Brain Computer Interface Switch Based on Quasi-Steady-State Visual Evoked Potentials

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Gaze detection by Steady State Visually Evoked Potentials (SSVEPs) has been a very popular topic for neural rehabilitation and especially Brain Computer Interface (BCI) research. Visual Evoked Potentials (VEPs) provide reliable robust electrophysiological signals for communication and control applications. In this research Quasi-Steady-State VEPs (QSS-VEPs) and their correspondence in this kind of dual target gaze detection application has been demonstrated. Methods for a dual target BCI switch has been developed. Since QSS-VEPs enable acquisition of both SSVEP and transient VEP (TR-VEP) signals at the same time, exploitation of them in a two target BCI application was reasonable. Stimulations of low and high rate pattern-reversal VEPs were utilized in gaze detection. QSS-VEPs and transient VEPs were compared. Receiver Operating Characteristics (ROC) curves were calculated in order to assess performance. We have found that it is possible to achieve high accuracy or ROC area values with QSS-VEPs. The best performance was obtained at 50 reversal per second (rps) stimulation rate. At this rate deconvolved transient signals, which normally has low performance compared to QSS-VEPs, resulted in comparable Information Transfer Rates (ITR) with QSS-VEPs.

Original languageEnglish (US)
Title of host publication9th International IEEE EMBS Conference on Neural Engineering, NER 2019
PublisherIEEE Computer Society
Pages1175-1178
Number of pages4
ISBN (Electronic)9781538679210
DOIs
StatePublished - May 16 2019
Event9th International IEEE EMBS Conference on Neural Engineering, NER 2019 - San Francisco, United States
Duration: Mar 20 2019Mar 23 2019

Publication series

NameInternational IEEE/EMBS Conference on Neural Engineering, NER
Volume2019-March
ISSN (Print)1948-3546
ISSN (Electronic)1948-3554

Conference

Conference9th International IEEE EMBS Conference on Neural Engineering, NER 2019
CountryUnited States
CitySan Francisco
Period3/20/193/23/19

Keywords

  • BCI Switch
  • Brain-computer Interfaces (BCI)
  • Quasi-Steady-State VEP (QSS-VEP)
  • Steady-State VEP (SSVEP)
  • Transient VEP
  • Visual Evoked Potential

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering

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  • Cite this

    Kaya, I., Bohorquez, J. E., & Ozdamar, O. (2019). Brain Computer Interface Switch Based on Quasi-Steady-State Visual Evoked Potentials. In 9th International IEEE EMBS Conference on Neural Engineering, NER 2019 (pp. 1175-1178). [8716894] (International IEEE/EMBS Conference on Neural Engineering, NER; Vol. 2019-March). IEEE Computer Society. https://doi.org/10.1109/NER.2019.8716894