EEG Signal Classification Using Bi-LSTMs

Sep 1, 2023 min read

EEG Signal Classification Using Bi-LSTMs

Research Project | 2023

Designed and implemented a Bi-LSTM model for classifying EEG signals into distinct categories, achieving 91% accuracy.

Key Achievements

  • Processed and analyzed complex EEG data using MNE library
  • Implemented and compared multiple deep learning architectures (LSTM, Bi-LSTM, GRU, CNN-LSTM)
  • Wrote a research paper detailing methodologies and findings, focusing on feature extraction and sequence modeling

Technologies Used

  • Deep Learning
  • Bi-LSTM
  • TensorFlow
  • EEG Analysis