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Efficient dual-frequency SSVEP brain-computer interface system exploiting interocular visual resource disparities

delete2024-10-01
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PRE
AI
Y
Yike Sun
Y
Yuhan Li
Y
Yuzhen Chen
C
Chen Yang
J
Jingnan Sun
L
Liyan Liang
X
Xiaogang Chen *
高小榕 封面图
高小榕 (Xiaorong Gao) *
DOI:10.1016/j.eswa.2024.124144delete
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摘要

摘要

En 中文
Here, we present a novel dual-frequency steady-state visual evoked potential (SSVEP) brain-computer interface (BCI) system with a unique human-computer interaction (HCI) feature that utilizes distinct visual resource disparities between the two eyes. By leveraging subtle differences in electroencephalography (EEG) responses due to binocular disparity, our system effectively distinguishes identical frequency targets. We conducted a twophase validation: initial offline experiments confirmed EEG differences from interocular disparity, followed by global optimization to refine the SSVEP coding and spatial arrangement, allowing for 40 distinct targets within 20 frequency combinationes. A tailored binocular-task-related component analysis (bTRCA) algorithm was developed, achieving a maximum individual information transmission rate (ITR) of 338.32 bits/min offline and an average of 224.96 bits/min, with the online version reaching an average ITR of 234.13 bits/min. These results indicate that this system is a leading candidate for dual-frequency SSVEP BCIs, opening new prospects for HCI applications.
Keyword:
Brain-computer interface
Human computer interaction
SSVEP
EEG
Binocular vision

期刊

Expert Systems with Applications 封面图
Expert Systems with Applications
IF:
7.5
论文数:
3.0W
被引数:
10.2W

机构

T
tsinghua university
学者数:
11.9W
论文数: 10.0W
被引数: 137
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institute of biomedical engineering - cams
学者数:
317
论文数: 258
被引数: 0
C
T
Tiangong University
学者数:
1.2W
论文数: 7.7K
被引数: 1.1W
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