Skip to main content
SpringerLink
Log in

Monitoring Attention of Crane Operators During Load Oscillations Using Gaze Entropy Measures

  • Conference paper
  • First Online:
HCI International 2021 - Late Breaking Papers: Cognition, Inclusion, Learning, and Culture (HCII 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 13096))

Included in the following conference series:

Abstract

This study evaluates mobile crane operator’s gaze pattern to discriminate effects of skills and performance. Scalar variables define the degree of disorder and distribution of gaze fixations between discrete Area-of-Interests (AOI). A field experiment was carried out to measure gaze behavior of operators from two skill categories. Gaze fixations on discrete Area-of-Interests (AOIs) are analyzed using the first order Markov transition matrix. Matrix elements are mapped to scalar variables such as gaze entropy for statistical analysis. The conventional mapping method is revised to accommodate sparse transition matrix resulting from large number of AOIs. The results suggest the revised scalar variables can be interpreted like those for non-sparse transition matrices. More importantly, the findings suggest statistically significant correlations between operators’ gaze patterns and performance. Therefore, operator attention is well-defined by these variables which are promising for development of work support or guidance system to facilitate crane operation.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Maczynski, A., Wojciech, S.: Dynamics of a mobile crane and optimization of the slewing motion of its upper structure. Nonlinear Dyn. 32, 259–290 (2003)

    Article  Google Scholar 

  2. Ouyang, H., Zhang, G., Mei, L., Deng, X., Wang, D.: Load vibration reduction in rotary cranes using robust two-degree-of-freedom control approach. Adv. Mech. Eng. 8, 1–11 (2016)

    Article  Google Scholar 

  3. Vaughan, J., Smith, A., Kang, S.J., Singhose, W.: Predictive graphical user interface elements to improve crane operator performance. IEEE Trans. Syst. Man Cybern. A 41, 323–330 (2011)

    Article  Google Scholar 

  4. Singhose, W., Kim, D., Kenison, M.: Input shaping control of double-pendulum bridge crane oscillations. J. Dyn. Syst. Trans. ASME, 130 (2008). 034504-1-7

    Google Scholar 

  5. Vazquez, C., Fridman, L., Collado, J., Castillo, I.: Second-order sliding mode control of a perturbed-crane. J. Dyn. Syst. Trans. ASME 137 (2015). 081010-1-7

    Google Scholar 

  6. 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, 347–357 (2007)

    Article  Google Scholar 

  7. Allsop, J., Gray, R.: Flying under pressure: effects of anxiety on attention and gaze behavior in aviation. J. Appl. Res. Memory Cogn. 3, 63–71 (2014)

    Article  Google Scholar 

  8. DiStasi, L.L., et al.: Saccadic eye movement metrics reflect surgical residents’ fatigue. Ann. Surg. 259, 824–829 (2014)

    Article  Google Scholar 

  9. Krejtz, K., Smidt, T., Duchowski, A.T., Krejtz, I.: Entropy-based statistical analysis of eye movement transitions. In: Proceedings of the Symposium on Eye Tracking Research and Applications (ETRA), Florida, USA (2014)

    Google Scholar 

  10. Tien, T., Pucher, P.H., Sodergren, M.H., Sriskandarajah, K., Yang, G.Z., Darzi, A.: Differences in gaze behavior of expert and junior surgeons performing open inguinal hernia repair. Surg. Endosc. 29, 405–413 (2015)

    Article  Google Scholar 

  11. Kohler, M., Falk, B., Schmitt, R.: Applying eye-tracking in Kansei engineering methodology for design evaluations in product development. Int. J. Affect. Eng. 14, 241–251 (2015)

    Article  Google Scholar 

  12. Mello-Thoms, C., Nodine, C.F., Kundel, H.L.: What attracts the eye to the location of missed and reported breast cancers? In: Proceedings of the Symposium on Eye Tracking Research and Applications (ETRA), New Orleans, USA (2002)

    Google Scholar 

  13. DeBruin, J.A., Malan, K.M., Eloff, J.H.P.: Saccade deviation indicators for automated eye tracking analysis. In: Proceedings of the 2013 Conference on Eye Tracking South Africa (ETSA), Cape Town, South Africa (2013)

    Google Scholar 

  14. Grindinger, T., Duchowski, A.T., Sawyer, M.: Group-wise similarity and classification of aggregate scanpaths. In: Proceedings of the Symposium on Eye Tracking Research and Applications (ETRA), Austin Texas, USA (2010)

    Google Scholar 

  15. Goldberg, J.H., Kotval, X.P.: Computer interface evaluation using eye movements: methods and constructs. Int. J. Ind. Ergon. 24, 631–645 (1999)

    Article  Google Scholar 

  16. Otsuka, K., Yamato, J., Takemae, Y., Murase, H.: Quantifying interpersonal influence in face-to-face conversations based on visual attention patterns. In: Human Factors in Computing Systems, Quebec, Canada (2006)

    Google Scholar 

  17. DiStasi, L.L., et al.: Gaze-entropy as a task load index for safety-critical operators: military pilots and surgeons. J. Vis. 16, 1341 (2016)

    Article  Google Scholar 

  18. Schieber, F., Gilland, J.: Visual entropy metric reveals differences in drivers’ eye gaze complexity across variations in age and subsidiary task load. In: Human Factors and Ergonomics Society Annual Meeting Proceedings, New York, USA (2008)

    Google Scholar 

  19. Chew, J.Y., Ohtomi, K., Suzuki, H.: Skill metrics for mobile crane operators based on gaze fixation pattern. Adv. Hum. Aspects Transp. Adv. Intell. Syst. Comput. 484, 1139–1149 (2016)

    Article  Google Scholar 

  20. Chew, J.Y., Ohtomi, K., Suzuki, H.: Glance behavior as design indices of in-vehicle visual support system: a study using crane simulators. Appl. Ergon. 73, 183–193 (2018)

    Article  Google Scholar 

  21. Teodorescu, J.: Maximum likelihood estimation for Markov Chains. arXiv, 0905.4131v1 (2009)

    Google Scholar 

  22. Ward, P., Williams, A.M., Bennett, S.J.: Visual search and biological motion perception in tennis. Res. Q. Exerc. Sport 73, 107–112 (2002)

    Article  Google Scholar 

  23. Button, C., Dicks, M., Haines, R., Barker, R., Davids, K.: Statistical modelling of gaze behavior as categorical time series: what you should watch to save soccer penalties. Cogn. Process 12, 235–244 (2011)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Precision Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan

    Jouh Yeong Chew, Koichi Ohtomi & Hiromasa Suzuki

  2. National Institute of Advanced Industrial Science and Technology, AIST Tsukuba Central 1, 1-1-1 Umezono, Tsukuba, Ibaraki, 305-8560, Japan

    Jouh Yeong Chew

Authors
  1. Jouh Yeong Chew
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Koichi Ohtomi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hiromasa Suzuki
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jouh Yeong Chew .

Editor information

Editors and Affiliations

  1. University of Crete and Foundation for Research and Technology – Hellas (FORTH), Heraklion, Crete, Greece

    Constantine Stephanidis

  2. Coventry University, Coventry, UK

    Don Harris

  3. Safety and Accident Investigation Centre, Cranfield University, Cranfield, UK

    Wen-Chin Li

  4. Soar Technology Inc., Orlando, FL, USA

    Dylan D. Schmorrow

  5. Design Interactive, Inc., Orlando, FL, USA

    Cali M. Fidopiastis

  6. Foundation for Research and Technology – Hellas (FORTH), Heraklion, Crete, Greece

    Margherita Antona

  7. Tsinghua University, Beijing, China

    Qin Gao

  8. Chongqing University, Chongqing, China

    Jia Zhou

  9. Department of Multimedia and Graphic Arts, Cyprus University of Technology, Limassol, Cyprus

    Panayiotis Zaphiris

  10. Department of Multimedia and Graphic Arts, Cyprus University of Technology, Limassol, Cyprus

    Andri Ioannou

  11. Soar Technology Inc., Orlando, FL, USA

    Robert A. Sottilare

  12. MMS, Fraunhofer FKIE, Wachtberg, Nordrhein-Westfalen, Germany

    Jessica Schwarz

  13. Industrial Design, Eindhoven University of Technology, Eindhoven, Noord-Brabant, The Netherlands

    Matthias Rauterberg

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Chew, J.Y., Ohtomi, K., Suzuki, H. (2021). Monitoring Attention of Crane Operators During Load Oscillations Using Gaze Entropy Measures. In: Stephanidis, C., et al. HCI International 2021 - Late Breaking Papers: Cognition, Inclusion, Learning, and Culture. HCII 2021. Lecture Notes in Computer Science(), vol 13096. Springer, Cham. https://doi.org/10.1007/978-3-030-90328-2_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-90328-2_3

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-90327-5

  • Online ISBN: 978-3-030-90328-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation