BCI-emotion-analysis-DREAMER

Emotion analysis on DREAMER dataset using various Deep Learning Techniques

• DREAMER_Preprocessing.ipynb

  • signal processing techniques and data prep as alpha, beta, theta, gamma for 12 segments of 5 segments each

• DREAMER_DL.ipynb

  • implemented of Paper: https://www.frontiersin.org/articles/10.3389/fnbot.2019.00037/full

• DREAMER_preprocess_without_DSP_(raw).ipynb

  • without signal processing,data prep for 640 segments for each of the 14 electrodes for each of the 12 segments of 5 seconds each

• DL_on_raw_data_without_DSP.ipynb

  • implementation of Paper:
    https://www.researchgate.net/profile/Salma_Alhagry/publication/320802497_Emotion_Recognition_based_on_EEG_using_LSTM_Recurrent_Neural_Network/links/5b39ff5a0f7e9b0df5e4cf26/Emotion-Recognition-based-on-EEG-using-LSTM-Recurrent-Neural-Network.pdf