Context-aware middleware for pervasive elderly homecare

  • Authors:
  • Hung Keng Pung;Tao Gu;Wenwei Xue;Paulito P. Palmes;Jian Zhu;Wen Long Ng;Chee Weng Tang;Nguyen Hoang Chung

  • Affiliations:
  • Department of Computer Science, School of Computing, National University of Singapore, Singapore;Institute for Infocomm Research, Singapore;Department of Computer Science, School of Computing, National University of Singapore, Singapore;Department of Computer Science, School of Computing, National University of Singapore, Singapore;Department of Computer Science, School of Computing, National University of Singapore, Singapore;Department of Computer Science, School of Computing, National University of Singapore, Singapore;Department of Computer Science, School of Computing, National University of Singapore, Singapore;Department of Computer Science, School of Computing, National University of Singapore, Singapore

  • Venue:
  • IEEE Journal on Selected Areas in Communications - Special issue on wireless and pervasive communications for healthcare
  • Year:
  • 2009

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Abstract

The growing aging population faces a number of challenges, including rising medical cost, inadequate number of medical doctors and healthcare professionals, as well as higher incidence of misdiagnosis. There is an increasing demand for a better healthcare support for the elderly and one promising solution is the development of a context-aware middleware infrastructure for pervasive health/wellness-care. This allows the accurate and timely delivery of health/medical information among the patients, doctors and healthcare workers through a widespread deployment of wireless sensor networks and mobile devices. In this paper, we present our design and implementation of such a Context-Aware Middleware for Pervasive Homecare (CAMPH). The middleware offers several key-enabling system services that consist of P2P-based context query processing, context reasoning for activity recognition and context-aware service management. It can be used to support the development and deployment of various homecare services for the elderly such as patient monitoring, location-based emergency response, anomalous daily activity detection, pervasive access to medical data and social networking. We have developed a prototype of the middleware and demonstrated the concept of providing a continuing-care to an elderly with the collaborative interactions spanning multiple physical spaces: person, home, office and clinic. The results of the prototype show that our middleware approach achieves good efficiency of context query processing and good accuracy of activity recognition.