Brainwave Typing: Comparative Study of P300 and Motor Imagery for Typing Using Dry-Electrode EEG Devices

  • Hadeel Al-Negheimish
  • Lama Al-Andas
  • Latifah Al-Mofeez
  • Aljawharah Al-Abdullatif
  • Nuha Al-Khalifa
  • Areej Al-Wabil
Part of the Communications in Computer and Information Science book series (CCIS, volume 373)

Abstract

This paper presents the findings of an exploratory study comparing two of Brain-Computer Interface approaches, P300 and Motor Imagery, with EEG signals acquired using the Emotiv Neuroheadset. It was conducted to determine the most suitable approach for typing applications based on BCI. Results show that while selection accuracy is similar for both, with mean of 50%, the speed varies greatly, with the former approach being approximately 2 times more efficient in typing. Implications presented in this document are useful for BCI researchers who seek to build brain-controlled Augmentative and Alternative Communication technologies.

Keywords

BCI Brain Computer Interface P300 Motor Imagery Brain Machine Interface BMI Augmentative and Alternative Communication AAC EEG 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Hadeel Al-Negheimish
    • 1
  • Lama Al-Andas
    • 1
  • Latifah Al-Mofeez
    • 1
  • Aljawharah Al-Abdullatif
    • 1
  • Nuha Al-Khalifa
    • 1
  • Areej Al-Wabil
    • 2
  1. 1.Information Technology Dept., College of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia
  2. 2.Software Engineering Dept., College of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia

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