Sensor-based indicators of performance changes between sessions during robotic surgery training

Multi-modal physiological sensing approach for distinguishing high workload events in remotely piloted aircraft simulation

“…The two sessions occurred on separate days, and the two-person team remained consistent for both sessions. Previous findings on the pilot role were presented at a conference (C. Wilson et al 2016), and the present study focused on workload for the sensor operators. In addition, this work goes beyond scenario-level analysis and provides in-depth findings on the effects of RPA simulation events.…”

“…SMEs were experts that had previous experiences with RPA. The following steps were followed for establishing the difficulty of the scenario (and further described in C. Wilson et al 2016): (1) research team and SME discussed RPA skills (e.g., navigating (pilot) and tracking targets (sensor operator)), (2) the team and SME identified obstacles RPA's may encounter, (3) scenario tasks and obstacles were rated by SME from 1 to 5, (4) ratings were used by research team to develop scenarios, and (5) SMEs evaluated the scenarios again and any alterations suggested implemented. Because the subjects participated in two sessions (once as pilot and once as the sensor operator), two versions of the scenarios (Version A and Version B) with the same complexity level were created by SMEs to reduce potential learning effects between sessions.…”

“…From the SME interviews, scenarios overall centered in targeting tasks, e.g., locating waypoints and tracking POIs (C. Wilson et al 2016), and the difficulty of these tasks were modulated by factors such as obstacles (e.g., no fly zones and visual obstructions), time limits, and target movement speeds. In all the scenarios, participants performed four tasks sequentially; each task had a specific point/target of interest.…”

“…When utilizing physiological measures to study workload, a common approach is summarizing (e.g., mean, median, and maximum) the physiological data across the entire session, operation, or scenario (Abdelrahman et al 2015;Ayaz et al 2012a;Ayaz et al 2012b;Böhm et al 2001;Cinaz et al 2013;Cinaz et al 2010;Rieger et al 2014;C. Wilson et al 2016;Yu et al 2017).…”

“…Exploratory studies on RPA and pilot operations have proposed several applications of workload sensing to individualize training and improve operator performance. In RPA mission simulations, pilot engagement (calculated using EEG) was predictive of scenario difficulty levels (C. Wilson et al 2016). Several adaptive aiding approaches have also been proposed using physiological sensors (Afergan et al 2014;Mark et al 2017;Teo et al 2019).…”