Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
Evoked potentials are one of the brain's electrical activity types. They appear on the human scalp as a result of a registration of an external stimulus (e.g. an appearance or a change of a sound, a flash of light or an image). Generally, they are used in medical diagnosis, but they also may be used in brain-computer interfaces. In this chapter a laboratory set for the acquisition and analysis of evoked potentials is described. The main part of this set is a photostimulator consisting of sixteen LEDs and the ATmega 328 microcontroller. The software created by the authors allows for: connection between EEG device, stimulator and computer, input stimulus control, output signal filtering and its classification. The presented set may support a process of brain-computer interface design.
Rocznik
Tom
Strony
102--110
Opis fizyczny
Bibliogr. 15 poz., rys.
Twórcy
autor
- Poznań University of Technology 60-965 Poznań, ul. Piotrowo 3a
autor
- Poznań University of Technology 60-965 Poznań, ul. Piotrowo 3a
Bibliografia
- [1] Bakardjian, H., Tanaka, T., & Cichocki, A. (2010), Optimization of SSVEP brain responses with application to eight-command Brain–Computer Interface, Neuroscience Letters, 469(1), 34-38.
- [2] Bin, G., Gao, X., Yan, Z., Hong, B., & Gao, S. (2009), An online multi-channel SSVEP-based brain–computer interface using a canonical correlation analysis method, Journal of Neural Engineering, 6(4), 046002.
- [3] Birbaumer, N., Breaking the silence: brain–computer interfaces (BCI) for communication and motor control, Psychophysiology, 43(6), 2006.
- [4] Cecotti, H. (2010), A self-paced and calibration-less SSVEP-based brain–computer interface speller, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 18(2), 127-133.
- [5] Graimann, B., Allison, B., Pfurtscheller, G., Brain–computer interfaces: A gentle introduction. In Brain-Computer Interfaces, Springer Berlin Heidelberg, 2010.
- [6] Hakvoort, G., Reuderink, B., & Obbink, M. (2011), Comparison of PSDA and CCA detection methods in a SSVEP-based BCI-system, Proc. of the 18th Int. Conference on Neural Information Processing, Shanghai, China, November 13-17, 2011.
- [7] Lin, Z., Zhang, C., Wu, W., & Gao, X. (2006), Frequency recognition based on canonical correlation analysis for SSVEP-based BCIs, IEEE Transactions on Biomedical Engineering, 53(12), 2610-2614.
- [8] Martinez, P., Bakardjian, H., & Cichocki, A. (2008), Multi-command real-time brain machine interface using SSVEP: feasibility study for occipital and forehead sensor locations, In: Advances in Cognitive Neurodynamics ICCN 2007, Springer Netherlands pp. 783-786.
- [9] Maggi, L., Parini, S., Piccini, L., Panfili, G., & Andreoni, G. (2006), A four command BCI system based on the SSVEP protocol, Proc. of the 28th Annual International Conference of the IEEE in Engineering in Medicine and Biology Society, 1264-1267.
- [10] Martinez, P., Bakardjian, H., & Cichocki, A. (2007), Fully online multicommand brain-computer interface with visual neurofeedback using SSVEP paradigm, Computational Intelligence and Neuroscience, 2007, 13-13.
- [11] Van Drongelen, W., Signal processing for neuroscientists: an introduction to the analysis of physiological signals, Academic Press 2006.
- [12] Vialatte, F. B., Maurice, M., Dauwels, J., Cichocki, A., Steady-state visually evoked potentials: focus on essential paradigms and future perspectives, Progress in Neurobiology, 90(4), 2010.
- [13] Wolpaw, J. R., Birbaumer, N., McFarland, D. J., Pfurtscheller, G., Vaughan, T. M., Brain–computer interfaces for communication and control, Clinical Neurophysiology, 113(6), 2002.
- [14] Wolpaw, J. R., Ramoser, H., McFarland, D. J., & Pfurtscheller, G. (1998), EEG-based communication: improved accuracy by response verification, IEEE Transactions on Rehabilitation Engineering, 6(3), 326-333.
- [15] http://www.bbci.de/competition/iii/
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-4bb4a4fc-f94d-4df5-b2f7-01568ee5c43b