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Section BRAIN-COMPUTER INTERFACES, COGNITIVE NAVIGATION WORKSHOP AND NEUROENGINEERING
Rapid SSVEP Mindspelling Achieved with Beamforming
Benjamin Wittevrongel and Marc M. Van Hulle*
Laboratory for Neuro- and Psychophysiology, KU Leuven, Leuven, Belgium. * Presenting e-mail: marc@neuro.kuleuven.be
In brain-computer interfacing (BCI) based on steady-state visual evoked potentials (SSVEPs), the number of selectable targets is rather limited when each target has its own stimulation frequency. One way to remedy this is by combining frequency- and phase-coding. We introduce a new multivariate spatiotemporal filter, based on Linearly Constraint Minimum Variance (LCMV) beamforming (van Vliet et al., 2015), for discriminating between frequency-phase coded targets more accurately, even when using short signal lengths, than with (extended) Canonical Correlation Analysis (CCA) that is traditionally posited for this stimulation paradigm (Nakanishi et al., 2014). Our results show that with our new decoding scheme and spatiotemporal beamforming, accurate spelling can be achieved even in an online setting.
Acknowledgements
BW is supported by the Agency for Innovation by Science and Technology in Flanders (IWT). MMVH is supported by research grants received from the program Financing program (PFV/10/008), an interdisciplinary research project (IDO/12/007) and an industrial research fund project (IOF/HB/12/O21) of the KU Leuven, the Belgian Fund for Scientific Research Flanders (G088314N, G0A0914N), the Interuniversity Attraction Poles Programme Belgian Science Policy (IUAP P7/11), the Flemish Regional Ministry of Education (Belgium) (GOA 10/019), and the Hercules Foundation (AKUL 043).
References
1. M. van Vliet, N. Chumerin, S. De Deyne, J.R. Wiersema, W. Fias, G. Storms, and M.M. Van Hulle, "Single-trial erp component analysis using a spatio-temporal lcmv beamformer," Biomedical Engineering, IEEE Transactions on, vol. PP, no. 99, pp. 1-1, 2015.A. One, B. Two, and C. Three, Phys. Rev., 1972, 8(3), 555-566.
2. Nakanishi M., Wang Y., Wang Y.T., Mitsukura Y., Jung T.P. A high-speed brain speller using steady-state visual evoked potentials. International journal of neural systems. 2014;24(06):1450019.
The Control Human Phantom Fingers by Means of P300 Brain-Computer Interface for Neurorehabilitation
A.Ya. Kaplan1,2 *, D.D.Zhigulskaya1, D.A.Kirjanov1
1 Laboratory for Neurophysiology and Nero-Computer Interfaces, Faculty of Biology, Lomonosov Moscow State University, Moscow;
2 Lobachevsky National Research State University of Nizhny Novgorod, Nizhny Novgorod * Presenting e-mail: akaplan@mail.ru
Aims of the study
Motor imagery (MI) that triggers restructuring of the motor act plan in neuronal networks can be as effective for the restoration of impaired motor coordination as the actual implementation of the movement. However, despite the seeming simplicity of MI, whether it is effective in triggering cortical restructuring depends on mental effort intensity, stability and direction. The feedback loop can be provided by brain-computer interface (BCI) technologies based on eEg recording and mu-rhythm depression that allow for detecting mental representations of movements and transforming those events into commands for controlling the external objects. Using this skill during training sessions is an effective trigger for adaptive plasticity processes in the corresponding brain structures [1]. The weakness of this approach is the extremely low level of differentiation of mental movement representations in relation to their subsequent BCI-based identification.
Opera Med Physiol 2016 Vol. 2 (S1) 73
OM&P
Spatiotemporal
