Measuring Situational Awareness Aptitude Using Functional Near-Infrared Spectroscopy

  • Leanne HirshfieldEmail author
  • Mark Costa
  • Danushka Bandara
  • Sarah Bratt
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9183)


Attempts have been made to evaluate people’s situational awareness (SA) in military and civilian contexts through subjective surveys, speed, and accuracy data acquired during SA target tasks. However, it is recognized in the SA domain that more systematic measurement is necessary to assess SA theories and applications. Recent advances in biomedical engineering have enabled relatively new ways to measure cognitive and physiological state changes, such as with functional near-infrared spectroscopy (fNIRS). In this paper, we provide a literature review relating to SA and fNIRS and present an experiment conducted with an fNIRS device comparing differences in the brains between people with high and low SA aptitude. Our results suggest statistically significant differences in brain activity between the high SA group and low SA group.


Situational awareness fNIRS HCI Brain measurement 


  1. 1.
    Grimes, D., et al.: Feasibility and pragmatics of classifying working memory load with an electroencephalograph. In: CHI 2008 Conference on Human Factors in Computing Systems, Florence (2008)Google Scholar
  2. 2.
    Hirshfield, L., et al.: This is your brain on interfaces: enhancing usability testing with functional near infrared spectroscopy. In: SIGCHI. ACM (2011)Google Scholar
  3. 3.
    Hirshfield, L.M., et al.: Using non-invasive brain measurement to explore the psychological effects of computer malfunctions on users during human-computer interactions. Adv. Hum.-Comput. Interact. 2014, 1–13 (2014)CrossRefGoogle Scholar
  4. 4.
    Berka, C., et al.: Real-time analysis of EEG indexes of alertness cognition, and memory acquired with a wireless EEG headset. Int. J. Hum. Comput. Interact. 17(2), 151–170 (2004)CrossRefGoogle Scholar
  5. 5.
    Gevins, A., Smith, M.: Neurophysiological measures of working memory and individual differences in cognitive ability and cogntive style. Cereb. Cortex 10(9), 829–839 (2000)CrossRefGoogle Scholar
  6. 6.
    Grabnera, R., Neubauera, A., Stern, E.: Superior performance and neural efficiency: The impact of intelligence and expertise. Brain Res. Bull. Sci. Direct 69(4), 422–439 (2006)CrossRefGoogle Scholar
  7. 7.
    Endsley, M.: Situation awareness. In: Salvendy, G. (ed.) Handbook of Human Factors and Ergonomics. Wiley, New York (2006)Google Scholar
  8. 8.
    Parasuraman, R., Rizzo, M.: Neuroergonomics: The Brain at Work. Oxford University Press, Oxford (2008)Google Scholar
  9. 9.
    Chance, B., et al.: A novel method for fast imaging of brain function, non-invasively, with light. Opt. Express 10(2), 411–423 (1988)Google Scholar
  10. 10.
    Izzetoglu, K., et al.: Functional near-infrared neuroimaging. In: Proceedings of IEEE EMBS (2004)Google Scholar
  11. 11.
    Hirshfield, L.M., et al.: Brain measurement for usability testing and adaptive interfaces: an example of uncovering syntactic workload in the brain using functional near infrared spectroscopy. In: Conference on Human Factors in Computing Systems: Proceeding of the Twenty-Seventh Annual SIGCHI Conference on Human Factors in Computing Systems (2009)Google Scholar
  12. 12.
    Matthews, M.D., et al.: Measures of infantry situation awareness in a virtual MOUT environment. In: Human Performance, Situation Awareness and Automation Conference, Savannah (2000)Google Scholar
  13. 13.
    Taylor, R.M.: Situational awareness rating technique (SART): the development of a tool for aircrew systems design. In: Situational Awareness in Aerospace Operations (AGARD-CP-478), Neuilly Sur Seine (1990)Google Scholar
  14. 14.
    Endsley, M.R., Garland, D.G.: Situation Awareness Analysis and Measurement. CRC Press, Atlanta (2000)Google Scholar
  15. 15.
    Anderson, E.J., et al.: Involvement of prefrontal cortex in visual search. Exp. Brain Res. 180(2), 289–302 (2007)CrossRefGoogle Scholar
  16. 16.
    Gross, J., Thompson, R.: Emotion regulation: conceptual foundations. In: Gross, J. (ed.) Handbook of Emotion Regulation. Guilford Press, New York (2007)Google Scholar
  17. 17.
    Buckner, R., Carrol, D.: Self-projection and the brain. Trends Cogn. Sci. 11(2), 49–57 (2006)CrossRefGoogle Scholar
  18. 18.
    Donmez, B.D., Nehme, C., Cummings, M.L.: Modeling workload impact in multiple unmanned vehicle supervisory control. IEEE J. Syst. Man Cybern. 40(6), 1180–1190 (2010)CrossRefGoogle Scholar
  19. 19.
    John, M.S., et al.: Overview of the DARPA augmented cognition technical integration experiment. Int. J. Hum.-Comput. Interact. 17(2), 131–149 (2004)CrossRefGoogle Scholar
  20. 20.
    Miller, W.: The US Air Force-Developed Adaptaion of the Multi-Attribute Task Battery. AFRL-RH-WP-TR-2010–0133 (2010)Google Scholar
  21. 21.
    Endsley, M.: Predictive utility of an objective measure of situation awareness. In: Proceedings of the Human Factors Society 34th Annual Meeting. Human Factors Society, Santa Monica (1990)Google Scholar
  22. 22.
    Arnegard, R., Comstock, R.: The multi-attribute task battery for human operator workload and strategic behavior research. NASA Technical Report (1992)Google Scholar
  23. 23.
    Arnett, J., Labovitz, S.: Effect of physical layout in performance of the Trail Making Test. Psychol. Assess. 7(2), 220–221 (1995)CrossRefGoogle Scholar
  24. 24.
    Eckstrom, R., et al.: Kit of Factor-Referenced Cognitive Tests. Educational testing service, Princeton (1976)Google Scholar
  25. 25.
    Ye, J.C., et al.: NIRS-SPM: statistical parametric mapping for near-infrared spectroscopy. Neuroimage 44(2), 428–447 (2009)CrossRefGoogle Scholar
  26. 26.
    Tsuzuki, D., et al.: Virtual spatial registration of stand-alone functional NIRS data to MNI space. NeuroImage 34, 1506–1518 (2007)CrossRefGoogle Scholar
  27. 27.
    Wilson, G.: Strategies for psychophysiological assessment of situation awareness. In: Endsley, M., Garland, D. (eds.) Situation Awareness: Analysis and Measurement. Lawrence Earlbaum Associates, NJ (2000)Google Scholar
  28. 28.
    Chance, B., et al.: Cognition activated low frequency modulation of light absorption in human brain. Proc. Nat. Acad. Sci. 90(8), 3770–3774 (1993)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Leanne Hirshfield
    • 1
    Email author
  • Mark Costa
    • 1
    • 2
  • Danushka Bandara
    • 1
    • 3
  • Sarah Bratt
    • 1
    • 2
  1. 1.M.I.N.D. Lab Newhouse School of CommunicationsSyracuseUSA
  2. 2.School of Information StudiesSyracuse UniversitySyracuseUSA
  3. 3.Electrical Engineering and Computer ScienceSyracuse UniversitySyracuseUSA

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