Portuguese Conference on Artificial Intelligence

EPIA 2015: Progress in Artificial Intelligence pp 128-133 | Cite as

Clinical Decision Support for Active and Healthy Ageing: An Intelligent Monitoring Approach of Daily Living Activities

  • Antonis S. Billis
  • Nikos Katzouris
  • Alexander Artikis
  • Panagiotis D. Bamidis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9273)

Abstract

Decision support concepts such as context awareness and trend analysis are employed in a sensor-enabled environment for monitoring Activities of Daily Living and mobility patterns. Probabilistic Event Calculus is employed for the former; statistical process control techniques are applied for the latter case. The system is tested with real senior users within a lab as well as their home settings. Accumulated results show that the implementation of the two separate components, i.e. Sensor Data Fusion and Decision Support System, works adequately well. Future work suggests ways to combine both components so that more accurate inference results are achieved.

Keywords

Decision support Unobtrusiveness Sensors Context awareness Trend analysis Statistical process control Event calculus 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Antonis S. Billis
    • 1
  • Nikos Katzouris
    • 2
    • 3
  • Alexander Artikis
    • 2
  • Panagiotis D. Bamidis
    • 1
  1. 1.Medical Physics Laboratory, Medical School, Faculty of Health SciencesAristotle University of ThessalonikiThessalonikiGreece
  2. 2.Institute of Informatics and TelecommunicationsNational Center for Scientific Research ‘Demokritos’Aghia ParaskeviGreece
  3. 3.Department of Informatics and TelecommunicationsNational Kapodistrian University of AthensAthensGreece

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