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Tuesday, June 7, 2016

Measuring Astronaut Performance During Long Missions

NASA Harnesses Draper’s Simulation Capability to Study Crew Health & Performance

CAMBRIDGE, MA – Astronaut Scott Kelly’s year-long stay in space is helping NASA learn more about how a long stay in space can affect the human body. Kelly underwent monitoring to determine how fluid distribution in his body affected functions including his eyesight, fine motor control and reaction speed. As NASA prepares to send astronauts on long voyages into space to visit an asteroid and ultimately Mars, the agency wants to better understand how behavioral health and performance factors, including isolation, stress, and lack of sleep may affect astronaut performance, and how to address these issues.

NASA is addressing these issues and is beginning to understand how they affect mission and task performance as astronauts conduct simulated space missions in the Human Exploration Research Analog (HERA), a high-fidelity research venue at Johnson Space Center. Starting in 2017, the agency will incorporate a cockpit simulation capability from Draper that monitors how human operators interact with space vehicle systems in real time to understand how changes in behavioral health and performance affect astronauts’ ability to control a spacecraft.

NASA’s Human Research Program selected Draper on May 16 to work on “Real-Time Estimation of the Effects of a Simulated Long-Duration Exploration Mission on Flight Performance, Workload and Situation Awareness.”  

Crews will spend 45 days working inside the HERA, while scientists gather data on their health and performance. Draper’s simulator monitors performance during scenarios including docking NASA’s Orion spacecraft with the International Space Station, space walks and landing a spacecraft on a planetary surface like the Moon or Mars.

“We have a validated hardware/software solution that has operational relevance for studying the factors associated with long-duration spaceflight and how those issues affect performance on mission critical tasks,” said Kevin Duda, the project’s principal investigator and Draper’s group leader for human systems integration.

Draper’s simulator software analyzes the motion and state of the spacecraft, the pilot’s control input and their spoken verbal callouts of key system parameters to objectively estimate the pilot’s performance, workload and situation awareness. The work leverages Draper’s expertise in spacecraft controls as well as using human systems engineering to optimize systems for astronauts, soldiers and other users.

Draper's simulator can help NASA better understand the effects of long-duration space flight on astronaut performance.
Capabilities Used
Human-Centered Solutions

Draper has continued to advance the understanding and application of human-centered engineering to optimize the interaction and capabilities of the human’s ability to better understand, assimilate and convey information for critical decisions and tasks. Through its Human-Centered Solutions capability, Draper enables accomplishment of users’ most critical missions by seamlessly integrating technology into a user’s workflow. This work leverages human-computer interaction through emerging findings in applied psychophysiology and cognitive neuroscience. Draper has deep skills in the design, development, and deployment of systems to support cognition – for users seated at desks, on the move with mobile devices or maneuvering in the cockpit of vehicles – and collaboration across human-human and human-autonomous teams.

Image & Data Analytics

Draper combines specific domain expertise and knowledge of how to apply the latest analytics techniques to extract meaningful information from raw data to better understand complex, dynamic processes. Our system design approach encompasses effective organization and processing of large data sets, automated analysis using algorithms and exploitation of results. To facilitate user interaction with these processed data sets, Draper applies advanced techniques to automate understanding and correlation of patterns in the data. Draper’s expertise encompasses machine learning (including deep learning), information fusion from diverse and heterogeneous data sources, optimized coupling of data acquisition and analysis and novel methods for analysis of imagery and video data.

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