Frequency- and Phase Encoded SSVEP Using Spatiotemporal Beamforming.

Benjamin Wittevrongel,Marc M Van Hulle,Mikhail A Lebedev

doi:10.1371/journal.pone.0159988

Benjamin Wittevrongel, Marc M Van Hulle + Show 1 more

Open Access

https://doi.org/10.1371/journal.pone.0159988

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Journal: PloS one	Publication Date: Aug 3, 2016
Citations: 45	License type: CC BY 4.0

Affiliation: KU Leuven

Abstract

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.

Highlights

We introduce a new multivariate spatiotemporal filter, based on Linearly Constrained Minimum Variance (LCMV) beamforming, for discriminating between frequencyphase encoded targets more accurately, even when using short signal lengths than with Canonical Correlation Analysis (CCA), which is traditionally posited for this stimulation paradigm
The steady-state visual evoked potential (SSVEP) is a neurophysiological response to a periodic visual stimulus commonly gauged with electroencephalography (EEG) over the occipital cortex when using stimuli flickering at a frequency above 6 Hz but in practice lower than about 30 Hz
Further studies have led to several SSVEP detection techniques that are able to work with shorter signals such as Similarity of Background (SOB) [5], Minimum Energy Combination (MEC) [6], time-domain analysis [7, 8], and the widely adopted Canonical Correlation Analysis (CCA) [9,10,11,12] and its variants [13, 14]

Summary

Introduction

The steady-state visual evoked potential (SSVEP) is a neurophysiological response to a periodic visual stimulus commonly gauged with electroencephalography (EEG) over the occipital cortex when using stimuli flickering at a frequency above 6 Hz but in practice lower than about 30 Hz (due to the usual 60 Hz screen refresh rate and the EEG bandwidth). When considering a display with several disjoint, spatially delimited stimuli, each one flickering at a different frequency, the stimulus the subject is currently gazing at can be inferred from a spectral analysis of the recorded EEG signals. This is the principle behind the SSVEP-based brain-computer interface (BCI) where those stimuli become selectable targets in a subject interaction paradigm. A simple frequency analysis technique based on the (fast) Fourier transform [1, 2] typically requires long (i.e., 3 seconds or more [3, 4]) signals to accurately discriminate targets flickering at nearby frequencies. Further studies have led to several SSVEP detection techniques that are able to work with shorter signals such as Similarity of Background (SOB) [5], Minimum Energy Combination (MEC) [6], time-domain analysis [7, 8], and the widely adopted Canonical Correlation Analysis (CCA) [9,10,11,12] and its variants [13, 14]

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