The correlation between visual fatigue and duration of viewing as assessed by brain monitoring

Abstract

Duration of viewing was considered as one of the most important factors of 3D visual fatigue. However, their relationship was not well studied. We proposed to use brain monitoring techniques to reveal more details about the variety of brain activity while watching three‐dimensional (3D) content. We investigated the spectral patterns in the electroencephalogram related to various duration of viewing and showed the power spectral density varied significantly along with the development of fatigue over occipital lobe, parietal lobe, and right frontal lobe. Moreover, we first described the trend of brain activity during 3D content viewing and revealed the location of significant components related to 3D visual fatigue. We believe that the absolute power describes more information and may be a better indicator of 3D visual fatigue assessment compared with relative power. We also first revealed the cortex location that is related to 3D visual fatigue. Our findings may help to define appropriate electroencephalogram features for online 3D visual fatigue detection while participants viewing 3D content.

68‐3: DeepFatigueNet: A Model for Automatic Visual Fatigue Assessment Based on Raw Single‐Channel EEG

“…Then ICA was conducted to remove the artifacts of EEG. Refer to Yue et al for detailed preprocessing procedure [2].…”

“…When watching three dimension content, a variety of unpleasant symptoms are associated such as headache, visual fatigue [1]. In particular, visual fatigue is quite common and usually occurs while watching 3D content and gets worse as the viewing time increases [2]. So visual fatigue assessment has received considerable attention and many methods have been proposed.…”

“…Hsu et al points out that EEG beta/alpha were the most effective power indexes for the visual fatigue assessment [6]. Recently many researchers started to use features extracted from EEG, such as power spectral density (PSD) [2]. Chen et al characterize the EEG signals using the gravity frequency and the power spectral entropy that served as indicators to evaluate the level of visual fatigue [7].…”

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.…”