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Intelligent Adaptive Monitoring for Cardiac Surveillance

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Computational Intelligence in Healthcare 4

Part of the book series: Studies in Computational Intelligence ((SCI,volume 309))

Abstract

Monitoring patients in intensive care units is a critical task. Simple condition detection is generally insufficient to diagnose a patient and may generate many false alarms to the clinician operator. Deeper knowledge is needed to discriminate among the flow of alarms those that necessitate urgent therapeutic action. Overall, it is important to take into account the monitoring context: sensor and signal context (are the signal data noisy or clear?), the patient condition (is the state of the patient evolving or stable? is the condition of the patient critical or safe?), the environmental context (do the external conditions influence the patient condition or not?). To achieve the best surveillance as possible, we propose an intelligent monitoring system that makes use of several artificial intelligence techniques: artificial neural networks for signal processing and temporal abstraction, temporal reasoning, model based diagnosis, decision rule based system for adaptivity and machine learning for knowledge acquisition. To tackle the difficulty of taking context change into account, we introduce a pilot aiming at adapting the system behavior by reconfiguring or tuning the parameters of the system modules. A prototype has been implemented and is currently experimented and evaluated. Some results, showing the benefits of the approach, are given.

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Author information

Authors and Affiliations

  1. INRIA/IRISA Rennes, France

    René Quiniou & Lucie Callens

  2. LTSI, University of Rennes 1, France

    Guy Carrault

  3. IRISA, University of Rennes 1, France

    Marie-Odile Cordier

  4. University of Lyon, University of Saint Etienne, France

    Elisa Fromont

  5. Dept. of Cardiology, CHU-University of Rennes 1, France

    Philippe Mabo

  6. IMAG, Grenoble, France

    François Portet

Authors
  1. René Quiniou
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  2. Lucie Callens
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  3. Guy Carrault
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  4. Marie-Odile Cordier
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  5. Elisa Fromont
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  6. Philippe Mabo
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  7. François Portet
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Editor information

Editors and Affiliations

  1. Institute of Technology/Computing and Software Systems, University ofWashington, Tacoma, 1900 Commerce Street, Campus Box 358426, 98402, Tacoma, WA, USA

    Isabelle Bichindaritz

  2. Flinders Medical Centre, Adelaide, South Australia, Australia

    Sachin Vaidya

  3. Royal Adelaide Hospital, Adelaide, South Australia, Australia

    Ashlesha Jain

  4. School of Electrical and Information Engineering, University of South Australia, SA 5095, South Australia, Australia

    Lakhmi C. Jain

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Quiniou, R. et al. (2010). Intelligent Adaptive Monitoring for Cardiac Surveillance. In: Bichindaritz, I., Vaidya, S., Jain, A., Jain, L.C. (eds) Computational Intelligence in Healthcare 4. Studies in Computational Intelligence, vol 309. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14464-6_15

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  • DOI: https://doi.org/10.1007/978-3-642-14464-6_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14463-9

  • Online ISBN: 978-3-642-14464-6

  • eBook Packages: EngineeringEngineering (R0)

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