FOIT: Fast Online Instance Transfer for Improved EEG Emotion Recognition

Code of paper FOIT: Fast Online Instance Transfer for Improved EEG Emotion Recognition

Datasets

The dataset files (SEED and SEED-IV) can be downloaded from the BCMI official website

To facilitate data retrieval, we divided both datasets into three folders according to the sessions, the file structure of the datasets should be like:

eeg_feature_smooth/
    1/
    2/
    3/
ExtractedFeatures/
    1/
    2/
    3/

Usage

Run python FOIT_ultra.py, and the results will be printed in the terminal.

Contributing

Issues are welcome. For major changes, please open an issue first to discuss what you would like to change.

Citation

If you find our work useful for your research, please consider citing our paper as:

@inproceedings{li2020foit,
  title={FOIT: Fast Online Instance Transfer for Improved EEG Emotion Recognition},
  author={Li, Jinpeng and Chen, Hao and Cai, Ting},
  booktitle={2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)},
  pages={2618--2625},
  year={2020},
  organization={IEEE}
}

License