Stimulus Design for Visual Evoked Potential Based Brain-Computer Interfaces

Autor: Haoyin Xu, Sheng-Hsiou Hsu, Masaki Nakanishi, Yufan Lin, Tzyy-Ping Jung, Gert Cauwenberghs
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 2545-2551 (2023)
Druh dokumentu: article
ISSN: 1558-0210
89377729
DOI: 10.1109/TNSRE.2023.3280081
Popis: Visual stimuli design plays an important role in brain-computer interfaces (BCIs) based on visual evoked potentials (VEPs). Variations in stimulus parameters have been shown to affect both decoding accuracy and subjective perception experience, implying the need for a trade-off in design. In this study, we comprehensively and systematically compared various combinations of amplitude contrast and spectral content parameters in the stimulus design to quantify their impact on decoding performance and subject comfort. Specifically, three parameters were investigated: 1) contrast level, 2) temporal pattern (periodic steady-state or pseudo-random code-modulated), and 3) frequency range. We collected electroencephalogram (EEG) data and subjective perception ratings from ten subjects and evaluated the decoding accuracy and subject comfort rating for different combinations of the stimulus parameters. Our results indicate that while high-frequency steady-state VEP (SSVEP) stimuli were rated the most comfortable, they also had the lowest decoding accuracy. Conversely, low-frequency SSVEP stimuli were rated the least comfortable but had the highest decoding accuracy. Standard and high-frequency M-sequence code-modulated VEPs (c-VEPs) produced intermediates between the two. We observed a consistent trade-off relationship between decoding accuracy and subjective comfort level across all parameters. Based on our findings, we offer c-VEP as a preferable stimulus for achieving reliable decoding accuracy while maintaining a reasonable level of comfortability.
Databáze: Directory of Open Access Journals
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