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Process-Oriented Analysis for Medical Devices

Authors: Vasiliki Sfyrla, Josep Carmona, and Pascal Henck

Published in: OASIcs, Volume 36, 5th Workshop on Medical Cyber-Physical Systems (2014)


Abstract
Medical Cyber Physical Systems are widely used in modern healthcare environments. Such systems are considered life-critical due to the severity of consequences that faults may cause. Effective methods, techniques and tools for modeling and analyzing medical critical systems are of major importance for ensuring system reliability and patient safety. This work is looking at issues concerning different types of medical industry needs including safety analysis, testing, conformance checking, performance analysis and optimization. We explore the possibility of addressing these issues by exploiting information recorded in logs generated by medical devices during execution. Process-oriented analysis of logs is known as process mining, a novel field that has gained considerable interest in several contexts in the last decade. Process mining techniques will be applied to an industrial use case provided by Fresenius, a manufacturer of medical devices, for analyzing process logs generated by an infusion pump.

Cite as

Vasiliki Sfyrla, Josep Carmona, and Pascal Henck. Process-Oriented Analysis for Medical Devices. In 5th Workshop on Medical Cyber-Physical Systems. Open Access Series in Informatics (OASIcs), Volume 36, pp. 143-146, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)


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@InProceedings{sfyrla_et_al:OASIcs.MCPS.2014.143,
  author =	{Sfyrla, Vasiliki and Carmona, Josep and Henck, Pascal},
  title =	{{Process-Oriented Analysis for Medical Devices}},
  booktitle =	{5th Workshop on Medical Cyber-Physical Systems},
  pages =	{143--146},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-66-8},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{36},
  editor =	{Turau, Volker and Kwiatkowska, Marta and Mangharam, Rahul and Weyer, Christoph},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.MCPS.2014.143},
  URN =		{urn:nbn:de:0030-drops-45335},
  doi =		{10.4230/OASIcs.MCPS.2014.143},
  annote =	{Keywords: Process Logs, Process Mining, Discovery, Formal Analysis, Infusion Pump}
}
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