Frequency- and Phase Encoded SSVEP Using Spatiotemporal Beamforming | Zendy

Benjamin Wittevrongel | Zendy; Marc M. Van Hulle | Zendy

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Frequency- and Phase Encoded SSVEP Using Spatiotemporal Beamforming

Author(s) -

Benjamin Wittevrongel,

Marc M. Van Hulle

Publication year - 2016

Publication title -

plos one

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.99

H-Index - 332

ISSN - 1932-6203

DOI - 10.1371/journal.pone.0159988

Subject(s) - beamforming , computer science , canonical correlation , phase (matter) , filter (signal processing) , encoding (memory) , speech recognition , pattern recognition (psychology) , brain–computer interface , signal (programming language) , artificial intelligence , electroencephalography , algorithm , neuroscience , physics , computer vision , biology , telecommunications , quantum mechanics , programming language

In brain-computer interfaces (BCIs) 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- with phase encoding. We introduce a new multivariate spatiotemporal filter, based on Linearly Constrained Minimum Variance (LCMV) beamforming, for discriminating between frequency-phase encoded targets more accurately, even when using short signal lengths than with (extended) Canonical Correlation Analysis (CCA), which is traditionally posited for this stimulation paradigm.

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