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

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...

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Bibliographic Details
Published in:	International journal of neural systems 2014-09, Vol.24 (6), p.1450019-1-1450019-18
Main Authors:	NAKANISHI, MASAKI, WANG, YIJUN, WANG, YU-TE, MITSUKURA, YASUE, JUNG, TZYY-PING
Format:	Article
Language:	eng
Subjects:	Algorithms Animals Applied sciences Biological and medical sciences Biophysics Brain - physiology Brain-Computer Interfaces Communication Computer science control theory systems Computer Simulation Computer systems and distributed systems. User interface Correlation analysis Data processing. List processing. Character string processing Electrodiagnosis. Electric activity recording Electroencephalography Evoked potentials Evoked Potentials, Visual - physiology Exact sciences and technology Eye and associated structures. Visual pathways and centers. Vision Feasibility studies Fundamental and applied biological sciences. Psychology High speed Human-computer interface Humans Information transfer Investigative techniques, diagnostic techniques (general aspects) Medical sciences Memory organisation. Data processing Monitors Nervous system Photic Stimulation Reaction Time - physiology Software Spelling Steady state Target recognition Time Factors Vertebrates: nervous system and sense organs Visual
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Summary:	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.
ISSN:	0129-0657 1793-6462