Motor and Speech Imagery EEG Dataset

<b>Overview and Methodology</b>This dataset contains motor imagery (MI) and speech imagery (SI) electroencephalogram (EEG) data recorded from 5 healthy subjects with a mean age of 24.4 years. MI involves the subject imagining movements in their limbs, whereas SI involves the subject imagining speaking words in their mind (thought-speech). The data was recorded using the BioSemi ActiveTwo electroencephalogram (EEG) recording equipment, at a sampling frequency of 2.048kHz. 24 channels of EEG data from the 10-20 system are available in the dataset. Four classes of data were recorded for each of the MI and SI paradigms. In the case of MI, left-hand, right-hand, legs and tongue MI tasks were recorded, and in the case of SI, the words, ‘left’, ‘right’, ‘up’ and ‘down’ were recorded. Data for the idle state, when the subject is mentally relaxed and not executing any tasks, was also recorded.Forty trials were recorded for each of the classes. These trials were recorded over four runs, with two runs being used to record MI trials, and two to record SI trials. The runs were interleaved, meaning that the first and third runs were used to record MI, and the second and fourth runs were used to record SI trials. During each run, twenty trials for each class in the paradigm were recorded. These trials were randomly ordered. Note that during each run, twenty trials of the idle state were also recorded. This means that in this database there are actually eighty idle state trials, with forty being recorded during MI runs and forty being recorded during SI runs.Subjects were guided through the data recording runs by a graphical user interface which issued instructions to them. At the start of a run, subjects are given one minute to settle down before the cued trials began. During a trial, a fixation cross first appears on-screen, indicating to the subject to remain relaxed but aware that the next trial will soon begin. After 2s a cue appears on-screen for 1.25s, indicating the particular task the subject should execute. The subject starts executing the task as soon as they see the cue, and continue even when it has disappeared, until the fixation cross appears again. The cues consist of a left-facing arrow (for left-hand MI or ‘left’ SI), a right-facing arrow (for right-hand MI or ‘right’ SI), an upward facing (for tongue MI or ‘up’ SI) and a downward facing arrow (for legs MI or ‘down’ SI). Each trial lasted 4 seconds. Between each run, subjects were given a 3–5-minute break. The data was re-referenced using channel Cz and then mean-centered it. The data was also passed through an anti-aliasing filter and down-sampled to 1kHz before being stored in .mat files for the data repository. The anti-aliasing filter was a low-pass filter with a cutoff frequency of 500Hz, implemented using the <i>lowpass</i> function in MATLAB, which produces a 60dB attenuation above the cutoff and automatically compensates for filter-induced delays.<b>Files</b>The dataset consists of 10 MAT-files, named <i>X</i>_Subject_<i>Y</i>.mat, where <i>X</i> is the acronym denoting the brain imagery type, either MI for motor imagery data or SI for speech imagery data, and <i>Z</i> is the subject number. Each file contains the trials for each run in the structure variables ‘run_1’ and ‘run_2’. Within each run structure there are two variables:‘EEG_Data’, a matrix containing the EEG data formatted as: [number of trials x channels x data samples]. The number of data samples is 4000 since the length of each trial was 4s, sampled at 1kHz. The relationship between the EEG channels and the channel number in the second dimension of this matrix is documented in the table stored within the ‘ChannelLocations.mat’ file, which is included with the dataset;‘labels’, a vector indicating which cue was issued, with the following numbers being used to represent the different cues: 1 – Right, 2 – Left, 3 – Up, 4 – Down, 5 – Idle, 6 – Fixation Cross.<b>Acknowledgements </b>The authors acknowledge that data collection for this project was funded through the project: “Setting up of transdisciplinary research and knowledge exchange (TRAKE) complex at the University of Malta (ERDF.01.124)”, which is being co-financed through the European Union through the European Regional Development Fund 2014–2020. The data was recorded by the Centre for Biomedical Cybernetics at the University of Malta.

**概述与研究方法**
本数据集包含来自5名健康受试者的运动想象（motor imagery, MI）与言语想象（speech imagery, SI）脑电图（electroencephalogram, EEG）数据，受试者平均年龄为24.4岁。运动想象指受试者想象肢体动作，而言语想象则指受试者在脑海中想象说出词语（即内心言语）。
本数据集采用BioSemi ActiveTwo脑电图采集设备进行数据录制，采样频率为2.048kHz。数据集包含基于国际10-20系统的24通道脑电图数据。
运动想象与言语想象两种范式均各记录了4类数据。运动想象范式下记录了左手、右手、腿部及舌部运动想象任务，言语想象范式下则记录了想象说出"left"、"right"、"up"与"down"四个词语的任务。此外还录制了受试者处于精神放松且未执行任何任务的静息态数据。
每类数据均录制了40次试次。所有试次分为4轮完成，其中2轮用于录制运动想象试次，另外2轮用于录制言语想象试次。轮次采用交错模式，即第1、3轮录制运动想象试次，第2、4轮录制言语想象试次。
每一轮中，对应范式下的每一类任务均录制了20次试次，且试次顺序为随机排列。需注意，每一轮中还录制了20次静息态试次。因此本数据集实际包含80次静息态试次，其中运动想象轮次与言语想象轮次各录制40次。
受试者由图形用户界面引导完成各轮数据录制，该界面会向受试者发出任务指令。每轮录制开始前，受试者有1分钟的适应时间，随后进入带提示的试次阶段。试次开始时，屏幕首先呈现固定十字，提示受试者保持放松并知晓下一试次即将开始；2秒后，屏幕将显示任务提示1.25秒，告知受试者需执行的具体任务。受试者看到提示后即刻开始执行任务，即便提示消失仍需持续执行，直至固定十字再次出现。任务提示分别为：向左箭头（对应左手运动想象或"left"言语想象）、向右箭头（对应右手运动想象或"right"言语想象）、向上箭头（对应舌部运动想象或"up"言语想象）、向下箭头（对应腿部运动想象或"down"言语想象）。每一试次时长为4秒。每轮录制结束后，受试者可休息3至5分钟。
数据采用Cz通道进行重参考，并进行了均值中心化处理。随后数据经过抗混叠滤波，并下采样至1kHz，最终以.mat格式文件存储至数据集仓库。本研究采用的抗混叠滤波器为低通滤波器，截止频率为500Hz，通过MATLAB中的`lowpass`函数实现，该滤波器在截止频率以上可实现60dB的衰减，并自动补偿滤波引入的延迟。

**数据集文件**
本数据集包含10个MAT格式文件，文件命名格式为`X_Subject_Y.mat`，其中`X`为脑想象类型的缩写，可取`MI`（运动想象数据）或`SI`（言语想象数据），`Y`为受试者编号。每个文件均通过结构体变量`run_1`与`run_2`存储对应轮次的试次数据。每个轮次结构体包含两个变量：
1. `EEG_Data`：存储脑电图数据的矩阵，格式为`[试次数量 × 通道数量 × 数据样本数]`。由于每一试次时长为4秒且采样率为1kHz，因此每个试次对应4000个数据样本；脑电图通道与该矩阵第二维的通道编号的对应关系，可参见数据集中附带的`ChannelLocations.mat`文件中存储的表格；
2. `labels`：用于标识任务提示的向量，各数字对应的任务如下：1代表右向任务，2代表左向任务，3代表上向任务，4代表下向任务，5代表静息态，6代表固定十字阶段。

**致谢**
本项目的数据采集工作由马耳他大学"Setting up of transdisciplinary research and knowledge exchange (TRAKE) complex at the University of Malta (ERDF.01.124)"项目资助，该项目由欧盟通过2014-2020年欧洲区域发展基金联合出资。数据录制工作由马耳他大学生物医学控制论中心完成。