EEG-EOG based Virtual Keyboard: Toward Hybrid Brain Computer Interface

  • Sarah M. Hosni
  • Howida A. Shedeed
  • Mai S. Mabrouk
  • Mohamed F. Tolba


The past twenty years have ignited a new spark in the research of Electroencephalogram (EEG), which was pursued to develop innovative Brain Computer Interfaces (BCIs) in order to help severely disabled people live a better life with a high degree of independence. Current BCIs are more theoretical than practical and are suffering from numerous challenges. New trends of research propose combining EEG to other simple and efficient bioelectric inputs such as Electro-oculography (EOG) resulting from eye movements, to produce more practical and robust Hybrid Brain Computer Interface systems (hBCI) or Brain/Neuronal Computer Interface (BNCI). Working towards this purpose, existing research in EOG based Human Computer Interaction (HCI) applications, must be organized and surveyed in order to develop a vision on the potential benefits of combining both input modalities and give rise to new designs that maximize these benefits. Our aim is to support and inspire the design of new hBCI systems based on both EEG and EOG signals, in doing so; first the current EOG based HCI systems were surveyed with a particular focus on EOG based systems for communication using virtual keyboard. Then, a survey of the current EEG-EOG virtual keyboard was performed highlighting the design protocols employed. We concluded with a discussion of the potential advantages of combining both systems with recommendations to give deep insight for future design issues for all EEG-EOG hBCI systems. Finally, a general architecture was proposed for a new EEG-EOG hBCI system. The proposed hybrid system completely alters the traditional view of the eye movement features present in EEG signal as artifacts that should be removed; instead EOG traces are extracted from EEG in our proposed hybrid architecture and are considered as an additional input modality sharing control according to the chosen design protocol.


Hybrid Brain-Computer Interface Brain/Neuronal Computer Interface Electroencephalogram Electrooculography Virtual Keyboard 


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Sarah M. Hosni
    • 1
  • Howida A. Shedeed
    • 1
  • Mai S. Mabrouk
    • 2
  • Mohamed F. Tolba
    • 1
  1. 1.Faculty of Computer and Information SciencesAin Shams UniversityCairoEgypt
  2. 2.Biomedical Engineering DepartmentMisr University for Science and TechnologyGizaEgypt

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