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Enhancement of Long-Term Behavioral Health Through Virtual Reality Technologies

Completed TRL 2 (started at 2, targeting 3)

Description

The behavioral health of astronauts on long duration exploration missions (LDEMs) is endangered by the negative effects of isolation, confinement, sensory deprivation, and other stressors associated with LDEMs. Decrements in behavioral health can negatively impact cognition and performance, placing mission success in jeopardy. This research proposes to target this risk by developing virtual reality(VR) technologies to enhance behavioral health. These technologies will come in two forms:1) VR accompanied by a suite of multisensory stimuli to enhance stress reduction. The incorporation of effects to target the users sense of smell and other ambient effects such as wind and heat will serve to increase user immersion and enhance the relaxing effects of the VR scene.2) A VR-based multi-player game to increase the sense of social connectedness among astronauts. Transitioning multi-player games from traditional media to VR could enhance the positive effect these games have on an individual's sense of social connectedness and increase general wellbeing. These technologies will ideally be validated in a long duration mission analog to more accurately simulate the isolation that would be experienced in a real LDEM. Validation of the effectiveness of these technologies will set the foundation for further development of VR technologies as a means of maintaining long-term behavioral health. In addition, this research will develop a machine-learning algorithm to predict an individual's performance based on the physiological and subjective data collected in the earlier experiments. This is desirable as this could simplify the process of astronaut selection and help mission control better predict astronaut performance and wellbeing.

Benefits

Validation of the effectiveness of these technologies will set the foundation for further development of VR technologies as a means of maintaining long-term behavioral health. In addition, this research will develop a machine-learning algorithm to predict an individual's performance based on the physiological and subjective data collected in the earlier experiments. This is desirable as this could simplify the process of astronaut selection and help mission control better predict astronaut performance and wellbeing.

Details

Technology areaHuman Health, Life Support, and Habitation Systems > Human Health and Performance > Behavioral Health and Performance
ProgramSpace Technology Research Grants (STRG)
Lead organizationTexas A & M University-College Station, College Station, TX
Start date2021-08-02
End date2025-08-01

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