Abstract
In order to solve the problem of the arrangement of user function information on the human eye control interface, this paper adopts the analytic hierarchy process (AHP) to transform the layout constraint content of the human eye control interface into a hierarchical model structure. Then the quantified experimental data are used to solve the optimal solution of eye-controlled interface layout by using genetic algorithm. After this paper takes an eye-control interactive assembly process development platform as an experimental case, uses genetic algorithm to obtain the optimal solution of eye-control interface layout. In order to verify the effectiveness of this method, Tobii eye tracker was used in this paper to conduct eye movement experiments on subjects with mechanical engineering knowledge, the purpose of this method was to collect subjective feelings and eye movement information of subjects when using the eye-control interface. The subjects show higher cognitive efficiency when using the interface generated by genetic algorithm.
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References
Gantovnik, V.B., Tiwari, S., Fadel, G.M., et al.: Multi-objective vehicle layout optimization, American Institute of Aeronautics and Astronautics (2008)
Chen, R.: Research on human-machine interface layout optimization and evaluation methods for special vehicles, Dalian University of Technology (2019)
Ma, J.: Optimization of mobile terminal interactive interface layout based on genetic algorithm. Packaging Eng. 38(10), 133–136 (2017)
Fan, W., Yu, S., Wang, W., Qi, B., Zong, L.: Ant colony algorithm for human-machine layout optimization problem. Mech. Sci. Technol. 32(07), 955–962 (2013)
Deng, L., Wang, G., Yu, S.: Genetic ant colony algorithm for optimization of manipulator layout in driller control room. J. Eng. Des. 23(02), 143–151 (2016)
de Campos, T., Csurka, G., Perronnin, F.: Images as sets of locally weighted features. Comput. Vis. Image Underst. 116(1), 68–85 (2012). https://doi.org/10.1016/j.cviu.2011.07.011
Li, S.: Research on the design and evaluation method of eye-control interface, Southeast University (2018)
Zhu, X.: Research on eye control interface interaction design based on eye Potential, Southeast University (2019)
Gotz, D., Zhou, M.X.: Characterizing users’ visual analytic activity for insight provenance, Palgrave Macmillan (2009)
About Face 4 Interactive Design Essence. Electronic Industry Press, Cooper (2015)
Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, MA (1989)
Nielsen, J.: F-Shaped pattern of reading on the web: misunderstood, but still relevant (even on Mobile). https://www.nngroup.com/articles/f-shaped-pattern-reading-web-content/
Morrison, R.E.: Manipulation of stimulus onset delay in reading: Evidence for parallel programming of saccades. J. Exp. Psychol.: Hum. Percept. Perform. 10(5), 667–682 (1984). https://doi.org/10.1037/0096-1523.10.5.667
Ren, H., Tan, Y.: Analysis of vehicle-mounted touch screen fixation behavior based on eye movement experiment. Packag. Eng. 41(20), 97–101 (2020)
Lin, L.I., Guo, G.A.N.G., Xu, N.A.: User-perceived styling experience of smart vehicles: a method to combine eye tracking with semantic differences. IET Intel. Transp. Syst. 13(1), 72–78 (2019)
Han, S., Li, R.: Evaluation of product design effect of e-commerce websites based on kansei engineering. J. Shanghai Univ. Sci. Technol. 41(01), 97–102 (2019)
Acknowledgments
This work was partially supported by the Preliminary Research Program of Equipment Development Department of China under Grant No. 61409230103 and Grant No. 41423010402.
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Chen, S., Liu, X. (2021). Optimization of Eye Control Interactive Interface Based on Genetic Algorithm. In: Rebelo, F. (eds) Advances in Ergonomics in Design. AHFE 2021. Lecture Notes in Networks and Systems, vol 261. Springer, Cham. https://doi.org/10.1007/978-3-030-79760-7_88
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DOI: https://doi.org/10.1007/978-3-030-79760-7_88
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