EEG dataset for motion sickness

EEG dataset for motion sicknessEEG_data/├─ README.txt├─ group_divide.txt├─ MISC_score.xlsx├─ MSSQ_score.xlsx├─ 25009/│ ├─ fast_driving/│ │ ├─ final/│ │ │ ├─ final1.edf│ │ │ ├─ final2.edf│ │ │ ├─ final3.edf│ │ │ ├─ final4.edf│ │ │ ├─ final5.edf│ │ │ └─ final6.edf│ │ ├─ data.bdf│ │ ├─ evt.bdf│ │ └─ recordInformation.json│ ├─ normal_driving/│ ├─ resting_after_fast_driving/│ │ ├─ data.bdf│ │ ├─ evt.bdf│ │ └─ recordInformation.json│ ├─ resting_after_normal_driving/│ ├─ resting_before_fast_driving/│ └─ resting_before_normal_driving/├─ 25010/├─ 25011/├─ ...└─ 25023/This dataset contains 32-channel EEG recordings from 15 healthy participants during real-world electric vehicle (EV) rides on a controlled L-shaped track, under normal driving (acceleration < 0.5 m/s²) and accelerated driving (acceleration ≈ 3 m/s²) with a cross-over design. Synchronous subjective motion sickness data (MISC scores) and motion sickness susceptibility (MSSQ-Short) are also included.Raw data comprise *.bdf EEG signals, *.evt.bdf event markers, and recordInformation.json metadata for resting-state (pre- and post-driving) and driving blocks. Preprocessed lap-segmented EEG data (6 laps per driving condition) are stored as final*.edf files in the final subfolder under each driving directory. The package also includes MISC/MSSQ scores, participant grouping, and a README file.This dataset supports research on EEG-based motion sickness assessment, cognitive state analysis, and BCI development for EV passenger comfort optimization.