Human computer interaction feedback based-on data visualization using MVAR and NN

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In the situation of pandemic with people being ill, contagious, or suffering from long-term effects, touchless human computer interfaces, and especially brain computer interfaces (BCI), could provide humans with safe communication technologies as well as user-centric systems for rehabilitation. Hence, this work studies at first the representation of electroencephalogram (EEG) signals in a data space which is appropriate for an efficient data processing and a user-friendly interpretation. Then, we propose 3D data visualizations mapping the human brain activity into that data space. The developed representations have been successfully tested within a BCI framework through 3D data visualizations the user can see and interact with in real time.
Original languageEnglish
Title of host publicationIEEE International Symposium on Applied Computational Intelligence and Informatics
Place of PublicationPiscataway, NJ
Number of pages6
Publication statusPublished - 30 Jun 2021


  • human computer interaction
  • brain computer interface
  • assistive technology
  • multi-variate signal processing
  • data processing
  • data visualization
  • machine learning
  • neural networks
  • reinforcement learning
  • 3D visual feedback
  • user-center graphical interface


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