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Toward New Modalities in Vep-Based Bci Applications Using Dynamical Stimuli: Introducing Quasi-Periodic and Chaotic Vep-Based Bci Publisher



Shirzhiyan Z1, 2, 3 ; Keihani A2, 3 ; Farahi M2, 3 ; Shamsi E2 ; Golmohammadi M3 ; Mahnam A4 ; Haidari MR5 ; Jafari AH2, 3
Authors
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Authors Affiliations
  1. 1. Computational Neuroscience, Institute of Medical Technology, Brandenburg University of Technology Cottbus-Senftenberg, Cottbus, Germany
  2. 2. Department of Medical Physics Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
  3. 3. Research Center for Biomedical Technologies and Robotics (RCBTR), Tehran University of Medical Sciences, Tehran, Iran
  4. 4. Department of Biomedical Engineering, Faculty of Engineering, University of Isfahan, Isfahan, Iran
  5. 5. Section of Neuroscience, Department of Neurology, Faculty of Medicine, Baqiyatallah University of Medical Sciences, Tehran, Iran

Source: Frontiers in Neuroscience Published:2020


Abstract

Visual evoked potentials (VEPs) to periodic stimuli are commonly used in brain computer interfaces for their favorable properties such as high target identification accuracy, less training time, and low surrounding target interference. Conventional periodic stimuli can lead to subjective visual fatigue due to continuous and high contrast stimulation. In this study, we compared quasi-periodic and chaotic complex stimuli to common periodic stimuli for use with VEP-based brain computer interfaces (BCIs). Canonical correlation analysis (CCA) and coherence methods were used to evaluate the performance of the three stimulus groups. Subjective fatigue caused by the presented stimuli was evaluated by the Visual Analogue Scale (VAS). Using CCA with the M2 template approach, target identification accuracy was highest for the chaotic stimuli (M = 86.8, SE = 1.8) compared to the quasi-periodic (M = 78.1, SE = 2.6, p = 0.008) and periodic (M = 64.3, SE = 1.9, p = 0.0001) stimulus groups. The evaluation of fatigue rates revealed that the chaotic stimuli caused less fatigue compared to the quasi-periodic (p = 0.001) and periodic (p = 0.0001) stimulus groups. In addition, the quasi-periodic stimuli led to lower fatigue rates compared to the periodic stimuli (p = 0.011). We conclude that the target identification results were better for the chaotic group compared to the other two stimulus groups with CCA. In addition, the chaotic stimuli led to a less subjective visual fatigue compared to the periodic and quasi-periodic stimuli and can be suitable for designing new comfortable VEP-based BCIs. © Copyright © 2020 Shirzhiyan, Keihani, Farahi, Shamsi, GolMohammadi, Mahnam, Haidari and Jafari.
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