Abstract
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. © 2012 Springer-Verlag.
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CITATION STYLE
Ayaz, H., Bunce, S., Shewokis, P., Izzetoglu, K., Willems, B., & Onaral, B. (2012). Using brain activity to predict task performance and operator efficiency. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7366 LNAI, pp. 147–155). https://doi.org/10.1007/978-3-642-31561-9_16
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