3d International ICST Conference on Pervasive Computing Technologies for Healthcare

Research Article

An integrated multi-sensing framework for pervasive healthcare monitoring

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  • @INPROCEEDINGS{10.4108/ICST.PERVASIVEHEALTH2009.6038,
        author={M. ElHelw and J Pansiot and D. McIlwraith and R. Ali and B. Lo and L. Atallah},
        title={An integrated multi-sensing framework for pervasive healthcare monitoring},
        proceedings={3d International ICST Conference on Pervasive Computing Technologies for Healthcare},
        proceedings_a={PERVASIVEHEALTH},
        year={2009},
        month={8},
        keywords={pervasive sensing body sensor networks vision sensor networks activity recognition data fusion behaviourprofiling data visualisation},
        doi={10.4108/ICST.PERVASIVEHEALTH2009.6038}
    }
    
  • M. ElHelw
    J Pansiot
    D. McIlwraith
    R. Ali
    B. Lo
    L. Atallah
    Year: 2009
    An integrated multi-sensing framework for pervasive healthcare monitoring
    PERVASIVEHEALTH
    ICST
    DOI: 10.4108/ICST.PERVASIVEHEALTH2009.6038
M. ElHelw1,*, J Pansiot1,*, D. McIlwraith1,*, R. Ali1,*, B. Lo1,*, L. Atallah1,*
  • 1: Department of Computing, Imperial College, London, UK
*Contact email: me@doc.ic.ac.uk, jpansiot@doc.ic.ac.uk, dm05@doc.ic.ac.uk, smrali@doc.ic.ac.uk, benlo@doc.ic.ac.uk, latallah@doc.ic.ac.uk

Abstract

Pervasive healthcare provides an effective solution for monitoring the wellbeing of elderly, quantifying post-operative patient recovery and monitoring the progression of neurodegenerative diseases such as Parkinson's. However, developing functional pervasive systems is a complex task that entails the creation of appropriate sensing platforms, integration of versatile technologies for data stream management and development of elaborate data analysis techniques. This paper describes a complete and an integrated multi-sensing framework, with which the sensing platforms, data fusion and analysis algorithms, and software architecture suitable for pervasive healthcare applications are presented. The potential value of the proposed framework for pervasive patient monitoring is demonstrated and initial results obtained from our current research experiences are described.