PHM for Astronauts – A New Application

Alexandre Popov, Wolfgang Fink, and Andrew Hess
Submission Type: 
Full Paper
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phmc_13_083.pdf401.08 KBOctober 10, 2013 - 5:41pm

This paper introduces a concept and approach on bridging Prognostics and Health Management (PHM), an engineering discipline, to Space Medicine (SM) in order to mitigate the Human Health and Performance (HH&P) risks of exploration-class space missions by focusing on efforts to reduce countermeasure mass and volume and drive the risks down to an acceptable level. The paper also discusses main risks of missions such as autonomous medical care risk (i.e., mission and long-term health risk due to the inability to provide adequate medical care throughout the mission) and Behavioral Health and Performance (BH&P) risk (i.e., mission and long-term behavioral health risk). The main objective of the HH&P technologies being developed for exploration-class missions is to maintain the health of the crew and support optimal and sustained performance throughout the duration of a mission. A PHM-based technology solution augmented with predictive diagnostics capability could be the one that meets the main objective. In discussing the similarities of and differences between the PHM and SM domains, the paper explores available solutions on crew health maintenance in terms of predictive diagnostics providing early and actionable real-time warnings of impending health problems that otherwise would have gone undetected. The paper discusses the use of PHM principles and techniques with data mining capabilities to assess the value of Electronic Health Records (EHR) augmented with real-time monitoring of data for accurate predictive diagnostics on manned space exploration programs. The proposed technology concept with predictive diagnostics capability and a pilot implementation of the technology on the International Space Station (ISS) includes evaluation and augmented research/testing of the technology, which will regularly and efficiently provide advancements during the development phases.

Publication Year: 
2013
Publication Volume: 
4
Publication Control Number: 
083
Page Count: 
8
Submission Keywords: 
prognostics and health management (PHM)
space medicine
human health and performance
prognostics
predictive analytics
predictive diagnostics
Submission Topic Areas: 
Data-driven methods for fault detection, diagnosis, and prognosis
Health management system design and engineering
Industrial applications
Model-based methods for fault detection, diagnostics, and prognosis
Software health management
Standards and methodologies
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