scholarly journals Assessing the Effect of the Refresh Rate of a Device on Various Motion Stimulation Frequencies Based on Steady-State Motion Visual Evoked Potentials

2022 ◽  
Vol 15 ◽  
Author(s):  
Chengcheng Han ◽  
Guanghua Xu ◽  
Xiaowei Zheng ◽  
Peiyuan Tian ◽  
Kai Zhang ◽  
...  
Keyword(s):  
Steady State ◽  
Visual Perception ◽  
Evoked Potentials ◽  
Motion Perception ◽  
Visual Evoked Potentials ◽  
Visual Stimulation ◽  
Correct Selection ◽  
Refresh Rate ◽  
Steady State Motion ◽  
Visual Evoked

The refresh rate is one of the important parameters of visual presentation devices, and assessing the effect of the refresh rate of a device on motion perception has always been an important direction in the field of visual research. This study examined the effect of the refresh rate of a device on the motion perception response at different stimulation frequencies and provided an objective visual electrophysiological assessment method for the correct selection of display parameters in a visual perception experiment. In this study, a flicker-free steady-state motion visual stimulation with continuous scanning frequency and different forms (sinusoidal or triangular) was presented on a low-latency LCD monitor at different refresh rates. Seventeen participants were asked to observe the visual stimulation without head movement or eye movement, and the effect of the refresh rate was assessed by analyzing the changes in the intensity of their visual evoked potentials. The results demonstrated that an increased refresh rate significantly improved the intensity of motion visual evoked potentials at stimulation frequency ranges of 7–28 Hz, and there was a significant interaction between the refresh rate and motion frequency. Furthermore, the increased refresh rate also had the potential to enhance the ability to perceive similar motion. Therefore, we recommended using a refresh rate of at least 120 Hz in motion visual perception experiments to ensure a better stimulation effect. If the motion frequency or velocity is high, a refresh rate of≥240 Hz is also recommended.

scholarly journals Generating Visual Flickers for Eliciting Robust Steady-State Visual Evoked Potentials at Flexible Frequencies Using Monitor Refresh Rate

PLoS ONE ◽  
2014 ◽  
Vol 9 (6) ◽  
pp. e99235 ◽  
Author(s):  
Masaki Nakanishi ◽  
Yijun Wang ◽  
Yu-Te Wang ◽  
Yasue Mitsukura ◽  
Tzyy-Ping Jung
Keyword(s):  
Steady State ◽  
Evoked Potentials ◽  
Visual Evoked Potentials ◽  
Refresh Rate ◽  
Visual Evoked

DECODING OF STEADY-STATE VISUAL EVOKED POTENTIALS BY FRACTAL ANALYSIS OF THE ELECTROENCEPHALOGRAPHIC (EEG) SIGNAL

Fractals ◽  
2018 ◽  
Vol 26 (06) ◽  
pp. 1850092 ◽  
Author(s):  
HAMIDREZA NAMAZI ◽  
TIRDAD SEIFI ALA ◽  
HOVAGIM BAKARDJIAN
Keyword(s):  
Steady State ◽  
Evoked Potentials ◽  
Visual Evoked Potentials ◽  
Fractal Structure ◽  
Visual Stimulation ◽  
Fractal Theory ◽  
Objective Assessment ◽  
Eeg Signal ◽  
Brain Response ◽  
Visual Evoked

Analysis of the brain response to different types of external stimuli has always been one of the major research areas in behavioral neuroscience. The electroencephalography (EEG) technique combined with different signal analysis approaches has been especially successful in revealing the detailed dynamic properties of the neural response to exogenous stimulation. In this analysis, we evaluated the nonlinear structure of the EEG signal using fractal theory in rest and visual stimulation (checkerboard reversal at 8, 14 and 28[Formula: see text]Hz). Our analysis showed a significant influence of stimulation on the fractal structure of EEG signal. On comparison between different conditions, 14-Hz steady-state visual evoked potentials (SSVEPs), previously shown to trigger an optimal brain response, exhibited the greatest influence on the complexity of the EEG signal. On the other hand, we observed the lowest complexity of EEG signal in the post-stimulation rest period. Statistical analysis confirmed significant differences in the fractal structure of the EEG signal between rest and different stimulation conditions. These findings demonstrate for the first time a direct relationship between the efficiency of brain processing and the complexity of the measured EEG signal, which could be employed for objective assessment and classification in various experimental paradigms.

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.

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