DocumentCode
1299865
Title
Frequency and Phase Mixed Coding in SSVEP-Based Brain--Computer Interface
Author
Jia, Chuan ; Gao, Xiaorong ; Hong, Bo ; Shangkai Gao
Author_Institution
Dept. of Biomed. Eng., Tsinghua Univ., Beijing, China
Volume
58
Issue
1
fYear
2011
Firstpage
200
Lastpage
206
Abstract
Frequency coding has been the traditional method implemented in steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCI). However, it is limited in terms of possible target numbers and, consequently, inappropriate for certain applications involving liquid crystal display (LCD) with multiple stimuli. This paper proposes an innovative coding method for SSVEP that, through a combination of frequency and phase, increases the number of targets, thus it improves the information transfer rate (ITR). With this method, a BCI system with 15 targets was developed using three stimulus frequencies, which is five times as many targets as the traditional method. Additionally, this paper defines the concept of reference phase, and decodes the EEG by means of Fourier coefficient projections onto the reference phase directions. Through the optimization of lead position, reference phase, data segment length, and harmonic components, the average ITR exceeded 60 bits/min in a simulated online test with ten subjects.
Keywords
brain-computer interfaces; electroencephalography; encoding; medical signal processing; visual evoked potentials; EEG; Fourier coefficient projections; LCD; SSVEP based BCI; SSVEP based brain-computer interface; SSVEP coding method; data segment length optimization; frequency-phase mixed coding; harmonic component optimization; information transfer rate; lead position optimization; liquid crystal display; multiple stimuli; reference phase directions; reference phase optimization; steady state visual evoked potential; Accuracy; Electroencephalography; Frequency measurement; Harmonic analysis; Lead; Materials; Phase measurement; Brain--computer interfaces (BCI); frequency coding; phase coding; steady-state visual evoked potential (SSVEP); Adult; Algorithms; Electroencephalography; Evoked Potentials, Visual; Fourier Analysis; Humans; Man-Machine Systems; Signal Processing, Computer-Assisted;
fLanguage
English
Journal_Title
Biomedical Engineering, IEEE Transactions on
Publisher
ieee
ISSN
0018-9294
Type
jour
DOI
10.1109/TBME.2010.2068571
Filename
5551180
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