EEG feature model

The EEG data in normal state and motion sickness state were collected for nearly 3 minutes, and the EEG data contained 29 channels. According to the conclusions of previous research literature on motion sickness, VR motion sickness occurs in parietal lobe, occipital lobe, frontal lobe and temporal lobe. In order to avoid too many channels of EEG data and irrelevant channels reducing the effect of feature extraction, according to the relationship between brain regions and EEG signal acquisition channels, we select the corresponding EEG channels for processing, and we only select eight channels as follows: FP1, FP2, C3, C4, P3, P4, O1 and O2 channel.This dataset contains only classification tasks.For convenience, we rearranged the order and put the required frequency bands in the first eight channels.
SSQ.xlsx is the score table of each subject watching video, and eegcut.py is the data script for our model classification experiment, which is used to segment the whole EEG data and save it as a new. mat file.

本次采集了正常状态与晕动状态下的脑电（Electroencephalogram, EEG）数据，采集时长近3分钟，该脑电数据共包含29个通道。根据既往晕动症相关研究文献的结论，VR晕动症的发生与顶叶、枕叶、额叶及颞叶相关。为避免脑电数据通道过多、无关通道削弱特征提取效果，结合脑区与脑电信号采集通道的对应关系，我们筛选出对应脑电通道进行处理，最终选取以下8个通道：FP1、FP2、C3、C4、P3、P4、O1及O2通道。本数据集仅包含分类任务。为便于使用，我们重新调整了通道顺序，并将所需频段置于前8个通道中。
SSQ.xlsx为每位受试者观看视频后的评分表，eegcut.py则是用于本模型分类实验的数据脚本，可对完整脑电数据进行分段并保存为新的.mat文件。