Jörn Kretschmer

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Potential harmful effects of ventilation therapy could be reduced by model-based predictions of the effects of ventilator settings to the patient. To obtain optimal predictions, the model has to be individualized based on patients' data. Given a nonlinear model, the result of parameter identification using iterative numerical methods depends on initial(More)
Doctors applying mechanical ventilation need to find the best balance between benefit and risk for the patient. Mathematical models simulating patient's reactions to alterations in the ventilation regime may be employed. A framework is introduced that is able to dynamically combine mathematical models from different model families to form a complex(More)
A mathematical model of gas exchange is proposed to predict time course of end-tidal CO<inf>2</inf> (etCO<inf>2</inf>) response to alterations in ventilation frequency. The model has been fit to experimental data of patients undergoing general anesthesia. The gas exchange model proposed by Chiari et al. has been extended by a variable dead space compartment(More)
BACKGROUND Successful application of mechanical ventilation as a life-saving therapy implies appropriate ventilator settings. Decision making is based on clinicians' knowledge, but can be enhanced by mathematical models that determine the individual patient state by calculating parameters that are not directly measurable. Evaluation of models may support(More)
The use of mathematical models can aid in optimizing therapy settings in ventilated patients to achieve certain therapy goals. Especially when multiple goals have to be met, the use of individualized models can be of great help. The presented work shows the potential of using models of respiratory mechanics and gas exchange to optimize minute ventilation(More)
Mathematical models are widely used to simulate physiological processes in the human body. They can be exploited for diagnostic purpose or the automation of therapeutical measures, if applied appropriately. In this work a feasible, hierarchical modeling approach with associated identification processes is proposed in the context of mechanical ventilation.(More)
Acute Respiratory Distress Syndrome (ARDS) is a major cause of morbidity and has a high rate of mortality. ARDS patients in the intensive care unit (ICU) require mechanical ventilation (MV) for breathing support, but inappropriate settings of MV can lead to ventilator induced lung injury (VILI). Those complications may be avoided by carefully optimizing(More)