Using Brain Activity to Predict Task Performance and Operator Efficiency

  • Hasan Ayaz
  • Scott Bunce
  • Patricia Shewokis
  • Kurtulus Izzetoglu
  • Ben Willems
  • Banu Onaral
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7366)


The efficiency and safety of many complex human-machine systems are closely related to the cognitive workload and situational awareness of their human operators. In this study, we utilized functional near infrared (fNIR) spectroscopy to monitor anterior prefrontal cortex activation of experienced operators during a standard working memory and attention task, the n-back. Results indicated that task efficiency can be estimated using operator’s fNIR and behavioral measures together. Moreover, fNIR measures had more predictive power than behavioral measures for estimating operator’s future task performance in higher difficulty conditions.


fNIR optical brain imaging working memory task efficiency cognitive workload 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Hasan Ayaz
    • 1
    • 2
  • Scott Bunce
    • 2
    • 3
  • Patricia Shewokis
    • 1
    • 2
    • 4
  • Kurtulus Izzetoglu
    • 1
    • 2
  • Ben Willems
    • 5
  • Banu Onaral
    • 1
    • 2
  1. 1.School of Biomedical Engineering, Science & Health SystemsDrexel UniversityPhiladelphiaUSA
  2. 2.Cognitive Neuroengineering and Quantitative Experimental Research, (CONQUER) CollaborativeDrexel UniversityPhiladelphiaUSA
  3. 3.Penn State Hershey Medical Center and Penn State College of MedicineHersheyUSA
  4. 4.College of Nursing and Health ProfessionsDrexel UniversityPhiladelphiaUSA
  5. 5.Federal Aviation Administration William J. Hughes Technical CenterUSA

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