期刊
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
卷 67, 期 11, 页码 3073-3082出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TBME.2020.2975614
关键词
Visualization; Electroencephalography; Instruction sets; Steady-state; Frequency modulation; Neural engineering; Brain-computer interfaces; P300; steady-state visual evoked potential (SSVEP); high-speed; hybrid BCI; concurrent EEG features; large instruction set
资金
- National Key Research and Development Program of China [2017YFB1300302]
- National Natural Science Foundation of China [81630051, 81601565, 61671424]
- Tianjin Key Technology RD Program [16ZXHLSY00270]
- Young Elite Scientist Sponsorship Program by CAST [2018QNRC001]
- Strategic Priority Research Program of Chinese Academy of Science [XDB32040200]
Objective: Recently, electroencephalography (EEG)- based brain-computer interfaces (BCIs) have made tremendous progress in increasing communication speed. However, current BCI systems could only implement a small number of command codes, which hampers their applicability. Methods: This study developed a high-speed hybrid BCI system containing as many as 108 instructions, which were encoded by concurrent P300 and steadystate visual evoked potential (SSVEP) features and decoded by an ensemble task-related component analysis method. Notably, besides the frequency-phase-modulated SSVEP and time-modulated P300 features as contained in the traditional hybrid P300 and SSVEP features, this study found two new distinct EEG features for the concurrent P300 and SSVEP features, i.e., time-modulated SSVEP and frequency-phase- modulated P300. Ten subjects spelled in both offline and online cued-guided spelling experiments. Other ten subjects took part in online copy-spelling experiments. Results: Offline analyses demonstrate that the concurrent P300 and SSVEP features can provide adequate classification information to correctly select the target from 108 characters in 1.7 seconds. Online cued-guided spelling and copy-spelling tests further show that the proposed BCI system can reach an average information transfer rate (ITR) of 172.46 +/- 32.91 bits/min and 164.69 +/- 33.32 bits/min respectively, with a peak value of 238.41 bits/min (The demo video of online copy-spelling can be found at https:// www.youtube.com/watch?v=EW2Q08oHSBo). Conclusion: We expand a BCI instruction set to over 100 command codes with high-speed in an efficient manner, which significantly improves the degree of freedom of BCIs. Significance: This study hold promise for broadening the applications of BCI systems.
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