Undernutrition prevention for disabled and elderly people in smart home with Bayesian networks and RFID sensors

  • Authors:
  • Nathalie Cislo

  • Affiliations:
  • PRISME Institute, University of Orleans, Bourges Cedex, France

  • Venue:
  • ICOST'10 Proceedings of the Aging friendly technology for health and independence, and 8th international conference on Smart homes and health telematics
  • Year:
  • 2010

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Abstract

Undernutrition prevention or detection for disabled or elderly people must be performed rapidly to avoid irremediable consequences. In this paper a classification of uncertainties centered on a meal notion is first proposed. Two of these uncertainties are developed in a smart home and homecare context. Meal preparation probability is evaluated by a simulation based on Naüve Bayesian Networks. To determine if a person is at risk of malnutrition or undernutrition, and to supervise prepared meal quality and quantity in terms of nutrients, the use of RFID tags is discussed, bringing many open issues for which additional sensors are proposed. This research work was initiated in a collaborative project called CaptHom.