8th International Conference on Body Area Networks

Research Article

Enhancement of a Body Area Network to support Smart Health monitoring at the digital home

  • @INPROCEEDINGS{10.4108/icst.bodynets.2013.253578,
        author={Laura Vadillo and Miguel Valero and Gema Gil},
        title={Enhancement of a Body Area Network to support Smart Health monitoring at the digital home},
        proceedings={8th International Conference on Body Area Networks},
        publisher={ICST},
        proceedings_a={BODYNETS},
        year={2013},
        month={10},
        keywords={smart health context aware system multiagent home platform},
        doi={10.4108/icst.bodynets.2013.253578}
    }
    
  • Laura Vadillo
    Miguel Valero
    Gema Gil
    Year: 2013
    Enhancement of a Body Area Network to support Smart Health monitoring at the digital home
    BODYNETS
    ACM
    DOI: 10.4108/icst.bodynets.2013.253578
Laura Vadillo1, Miguel Valero2,*, Gema Gil3
  • 1: T>SIC. Universidad Politécnica de Madrid
  • 2: DIATEL. Universidad Politécnica de Madrid
  • 3: Primary Care Service of Perales de Tajuña
*Contact email: mavalero@diatel.upm.es

Abstract

The deployment of home-based smart health services requires effective and reliable systems for personal and environmental data management. Cooperation between Home Area Networks (HAN) and Body Area Networks (BAN) can provide smart systems with ad hoc reasoning information to support health care. This paper details the implementation of an architecture that integrates BAN, HAN and intelligent agents to manage physiological and environmental data to proactively detect risk situations at the digital home. The system monitors dynamic situations and timely adjusts its behavior to detect user risks concerning to health. Thus, this work provides a reasoning framework to infer appropriate solutions in cases of health risk episodes. Proposed smart health monitoring approach integrates complex reasoning according to home environment, user profile and physiological parameters defined by a scalable ontology. As a result, health care demands can be detected to activate adequate internal mechanisms and report public health services for requested actions.