The assessment of the visual discomfort caused by vergence‐accommodation conflicts based on EEG

Abstract

Stereoscopic displays have gained much popularity, while visual discomfort during watching stereoscopic displays is becoming an increasing concern. Vergence‐accommodation conflicts are one of factors inducing visual discomfort. How to properly assess the visual discomfort by vergence‐accommodation conflicts has been the focus of researchers. Compared with previous studies, this paper aims to address two problems: (1) designing an elaborate experiment to induce visual discomfort without interference of the long performance time and (2) objectively selecting fewer electrodes and extracting electroencephalogram (EEG) features much related to visual discomfort. The results show that, better than previous experimental paradigm, the designed experimental paradigm not only causes the visual discomfort properly but also shortens the performance time to less than an hour. Moreover, for the proposed model, the visual discomfort can be evaluated well based only on six selected electrodes or even better than previous models relying on much more electrodes.

Mixture Kernel Density Estimation and Remedied Correlation Matrix on the EEG-Based Copula Model for the Assessment of Visual Discomfort

“…The rounded average level from all participants is regarded as a label of the stimulus. Referring to the studies of other researchers and our previous research [5,[40][41][42], disparity images with disparities ranging from ±0.1 • to ±1 • are used as stimuli. The designed stimuli are presented by the LG D2343P display with 1920 × 1080 resolution.…”

Assessment of visual fatigue under LED tunable white light with different blue components

“…Electroencephalogram (EEG) is often used to monitor brain activity that reveals corresponding changes of the CNS. According to the literature, there are four main brain rhythms extracted from EEG signals, which closely relate to visual fatigue: delta, theta, alpha, and beta brain waves . Physiological signals such as skin temperature (SKT), oxygen saturation (SpO 2 ), and electrocardiogram (ECG) provide insight into ANS activities and can be considered the quantification of visual fatigue .…”

“…According to the literature, there are four main brain rhythms extracted from EEG signals, which closely relate to visual fatigue: delta, theta, alpha, and beta brain waves. [13][14][15] Physiological signals such as skin temperature (SKT), oxygen saturation (SpO 2 ), and electrocardiogram (ECG) provide insight into ANS activities and can be considered the quantification of visual fatigue. [16][17][18] Heart rate variability (HRV), a measure of the variation in time between each heartbeat, was extracted from ECG and testified as a good marker reflecting visual fatigue.…”