NDLI: Real time modeling of the cognitive load of an Urban Search And Rescue robot operator

Content Provider	IEEE Xplore Digital Library
Author	Colin, T.R. Smets, N.J.J.M. Mioch, T. Neerincx, M.A.
Copyright Year	2014
Description	Author affiliation: TNO Soesterberg, Soesterberg, Netherlands (Smets, N.J.J.M.; Mioch, T.; Neerincx, M.A.) \|\| Utrecht Univ., Utrecht, Netherlands (Colin, T.R.)
Abstract	Urban Search And Rescue (USAR) robots are used to find and save victims in the wake of disasters such as earthquakes or terrorist attacks. The operators of these robots are affected by high cognitive load; this hinders effective robot usage. This paper presents a cognitive task load model for real-time monitoring and, subsequently, balancing of workload on three factors that affect operator performance and mental effort: time occupied, level of information processing, and number of task switches. To test an implementation of the model, five participants drove a shape-shifting USAR robot, accumulating over 16 hours of driving time in the course of 485 USAR missions with varying objectives and difficulty. An accuracy of 69% was obtained for discrimination between low and high cognitive load; higher accuracy was measured for discrimination between extreme cognitive loads. This demonstrates that such a model can contribute, in a non-invasive manner, to estimating an operator's cognitive state. Several ways to further improve accuracy are discussed, based on additional experimental results.
Starting Page	874
Ending Page	879
File Size	677213
Page Count	6
File Format	PDF
ISBN	9781479967636
e-ISBN	9781479967650
DOI	10.1109/ROMAN.2014.6926363
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-25
Publisher Place	UK
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robots Load modeling Accuracy Atmospheric measurements Particle measurements Brain modeling
Content Type	Text
Resource Type	Article

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