Objective and quantitative assessment of visual acuity and contrast sensitivity based on steady-state motion visual evoked potentials using concentric-ring paradigm

2019 ◽  
Vol 139 (2) ◽  
pp. 123-136 ◽  
Author(s):  
Xiaowei Zheng ◽  
Guanghua Xu ◽  
Yunyun Wang ◽  
Chengcheng Han ◽  
Chenghang Du ◽  
...  
Keyword(s):  
Visual Acuity ◽  
Steady State ◽  
Evoked Potentials ◽  
Contrast Sensitivity ◽  
Visual Evoked Potentials ◽  
Quantitative Assessment ◽  
Concentric Ring ◽  
Steady State Motion ◽  
Visual Evoked

scholarly journals An Objective and Sensitive Visual Acuity Assessment Method for Preverbal and Infantile Children Based on Steady-State Motion Visual Evoked Potentials

2019 ◽  
Vol 19 (10) ◽  
pp. 116a
Author(s):  
Xiaowei Zheng ◽  
Guanghua Xu ◽  
Yunyun Wang ◽  
Sicong Zhang ◽  
Chenghang Du ◽  
...  
Keyword(s):  
Visual Acuity ◽  
Steady State ◽  
Evoked Potentials ◽  
Visual Evoked Potentials ◽  
Assessment Method ◽  
Steady State Motion ◽  
Visual Evoked

scholarly journals A Radial Zoom Motion-Based Paradigm for Steady State Motion Visual Evoked Potentials

2019 ◽  
Vol 13 ◽  
Author(s):  
Xiaoke Chai ◽  
Zhimin Zhang ◽  
Kai Guan ◽  
Guitong Liu ◽  
Haijun Niu
Keyword(s):  
Steady State ◽  
Evoked Potentials ◽  
Visual Evoked Potentials ◽  
Steady State Motion ◽  
Visual Evoked

scholarly journals Comparison of Modern Highly Interactive Flicker-Free Steady State Motion Visual Evoked Potentials for Practical Brain–Computer Interfaces

2020 ◽  
Vol 10 (10) ◽  
pp. 686
Author(s):  
Piotr Stawicki ◽  
Ivan Volosyak
Keyword(s):  
Steady State ◽  
Evoked Potentials ◽  
Visual Evoked Potentials ◽  
Information Transfer ◽  
Minimum Energy ◽  
Brain Computer Interfaces ◽  
Steady State Motion ◽  
Computer Interfaces ◽  
Information Transfer Rate ◽  
Visual Evoked

Motion-based visual evoked potentials (mVEP) is a new emerging trend in the field of steady-state visual evoked potentials (SSVEP)-based brain–computer interfaces (BCI). In this paper, we introduce different movement-based stimulus patterns (steady-state motion visual evoked potentials—SSMVEP), without employing the typical flickering. The tested movement patterns for the visual stimuli included a pendulum-like movement, a flipping illusion, a checkerboard pulsation, checkerboard inverse arc pulsations, and reverse arc rotations, all with a spelling task consisting of 18 trials. In an online experiment with nine participants, the movement-based BCI systems were evaluated with an online four-target BCI-speller, in which each letter may be selected in three steps (three trials). For classification, the minimum energy combination and a filter bank approach were used. The following frequencies were utilized: 7.06 Hz, 7.50 Hz, 8.00 Hz, and 8.57 Hz, reaching an average accuracy between 97.22% and 100% and an average information transfer rate (ITR) between 15.42 bits/min and 33.92 bits/min. All participants successfully used the SSMVEP-based speller with all types of stimulation pattern. The most successful SSMVEP stimulus was the SSMVEP1 (pendulum-like movement), with the average results reaching 100% accuracy and 33.92 bits/min for the ITR.

An attention‐driven videogame based on steady‐state motion visual evoked potentials

2021 ◽  
Author(s):  
Eduardo Perez‐Valero ◽  
Miguel Angel Lopez‐Gordo ◽  
Miguel A. Vaquero‐Blasco
Keyword(s):  
Steady State ◽  
Evoked Potentials ◽  
Visual Evoked Potentials ◽  
Steady State Motion ◽  
Visual Evoked
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