On-Orbit Operations Simulator for Workload Measurement during Telerobotic Training
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Training for telerobotic systems often makes heavy use of simulated platforms, which ensure safe operation during the learning process. Outer space is one domain in which such a simulated training platform would be useful, as On-Orbit Operations (O3) can be costly, inefficient, or even dangerous if not performed properly. In this paper, we present a new telerobotic training simulator for the Canadarm2 on the International Space Station (ISS), and record physiological data from subjects as they perform a task from the simulator under conditions which increased workload (e.g. latency and time pressure). As most current workload measures are subjective and non-continuous, we analyse how objective measures from the simulator and physiological data can provide a more reliable and continuous measure. ANOVA of task data revealed which simulator-based performance measures could predict the presence of latency and time pressure. Furthermore, EEG classification using a Riemannian classifier and Leave-One-Subject-Out cross-validation showed promising classification performance. EEG results also reveal that Independent Component Analysis (ICA) preprocessing and centrally located channels are more discriminative for 5-class discrimination, whereas information derived from the EEG parietal channels was more accurate in two-class classification of latency and time pressure paradigms.
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