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

Ibrahim Kaya; Jorge E. Bohorquez; Ozcan Ozdamar

doi:10.1109/NER.2019.8716894

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

Ibrahim Kaya, Jorge E. Bohorquez, Ozcan Ozdamar

Biomedical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English (US)
Title of host publication	9th International IEEE EMBS Conference on Neural Engineering, NER 2019
Publisher	IEEE Computer Society
Pages	1175-1178
Number of pages	4
ISBN (Electronic)	9781538679210
DOIs	https://doi.org/10.1109/NER.2019.8716894
State	Published - May 16 2019
Event	9th International IEEE EMBS Conference on Neural Engineering, NER 2019 - San Francisco, United States Duration: Mar 20 2019 → Mar 23 2019

Publication series

Name	International IEEE/EMBS Conference on Neural Engineering, NER
Volume	2019-March
ISSN (Print)	1948-3546
ISSN (Electronic)	1948-3554

Conference

Conference	9th International IEEE EMBS Conference on Neural Engineering, NER 2019
Country	United States
City	San Francisco
Period	3/20/19 → 3/23/19

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

Access to Document

10.1109/NER.2019.8716894

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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

Brain Computer Interface Switch Based on Quasi-Steady-State Visual Evoked Potentials. / Kaya, Ibrahim; Bohorquez, Jorge E.; Ozdamar, Ozcan.

9th International IEEE EMBS Conference on Neural Engineering, NER 2019. IEEE Computer Society, 2019. p. 1175-1178 8716894 (International IEEE/EMBS Conference on Neural Engineering, NER; Vol. 2019-March).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kaya, I, Bohorquez, JE & 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., 8716894, International IEEE/EMBS Conference on Neural Engineering, NER, vol. 2019-March, IEEE Computer Society, pp. 1175-1178, 9th International IEEE EMBS Conference on Neural Engineering, NER 2019, San Francisco, United States, 3/20/19. https://doi.org/10.1109/NER.2019.8716894

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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.",

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