Performance analysis and optimal parameter selection for 300-based brain-computer interface

• Autorzy: Plechawska-Wójcik M. , Kaczorowska M.

Warianty tytułu

PL

Analiza doboru parametrów interfejsu mózg-komputer opartego na paradygmacie P300

• Języki publikacji: EN

Abstrakty

EN

The paper is dedicated to parameter adjustment and performance analysis of the brain-computer interface based on P300 paradigm. The aim of the paper is to present the construction of the brain-computer interface and the study of optimal parameter selection as well as the data analysis process. The BCI with different parameters was run and tested under the case study. The aim of the study was to find the most suitable parameter of P300-based BCI.

PL

Artykuł poświęcony jest dostosowaniu parametrów oraz analizie wydajności interfejsu mózg-komputer opartego na paradygmacie P300. Opisano konstrukcję interfejsu oraz proces doboru jego parametrów, a także cały proces analizy. Interfejs BCI z różnymi zestawami parametrów został uruchomiony i przetestowany. Przedstawiono studium przypadku poświęcone analizie danych oraz analizie wydajnościowej danych pochodzących z interfejsu BCI.

Słowa kluczowe

EN

EEG; P300 paradigm; Brain-Computer Interface

PL

EEG; paradygmat P300; interfejs mózg-komputer

• Wydawca: Wydawnictwo Politechniki Śląskiej
• Czasopismo: Studia Informatica
• Rocznik: 2016
• Tom: Vol. 37, nr 1
• Strony: 41--54
• Opis fizyczny: Bibliogr. 23 poz.

Twórcy

autor

Plechawska-Wójcik M.

• Lublin University of Technology, Institute of Computer Science, ul. Nadbystrzycka 36b, 20-618 Lublin, Poland

autor

Kaczorowska M.

• Lublin University of Technology, Institute of Computer Science, ul. Nadbystrzycka 36b, 20-618 Lublin, Poland

Bibliografia

• 1. An X., Kuang D., Guo X., Zhao Y., He L.: A deep learning method for classification of EEG data based on motor imagery. [in:] Huang D.-S., Han K., Gromiha M. (eds.): ICIC 2014, LNCS, Vol. 8590, Springer, Heidelberg 2014, p. 203÷210.
• 2. Beverina F., Palmas G., Silvoni S., Piccione F., Giove S.: User adaptive BCIs: SSVEP and P300 based interfaces. PsychNol. J., 2003.
• 3. Cho B., Lee J., Ku J., Jang D., Kim J., Kim I., Kim S.: Attention enhancement system using virtual reality and EEG biofeedback. Virtual Reality, Proceedings, IEEE, 2002, p. 156÷163.
• 4. Corralejo R., Nicolás-Alonso L.F., Álvarez D., Hornero R.: A P300-based brain-computer interface aimed at operating electronic devices at home for severely disabled people. Medical & biological engineering & computing, Vol. 52(10), 2014, p. 861÷872.
• 5. Cunnington R., Iansek R., Bradshaw J.L., Phillips, J.G.: Movement-related potentials associated with movement preparation and motor imagery. Experimental brain research, Vol. 111(3), 1996, p. 429÷436.
• 6. Donchin E., Spencer K.M., Wijesinghe R.: The mental prosthesis: assessing the speed of a P300-based brain-computer interface. Rehabilitation Engineering, IEEE Transactions on, Vol. 8(2), 2000, p. 174÷179.
• 7. Dornhege G.: Toward brain-computer interfacing. MIT Press, 2007.
• 8. Dornhege G., Blankertz B., Krauledat M., Losch F., Curio G., Muller K. R.: Combined optimization of spatial and temporal filters for improving brain-computer interfacing. Biomedical Engineering, IEEE Transactions on, Vol. 53(11), 2006, p. 2274÷2281.
• 9. Farwell L. A., Donchin E.: Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials. Electroencephalography and clinical Neurophysiology, Vol. 70(6), 1988, p. 510÷523.
• 10. Fazel-Rezai R., Allison B.Z., Guger C., Sellers E.W., Kleih S.C., Kübler A.: P300 brain computer interface: current challenges and emerging trends. Frontiers in Neuroengineering, Vol. 5(14), 2012, p. 14.
• 11. Gentiletti G.G., Gebhart J.G., Acevedo R.C., Yánez-Suárez O., Medina-Banuelos V.: Command of a simulated wheelchair on a virtual environment using a brain-computer interface. Irbm, Vol. 30(5), 2009, p. 218÷225.
• 12. Jin J., Sellers E.W., Zhou S., Zhang Y., Wang X., Cichocki A.: A P300 brain–computer interface based on a modification of the mismatch negativity paradigm. International journal of neural systems, Vol. 25(03), 2015.
• 13. Li Y., Nam C.S., Shadden B.B., Johnson S.L.: A P300-based brain-computer interface: Effects of interface type and screen size. Intl. Journal of Human-Computer Interaction, Vol. 27(1), 2010, p. 52÷68.
• Mak J.N., Wolpaw J.R.: Clinical applications of brain-computer interfaces: current state and future prospects. Biomedical Engineering, IEEE Reviews, Vol. 2, 2009, p. 187÷199.
• 14. Mano M., Zulkifli M., Mitsuki K., Genci C.: A new BMI Based Method for Wheelchair Robot Navigation. Proc. of the Intl. Conf. on Advances in Computer and Electronics, 2013, p. 6÷10.
• 15. Millán J., Rupp R., Müller-Putz G.R., Murray-Smith R., Giugliemma C.: Combining brain-computer interfaces and assistive technologies: state-of-the-art and challenges. Frontiers in neuroscience, Vol. 4, 2010, p. 1÷15.
• 16. Perrin X., Chavarriaga R., Colas F., Siegwart R., Millán J.D.R.: Brain-coupled interaction for semi-autonomous navigation of an assistive robot. Robotics and Autonomous Systems, Vol. 58(12), 2010, p. 1246÷1255.
• 17. Pfurtscheller G., Neuper C.: Motor imagery and direct brain-computer communication. Proceedings of the IEEE, Vol. 89 (7), 2001, p. 1123÷1134.
• 18. Szelenberger W.: Evoked potentials. (in Polish: Potencjały wywołane). Elmiko, Warszawa 2000.
• 19. Tong S., Thakor N.V.: Quantitative EEG analysis methods and clinical applications. Artech House, 2009.
• 20. Wolpaw J.R., Birbaumer N., Heetderks W.J., McFarland D.J., Peckham P.H., Schalk G., Vaughan T.: Brain-computer interface technology: a review of the first international meeting. IEEE transactions on rehabilitation engineering, Vol. 8(2), 2000, p. 164÷173.
• 21. Wolpaw J.R., Birbaumer N., McFarland D.J.: Brain-computer interfaces for communication and control. Clinical neurophysiology, Vol. 113(6), 2002, p. 767÷791.
• 22. Zielosko B.: Optimization of inhibitory decision rules relative to coverage – comparative studies. [in:] Kozielski S., Mrozek D. et al. (eds.): BDAS 2014, CCIS, Vol. 424, Springer, Heidelberg 2014, p. 267÷276.
• 23. Szelenberger W.: Evoked potentials. (in Polish: Potencjały wywołane). Elmiko, Warszawa 2000.

Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.