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Psychophysiological Monitoring of Aerospace Crew StateAs next-generation space exploration missions necessitate increasingly autonomous systems, there is a critical need to better detect and anticipate crewmember interactions with these systems. The success of present and future autonomous technology in exploration spaceflight is ultimately dependent upon safe and efficient interaction with the human operator. Optimal interaction is particularly important for surface missions during highly coordinated extravehicular activity (EVA), which consists of high physical and cognitive demands with limited ground support. Crew functional state may be affected by a number of variables including workload, stress, and motivation. Real-time assessments of crew state that do not require a crewmember’s time and attention to complete will be especially important to assess operational performance and behavioral health during flight. In response to the need for objective, passive assessment of crew state, the aim of this work is to develop an accurate and precise prediction model of human functional state for surface EVA using multi-modal psychophysiological sensing. The psychophysiological monitoring approach relies on extracting a set of features from physiological signals and using these features to classify an operator’s cognitive state. This work aims to compile a non-invasive sensor suite to collect physiological data in real-time. Training data during cognitive and more complex functional tasks will be used to develop a classifier to discriminate high and low cognitive workload crew states. The classifier will then be tested in an operationally relevant EVA simulation to predict cognitive workload over time. Once a crew state is determined, further research into specific countermeasures, such as decision support systems, would be necessary to optimize the automation and improve crew state and operational performance.
Document ID
20190032493
Acquisition Source
Johnson Space Center
Document Type
Conference Paper
Authors
Wusk, Grace C. (Virginia Tech Blacksburg, VA, United States)
Abercromby, Andrew F. (NASA Johnson Space Center Houston, TX, United States)
Gabler, Hampton C. (Virginia Tech Blacksburg, VA, United States)
Date Acquired
November 5, 2019
Publication Date
September 9, 2019
Subject Category
Man/System Technology And Life Support
Report/Patent Number
JSC-E-DAA-TN72202
Meeting Information
Meeting: ISWC/UBICOMP 2019
Location: London, Enland
Country: United Kingdom
Start Date: September 9, 2019
End Date: September 13, 2019
Sponsors: Nokia Corp.
Distribution Limits
Public
Copyright
Public Use Permitted.

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