Abstract
In this paper we focus on the effect of different interface designs on the performance and cognitive workload of sensor operators (SO) during a target detection task in a simulated environment. Functional near-infrared (fNIR) spectroscopy is used to investigate whether there is a relationship between target detection performance across three SO interfaces and brain activation data obtained from the subjects’ prefrontal cortices that are associated with relevant higher-order cognitive functions such as attention, response selection and decision making. The preliminary findings of the study suggest that brain regions in the vicinity of medial frontal gyrus of the right hemisphere respond differentially to the cognitive workload induced by different interfaces.
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References
Cooke, N.J., Pringle, H., Pederson, H., Connor, O., Salas, E.: Human Factors of Remotely Operated Vehicles. Elsevier, The Netherlands (2006)
Bethke, B., Valenti, M., How, J.: Cooperative Vision Based Estimation and Tracking Using Multiple UAVs. In: Hirsch, M.J., et al. (eds.) Adv. In Cooper. Ctrl & Optimization. LNCIS, vol. 369, pp. 179–189 (2007)
Leduc, P.A., Rash, C.E., Manning, M.S.: Human factors in UAV accidents. Special Operations Technology 3(8) (2005)
Tvaryanas, A.P., Thompson, W.T.: Recurrent error pathways in HFACS data: analysis of 95 mishaps with remotely piloted aircraft. Aviation, Space, and Environmental Medicine 79(5), 525–532 (2008)
Ayaz, H., Shewokis, P.A., Bunce, S., Izzetoglu, K., Willems, B., Onaral, B.: Optical brain monitoring for operator training and mental workload assessment. Neuroimage 59(1), 36–47 (2012)
Curtis, C., D’Esposito: Persistent activity in the prefrontal cortex during working memory. Trends in Cognitive Sciences 7(9), 415–423 (2003)
Villringer, A., Chance, B.: Non-invasive optical spectroscopy and imaging of human brain function. Trends in Neurosciences 20(10), 435–442 (1997)
Chance, B., Anday, E., Nioka, S., Zhou, S., Hong, L., Worden, K., Li, C., Murray, T., Ovetsky, Y., Pidikiti, D., Thomas, R.: A novel method for fast imaging of brain function, non-invasively, with light. Optics Express 2(10), 411–423 (1998)
Strangman, G., Boas, D.A., Sutton, J.P.: Non-invasive neuroimaging using near-infrared light. Biol. Psychiatry 52(7), 679–693 (2002)
Izzetoglu, M., et al.: Functional near-infrared neuroimaging. IEEE Trans. Neural Syst. Rehabil. Eng. 13(2), 153–159 (2005)
Ayaz, H., Shewokis, P.A., Curtin, A., Izzetoglu, M., Izzetoglu, K., Onaral, B.: Using MazeSuite and Functional Near Infrared Spectroscopy to Study Learning in Spatial Navigation. J. Vis. Exp. e3443 (2011)
Ayaz, H., Izzetoglu, M., Shewokis, P.A., Onaral, B.: Sliding-window motion artifact rejection for functional near-infrared spectroscopy. In: EMBC 2010 (2010)
Huettel, S., McCarthy, G.: What is odd in the oddball task? Prefrontal cortex is activated by dynamic changes in response strategy. Neuropsychologia 42(2004), 379–386 (2004)
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Çakır, M.P., Şenyiğit, A.M., Akay, D.M., Ayaz, H., İşler, V. (2012). Evaluation of UAS Camera Operator Interfaces in a Simulated Task Environment: An Optical Brain Imaging Approach. In: Zhang, H., Hussain, A., Liu, D., Wang, Z. (eds) Advances in Brain Inspired Cognitive Systems. BICS 2012. Lecture Notes in Computer Science(), vol 7366. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31561-9_7
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DOI: https://doi.org/10.1007/978-3-642-31561-9_7
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