Paper Info
Title
Optimizing SSVEP-Based BCI System towards Practical High-Speed Spelling.
Abstract
The brain-computer interface (BCI) spellers based on steady-state visual evoked potentials (SSVEPs) have recently been widely investigated for their high information transfer rates (ITRs). This paper aims to improve the practicability of the SSVEP-BCIs for high-speed spelling. The system acquired the electroencephalogram (EEG) data from a self-developed dedicated EEG device and the stimulation was arranged as a keyboard. The task-related component analysis (TRCA) spatial filter was modified (mTRCA) for target classification and showed significantly higher performance compared with the original TRCA in the offline analysis. In the online system, the dynamic stopping (DS) strategy based on Bayesian posterior probability was utilized to realize alterable stimulating time. In addition, the temporal filtering process and the programs were optimized to facilitate the online DS operation. Notably, the online ITR reached 330.4 +/- 45.4 bits/min on average, which is significantly higher than that of fixed stopping (FS) strategy, and the peak value of 420.2 bits/min is the highest online spelling ITR with a SSVEP-BCI up to now. The proposed system with portable EEG acquisition, friendly interaction, and alterable time of command output provides more flexibility for SSVEP-based BCIs and is promising for practical high-speed spelling.
Year
DOI
Venue
2020
10.3390/s20154186
SENSORS
Keywords
DocType
Volume
brain-computer interface (BCI),steady-state visual evoked potential (SSVEP),practical,dynamic stopping (DS),modified task-related component analysis (mTRCA)
Journal
20
Issue
ISSN
Citations 
15
1424-8220
0
PageRank 
References 
Authors
0.34
0
7
Name
Order
Citations
PageRank
Jiabei Tang113.42
Minpeng Xu22717.17
Jin Han300.34
Miao Liu43211.69
Tingfei Dai500.34
Shanguang Chen600.34
Dong Ming710551.47