Identifiable reduced Complexity Model for the Human Respiratory and Cardiovascular System
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Proceedings of 5th MATHOD Conference, Vienna, 2006
There exist several mathematical models of the human body during exercise as presented for example in , ,  and . Even models which contain the periodicity of breathing, like the one presented by Grodins  have been developed. Most of them are highly complex and contain several unknown parameters, which however cannot be easily identified from non invasive measurements. The aim of this work is to propose a model of the cardiovascular and respiratory system of reduced complexity which captures the central characteristics of the system and can be parameterized using simple measurements. This paper starts with deriving a reduced complexity model from the model proposed by Batzel  and Khoo . An ergometer is then used to gather measurement data of a test person and to use those to identify the model parameters. The parameterized model was then implemented to simulate the behavior of the human body under aerobic exercise. Comparisons between measurements and computed values confirm the validity of the approach.
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Proceedings of 5th MATHOD Conference, February 8-10, 2006; Vienna, Austria