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Using time-oriented data abstraction methods to optimize oxygen supply for neonates
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Using time-oriented data abstraction methods to optimize oxygen supply for neonates
Andreas Seyfang4  , Silvia Miksch4, Werner Horn5, Michael S. Urschitz6, 5, Christian Popow7 and Christian F. Poets6
| (4) |
Institute of Software Technology, University of Technology, Vienna, Austria |
| (5) |
Department of Medical Cybernetics and Artificial Intelligence, University of Vienna, and Austrian Research Institute for Artificial Intelligence, Austria |
| (6) |
Department of Neonatology and Pediatric Pulmonology, School of Medicine, Hannover, Germany |
| (7) |
Department of Pediatrics, University of Vienna, Austria |
Abstract
Therapy management needs sophisticated patient monitoring and therapy planning, especially in high-frequency domains, like
Neonatal Intensive Care Units (NICUs), where complex data sets are collected every second. An elegant method to tackle this
problem is the use of time-oriented, skeletal plans. Asgaard is a framework for the representation, visualization, and execution of such plans. These plans work on qualitative abstracted
time-oriented data which closely resemble the concepts used by experienced clinicians.
This papers presents the data abstraction unit of the Asgaard system. It provides a range of connectable data abstraction methods bridging the gap between the raw data collected by monitoring
devices and the abstract concepts used in therapeutic plans. The usability of this data abstraction unit is demonstrated by
the implementation of a controller for the automated optimization of the fraction of inspired oxygen (FiO2). The use of the time-oriented data abstraction methods results in safe and smooth adjustment actions of our controller in
a neonatal care setting.
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