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Application of Grid technology for automated detection of sleep disordered breathing
Sebastian Canisius1, Thomas Penzel, Karl Kesper
1Philipps-University Marburg, Faculty of Medicine, Department for Internal Medicine, Marburg, Germany.
Abstract:
Sleep related breathing disorders (SRBD) represent a major disease in sleep medicine. For diagnosis and therapy control, extensive overnight investigations are required, encompassing long-term measurement of multiple biosignals in specialized sleep disorders centers. To date, evaluation of the examination is realized by comprehensive visual inspection of the data by an expert. Therefore, many approaches have been made to facilitate diagnosis, among them automated analysis of the ECG signal. In this article, we present a grid based infrastructure for computer aided diagnosis of SRBD, accessible for distributed users. As the analysis algorithms itself are still in a validation phase, and the Grid infrastructure is not approved for clinical applications, the application is currently used for research purposes only. But as important aspects of data-security, accessibility from protected environments, usability and fault-tolerance are already covered, the implementation is a solid base for further enhancement of the platform and paves the way for a sustainable service grid for sleep medicine.

