compatibility in Workflows for Electrophysiology},
booktitle={Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2014)},
year={2014},
pages={442-446},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004909304420446},
isbn={978-989-758-010-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2014)
TI - Model of Syntactic Compatibility in Workflows for Electrophysiology
SN - 978-989-758-010-9
AU - Štebeták J.
AU - Moucek R.
PY - 2014
SP - 442
EP - 446
DO - 10.5220/0004909304420446