Wirawan I Made Agus, Maneetham Dechrit, Darmawiguna I Gede Mahendra, Niyomphol Arnon, Sawetmethikul Pakornkiat, Crisnapati Padma Nyoman, Thwe Yamin, Agustini Ni Nyoman Mestri
Data Science Lab, Engineering and Vocational Faculty, Universitas Pendidikan Ganesha, Udayana Street, No. 11 Singaraja, Bali, 81116, Indonesia.
Mechatronics Engineering lab, Faculty of Technical Education, Rajamangala University of Technology Thanyabur, 39 หมู่ที่ 1 ถนน รังสิต - นครนายก Tambon Khlong Hok, Amphoe Khlong Luang, Chang Wat Pathum Thani 12110, Thailand.
Data Brief. 2024 Aug 14;56:110833. doi: 10.1016/j.dib.2024.110833. eCollection 2024 Oct.
The MIMED dataset is a dataset that provides raw electroencephalogram signal data for activities: raising the right-hand, lowering the right-hand, raising the left-hand, lowering the left-hand, standing, and sitting. In addition to raw data, this dataset provides feature data that undergoes a baseline reduction process. The baseline reduction process is a process to increase the value of EEG signal features. The feature values of the enhanced EEG signal can be easily recognized in the classification process. The device used is Emotiv Epoc X, which consists of 14 channels. Participants involved in this experiment were 30 students from the Bali region in Indonesia. Four recording scenarios were carried out on the first day and four further scenarios on the second day. Two datasets were obtained based on the recording scenario: the motor movement and image datasets. The duration of motor execution is 40 minutes, while motor imagery is 8 minutes for each scenario.
MIMED数据集是一个为以下活动提供原始脑电图信号数据的数据集:举起右手、放下右手、举起左手、放下左手、站立和坐下。除了原始数据外,该数据集还提供经过基线降低处理的特征数据。基线降低处理是一个增加脑电图信号特征值的过程。增强后的脑电图信号的特征值在分类过程中可以很容易地被识别。所使用的设备是Emotiv Epoc X,它由14个通道组成。参与该实验的是来自印度尼西亚巴厘岛地区的30名学生。第一天进行了四种记录场景,第二天又进行了四种场景。基于记录场景获得了两个数据集:运动运动和图像数据集。运动执行的持续时间为40分钟,而每个场景的运动想象为8分钟。