A HIGH-SPEED BRAIN SPELLER USING STEADY-STATE VISUAL EVOKED POTENTIALS-Reference-Cited by-同舟云学术

A HIGH-SPEED BRAIN SPELLER USING STEADY-STATE VISUAL EVOKED POTENTIALS

Published:2014-07-31 Issue:06 Volume:24 Page:1450019
ISSN:0129-0657
Container-title:International Journal of Neural Systems
language:en
Short-container-title:Int. J. Neur. Syst.

Author:

NAKANISHI MASAKI¹,WANG YIJUN²,WANG YU-TE²,MITSUKURA YASUE¹,JUNG TZYY-PING³

Affiliation:

1. Graduate School of Science and Technology, Keio University, Yokohama, Kanagawa, 223-8522, Japan

2. Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California, San Diego, La Jolla, California, 92093, USA

3. Swartz Center for Computational Neuroscience, Institute for Neural Computation, Center for Advanced Neurological Engineering, Institute of Engineering in Medicine, University of California, San Diego, La Jolla, California, 92093, USA

Abstract

Implementing a complex spelling program using a steady-state visual evoked potential (SSVEP)-based brain–computer interface (BCI) remains a challenge due to difficulties in stimulus presentation and target identification. This study aims to explore the feasibility of mixed frequency and phase coding in building a high-speed SSVEP speller with a computer monitor. A frequency and phase approximation approach was developed to eliminate the limitation of the number of targets caused by the monitor refresh rate, resulting in a speller comprising 32 flickers specified by eight frequencies (8–15 Hz with a 1 Hz interval) and four phases (0°, 90°, 180°, and 270°). A multi-channel approach incorporating Canonical Correlation Analysis (CCA) and SSVEP training data was proposed for target identification. In a simulated online experiment, at a spelling rate of 40 characters per minute, the system obtained an averaged information transfer rate (ITR) of 166.91 bits/min across 13 subjects with a maximum individual ITR of 192.26 bits/min, the highest ITR ever reported in electroencephalogram (EEG)-based BCIs. The results of this study demonstrate great potential of a high-speed SSVEP-based BCI in real-life applications.

Publisher

World Scientific Pub Co Pte Lt

Subject

Computer Networks and Communications,General Medicine

Link

https://www.worldscientific.com/doi/pdf/10.1142/S0129065714500191

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