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A Fuzzy-Based Fusion Method of Multimodal Sensor-Based Measurements for the Quantitative Evaluation of Eye Fatigue on 3D Displays.

Bang JW, Choi JS, Heo H, Park KR - Sensors (Basel) (2015)

Bottom Line: This research is novel for the following four reasons: first, for the evaluation of eye fatigue with high credibility on 3D displays, a fuzzy-based fusion method (FBFM) is proposed based on the multimodalities of EEG signals, eye blinking rate (BR), facial temperature (FT), and subjective evaluation (SE); second, to measure a more accurate variation of eye fatigue (before and after watching a 3D display), we obtain the quality scores of EEG signals, eye BR, FT and SE; third, for combining the values of the four modalities we obtain the optimal weights of the EEG signals BR, FT and SE using a fuzzy system based on quality scores; fourth, the quantitative level of the variation of eye fatigue is finally obtained using the weighted sum of the values measured by the four modalities.Experimental results confirm that the effectiveness of the proposed FBFM is greater than other conventional multimodal measurements.Moreover, the credibility of the variations of the eye fatigue using the FBFM before and after watching the 3D display is proven using a t-test and descriptive statistical analysis using effect size.

View Article: PubMed Central - PubMed

Affiliation: Division of Electronics and Electrical Engineering, Dongguk University, 26 Pil-dong 3-ga, Jung-gu, Seoul 100-715, Korea. bangjw@dgu.edu.

ABSTRACT
With the rapid increase of 3-dimensional (3D) content, considerable research related to the 3D human factor has been undertaken for quantitatively evaluating visual discomfort, including eye fatigue and dizziness, caused by viewing 3D content. Various modalities such as electroencephalograms (EEGs), biomedical signals, and eye responses have been investigated. However, the majority of the previous research has analyzed each modality separately to measure user eye fatigue. This cannot guarantee the credibility of the resulting eye fatigue evaluations. Therefore, we propose a new method for quantitatively evaluating eye fatigue related to 3D content by combining multimodal measurements. This research is novel for the following four reasons: first, for the evaluation of eye fatigue with high credibility on 3D displays, a fuzzy-based fusion method (FBFM) is proposed based on the multimodalities of EEG signals, eye blinking rate (BR), facial temperature (FT), and subjective evaluation (SE); second, to measure a more accurate variation of eye fatigue (before and after watching a 3D display), we obtain the quality scores of EEG signals, eye BR, FT and SE; third, for combining the values of the four modalities we obtain the optimal weights of the EEG signals BR, FT and SE using a fuzzy system based on quality scores; fourth, the quantitative level of the variation of eye fatigue is finally obtained using the weighted sum of the values measured by the four modalities. Experimental results confirm that the effectiveness of the proposed FBFM is greater than other conventional multimodal measurements. Moreover, the credibility of the variations of the eye fatigue using the FBFM before and after watching the 3D display is proven using a t-test and descriptive statistical analysis using effect size.

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Flow chart of proposed method.
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sensors-15-10825-f001: Flow chart of proposed method.

Mentions: Figure 1 presents the proposed method for FBFM for multiple modalities considering the quality values of the modalities. To measure the SE before watching the 3D content, the subject’s condition is verified with a questionnaire regarding watching 3D content. To compare the eye BR before and after watching 3D content, the normal eye BR of the subjects is measured for one minute before watching the 3D content. Then, we proceed with the phase of measuring the subject’s EEG data and FT for five minutes with eyes closed to minimize any external visual stimuli that could influence the EEG data. Next, the subjects watch the 3D content for 30 min. The eye BR is measured for the final one minute of the 3D content watching period to obtain an accurate comparison of the variation of the eye BR before and after watching the 3D content. After watching 3D content, to compare the variations of the EEG data and FT before and after watching 3D content, the subject’s EEG data and FT are measured again for five minutes with eyes closed. Finally, the subject’s condition is again verified using an SE questionnaire.


A Fuzzy-Based Fusion Method of Multimodal Sensor-Based Measurements for the Quantitative Evaluation of Eye Fatigue on 3D Displays.

Bang JW, Choi JS, Heo H, Park KR - Sensors (Basel) (2015)

Flow chart of proposed method.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4481891&req=5

sensors-15-10825-f001: Flow chart of proposed method.
Mentions: Figure 1 presents the proposed method for FBFM for multiple modalities considering the quality values of the modalities. To measure the SE before watching the 3D content, the subject’s condition is verified with a questionnaire regarding watching 3D content. To compare the eye BR before and after watching 3D content, the normal eye BR of the subjects is measured for one minute before watching the 3D content. Then, we proceed with the phase of measuring the subject’s EEG data and FT for five minutes with eyes closed to minimize any external visual stimuli that could influence the EEG data. Next, the subjects watch the 3D content for 30 min. The eye BR is measured for the final one minute of the 3D content watching period to obtain an accurate comparison of the variation of the eye BR before and after watching the 3D content. After watching 3D content, to compare the variations of the EEG data and FT before and after watching 3D content, the subject’s EEG data and FT are measured again for five minutes with eyes closed. Finally, the subject’s condition is again verified using an SE questionnaire.

Bottom Line: This research is novel for the following four reasons: first, for the evaluation of eye fatigue with high credibility on 3D displays, a fuzzy-based fusion method (FBFM) is proposed based on the multimodalities of EEG signals, eye blinking rate (BR), facial temperature (FT), and subjective evaluation (SE); second, to measure a more accurate variation of eye fatigue (before and after watching a 3D display), we obtain the quality scores of EEG signals, eye BR, FT and SE; third, for combining the values of the four modalities we obtain the optimal weights of the EEG signals BR, FT and SE using a fuzzy system based on quality scores; fourth, the quantitative level of the variation of eye fatigue is finally obtained using the weighted sum of the values measured by the four modalities.Experimental results confirm that the effectiveness of the proposed FBFM is greater than other conventional multimodal measurements.Moreover, the credibility of the variations of the eye fatigue using the FBFM before and after watching the 3D display is proven using a t-test and descriptive statistical analysis using effect size.

View Article: PubMed Central - PubMed

Affiliation: Division of Electronics and Electrical Engineering, Dongguk University, 26 Pil-dong 3-ga, Jung-gu, Seoul 100-715, Korea. bangjw@dgu.edu.

ABSTRACT
With the rapid increase of 3-dimensional (3D) content, considerable research related to the 3D human factor has been undertaken for quantitatively evaluating visual discomfort, including eye fatigue and dizziness, caused by viewing 3D content. Various modalities such as electroencephalograms (EEGs), biomedical signals, and eye responses have been investigated. However, the majority of the previous research has analyzed each modality separately to measure user eye fatigue. This cannot guarantee the credibility of the resulting eye fatigue evaluations. Therefore, we propose a new method for quantitatively evaluating eye fatigue related to 3D content by combining multimodal measurements. This research is novel for the following four reasons: first, for the evaluation of eye fatigue with high credibility on 3D displays, a fuzzy-based fusion method (FBFM) is proposed based on the multimodalities of EEG signals, eye blinking rate (BR), facial temperature (FT), and subjective evaluation (SE); second, to measure a more accurate variation of eye fatigue (before and after watching a 3D display), we obtain the quality scores of EEG signals, eye BR, FT and SE; third, for combining the values of the four modalities we obtain the optimal weights of the EEG signals BR, FT and SE using a fuzzy system based on quality scores; fourth, the quantitative level of the variation of eye fatigue is finally obtained using the weighted sum of the values measured by the four modalities. Experimental results confirm that the effectiveness of the proposed FBFM is greater than other conventional multimodal measurements. Moreover, the credibility of the variations of the eye fatigue using the FBFM before and after watching the 3D display is proven using a t-test and descriptive statistical analysis using effect size.

Show MeSH
Related in: MedlinePlus