Investigation of adaptation mechanisms during five-day dry immersion utilizing big-data analytics

Prysyazhnyuk, A; Mcgregor, C; Bersenev, E; Slonov, AV

Investigation of adaptation mechanisms during five-day dry immersion utilizing big-data analytics

Prysyazhnyuk, A Mcgregor, C

Bersenev, E Slonov, AV

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Publication Type:: Conference Proceeding
Citation:: 2018 IEEE Life Sciences Conference, LSC 2018, 2018, pp. 247 - 250
Issue Date:: 2018-12-10

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Field	Value	Language
dc.contributor.author	Prysyazhnyuk, A	en_US
dc.contributor.author	Mcgregor, C https://orcid.org/0000-0002-0491-4403	en_US
dc.contributor.author	Bersenev, E	en_US
dc.contributor.author	Slonov, AV	en_US
dc.date.issued	2018-12-10	en_US
dc.identifier.citation	2018 IEEE Life Sciences Conference, LSC 2018, 2018, pp. 247 - 250	en_US
dc.identifier.isbn	9781538667095	en_US
dc.identifier.uri	http://hdl.handle.net/10453/131673
dc.description.abstract	© 2018 IEEE. Emerging technology continues to redefine the concept of health and human capacity to adapt to various extreme environments on Earth, as well as in space, while preserving performance and alleviating adverse effects on the human body. Technological advancements enable effective modeling of extreme environmental conditions in terrestrial facilities, demonstrating great potential for scientific discovery, modernization of available countermeasure systems and development of comprehensive software tools for clinical decision support. To date, a vast amount of knowledge has been accumulated on physiological deconditioning in response to spaceflight environment. The underlying conditions are often closely associated with maladaptation, supported by changes in heart rate variability parameters. However, existing methods do not support real-time data acquisition, processing and analytics, thereby limiting the usability of physiological data to inform clinical decision making and timely introduction of countermeasure systems. The proposed extension of Artemis, big data analytics platform and modernization of the wellness algorithm, demonstrate great potential to address limitations of existing methods, while significantly improve the provision of medical care in space or in terrestrial environments for individuals working and/or living under conditions of chronic stress. Current study demonstrates application of the proposed big-data analytics framework in a 5-day dry immersion experiment.	en_US
dc.relation.ispartof	2018 IEEE Life Sciences Conference, LSC 2018	en_US
dc.relation.isbasedon	10.1109/LSC.2018.8572155	en_US
dc.title	Investigation of adaptation mechanisms during five-day dry immersion utilizing big-data analytics	en_US
dc.type	Conference Proceeding
utslib.for	0401 Atmospheric Sciences	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2018 IEEE. Emerging technology continues to redefine the concept of health and human capacity to adapt to various extreme environments on Earth, as well as in space, while preserving performance and alleviating adverse effects on the human body. Technological advancements enable effective modeling of extreme environmental conditions in terrestrial facilities, demonstrating great potential for scientific discovery, modernization of available countermeasure systems and development of comprehensive software tools for clinical decision support. To date, a vast amount of knowledge has been accumulated on physiological deconditioning in response to spaceflight environment. The underlying conditions are often closely associated with maladaptation, supported by changes in heart rate variability parameters. However, existing methods do not support real-time data acquisition, processing and analytics, thereby limiting the usability of physiological data to inform clinical decision making and timely introduction of countermeasure systems. The proposed extension of Artemis, big data analytics platform and modernization of the wellness algorithm, demonstrate great potential to address limitations of existing methods, while significantly improve the provision of medical care in space or in terrestrial environments for individuals working and/or living under conditions of chronic stress. Current study demonstrates application of the proposed big-data analytics framework in a 5-day dry immersion experiment.

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http://hdl.handle.net/10453/131673