TSception

This is the PyTorch implementation of TSception V2 using DEAP dataset in our paper:

Yi Ding, Neethu Robinson, Su Zhang, Qiuhao Zeng, Cuntai Guan, "TSception: Capturing Temporal Dynamics and Spatial Asymmetry from EEG for Emotion Recognition", accepted as a regular paper in IEEE Transactions on Affective Computing, preprint available at arXiv

It is an end-to-end multi-scale convolutional neural network to do classification from EEG signals. Previous version of TSception(IJCNN'20) can be found at website

Prepare the python virtual environment

Please go to the working directory by:

$ cd ./code

Please create an anaconda virtual environment by:

$ conda create --name TSception

Activate the virtual environment by:

$ conda activate TSception

Install the requirements by:

$ pip3 install -r requirements.txt

Run the code

Please download the DEAP dataset at website. Please place the "data_preprocessed_python" folder at the same location of the script (./code/).

To run the code for arousal dimension, please type the following command in terminal:

$ python3 main-DEAP.py --data-path './data_preprocessed_python/' --label-type 'A'

To run the experiments for valance please set the --label-type 'V'. The results will be saved into "result.txt" located at the same place as the script.

Reproduce the results

We highly suggest to run the code on a Ubuntu 18.04 or above machine using anaconda with the provided requirements to reproduce the results. You can also download the saved model at website to reproduce the results in the paper. After extracting the downloaded "save.zip", please place it at the same location of the scripts (./code/), run the code by:

$ python3 main-DEAP.py --data-path './data_preprocessed_python/' --label-type 'A' --reproduce True

Apply TSception to other datasets

If you are interested to apply TSception to other datasets, you can use generate_TS_channel_order() in utils.py to generate the suitable channel order for TSception, and reorder your data on channel dimension before feeding the data to TSception as what we did in reorder_channel() in prepare_data_DEAP.py

Acknowledgment

The author would like to thank Su Zhang, Quihao Zeng and Tushar Chouhan for checking the code

Cite

Please cite our paper if you use our code in your own work:

@ARTICLE{9762054,
  author={Ding, Yi and Robinson, Neethu and Zhang, Su and Zeng, Qiuhao and Guan, Cuntai},
  journal={IEEE Transactions on Affective Computing}, 
  title={TSception: Capturing Temporal Dynamics and Spatial Asymmetry from EEG for Emotion Recognition}, 
  year={2022},
  volume={},
  number={},
  pages={1-1},
  doi={10.1109/TAFFC.2022.3169001}}

mzqolive / TSception