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- W4249442828 abstract "The invited symposium session consists of four papers describing the S-PRINT project, sponsored by NASA’s Human Research Program (HRP). The efforts undertaken as part of this project were to develop tools and empirically-based guidelines that support human performance researchers, mission planners, automation designers, and astronauts in long-duration missions. The Space Performance Research Integration Tool (S- PRINT) project addresses aspects of the work environment that are characterized by workload transitions that might occur during long-duration missions. Workload transitions are a potential worst-case scenario, in which under-loaded astronauts experience automation failures that require immediate diagnosis and intervention. The research has focused on the underload situation and on the effects that fatigue has on performance, human performance during overload / multitasking situations, and on automation design factors that affect operator performance. In this symposium, the investigators will present four papers (identified below) that describe different aspects of the research completed to develop the S-PRINT model. The session will show an integrated approach of using empirical research and human performance modeling to predict operator performance in operations that are in the design phase. In part, this symposium will highlight the way that the products from this research can be used to help the above-listed users (a) anticipate and avoid potential problems related to unexpected workload transitions by identifying the expected effects of operator fatigue, automation system design, and task factors on overload performance, and to (b) assure systems can be designed in such a way as to optimize performance in space exploration missions, particularly those that are experienced during longer term missions (6+ months)." @default.
- W4249442828 created "2022-05-12" @default.
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- W4249442828 date "2015-09-01" @default.
- W4249442828 modified "2023-09-27" @default.
- W4249442828 title "Using Empirical Research and Human Performance Modeling to Predict Astronaut Performance in Long-Duration Space Missions" @default.
- W4249442828 doi "https://doi.org/10.1177/1541931215591220" @default.
- W4249442828 hasPublicationYear "2015" @default.
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