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Optimization of External Stimulus Features for Hybrid Visual Brain–Computer Interface

  • Deepak KapgateEmail author
  • Dhananjay Kalbande
  • Urmila Shrawankar
Conference paper
  • 30 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1087)

Abstract

To make brain–computer interface (BCI) systems effective, complex cortical processing algorithms get attention in past few years rather than optimizing different external stimulus properties. Work on finding optimal stimulus properties is still incomplete. The objective of this study is to find stimulus properties that evoke stronger cortical responses. Stimulus parameters like different size, color and frequency are analyzed for hybrid visual BCI based on steady-state visual-evoked potentials (SSVEP) and event-related potentials (P300) (Hybrid SSVEP + P300 BCI). Study revealed that stimulus with frequency—15 Hz, color—red and size (in angular degree) \(7.96^{\circ }\) evoked stronger cortical potentials and higher signal to noise ratio (SNR). Further, green and yellow colors are found comfortable as compared to red which generates more fatigue. Maximum cortical mean SSVEP amplitude calculated is 5.1 \(\upmu \)V and for P300 is 4.9 \(\upmu \)V.

Keywords

Hybrid brain–computer interface Stimulus features Visual-evoked potential’s amplitude Optimization 

Notes

Acknowledgements

Authors thankful to Director G. H. Raisoni College of Engineering, Nagpur University for valuable support.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Deepak Kapgate
    • 1
    Email author
  • Dhananjay Kalbande
    • 1
  • Urmila Shrawankar
    • 1
  1. 1.Department of Information TechnologyG. H. Raisoni College of EngineeringNagpurIndia

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