Open AccessFrequency- 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) , encoding (memory) , speech recognition , filter (signal processing) , signal (programming language) , pattern recognition (psychology) , brain–computer interface , 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.