Acquisition and processing of Motor Imagery and Motor Execution Dataset (MIMED) for six movement activities

Abstract

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.

Keywords

• Motor imagery
• Motor execution
• Electroencephalogram
• Baseline reduction