MIMED
Description
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 increases 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 Epoch 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.
Files
Steps to reproduce
There are ten steps to collect the data: a. Determination of Participants b. Arrangement of EEG signal recording infrastructure c. Recording scenarios d. Data analysis e. Segmentation f. Normalization g. Decomposition h. Feature extraction i. Baseline reduction j. Classification
Institutions
Categories
Funding
the Institute for Research and Community Service at the Universitas Pendidikan Ganesha
1175/UN48.16/LT/2023