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Deep Learning for EEG Signals Analysis 🧠

Survey on state of the art Deep Learning (DL) methods for EEG signal analysis, done during the course Control of Autonomouos and Multi-Agent Systems at Sapienza University of Rome.

The report is organized as follows:

  • In section II, a theoretical introduction of EEG signal processing is provided.
  • In section III a summary which investigates the most common DL architectures in EEG-based applications is described.
  • Section IV explores a series of meaningful applications which make use of EEG signals.
  • In section V and VI EEG-based methodsfor epileptic seizure and Alzheimer’s disease detection tasks are deeply described, respectively.
  • Finally, section VII concerns the conclusions.