An open dataset for human SSVEPs in the frequency range of 1-60 Hz.
Meng GuWeihua PeiXiaorong GaoYijun WangPublished in: Scientific data (2024)
A steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) system relies on the photic driving response to effectively elicit characteristic electroencephalogram (EEG) signals. However, traditional visual stimuli mainly adopt high-contrast black-and-white flickering stimulations, which are easy to cause visual fatigue. This paper presents an SSVEP dataset acquired at a wide frequency range from 1 to 60 Hz with an interval of 1 Hz using flickering stimuli under two different modulation depths. This dataset contains 64-channel EEG data from 30 healthy subjects when they fixated on a single flickering stimulus. The stimulus was rendered on an LCD display with a refresh rate of 240 Hz. Initially, the dataset was rigorously validated through comprehensive data analysis to investigate SSVEP responses and user experiences. Subsequently, BCI performance was evaluated through offline simulations of frequency-coded and phase-coded BCI paradigms. This dataset provides comprehensive and high-quality data for studying and developing SSVEP-based BCI systems.
Keyphrases
- data analysis
- resting state
- functional connectivity
- electronic health record
- working memory
- endothelial cells
- magnetic resonance
- mental health
- deep learning
- magnetic resonance imaging
- risk assessment
- physical activity
- induced pluripotent stem cells
- machine learning
- brain injury
- high density
- climate change
- pluripotent stem cells