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A Tri-Hybrid Brain-Computer Interface for Neuro-Information Systems

In: Information Systems and Neuroscience

Author

Listed:
  • Daniel Godfrey

    (Dalhousie University)

  • Chantel Findlay

    (Dalhousie University)

  • Dinesh Mulchandani

    (Dalhousie University)

  • Ravishankar Subramanilyer

    (Dalhousie University)

  • Colin Conrad

    (Dalhousie University)

  • Aaron Newman

    (Dalhousie University)

Abstract

Brain-computer interfaces (BCIs) are computerized systems that convert brain activity into control commands to operate software or external devices. Though promising, BCIs currently have limited practicality and usership due to poor signal classification and large training data requirements. The present study aims to overcome both challenges by combining three brain signals. This paradigm could improve existing BCI technical efficacy, and extrapolate to applications where hands-free visual interfaces could equip users with communication and information resources that improve work processes.

Suggested Citation

  • Daniel Godfrey & Chantel Findlay & Dinesh Mulchandani & Ravishankar Subramanilyer & Colin Conrad & Aaron Newman, 2020. "A Tri-Hybrid Brain-Computer Interface for Neuro-Information Systems," Lecture Notes in Information Systems and Organization, in: Fred D. Davis & René Riedl & Jan vom Brocke & Pierre-Majorique Léger & Adriane B. Randolph & Thomas (ed.), Information Systems and Neuroscience, pages 291-297, Springer.
    • Handle: RePEc:spr:lnichp:978-3-030-60073-0_34
    DOI: 10.1007/978-3-030-60073-0_34
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