EEG driver drowsiness dataset

The dataset contains EEG signals from 11 subjects with labels of alert and drowsy. It can be opened with Matlab. We extracted the data for our own research purpose from another public dataset:<br>Cao, Z., et al., Multi-channel EEG recordings during a sustained-attention driving task. Scientific data, 2019. 6(1): p. 1-8.<br>If you find the dataset useful, please give credits to their works. <br>The details on how the data were extracted are described in our paper:<br>"Jian Cui, Zirui Lan, Yisi Liu, Ruilin Li, Fan Li, Olga Sourina, Wolfgang Müller-Wittig, A Compact and Interpretable Convolutional Neural Network for Cross-Subject Driver Drowsiness Detection from Single-Channel EEG, Methods, 2021, ISSN 1046-2023, https://doi.org/10.1016/j.ymeth.2021.04.017."<br><br>The codes of the paper above are accessible from:<br>https://github.com/cuijiancorbin/A-Compact-and-Interpretable-Convolutional-Neural-Network-for-Single-Channel-EEG<br><br>The data file contains 3 variables and they are EEGsample, substate and subindex.<br>"EEGsample" contains 2022 EEG samples of size 20x384 from 11 subjects. Each sample is a 3s EEG data with 128Hz from 30 EEG channels."subindex" is an array of 2022x1. It contains the subject indexes from 1-11 corresponding to each EEG sample."substate" is an array of 2022x1. It contains the labels of the samples. 0 corresponds to the alert state and 1 correspond to the drowsy state.<br>The unbalanced version of this dataset is accessible from:https://figshare.com/articles/dataset/EEG_driver_drowsiness_dataset_unbalanced_/16586957<br>

本数据集包含11名受试者的脑电（EEG）信号，标注有清醒（alert）与嗜睡（drowsy）两种状态，可通过Matlab软件打开。我们从另一公开数据集提取了适配本研究的相关数据：Cao Z等学者发表于《科学数据》（Scientific Data）2019年第6卷第1期第1-8页的论文《Multi-channel EEG recordings during a sustained-attention driving task》（持续注意力驾驶任务中的多通道脑电记录）。若您认为本数据集对研究有所帮助，请引用该原文献。
有关数据提取的详细说明，请参见本团队的研究论文：
"Jian Cui, Zirui Lan, Yisi Liu, Ruilin Li, Fan Li, Olga Sourina, Wolfgang Müller-Wittig. A Compact and Interpretable Convolutional Neural Network for Cross-Subject Driver Drowsiness Detection from Single-Channel EEG. Methods, 2021, ISSN 1046-2023, https://doi.org/10.1016/j.ymeth.2021.04.017."
该论文的配套代码可从以下仓库获取：
https://github.com/cuijiancorbin/A-Compact-and-Interpretable-Convolutional-Neural-Network-for-Single-Channel-EEG

本数据集文件包含3个变量，分别为EEGsample、substate与subindex。
EEGsample包含来自11名受试者的2022条脑电样本，每条样本维度为20×384，为时长3秒、采样率128Hz的30通道脑电数据。
subindex为2022×1的数组，存储每条脑电样本对应的受试者编号，取值范围为1至11。
substate为2022×1的数组，存储样本的状态标签：0代表清醒状态，1代表嗜睡状态。

本数据集的非平衡版本可从以下链接获取：
https://figshare.com/articles/dataset/EEG_driver_drowsiness_dataset_unbalanced_/16586957