Multi-Brain Coding Expands the Instruction Set in SSVEP-Based Brain-Computer Interfaces

Previous studies have made great efforts to expand the instruction set in steady-state visual evoked potential (SSVEP)-based brain-computer interfaces. However, most systems are limited to single persons and expand the instruction set by increasing the flicker stimulation frequency range or via mult...

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Bibliographic Details
Published in:IEEE transactions on human-machine systems 2023-10, Vol.53 (5), p.1-9
Main Authors: Chu, Xingxing, Yu, Yang, Liu, Kaixuan, Ye, Zeqi, Hu, Dewen, Zeng, Ling-Li
Format: Article
Language:English
Subjects:
Brain-computer interface (BCIs)
Coding
Correlation
Electrodes
Electroencephalography
electroencephalography (EEG)
Encoding
Flicker
Frequency ranges
Human-computer interface
Information transfer
instruction set
Instruction sets
Instruction sets (computers)
Interference
multibrain coding
steady-state visual evoked potential (SSVEP)
Visualization
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Summary:Previous studies have made great efforts to expand the instruction set in steady-state visual evoked potential (SSVEP)-based brain-computer interfaces. However, most systems are limited to single persons and expand the instruction set by increasing the flicker stimulation frequency range or via multiple frequencies sequential coding or joint frequency/phase coding. In this article, we propose a multibrain coding SSVEP paradigm that encodes the SSVEP instructions generated by N independent subjects with M flicker stimuli, thus increasing the instruction set to M N instructions. A total of 40 subjects participated in online experiments in this article. The results show that there is no significant difference in accuracy ( p > 0.05, paired t test) between the multibrain and single-brain coding systems, while the information transfer rate (ITR) increases significantly ( p < 0.0001, paired t test), with the ITR increasing from 37.66 ± 3.60 bits/min for the single-brain coding system to 111.65 ± 10.84 bits/min for multibrain coding system when N = 3 and M = 5. In summary, the proposed multibrain coding paradigm exponentially increases the number of instructions without increasing the output instruction time, which is of great significance to the application and promotion of BCIs.
ISSN:2168-2291
2168-2305
DOI:10.1109/THMS.2023.3273538