Monitoring performance and mental workload in an automated system

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Abstract

Human performance in computer-aided system has engrossed inevitably human issues in cognitive functioning. The present endeavor focuses on the associated influence of training, automation reliability on the monitoring performance and workload in multi-task ambience. MAT battery was utilized with engine-system monitoring, two dimensional tracking, and fuel resource management tasks were the concerned elements, in which only system engine-monitoring task was automated in the training as well as in the final test sessions. A 2 × 2 × 2 × 3, mixed factorial design was employed. Monitoring performance, false alarms, reaction time and root mean square error performance were recorded as dependent measures. Results revealed that automation-induced complacency might be the feature of multi-task condition where subjects detected automation failures under high static system reliability. Results further showed that mental workload significantly reduced from pre- to post-sessions. © Springer-Verlag Berlin Heidelberg 2007.

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APA

Singh, I. L., Singh, A. L., & Saha, P. K. (2007). Monitoring performance and mental workload in an automated system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4562 LNAI, pp. 426–435). Springer Verlag. https://doi.org/10.1007/978-3-540-73331-7_47

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