Exploration of deep space poses many challenges. Mission support personnel will not be immediately available to assist crewmembers performing complex operations on future long-duration exploration operations. Consequently, it is imperative that crewmembers have objective, reliable, and non-invasive metrics available to aid them in determining their fitness for duty prior to engaging in potentially dangerous tasks. The Robotics On-Board Trainer (ROBoT) task is NASA's platform for training astronauts to perform docking and grappling maneuvers. It is regularly used by crewmembers during spaceflight for refresher training. The operational ROBoT system, however, does not record data. Thus, a research version of ROBoT, called ROBoT-r, was developed so that operationally relevant data could be mined to provide feedback to crewmembers. We investigated whether ROBoT-r metrics would change according to sleep loss and circadian phase in a 28-h laboratory-based sleep deprivation study. Overall, participants showed improvement over time despite sleep loss, indicating continued learning. Performance on the psychomotor vigilance task (PVT) followed an expected profile, with reduced performance across the night. These findings suggest that individuals may be able to temporarily compensate for sleep loss to maintain performance on complex, novel tasks. It is possible that some ROBoT-r metrics may be sensitive to sleep loss after longer bouts of wakefulness or after individuals have habituated to the task. Studies with additional participants and extended pre-training on the ROBoT-r task should be conducted to disentangle how brain activity may change as individuals learn and habituate to complex tasks during sleep loss.
Stress resilience is recognized as an important occupational prerequisite for air traffic controllers (ATCs). A system for input/output multimodal stress resilience assessment based on physiological features has been developed and applied in the ATC selection process on 40 ATC candidates, as well as on 40 age/sex-matched control subjects. The input stimulation paradigm includes acoustic startle stimuli and their prepulse and fear-potentiated modulations, airblasts, and semantically relevant aversive images and sounds. The output physiological features include resting heart rate variability and respiratory sinus arrhythmia, cardiac allostasis, electromyogram-and electrodermal activity-based acoustic startle response features, like startle reactivity and startle habituation, and acoustic startle modulation-related features, like fear-potentiated startle, prepulse inhibition of the startle response, and discrimination of startle responses in danger versus safety experimental conditions. Variability of each feature is assessed and illustrated in 8-D physiological resilience space. Statistically significant differences (p < 0.05) between the two groups have been obtained for the three most relevant of eight applied features; specifically, ATC candidates exhibited significantly higher resting respiratory sinus arrhythmia, lower startle reactivity, and more pronounced cardiac allostasis than the control group. The observed feature variability justifies future research efforts toward augmenting the traditional ATC selection process with the presented stress resilience assessment approach. The proposed research paradigm can be also applied in selection processes of similarly stressful occupations such as first responders, airline/military pilots, military personnel, among others.INDEX TERMS Stress resilience assessment, air traffic controller, startle stimuli, heart rate variability, respiratory sinus arrhythmia.
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