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The goal of this work is to review the population accommodation principles and methodologies NASA Johnson Space Center has developed for the spacesuit, vehicle hardware, and habitats. NASA has defined the target population characteristics in the Human-System Integration Requirements based on the US Army Anthropometric Survey (ANSUR) database. However, the data was screened to select the cases of 30-50 year old subjects, given the historical characteristics of the crew. Further, accommodation ranges were defined for critical body measurements, as NASA aims to accommodate 1st percentile female to 99th percentile male of the crew-like population. The historical truncation thresholds of 5-95th percentiles were not used. This ensured that the accommodation range was not limited and accounted for the current astronaut population. A simulation study also showed that less than 68% of the population may have remained after multiple measurement truncations due to the anthropometry covariance patterns if the narrower range was retained. The ranges were also adjusted for long-term trends of body shape changes as predicted by the US National Health and Nutrition Examination Survey. Overall, the requirements were deemed critical to ensure the fit and accommodation of the new suit and space hardware. The requirements have specifically defined boundary cases for verifications and validations, of which the details have proven useful as standards across the different space programs. The specific use and benefits will be further discussed through case studies at the presentation.

During future missions to the Moon and Mars, each crewmember will most likely perform up to 24 hours a week of extravehicular activity (EVA) in support of exploration, science, construction, and maintenance tasks. Achieving mission objectives will require EVA systems and operations concepts that maximize human performance and efficiency while minimizing health and safety risks for crewmembers. Currently, over 450 EVAs have been performed in microgravity using the Extravehicular Mobility Unit (EMU). The EMU space suit has enabled the successful assembly and maintenance of the International Space Station (ISS) for over 20 years, as well as deployment of payload experiments, solar arrays, satellite launches and repairs. This EVA work was accomplished at a slower cadence than is expected for Moon and Mars, with ISS crewmembers performing no more than 7 EVAs during a single mission and without any back-to-back EVAs. Despite their success, ISS EVAs have resulted in more injury to EVA crewmembers than may be acceptable for long-duration exploration missions. The Apollo astronauts completed EVA tasks in suits that were designed for their short-duration lunar missions, although suit mobility problems were evident. The more frequent EVAs and more varied EVA tasks that are anticipated during the future longer-duration exploration missions will require EVA suits and systems that are better oriented to human health and performance than those used during the Apollo Program. Many of the problems that were encountered with the Apollo EVA suits (e.g., limited mobility and dexterity, high and aft center of gravity, and other features requiring significant crew compensation) will need to be corrected or mitigated to optimize EVA objectives of exploration missions. It is critical that we understand how EVA system design variables such as suit pressure, weight/mass, center-of-gravity location, joint ranges of motion, and biomedical monitoring, affects the ability of astronauts to perform safe, efficient, and effective EVAs. To achieve this understanding, EVA researchers will need to develop and execute an integrated human testing program across multiple environments. The research will provide objective data that will enable informed design decisions and crewmember standards, thereby ensuring EVA systems that optimize crewmember health, safety, efficiency, and performance. This report describes the risks to crew health, safety, performance, and efficiency caused by EVA operations, and it provides the evidence base to substantiate the importance of the risk.