Deep autoencoder for real-time EEG artifact removal and its Android smartphone implementation



This project (linked to the GitHub repository) developed a novel Deep Convolutional Autoencoder neural network for single-channel EEG (electroencephalogram) artifact removal in real-time, and the proposed model has also been implemented into an Android Smartphone App for mobile EEG and potential portable Brain-Computer Interfaces applications. The repository contains the pre-processed EEG data used, Python code and Android Studio project.
Date made available23 May 2023
PublisherUniversity of Manchester Figshare


  • autoencoder neural network
  • EEG artifact removal
  • smartphone app objectives
  • deep learning application on EEG
  • brain computer interface research
  • hardware acceleration

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