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Mental Workload (MWL) is traditionally evaluated by psychophysiological signals using spectral analysis and event-related potentials. Robot-assisted Surgery (RAS) is a complex task that involves human-robot interaction, multitasking, quick and appropriate reactions to various stimuli and unforeseen circumstances, as well as frequent switches between surgical subtasks. There is a lack of standardized methodology for objectively monitoring a surgeon's MWL during RAS. In this study, we propose andoi:10.1109/access.2020.3036751 fatcat:j6h7doubo5gfnhoronjzgwandq