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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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Example of obtaining the output value of the input membership function for SE, (a) F1 of SE; (b) F2 of SE.
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sensors-15-10825-f011: Example of obtaining the output value of the input membership function for SE, (a) F1 of SE; (b) F2 of SE.

Mentions: In this section, we explain the procedure for obtaining the output value of the input membership function. For example, three outputs (0 (L), 0.857142 (M), 0.142858 (H)) are obtained based on the input membership function displayed in Figure 11a assuming that one input F1SE is 0.571429. Three outputs (0.111112 (L), 0.888888 (M), 0 (H)) are obtained indicated in Figure 11b assuming that one input F2SE is 0.444444. With these outputs, nine combination pairs of output using F1SE and F2SE are obtained as presented in Table 4.


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)

Example of obtaining the output value of the input membership function for SE, (a) F1 of SE; (b) F2 of SE.
© Copyright Policy
Related In: Results  -  Collection

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

sensors-15-10825-f011: Example of obtaining the output value of the input membership function for SE, (a) F1 of SE; (b) F2 of SE.
Mentions: In this section, we explain the procedure for obtaining the output value of the input membership function. For example, three outputs (0 (L), 0.857142 (M), 0.142858 (H)) are obtained based on the input membership function displayed in Figure 11a assuming that one input F1SE is 0.571429. Three outputs (0.111112 (L), 0.888888 (M), 0 (H)) are obtained indicated in Figure 11b assuming that one input F2SE is 0.444444. With these outputs, nine combination pairs of output using F1SE and F2SE are obtained as presented in Table 4.

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