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Towards Reduced EEG Based Brain-Computer Interfacing for Mobile Robot Navigation

  • Mufti Mahmud
  • Amir Hussain
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8266)

Abstract

Rapid development in highly parallel neurophysiological recording techniques along with sophisticated signal processing tools allow direct communication with neuronal processes at different levels. One important level from the point of view of Rehabilitation Engineering & Assistive Technology is to use the Electroencephalogram (EEG) signals to interface with assistive devices. This type of brain-computer interface (BCI) aims to reestablish the broken loop of the persons with motor dysfunction(s). However, with the growing availability of of instruments and processes for implementation, the BCI is also getting more complex. In this work, the authors present a model for reduced complexity BCI based on EEG signals through a few simple processes for automated navigation and control of robotic device. It is demonstrated that not only with few number of electrodes, but also using simple features like evoked responses caused by Saccadic eye movement can be used in building robust BCI for rehabilitation which may revolutionize the development of assitive devices for the disabled.

Keywords

Brain-computer interface Electroencephalogram mobile robot robot navigation neuronal signal analysis 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Mufti Mahmud
    • 1
    • 2
    • 3
  • Amir Hussain
    • 3
  1. 1.Theoretical Neurobiology & Neuroengineering Lab, Department of Biomedical SciencesUniversity of AntwerpWilrijkBelgium
  2. 2.Institute of Information TechnologyJahangirnagar UniversitySavarBangladesh
  3. 3.Cognitive Signal Image and Control Processing Research (COSIPRA) Laboratory, School of Natural SciencesUniversity of StirlingStirlingUK

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