Advertisement

Where Do We Look? An Eye-Tracking Study of Architectural Features in Building Design

  • Zhengbo Zou
  • Semiha Ergan
Conference paper

Abstract

Built environment plays an essential role in shaping the physical, physiological, and psychological human well-being given the fact that we spend more than ¾ of our times indoors. Various studies that investigated the impact of architecture on human health and well-being provided evidences on the influence of architecture with faster recovery in hospitals, better learning in schools, and more productivity in offices under variant configurations of architectural design features. This paper studied the impact of architectural design features (e.g., presence/size of windows, level of natural light and nature view) on human experience in buildings using a mobile eye-tracking solution to capture the subjects’ attention toward various design features. The subjects were exposed to two distinct virtual environments designed with polarizing features, and were instructed to conduct a series of navigational and informational tasks. The eye-tracking results showed that subjects were more focused and had higher attention level in the positively configured virtual environment. The result of the informational task, where the subjects were asked to recall an array of words they just saw in the virtual environment, showed that subjects performed better (i.e., recalled more words) and experienced positive recall (i.e., recalled more positive words) in the positively configured environment.

Keywords

Eye-Tracking Architectural design Virtual reality Human experience 

References

  1. 1.
    Aries, M.B., Veitch, J.A., Newsham, G.R.: Windows, view, and office characteristics predict physical and psychological discomfort. J. Environ. Psychol. 30(4), 533–541 (2010)CrossRefGoogle Scholar
  2. 2.
    Dravigne, A., Waliczek, T.M., Lineberger, R.D., Zajicek, J.M.: The effect of live plants and window views of green spaces on employee perceptions of job satisfaction. HortScience 43(1), 183–187 (2008)Google Scholar
  3. 3.
    Ehmke, C., Wilson, S.: Identifying web usability problems from eye-tracking data. In: Proceedings of the 21st British HCI Group Annual Conference on People and Computers, September 2007Google Scholar
  4. 4.
    Kaplan, S.: The restorative benefits of nature: toward an integrative framework. J. Environ. Psychol. 15(3), 169–182 (1995)CrossRefGoogle Scholar
  5. 5.
    Pan, B., Hembrooke, H.A., Gay, G.K., Granka, L.A., Feusner, M.K., Newman, J.K.: The determinants of web page viewing behavior: an eye-tracking study. In: Proceedings of the 2004 Symposium on Eye Tracking Research and Applications, pp. 147–154, March 2004Google Scholar
  6. 6.
    Hedge, A., Burge, P.S., Robertson, A.S., Wilson, S., Harris-Bass, J.: Work-related illness in offices: a proposed model of the “sick building syndrome”. Environ. Int. 15(1–6), 143–158 (1989)CrossRefGoogle Scholar
  7. 7.
    Radwan, A., Ergan, S.: Quantifying human experience in interior architectural spaces. Comput. Civ. Eng. 2017, 373–380 (2017)Google Scholar
  8. 8.
    Bratman, G.N., Hamilton, J.P., Daily, G.C.: The impacts of nature experience on human cognitive function and mental health. Ann. N. Y. Acad. Sci. 1249(1), 118–136 (2012)CrossRefGoogle Scholar
  9. 9.
    Franz, G., von der Heyde, M., Bülthoff, H.H.: Predicting experiential qualities of architecture by its spatial properties. In: Proceedings of 18th IAPS-Conference, pp. 1–10 (2004)Google Scholar
  10. 10.
    Dzeng, R.J., Lin, C.T., Fang, Y.C.: Using eye-tracker to compare search patterns between experienced and novice workers for site hazard identification. Saf. Sci. 82, 56–67 (2016)CrossRefGoogle Scholar
  11. 11.
    Hasanzadeh, S., Esmaeili, B., Dodd, M.D.: Measuring construction workers’ real-time situation awareness using mobile eye-tracking. In: Construction Research Congress 2016, pp. 2894–2904 (2016)Google Scholar
  12. 12.
    Navalpakkam, V., Arbib, M., Itti, L.: Attention and scene understanding. In: Neurobiology of Attention, pp. 197–203 (2005)CrossRefGoogle Scholar
  13. 13.
    Wedel, M., Pieters, R.: A review of eye-tracking research in marketing. Review of Marketing Research, pp. 123–147. Emerald Group Publishing Limited, Bingley (2008)CrossRefGoogle Scholar
  14. 14.
    Sarter, N.B., Mumaw, R.J., Wickens, C.D.: Pilots’ monitoring strategies and performance on automated flight decks: an empirical study combining behavioral and eye-tracking data. Hum. Factors 49(3), 347–357 (2007)CrossRefGoogle Scholar
  15. 15.
    Yousefi, M.V., Karan, E., Mohammadpour, A., Asadi, S.: Implementing eye tracking technology in the construction process (2015)Google Scholar
  16. 16.
    Du, J., Zou, Z., Shi, Y., Zhao, D.: Zero latency: real-time synchronization of BIM data in virtual reality for collaborative decision-making. Autom. Constr. 85, 51–64 (2018)CrossRefGoogle Scholar
  17. 17.
    Du, J., Shi, Y., Zou, Z., Zhao, D.: CoVR: cloud-based multiuser virtual reality headset system for project communication of remote users. J. Constr. Eng. Manage. 144(2), 04017109 (2017)CrossRefGoogle Scholar
  18. 18.
    Cutrell, E., Guan, Z.: What are you looking for: an eye-tracking study of information usage in web search. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 407–416, April 2007Google Scholar
  19. 19.
    Djamasbi, S., Siegel, M., Tullis, T.: Visual hierarchy and viewing behavior: an eye tracking study. In: International Conference on Human-Computer Interaction, pp. 331–340, July 2011CrossRefGoogle Scholar
  20. 20.
    Palinko, O., Kun, A.L., Shyrokov, A., Heeman, P. Estimating cognitive load using remote eye tracking in a driving simulator. In: Proceedings of the 2010 Symposium on Eye-Tracking Research and Applications, pp. 141–144, March 2010Google Scholar
  21. 21.
    Jaimes, A., Sebe, N.: Multimodal human–computer interaction: a survey. Comput. Vis. Image Underst. 108(1–2), 116–134 (2007)CrossRefGoogle Scholar
  22. 22.
    Jacob, R. J., & Karn, K. S. (2003). Eye tracking in human-computer interaction and usability research: Ready to deliver the promises. In The mind’s eye (pp. 573–605)CrossRefGoogle Scholar
  23. 23.
    Ehmke, C., Wilson, S.: Identifying web usability problems from eye-tracking data. In: Proceedings of the 21st British HCI Group Annual Conference on People and Computers, September 2007Google Scholar
  24. 24.
    Thiessen, A., Beukelman, D., Ullman, C., Longenecker, M.: Measurement of the visual attention patterns of people with aphasia: a preliminary investigation of two types of human engagement in photographic images. Augmentative Altern. Commun. 30(2), 120–129 (2014)CrossRefGoogle Scholar
  25. 25.
    Pan, B., Hembrooke, H.A., Gay, G.K., Granka, L.A., Feusner, M.K., Newman, J.K.: The determinants of web page viewing behavior: an eye-tracking study. In: Proceedings of the 2004 Symposium on Eye Tracking Research and Applications, pp. 147–154, March 2004Google Scholar
  26. 26.
    Kasireddy, V., Zou, Z., Akinci, B., Rosenberry, J.: Evaluation and comparison of different virtual reality environments towards supporting tasks done on a virtual construction site. In: Construction Research Congress, pp. 2371–2381 (2016)Google Scholar
  27. 27.
    McGinnies, E.: Emotionality and perceptual defense. Psychol. Rev. 56(5), 244 (1949)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.New York UniversityNew YorkUSA

Personalised recommendations