Graduated Stress Exposure of Spaceflight Hazards in a Virtual Environment

Stress experienced by astronauts during high-level hazardous situations may poses risk to personnel wellbeing and to mission success. Stress inoculation training (SIT) provides individuals with experience of minor stressors and coping skills during non-critical times to enhance their resistance to stress. This study evaluates the effect of exposure to a low level stressor on physiological response and cognitive load in high level stressor setting. Simulation of fire emergency on the International Space Station (ISS) in a full-scale, immersive, interactive, 3D virtual reality environment facilitated a process for stress inoculation. The experimental settings included two groups that have been exposed to either virtual no-smoke or to virtual light-smoke conditions. The two groups then experienced a subsequent stress exposure in a later trail to heavy-smoke conditions. Physiological responses and cognitive load measure were collected during the trials. The results indicated weak differences in physiological responses between the two groups, in the heavy smoke conditions. Overall, no significant differences have been detected on cognitive load categories according to NASA TLX

The Interaction Between Physical and Psychosocial Stressors

Do physical and psychosocial stressors interact to increase stress in ways not explainable by the stressors alone? A preliminary study compared participants’ stress response while subjected to a physical stressor (reduced or full physical load) and a predetermined social stressor (confronted by calm or aggressive behavior). Salivary cortisol samples measured endocrine stress. Heart rate variability (HRV) and electrodermal activity (EDA) measured autonomic stress. Perceived stress was measured via discomfort and stress state surveys. Participants with a heavier load reported increased distress and discomfort. Encountering an aggressive individual increased endocrine stress, distress levels, and perceived discomfort. Higher autonomic stress and discomfort were found in participants with heavier physical load and aggressive individuals. The results suggest a relationship where physical load increases the stressfulness of aggressive behavior in ways not explainable by the effects of the stressors alone. Future research is needed to confirm this investigation’s findings

Adaptive virtual reality stress training for spaceflight emergency procedures

Emergency training is an essential tool to mitigate safety risks to vehicles, operators, and for mission success. NASA astronauts go through extensive training to prepare for such situations. Astronauts can experience acute stress during hazardous, potentially life-threatening, situations that may erode any prior training and diminish remedial performance. Even high levels of skill training can succumb to the stress associated with the existential threat from an emergency. Incorporating stress training into the emergency training process may prepare astronauts to respond more favorably to stressful events. However, the implementation of stress training is difficult due to resource limitations, wide-variation between individual’s stress responses, optimizing training to match user competency levels, and fidelity of the training environment. The research objective is to develop and test an adaptive virtual reality (VR) stress training system as a countermeasure strategy against acute stress from spaceflight emergency operations. An adaptive VR training system may help astronauts develop resilience in preparation for high-stress operations. Four studies investigated the components and overall evaluation of the adaptive VR stress training system. The first study evaluated the effect of gradual exposure to stressors on building stress resilience. Participants were tasked with locating a fire on a virtual International Space Station (VR-ISS). Physiological and psychological measures were taken and results showed that prior exposure, as would be experienced during a gradual exposure to stress, enhanced relaxation behavior when confronted with a subsequent stressful condition. The second study developed and evaluated an emergency procedure, then manipulated a VR-ISS environment with three levels of stressors to induce psychological stress. The third study developed and tested a physiologically based stress detection system that uses personalized interval methods to classify stress levels during tasks of ever-higher complexity, including an emergency fire procedure on the VR-ISS. A classifier was developed and tested against standard machine learning classifiers. Results from a human research study show high levels of accuracy in detecting multiple stress levels, even across tasks and when compared to other machine learning classifiers. The fourth study integrated the components from prior studies and evaluated a real-time adaptive stress training system. Using a VR simulation of a spaceflight emergency fire, predictions of the individual’s stress levels were used to trigger adaptations of the environmental stressors (e.g., smoke, alarms, flashing lights), with the goal of maintaining an optimal level of stress during training. The adaptive training was compared to predetermined gradual increases in stressors (graduated), and trials with constant low-level stressors (skill-only). Results suggests that all training conditions lowered stress, but the adaptive condition was more successful decreasing multiple stress measures during the stress exposure. Lastly, the lessons learned from each of the studies was compiled into a list of recommendations to aid future researchers looking to improve training, stress detection, or adaptive systems

Adaptive virtual reality stress training for spaceflight emergency procedures

Emergency training is an essential tool to mitigate safety risks to vehicles, operators, and for mission success. NASA astronauts go through extensive training to prepare for such situations. Astronauts can experience acute stress during hazardous, potentially life-threatening, situations that may erode any prior training and diminish remedial performance. Even high levels of skill training can succumb to the stress associated with the existential threat from an emergency. Incorporating stress training into the emergency training process may prepare astronauts to respond more favorably to stressful events. However, the implementation of stress training is difficult due to resource limitations, wide-variation between individual’s stress responses, optimizing training to match user competency levels, and fidelity of the training environment. The research objective is to develop and test an adaptive virtual reality (VR) stress training system as a countermeasure strategy against acute stress from spaceflight emergency operations. An adaptive VR training system may help astronauts develop resilience in preparation for high-stress operations. Four studies investigated the components and overall evaluation of the adaptive VR stress training system. The first study evaluated the effect of gradual exposure to stressors on building stress resilience. Participants were tasked with locating a fire on a virtual International Space Station (VR-ISS). Physiological and psychological measures were taken and results showed that prior exposure, as would be experienced during a gradual exposure to stress, enhanced relaxation behavior when confronted with a subsequent stressful condition. The second study developed and evaluated an emergency procedure, then manipulated a VR-ISS environment with three levels of stressors to induce psychological stress. The third study developed and tested a physiologically based stress detection system that uses personalized interval methods to classify stress levels during tasks of ever-higher complexity, including an emergency fire procedure on the VR-ISS. A classifier was developed and tested against standard machine learning classifiers. Results from a human research study show high levels of accuracy in detecting multiple stress levels, even across tasks and when compared to other machine learning classifiers. The fourth study integrated the components from prior studies and evaluated a real-time adaptive stress training system. Using a VR simulation of a spaceflight emergency fire, predictions of the individual’s stress levels were used to trigger adaptations of the environmental stressors (e.g., smoke, alarms, flashing lights), with the goal of maintaining an optimal level of stress during training. The adaptive training was compared to predetermined gradual increases in stressors (graduated), and trials with constant low-level stressors (skill-only). Results suggests that all training conditions lowered stress, but the adaptive condition was more successful decreasing multiple stress measures during the stress exposure. Lastly, the lessons learned from each of the studies was compiled into a list of recommendations to aid future researchers looking to improve training, stress detection, or adaptive systems

Training for Stressful Operations using Adaptive Systems: Conceptual Approaches and Applications

Training systems are a potential stress countermeasure by simulating high stress conditions in a safe and controlled environment. Training often involves increasing the complexity of scenarios over time until trainees can reliably execute the task. However, several limitations reduce the long-term retention and robustness of training during intense acute stress felt in-situ. These limitations include generalized training practices that are not tailored to the individual, the unreliability of self-reported subjective stress, over-trained skills that are inflexible and not robust to novel stressors, training pedagogies that focus too much on task proficiency rather than how the individual manages stress during task execution, and ambiguity for when trainers should increase/decrease training difficulty. Adaptive systems are proposed as a supplement while training individuals to maintain task performance. An adaptive system is a joint human-computer system that is able to automate functions/tasks to varying degrees to help the user, often without explicit instruction. In the context of training for stressful tasks, an adaptive system could detect and monitor stress using physiological sensors and machine learning and use this information to modify scenarios to provide individualized training. This would allow coping skills to be practiced without overwhelming or under-stimulating the trainee’s stress tolerance, adapt training according to proficiency in both task execution and physiological stress, and offer clear benchmarks for when to increase/decrease training difficulty. When coupled with a simulated training environment, an adaptive system could adapt training by altering the task procedure and implicitly changing the task environment to help the user build resilience to novel stressors. This paper presents conceptual approaches and applications for training stressful operations using adaptive systems. A generic adaptive stress training system framework is described along with recommendations based on an experimental example in the spaceflight domain for training emergency fire procedures in a virtual reality International Space Station.This proceeding is published as Finseth, Tor, Michael Dorneich, Nir Keren, Warren Franke, and Stephen Vardeman. (2021). "Training for Stressful Operations using Adaptive Systems: Conceptual Approaches and Applications." In: Proceedings of the Interservice/industry training, simulation, and education conference (I/ITSEC). Orlando, FL: Interservice/Industry Training, Simulation and Education Conference (I/ITSEC). Paper No. 21226. Volume 2021. Copyright 2021 I/ITSEC. Posted with permission

Real-Time Personalized Physiologically Based Stress Detection for Hazardous Operations

When training for hazardous operations, real-time stress detection is an asset for optimizing task performance and reducing stress. Stress detection systems train a machine-learning model with physiological signals to classify stress levels of unseen data. Unfortunately, individual differences and the time-series nature of physiological signals limit the effectiveness of generalized models and hinder both post-hoc stress detection and real-time monitoring. This study evaluated a personalized stress detection system that selects a personalized subset of features for model training. The system was evaluated post-hoc for real-time deployment. Further, traditional classifiers were assessed for error caused by indirect approximations against a benchmark, optimal probability classifier (Approximate Bayes; ABayes). Healthy participants completed a task with three levels of stressors (low, medium, high), either a complex task in virtual reality (responding to spaceflight emergency fires, n =27) or a simple laboratory-based task (N-back, n =14). Heart rate, blood pressure, electrodermal activity, and respiration were assessed. Personalized features and window sizes were compared. Classification performance was compared for ABayes, support vector machine, decision tree, and random forest. The results demonstrate that a personalized model with time series intervals can classify three stress levels with higher accuracy than a generalized model. However, cross-validation and holdout performance varied for traditional classifiers vs. ABayes, suggesting error from indirect approximations. The selected features changed with window size and tasks, but found blood pressure was most prominent. The capability to account for individual difference is an advantage of personalized models and will likely have a growing presence in future detection systems.This article is published as Finseth, Tor T., Michael C. Dorneich, Stephen Vardeman, Nir Keren, and Warren D. Franke. "Real-time Personalized Physiologically Based Stress Detection for Hazardous Operations." IEEE Access 11 (2023): 25431 - 25454. DOI: 10.1109/ACCESS.2023.3254134. Copyright 2023 The Authors. Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0). Posted with permission

Manipulating Stress Responses during Spaceflight Training with Virtual Stressors

Virtual reality (VR) provides the ability to simulate stressors to replicated real-world situations. It allows for the creation and validation of training, therapy, and stress countermeasures in a safe and controlled setting. However, there is still much unknown about the cognitive appraisal of stressors and underlying elements. More research is needed on the creation of stressors and to verify that stress levels can be effectively manipulated by the virtual environment. The objective of this study was to investigate and validate different VR stressor levels from existing emergency spaceflight procedures. Experts in spaceflight procedures and the human stress response helped design a VR spaceflight environment and emergency fire task procedure. A within-subject experiment evaluated three stressor levels. Forty healthy participants each completed three trials (low, medium, high stressor levels) in VR to locate and extinguish a fire on the International Space Station (VR-ISS). Since stress is a complex construct, physiological data (heart rate, heart rate variability, blood pressure, electrodermal activity) and self-assessment (workload, stress, anxiety) were collected for each stressor level. The results suggest that the environmental-based stressors can induce significantly different, distinguishable levels of stress in individuals

Stress Inducing Demands in Virtual Environments

This study investigated how simulated features in a virtual reality (VR) induce stress by means of user-focused demands in serious games. VR serious games have been used for therapeutic interventions, standardized stress tests, and occupational training. However, it is an open question how stress can be induced using serious games formal features, such as tasks/sensory modalities, music, pace of the game, and graphics. The Highrise VR standardized stress simulation was built to induce stress cohesively based on emotional, social, cognitive, and physical demands. The simulation induces stress by requiring coping with emotional demand (innate fear) of being at a simulated height, social demand of being evaluated by researchers, cognitive demand of a mental math task, and physical demand of balancing on a walking-plank. The stress response in participants was measured with two biomarkers: heart rate and salivary cortisol. Heart rate and salivary cortisol both showed significant and prolonged increases in response to the Highrise VR, suggesting that the task can successfully induce a stress response using game features. Among the participants, the response rate to the stressor was 77%, demonstrating a response rate on par with traditional standardized stress tests. Findings from this study warrant further investigation into how VR simulations induce stress for serious games and may add to a new body of literature that uses VR to investigate underlying mechanisms of physiological stress reactivity.This is a manuscript of a proceeding published as Finseth, Tor, Neil Barnett, Elizabeth A. Shirtcliff, Michael C. Dorneich, and Nir Keren. "Stress Inducing Demands in Virtual Environments." Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 62, no. 1 (2018): 2066-2070. DOI: 10.1177%2F1541931218621466. Posted with permission.</p