This paper presents a new framework, CVSys, for dynamic and fully distributed cardiovascular simulation with natural behavior flow and dynamic simulation control. This coordination framework uniquely incorporates attributes of open-endedness in terms of dynamic interactive entry of changing states during runtime, flexibility of event handling and system extensibility. The coordination framework relies on the autonomous object paradigm underlying a new distributed computing environment, MESSENGERS 1 .CVSys exploits extensive parallelism found in physiological processes. Natural behavior flow is the guiding principle of design and development, closely coupling model and compute processes to actual physical entity flow patterns, resulting in a more indigenous and a more integrated system representation. Dynamic simulation control serves to interject new events or state changes into the simulation in a random and dynamic method during runtime without halting execution and under fully distributed control. We distinguish two types of dynamic simulation control, Reflex arc network activated internally at receptor sites from detected state changes, and Simulation steering activated in response to externally introduced events. The CVSys Coordination Framework including natural behavior flow and dynamic simulation control features enable a more expressive cardiovascular modeling system. Also noteworthy is the representation of regional circulatory beds with related short term response adaptations, handled in a fully distributed and dynamic approach. Advancement of the current state of cardiovascular simulation is found in CVSys, realized through the introduction of new distributed and parallel computing methods.
This paper describes the Integrated Medical Analysis System. This evolving system consists of an integrated suite of models and tools providing quantitative and dynamic analysis from physiological function models, clinical care patient input, medical device data, and Northrop Grumman medical products. The System is being developed for requirements definition, testing, validation, control theory, and real-time diagnostic insights.Unique system integration of components is achieved. The current prototype emphasizes cardiovascular and pulmonary physiological functions and integration of patient device data. An overview of the project and preliminary findings are introduced.
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, realtime scientific visualization, and application of strong system integration principles.The Integrated Medical Analysis System (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.
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