DocumentCode
1932652
Title
Using the brain´s fight-or-flight response for predicting mental illness on the human space flight program
Author
Losik, L.
Author_Institution
Failure Anal., Capitola, PA, USA
fYear
2013
fDate
2-9 March 2013
Firstpage
1
Lastpage
20
Abstract
A predictive medicine program allows disease and illness including mental illness to be predicted using tools created to identify the presence of accelerated aging (a.k.a. disease) in electrical and mechanical equipment. When illness and disease can be predicted, actions can be taken so that the illness and disease can be prevented and eliminated. A predictive medicine program uses the same tools and practices from a prognostic and health management program to process biological and engineering diagnostic data provided in analog telemetry during prelaunch readiness and space exploration missions. The biological and engineering diagnostic data necessary to predict illness and disease is collected from the pre-launch spaceflight readiness activities and during space flight for the ground crew to perform a prognostic analysis on the results from a diagnostic analysis. The diagnostic, biological data provided in telemetry is converted to prognostic (predictive) data using the predictive algorithms. Predictive algorithms demodulate telemetry behavior. They illustrate the presence of accelerated aging/disease in normal appearing systems that function normally. Mental illness can predicted using biological diagnostic measurements provided in CCSDS telemetry from a spacecraft such as the ISS or from a manned spacecraft in deep space. The measurements used to predict mental illness include biological and engineering data from an astronaut´s circadian and ultranian rhythms. This data originates deep in the brain that is also damaged from the long-term exposure to cortisol and adrenaline anytime the body´s fight or flight response is activated. This paper defines the brain´s FOFR; the diagnostic, biological and engineering measurements needed to predict mental illness, identifies the predictive algorithms necessary to process the behavior in CCSDS analog telemetry to predict and thus prevent mental illness from occurring on human spaceflight missions.
Keywords
biomedical telemetry; brain; circadian rhythms; diseases; medical diagnostic computing; neurophysiology; patient diagnosis; CCSDS analog telemetry; accelerated aging-disease; adrenaline; analog telemetry; astronaut circadian rhythms; astronaut ultranian rhythms; biological diagnostic data; brain fight-or-flight response; cortisol; diagnostic analysis; electrical equipment; engineering diagnostic data; ground crew; health management program; human space flight program; human spaceflight missions; long-term exposure; mechanical equipment; mental illness; predictive medicine program; prelaunch spaceflight readiness activities; prognostic analysis; prognostic program; space exploration missions; Biology; Extraterrestrial measurements; Heuristic algorithms; Medical diagnostic imaging; Prediction algorithms; Receivers; Transponders;
fLanguage
English
Publisher
ieee
Conference_Titel
Aerospace Conference, 2013 IEEE
Conference_Location
Big Sky, MT
ISSN
1095-323X
Print_ISBN
978-1-4673-1812-9
Type
conf
DOI
10.1109/AERO.2013.6496840
Filename
6496840
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