Classification of Exoskeleton Conditions using Machine Learning on EEG Signals

Master thesis

  • Explore and implement machine learning methods, especially Transformer-based models and hybrid architectures, to classify exoskeleton assistance conditions (PAM pressure levels & subjects scores) using EEG signals.
  • Evaluate and optimize the classification performance of various models.
  • Investigate the interpretability of trained models to identify significant EEG features corresponding to different exoskeleton conditions.