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Session: Poster session II
Session starts: Thursday 24 January, 16:00

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Thu Nguyen (ITEM)
Jörn Kretschmer (ITEM)
Knut Möller (ITEM)

Abstract:
Modern approaches to respiratory therapy based on computer modeling ought to keep up with the latest technologies. In the era of tablet PCs and smartphones, lung diagnoses and therapy optimization could be brought to patients right at their bedside. To this end, previously presented simulations of patient physiology [1] were redesigned to run on mobile devices. In order to run the application on an Android operating system, the previously developed MATLAB code must be rewritten in Java. The Java codes are then converted to a special bytecode run by Dalvik Virtual Machine provided by Android. Development tools and integrated environment required are: Android software development kit (SDK), Eclipse IDE and Android Development Tools (ADT) plugin. With ADT plugin being installed for Eclipse, Android applications are easily built and debugged using Android SDK tools. Moreover, the layout for user interface (UI) elements defined via XML is fully supported on Android. A Graphical User Interface (GUI) was designed so that one can choose any combination of a ventilation mode (Volume Control, Pressure Control, SIMV or BiPAP), a combination of submodels describing lung mechanics, gas exchange and cardiovascular dynamics. Moreover, simulation can be adapted to individual patients by selecting lung diseases (chronic obstructive pulmonary disease or adult respiratory distress syndrome), as well as enter parameters for those selections. Outputs of interest such as airway pressure or flow can be reviewed after running the simulation thanks to an android library called androidplot. Volume controlled, pressure controlled, SIMV and BiPAP ventilation applied on a 1st order respiratory mechanics [1] model have been successfully developed. Initial tests show that mobile devices can easily be implemented in today’s medical decision support. The presented software is constantly improved and extended to further implement additional ventilation modes and patient models. Simulation is run with Euler integration, Ordinary Differential Equation (ODE) solver applying Runge Kutta method with either fixed step-size or step-size control. Other solver algorithms can be added in the future. REFERENCES [1] Kretschmer J, Wahl A, Möller K, “Dynamics generated models for medical decision support systems”, Comput Biol Med., 41(10):899-907, October 2011. [2] Nguyen T, Zhao Z, Kretschmer J, Möller K, “Simulation model for patient ventilator interaction with focus on changing disease states”, 6th International Conference on Bioinformatics and Biomedical Engineering (iCBBE), Shanghai, China, 2012