Abstract
An autonomous medical response agent (AMRA) is envisioned to help astronauts address medical complaints, develop a differential diagnosis, and guide self-treatment until a healthy state is restored. AMRA develops a process of personalized diagnosis and treatment through a Bayesian predictive control system that recommends therapeutic control actions to crewmembers (Menon 2020). The Human Computer Interaction (HCI) lab from NASA Ames Research Center’s (ARC) Human Systems Integration Division has collaborated with Nahlia Inc. in order to develop a human-centered design for AMRA. Funded by the Translational Research Institute for Space Health (TRISH), this design introduces an interactive user-interface prototype that guides astronauts through self-diagnosis, treatment, and rehabilitation while communicating with remote specialists in ground support (most notably a patient’s flight surgeon). The interface prototype, AMRA Aggregate Information Display (AMRA AID), is an integrated information system for comprehensive autonomous medical guidance of in-flight medical conditions experienced by crewmembers. This paper describes the interaction design process contributing to the user interface design and workflow of a crewmember using AMRA AID, developed through user research, iterative prototyping, and usability testing.
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Acknowledgments
We would like to thank the NASA flight surgeons, astronauts, and subject matter experts affiliated with NASA ExMC who consulted on this project as well as all usability test subjects at NASA Johnson Space Center and Ames Research Center who participated in studies relevant to the grant. This work has been supported by the Translational Research Institute through NASA Cooperative Agreement NNX16AO69A.
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Yashar, M., Marquez, J., Menon, J., Torron, I. (2020). Preliminary Design of an ‘Autonomous Medical Response Agent’ Interface Prototype for Long-Duration Spaceflight. In: Stephanidis, C., Marcus, A., Rosenzweig, E., Rau, PL.P., Moallem, A., Rauterberg, M. (eds) HCI International 2020 - Late Breaking Papers: User Experience Design and Case Studies. HCII 2020. Lecture Notes in Computer Science(), vol 12423. Springer, Cham. https://doi.org/10.1007/978-3-030-60114-0_37
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