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Using an EEG-Based Brain-Computer Interface for Virtual Cursor Movement with BCI2000
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EEG-EOG based Virtual Keyboard: Toward Hybrid Brain Computer Interface.

Sarah M Hosni1, Howida A Shedeed1, Mai S Mabrouk2

  • 1Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt.

Neuroinformatics
|October 29, 2018
PubMed
Summary
This summary is machine-generated.

This study explores hybrid Brain Computer Interfaces (hBCI) combining Electroencephalogram (EEG) and Electro-oculography (EOG) signals. By integrating EOG, researchers aim to create more practical and robust systems for individuals with disabilities.

Keywords:
Brain/Neuronal Computer InterfaceElectroencephalogramElectrooculographyHybrid Brain-Computer InterfaceVirtual Keyboard

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Human-Computer Interaction

Background:

  • Electroencephalogram (EEG) research has surged for Brain Computer Interfaces (BCIs) to aid disabled individuals.
  • Current BCIs face practical limitations, prompting research into hybrid systems.
  • Hybrid Brain Computer Interfaces (hBCI) integrate multiple bioelectric signals for improved functionality.

Purpose of the Study:

  • To survey existing Electro-oculography (EOG) based Human Computer Interaction (HCI) systems, particularly virtual keyboards.
  • To review current EEG-EOG virtual keyboard systems and their design protocols.
  • To propose a novel architecture for an EEG-EOG hBCI system that leverages EOG signals from EEG.

Main Methods:

  • Systematic review of EOG-based HCI applications for communication.
  • Analysis of existing EEG-EOG virtual keyboard designs and protocols.
  • Development of a new hybrid architecture integrating EEG and EOG signals.

Main Results:

  • Identified limitations in current BCIs and highlighted the potential of hybrid systems.
  • Surveyed EOG and EEG-EOG virtual keyboard systems, detailing design approaches.
  • Proposed a novel hBCI architecture that utilizes EOG signals extracted from EEG.

Conclusions:

  • Combining EEG and EOG signals offers significant advantages for hBCI development.
  • The proposed architecture redefines the use of eye movement artifacts in EEG.
  • Future hBCI designs can benefit from integrating EOG as a distinct input modality.