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Proceedings Paper

Systems analysis with an integrated medical analysis system (IMAS)
Author(s): John Koelsch; Susan L. Mabry; Samuel Rodriquez; Paul Takemura
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Paper Abstract

This paper describes the integrated medical analysis system (IMAS) The evolving system consists of an integrated suite of models and tools providing quantitative and dynamic analysis from multiple physiological function models, clinical care patient input, medical device data, and integrated medical systems. The system is being developed for requirements definition, patient assessment, control theory, training, instrumentation testing and validation. Traditionally, human models and simulations are performed on small scale, isolated problems, usually consisting of detached mathematical models or measurements studies. These systems are not capable of portraying the interactive effects of such systems and certainly are not capable of integrating multiple external entities such as device data, patient data, etc. The human body in and of itself is a complex, integrated system. External monitors, treatments, and medical conditions interact at yet another level. Hence, a highly integrated, interactive simulation system with detailed subsystem models is required for effective quantitative analysis. The current prototype emphasizes cardiovascular, respiratory and thermoregulatory functions with integration of patient device data. Unique system integration of these components is achieved through four facilitators. These facilitators include a distributed interactive computing architecture, application of fluid and structural engineering principles to the models, real-time scientific visualization, and application of strong system integration principles. The IMAS forms a complex analytical tool with emphasis on integration and interaction at multiple levels between components. This unique level of integration and interaction facilitates quantitative analysis for multiple purposes and varying levels of fidelity. An overview of the project and preliminary findings are introduced.

Paper Details

Date Published: 1 May 1998
PDF: 9 pages
Proc. SPIE 3253, Biomedical Sensing and Imaging Technologies, (1 May 1998); doi: 10.1117/12.308032
Show Author Affiliations
John Koelsch, Northrop Grumman Corp. (United States)
Susan L. Mabry, Northrop Grumman Corp. (United States)
Samuel Rodriquez, Northrop Grumman Corp. (United States)
Paul Takemura, Northrop Grumman Corp. (United States)


Published in SPIE Proceedings Vol. 3253:
Biomedical Sensing and Imaging Technologies
Robert A. Lieberman; Tuan Vo-Dinh, Editor(s)

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