Supporting data for "A multi-day and multi-band dataset for steady-state visual evoked potential-based brain-computer interface"

A steady-state visual-evoked potential (SSVEP) is a brain response to visual stimuli modulated at certain frequencies; it has been widely used in electroencephalography (EEG)-based braincomputer interface (BCI) research. However, there are few published SSVEP datasets for BCIs. In this study, we obtained a new SSVEP dataset based on measurements from 30 subjects, performed on two days; our dataset complements existing SSVEP datasets: i) multi-band SSVEP datasets are provided, and all three possible frequency bands (low, middle, and high) were used for SSVEP stimulation; ii) multi-day datasets are included; and iii) the EEG datasets include simultaneously obtained physiological measurements, such as respiration, electrocardiography, electromyography, head motion (accelerator), and body temperature.<br>To validate our dataset, we estimated the spectral powers and classification performance for the EEG (SSVEP) datasets, and created an example plot to visualize the physiological time-series data. Strong SSVEP responses were observed at stimulation frequencies, and the mean classification performance of the middle frequency band was significantly higher than the low- and high-frequency bands. Other physiological data also showed reasonable results.<br>Our multi-band, multi-day SSVEP datasets can be used to optimize stimulation frequencies because they enable simultaneous investigation of the characteristics of the SSVEPs evoked in each of the three frequency bands, and solve session-to-session (day-to-day) transfer problems by enabling investigation of the nonstationarity of SSVEPs measured on different days. Additionally, auxiliary physiological data can be used to explore the relationship between SSVEP characteristics and physiological conditions, providing useful information for optimizing experimental paradigms to achieve high performance.