MP: A steady-state visual evoked potential dataset based on multiple paradigms

• Published in: iScience Vol. 27; no. 11; p. 111030
• Main Authors: Zhao, Xi, Xu, Shencheng, Geng, Kexing, Zhou, Ting, Xu, Tianheng, Wang, Zhenyu, Feng, Shilun, Hu, Honglin
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 15.11.2024; Elsevier
• Subjects: computer science; Health sciences; Natural sciences; Natural sciences; computer science; Health sciences
• ISSN: 2589-0042; 2589-0042
• DOI: 10.1016/j.isci.2024.111030

In the field of steady-state visual evoked potential (SSVEP), stimulus paradigms are regularly arranged or mimic the style of a keyboard with the same size. However, stimulation paradigms have important effects on the performance of SSVEP systems, which correlate with the electroencephalogram (EEG) signal amplitude and recognition accuracy. This paper provides MP dataset that was acquired using a 12-target BCI speller. MP dataset contains 9-channel EEG signals from the occipital region of 24 subjects under 5 stimulation paradigms with different stimulus sizes and arrangements. Stimuli were encoded using joint frequency and phase modulation (JFPM) method. Subjects completed an offline prompted spelling task using a speller under 5 paradigms. Each experiment contains 8 blocks, and each block contains 12 trials. Designers can use this dataset to test the performance of algorithms considering “stimulus size” and “stimulus arrangement”. EEG data showed SSVEP features through amplitude-frequency analysis. FBCCA and TRCA confirmed its suitability. [Display omitted] •A steady-state visual evoked potential dataset based on multiple stimulus paradigms•Effects of stimulus size and arrangement on the SSVEP system performance•Algorithm performance test, FBCCA and TRCA as examples•Availability and improvement potential of dataset Health sciences; Natural sciences; Computer science