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An Event-Driven Approach to Activity Recognition in Ambient Assisted Living

  • Holger Storf
  • Thomas Kleinberger
  • Martin Becker
  • Mario Schmitt
  • Frank Bomarius
  • Stephan Prueckner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5859)

Abstract

One central challenge of Ambient Assisted Living systems is reliable recognition of the assisted person’s current behavior, so that adequate assistance services can be offered in a specific situation. In the context of emergency support, such a situation might be an acute emergency situation or a deviation from the usual behavior. To optimize prevention of emergencies, reliable recognition of charac teristic Activities of Daily Living (ADLs) is promising. In this paper, we present our approach to processing information for the detection of ADLs in the EMERGE project. The approach is based on our multi-agent activity recog nition framework EARS with its special definition language EARL. An evaluation with controlled experiments has proven its suitability.

Keywords

Information Processing Activity Recognition Ambient Assisted Living Multi-Agent Systems Complex Event Processing 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Holger Storf
    • 1
  • Thomas Kleinberger
    • 1
  • Martin Becker
    • 1
  • Mario Schmitt
    • 1
  • Frank Bomarius
    • 1
  • Stephan Prueckner
    • 2
  1. 1.Fraunhofer-Institute Experimental Software EngineeringKaiserslauternGermany
  2. 2.Department of Anaesthesiology and Emergency MedicineWestpfalz-Klinikum GmbHKaiserslauternGermany

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