With the development of 3D displays, user's eye fatigue has been an important issue when viewing these displays. There have been previous studies conducted on eye fatigue related to 3D display use, however, most of these have employed a limited number of modalities for measurements, such as electroencephalograms (EEGs), biomedical signals, and eye responses. In this paper, we propose a new assessment of eye fatigue related to 3D display use based on multimodal measurements. compared to previous works Our research is novel in the following four ways: first, to enhance the accuracy of assessment of eye fatigue, we measure EEG signals, eye blinking rate (BR), facial temperature (FT), and a subjective evaluation (SE) score before and after a user watches a 3D display; second, in order to accurately measure BR in a manner that is convenient for the user, we implement a remote gaze-tracking system using a high speed (mega-pixel) camera that measures eye blinks of both eyes; thirdly, changes in the FT are measured using a remote thermal camera, which can enhance the measurement of eye fatigue, and fourth, we perform various statistical analyses to evaluate the correlation between the EEG signal, eye BR, FT, and the SE score based on the T-test, correlation matrix, and effect size. Results show that the correlation of the SE with other data (FT, BR, and EEG) is the highest, while those of the FT, BR, and EEG with other data are second, third, and fourth highest, respectively.

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Abstract. Recently, it has become necessary to evaluate the performance of display devices in terms of human factors. To meet this requirement, several studies have been conducted to measure the eyestrain of users watching display devices. However, these studies were limited in that they did not consider precise human visual information. Therefore, a new eyestrain measurement method is proposed that uses a liquid crystal display (LCD) to measure a user's gaze direction and visual field of view. Our study is different in the following four ways. First, a user's gaze position is estimated using an eyeglass-type eye-image capturing device. Second, we propose a new eye foveation model based on a wavelet transform, considering the gaze position and the gaze detection error of a user. Third, three video adjustment factors-variance of hue (VH), edge, and motion information-are extracted from the displayed images in which the eye foveation models are applied. Fourth, the relationship between eyestrain and three video adjustment factors is investigated. Experimental results show that the decrement of the VH value in a display induces a decrease in eyestrain. In addition, increased edge and motion components induce a reduction in eyestrain.

Most previous research into emotion recognition used either a single modality or multiple modalities of physiological signal. However, the former method allows for limited enhancement of accuracy, and the latter has the disadvantages that its performance can be affected by head or body movements. Further, the latter causes inconvenience to the user due to the sensors attached to the body. Among various emotions, the accurate evaluation of fear is crucial in many applications, such as criminal psychology, intelligent surveillance systems and the objective evaluation of horror movies. Therefore, we propose a new method for evaluating fear based on nonintrusive measurements obtained using multiple sensors. Experimental results based on the t-test, the effect size and the sum of all of the correlation values with other modalities showed that facial temperature and subjective evaluation are more reliable than electroencephalogram (EEG) and eye blinking rate for the evaluation of fear.

We propose a new method for measuring the degree of eyestrain on 3D stereoscopic displays using a glasses-type of eye tracking device. Our study is novel in the following four ways: first, the circular area where a user's gaze position exists is defined based on the calculated gaze position and gaze estimation error. Within this circular area, the position where edge strength is maximized can be detected, and we determine this position as the gaze position that has a higher probability of being the correct one. Based on this gaze point, the eye foveation model is defined. Second, we quantitatively evaluate the correlation between the degree of eyestrain and the causal factors of visual fatigue, such as the degree of change of stereoscopic disparity (CSD), stereoscopic disparity (SD), frame cancellation effect (FCE), and edge component (EC) of the 3D stereoscopic display using the eye foveation model. Third, by comparing the eyestrain in conventional 3D video and experimental 3D sample video, we analyze the characteristics of eyestrain according to various factors and types of 3D video. Fourth, by comparing the eyestrain with or without the compensation of eye saccades movement in 3D video, we analyze the characteristics of eyestrain according to the types of eye movements in 3D video. Experimental results show that the degree of CSD causes more eyestrain than other factors.