skip to main content
10.1145/3050385.3050391acmotherconferencesArticle/Chapter ViewAbstractPublication Pagesergo-iaConference Proceedingsconference-collections
short-paper

"Human monitoring" monitoring: how real-time cognitive state assessment impacts cognition?

Published:06 July 2016Publication History

ABSTRACT

For a long time, literature has identified some psychophysiological measures that proved reliable to assess cognitive states in controlled conditions. Smaller, more reliable and more affordable sensors made the industrial community dream to design systems that would adapt themselves to the ability of their users to operate them. Thus an important human factors question must be asked: what is the impact of such a feedback on users' performance and cognitive workload? We designed a protocol to compare the influence of a cognitive load feedback in a Multiple Object Tracking task. Reliability of this feedback was also evaluated. Performance in a dual task paradigm, pupil dilation and the Overall Workload Scale were used to assess cognitive load.

References

  1. N. Egelund, "Spectral analysis of heart rate variability as an indicator of driver fatigue.," Ergonomics, vol. 25, no. 7, pp. 663--672, 1982.Google ScholarGoogle Scholar
  2. J. Beatty and B. Lucero-Wagoner, "The pupillary system.," in Handbook of psychophysiology, 2nd ed., New York, NY, US: Cambridge University Press, 2000, pp. 142--162.Google ScholarGoogle Scholar
  3. S. Valins and A. A. Ray, "Effects of cognitive desensitization on avoidance behavior.," J. Pers. Soc. Psychol., vol. 7, no. 4p1, p. 345, 1967.Google ScholarGoogle ScholarCross RefCross Ref
  4. T. J. Story and M. G. Craske, "Responses to false physiological feedback in individuals with panic attacks and elevated anxiety sensitivity," Behav. Res. Ther., vol. 46, no. 9, pp. 1001--1008, 2008.Google ScholarGoogle ScholarCross RefCross Ref
  5. A. N. Kluger and A. DeNisi, "The effects of feedback interventions on performance: a historical review, a meta-analysis, and a preliminary feedback intervention theory.," Psychol. Bull., vol. 119, no. 2, p. 254, 1996.Google ScholarGoogle Scholar
  6. Z. W. Pylyshyn and R. W. Storm, "Tracking multiple independent targets: Evidence for a parallel tracking mechanism*," Spat. Vis., vol. 3, no. 3, pp. 179--197, 1988.Google ScholarGoogle ScholarCross RefCross Ref
  7. R. Allen, P. McGeorge, D. Pearson, and A. B. Milne, "Attention and expertise in multiple target tracking," Appl. Cogn. Psychol., vol. 18, no. 3, pp. 337--347, 2004.Google ScholarGoogle ScholarCross RefCross Ref
  8. C. D. Wickens, K. Gempler, and M. E. Morphew, "Workload and Reliability of Predictor Displays in Aircraft Traffic Avoidance," Transp. Hum. Factors, vol. 2, no. 2, pp. 99--126, 2000.Google ScholarGoogle ScholarCross RefCross Ref
  9. T. Drew, T. S. Horowitz, and E. K. Vogel, "Swapping or dropping? Electrophysiological measures of difficulty during multiple object tracking," Cognition, vol. 126, no. 2, pp. 213--223, 2013.Google ScholarGoogle ScholarCross RefCross Ref
  10. L. Oksama and J. Hyönä, "Is multiple object tracking carried out automatically by an early vision mechanism independent of higher-order cognition? An individual difference approach," Vis. cogn., vol. 11, no. 5, pp. 631--671, 2004.Google ScholarGoogle ScholarCross RefCross Ref
  11. Z. Pylyshyn, "Some puzzling findings in multiple object tracking: I. Tracking without keeping track of object identities," Vis. cogn., vol. 11, no. 7, pp. 801 -- 822, 2004.Google ScholarGoogle ScholarCross RefCross Ref
  12. D. Kahneman and J. Beatty, "Pupil diameter and load on memory," Science (80-. )., vol. 154, no. 3756, pp. 1583--1585, 1966.Google ScholarGoogle ScholarCross RefCross Ref
  13. J. Beatty, "Pupillometric signs of selective attention in man," in Neurophysiology and psychophysiology: Experimental and clinical applications, E. Donchin, G. Galbraith, and M. L. Kietzman, Eds. 1988, pp. 138--143.Google ScholarGoogle Scholar
  14. T. Makovski, G. A. Vázquez, and Y. V Jiang, "Visual learning in multiple-object tracking," PLoS One, vol. 3, no. 5, p. e2228, 2008.Google ScholarGoogle ScholarCross RefCross Ref

Recommendations

Comments

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Sign in
  • Published in

    cover image ACM Other conferences
    Ergo'IA '16: Proceedings of the 15th Ergo'IA "Ergonomie Et Informatique Avancée" Conference
    July 2016
    163 pages
    ISBN:9781450347853
    DOI:10.1145/3050385

    Copyright © 2016 ACM

    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 6 July 2016

    Permissions

    Request permissions about this article.

    Request Permissions

    Check for updates

    Qualifiers

    • short-paper
  • Article Metrics

    • Downloads (Last 12 months)0
    • Downloads (Last 6 weeks)0

    Other Metrics

PDF Format

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader