Paper Info
Title
A High-Speed Brain Speller Using Steady-State Visual Evoked Potentials
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 1Hz interval) and four phases (0 degrees, 90 degrees, 180 degrees, and 270 degrees). 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.
Year
DOI
Venue
2014
10.1142/S0129065714500191
INTERNATIONAL JOURNAL OF NEURAL SYSTEMS
Keywords
Field
DocType
Steady-state visual evoked potential, brain-computer interface, mixed frequency and phase coding, speller
Training set,Computer monitor,Pattern recognition,Computer science,Brain–computer interface,Speech recognition,Refresh rate,Phase coding,Evoked potential,Artificial intelligence,Steady state,Electroencephalography
Journal
Volume
Issue
ISSN
24
6
0129-0657
Citations 
PageRank 
References 
51
2.74
20
Authors
5
Name
Order
Citations
PageRank
Masaki Nakanishi113121.62
Yijun Wang230846.68
Yu-Te Wang313517.37
Yasue Mitsukura416347.48
Tzyy-Ping Jung51410202.52