Method of Measuring Subjective 3D Visual Fatigue: A Five-Factor Model

Li, Hyung-Chul O.; Seo, Jung Hun; Kham, Keetaek; Lee, Seung–Hyun

doi:10.1364/dh.2008.dwa5

Cited by 12 publications

(7 citation statements)

References 4 publications

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“…A considerable number of studies have been carried out to evaluate mental fatigue by various measures, including both subjective and objective evaluations. Subjective evaluation is mainly in the form of questionnaires, such as the Piper Fatigue Scale or the Epworth Sleepiness Scale [6,7]. However, subjective evaluation is easily affected by individual difference.…”

Section: Introductionmentioning

confidence: 99%

Electroencephalogram assessment of mental fatigue in visual search

Fan

Zhou

Liu

et al. 2015

BME

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Abstract. Mental fatigue is considered to be a contributing factor responsible for numerous road accidents and various medical conditions and the efficiency and performance could be impaired during fatigue. Hence, determining how to evaluate mental fatigue is very important. In the present study, ten subjects performed a long-term visual search task with electroencephalogram recorded, and self-assessment and reaction time (RT) were combined to verify if mental fatigue had been induced and were also used as confirmatory tests for the proposed measures. The changes in relative energy in four wavebands į ș Į and ȕ), four ratio formulas [(D + T)/E, D/E, (D + T)/(D + E), and T/E], and Shannon's entropy (SE) were compared and analyzed between the beginning and end of the task. The results showed that a significant increase occurred in alpha activity in the frontal, central, posterior temporal, parietal, and occipital lobes, and a dip occurred in the beta activity in the pre-frontal, inferior frontal, posterior temporal, and occipital lobes. The ratio formulas clearly increased in all of these brain regions except the temporal region, where only D/E changed obviously after finishing the 60-min visual search task. SE significantly increased in the posterior temporal, parietal, and occipital lobes. These results demonstrate some potential indicators for mental fatigue detection and evaluation, which can be applied in the future development of countermeasures to fatigue.

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Section: Introductionmentioning

confidence: 99%

Electroencephalogram assessment of mental fatigue in visual search

Fan

Zhou

Liu

et al. 2015

BME

View full text Add to dashboard Cite

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“…According to the BN theorem, 4 the conditional probability of node Z given the occurrence evidence can be obtained by combining Eqs. (2) and (3); and it can be written as in Ref.…”

Section: Calculating Bayesian Networkmentioning

confidence: 99%

“…Thus, many studies have investigated the visual fatigue of stereoscopy. [3][4][5][6] Figure 1(a) describes the main measurement schemes existing in 3-D visual fatigue research: the mean opinion score (MOS)-based scheme, the contact and contactless physiological feature (CLPF)-based scheme [such as electroencephalogram (EEG), electrocardiograph (ECG), and eye movement (EM) detection]. As noted by Kim and Cho,7 the MOS is to measure subjective 3-D visual fatigue using questionnaires that have high correlation with the subjective 3-D visual fatigue.…”

Section: Introductionmentioning

confidence: 99%

Visual fatigue measurement model in stereoscopy based on Bayesian network

2013

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Abstract. A stereoscopic visual fatigue measurement model based on Bayesian networks (BNs) is presented. Our approach focuses on the interdependencies between factors, such as contextual and environmental, and the phenomena of visual fatigue in stereoscopy. Specifically, the implementation of BN with the use of multiple features provides a systematic way to project and evaluate visual fatigue. Compared with another measurement model, our present BN-based scheme is more comprehensive. The test validation also indicates that our proposed model can be used as a reliable method for the visual fatigue inferring in stereoscopy.

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“…Early research methods classify 3DTV fatigue by subjective and objective evaluation. Subjective assessment methods, which is mainly conducted by means of questionnaires [7], as a means to perceptually evaluate visual fatigue are nowadays widely accepted and applied. However, these methods are high dependence on individuals' self-appraisal and its evaluation standard is not unified.…”

Section: Introductionmentioning

confidence: 99%

P‐34: Compare and Model Multi‐level Stereoscopic 3D Visual Fatigue Based on EEG

Kang

Wang

et al. 2017

Symp Digest of Tech Papers

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In this paper, we designed an experiment to observe changes for different fatigue level in human brain when watching random dot stereogram (RDS) using the method of EEG. The subjects were asked to watch 3D content for 30 minutes and the disparity of RDS changed every 10 seconds. During this watching task, subjects should rate their extent of fatigue during the experiment on the scale of one to five only when they felt worse or better. 30 channels electroencephalogram (EEG) signals were recorded through the experiment. Finally, the relationship between various fatigue levels and disparities which revealed by EEG signals were investigated. Our results show that the power of waveband, namely alpha increased with the fatigue level increasing from one to four during watching RDS, but decreased in level five. We have employed logistic regression to model fatigue level and achieved classification accuracy of 94.18%. Our research has important implications for the continuous monitoring of user's fatigue in the future.

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Method of Measuring Subjective 3D Visual Fatigue: A Five-Factor Model

Cited by 12 publications

References 4 publications

Electroencephalogram assessment of mental fatigue in visual search

Electroencephalogram assessment of mental fatigue in visual search

Visual fatigue measurement model in stereoscopy based on Bayesian network

P‐34: Compare and Model Multi‐level Stereoscopic 3D Visual Fatigue Based on EEG

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