IDEAS home Printed from https://ideas.repec.org/p/ahh/wpaper/worms1706.html
   My bibliography  Save this paper

Applying hidden Markov models to visual activity analysis for simple digital control panel operations

Author

Listed:
  • Jerzy Grobelny
  • Rafal Michalski

Abstract

The paper presents an application of Hidden Markov Models (HMM) to fixations’ sequences analysis. The examination concerns eye tracking data gathered during performing simple comparison and decision tasks for four versions of plain control panels. The panels displayed the target and current velocity either on a digital or analog (clock-face) speedometers. Subjects were to decide whether increase or decrease the current speed by pressing the appropriate button. The obtained results suggest that females, generally exhibit different covert attention patterns than men. Moreover, the article demonstrates the estimated four HMM with three hidden states for every examined control panels variant and provides discussion of the outcomes.

Suggested Citation

  • Jerzy Grobelny & Rafal Michalski, 2017. "Applying hidden Markov models to visual activity analysis for simple digital control panel operations," WORking papers in Management Science (WORMS) WORMS/17/06, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
  • Handle: RePEc:ahh:wpaper:worms1706
    DOI: 10.1007/978-3-319-28555-9_15
    as

    Download full text from publisher

    File URL: https://worms.pwr.edu.pl/RePEc/ahh/wpaper/WORMS_17_06.pdf
    File Function: Final version, 2017
    Download Restriction: no

    File URL: https://libkey.io/10.1007/978-3-319-28555-9_15?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. John Liechty & Rik Pieters & Michel Wedel, 2003. "Global and local covert visual attention: Evidence from a bayesian hidden markov model," Psychometrika, Springer;The Psychometric Society, vol. 68(4), pages 519-541, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Berna Haktanirlar Ulutas & N. Fırat Özkan & Rafał Michalski, 2020. "Application of hidden Markov models to eye tracking data analysis of visual quality inspection operations," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(2), pages 761-777, June.
    2. Jerzy Grobelny & Rafal Michalski, 2020. "Investigating human visual behavior by hidden Markov models in the design of marketing information," WORking papers in Management Science (WORMS) WORMS/20/09, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    3. Rafal Michalski & Jerzy Grobelny & Anna Bezdzietna, 2020. "Column versus tabular layout of paragraphs in message conveyance: visual processing study based on eye-tracking data," WORking papers in Management Science (WORMS) WORMS/20/19, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    4. Rafal Michalski & Joanna Koszela-Kulinska, 2020. "Eye-tracking examination of the anthropological race, gender and verbal-pictorial relative positions on ergonomics of visual information presentation," WORking papers in Management Science (WORMS) WORMS/20/10, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    5. Jerzy Grobelny & Rafal Michalski, 2021. "Hidden Markov models for visual processing of marketing leaflets," WORking papers in Management Science (WORMS) WORMS/21/08, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    6. Jerzy Grobelny & Rafal Michalski & Gerhard-Wilhelm Weber, 2021. "Modeling human thinking about similarities by neuromatrices in the perspective of fuzzy logic," WORking papers in Management Science (WORMS) WORMS/21/09, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Martinovici, A., 2019. "Revealing attention - how eye movements predict brand choice and moment of choice," Other publications TiSEM 7dca38a5-9f78-4aee-bd81-c, Tilburg University, School of Economics and Management.
    2. Amy Wenxuan Ding & Shibo Li & Patrali Chatterjee, 2015. "Learning User Real-Time Intent for Optimal Dynamic Web Page Transformation," Information Systems Research, INFORMS, vol. 26(2), pages 339-359, June.
    3. Ricardo Montoya & Oded Netzer & Kamel Jedidi, 2010. "Dynamic Allocation of Pharmaceutical Detailing and Sampling for Long-Term Profitability," Marketing Science, INFORMS, vol. 29(5), pages 909-924, 09-10.
    4. Amirali Kani & Wayne S. DeSarbo & Duncan K. H. Fong, 2018. "A Factorial Hidden Markov Model for the Analysis of Temporal Change in Choice Models," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 5(3), pages 162-177, December.
    5. Qin Zeng & Yun Chen & Xiazhong Zheng & Shiyu He & Donghui Li & Benwu Nie, 2023. "Optimization of Underground Cavern Sign Group Layout Using Eye-Tracking Technology," Sustainability, MDPI, vol. 15(16), pages 1-32, August.
    6. Peter Stüttgen & Peter Boatwright & Robert T. Monroe, 2012. "A Satisficing Choice Model," Marketing Science, INFORMS, vol. 31(6), pages 878-899, November.
    7. Michel Wedel & Rik Pieters & Ralf Lans, 2023. "Modeling Eye Movements During Decision Making: A Review," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 697-729, June.
    8. Jerzy Grobelny & Rafal Michalski, 2020. "Investigating human visual behavior by hidden Markov models in the design of marketing information," WORking papers in Management Science (WORMS) WORMS/20/09, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    9. Erik Reichle & Jessica Nelson, 2003. "Local vs. global covert visual attention: Are two states necessary? Comment on Liechty et al., 2003," Psychometrika, Springer;The Psychometric Society, vol. 68(4), pages 543-549, December.
    10. Sam Hui & Eric Bradlow, 2012. "Bayesian multi-resolution spatial analysis with applications to marketing," Quantitative Marketing and Economics (QME), Springer, vol. 10(4), pages 419-452, December.
    11. LouAnne Boyd & Vincent Berardi & Deanna Hughes & Franceli Cibrian & Jazette Johnson & Viseth Sean & Eliza DelPizzo-Cheng & Brandon Mackin & Ayra Tusneem & Riya Mody & Sara Jones & Karen Lotich, 2022. "Manipulating image luminance to improve eye gaze and verbal behavior in autistic children," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-9, December.
    12. Eric M. Schwartz & Eric T. Bradlow & Peter S. Fader, 2014. "Model Selection Using Database Characteristics: Developing a Classification Tree for Longitudinal Incidence Data," Marketing Science, INFORMS, vol. 33(2), pages 188-205, March.
    13. Krucien, Nicolas & Ryan, Mandy & Hermens, Frouke, 2017. "Visual attention in multi-attributes choices: What can eye-tracking tell us?," Journal of Economic Behavior & Organization, Elsevier, vol. 135(C), pages 251-267.
    14. Savannah Wei Shi & Michel Wedel & F. G. M. (Rik) Pieters, 2013. "Information Acquisition During Online Decision Making: A Model-Based Exploration Using Eye-Tracking Data," Management Science, INFORMS, vol. 59(5), pages 1009-1026, May.
    15. Berna Haktanirlar Ulutas & N. Fırat Özkan & Rafał Michalski, 2020. "Application of hidden Markov models to eye tracking data analysis of visual quality inspection operations," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(2), pages 761-777, June.
    16. Yegoryan, Narine & Guhl, Daniel & Klapper, Daniel, 2018. "Inferring Attribute Non-Attendance Using Eye Tracking in Choice-Based Conjoint Analysis," Rationality and Competition Discussion Paper Series 111, CRC TRR 190 Rationality and Competition.
    17. Michel Wedel & Rik Pieters & John Liechty, 2003. "Evidence for covert attention switching from eye-movements. Reply to commentaries on Liechty et al., 2003," Psychometrika, Springer;The Psychometric Society, vol. 68(4), pages 557-562, December.
    18. Yegoryan, Narine & Guhl, Daniel & Klapper, Daniel, 2020. "Inferring attribute non-attendance using eye tracking in choice-based conjoint analysis," Journal of Business Research, Elsevier, vol. 111(C), pages 290-304.
    19. Clarence Lee & Elie Ofek & Thomas J. Steenburgh, 2018. "Personal and Social Usage: The Origins of Active Customers and Ways to Keep Them Engaged," Management Science, INFORMS, vol. 64(6), pages 2473-2495, June.
    20. John R. Hauser & Glen L. Urban & Guilherme Liberali & Michael Braun, 2009. "Website Morphing," Marketing Science, INFORMS, vol. 28(2), pages 202-223, 03-04.

    More about this item

    Keywords

    Ergonomics; Control panel design; Human visual behavior; Human-computer interaction;
    All these keywords.

    JEL classification:

    • C00 - Mathematical and Quantitative Methods - - General - - - General
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D87 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Neuroeconomics
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality
    • L23 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Organization of Production
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ahh:wpaper:worms1706. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Anna Kowalska-Pyzalska (email available below). General contact details of provider: https://edirc.repec.org/data/kbpwrpl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.