11th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services

Research Article

Situation-Aware Mobile Health Monitoring

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  • @INPROCEEDINGS{10.4108/icst.mobiquitous.2014.257974,
        author={Pari Delir Haghighi and Averi Perera and Maria Indrawan-Santiago and Tuan Minh  Huynh},
        title={Situation-Aware Mobile Health Monitoring},
        proceedings={11th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services},
        publisher={ICST},
        proceedings_a={MOBIQUITOUS},
        year={2014},
        month={11},
        keywords={situation-aware computing data fusion mobile healthcare activity recognition energy management},
        doi={10.4108/icst.mobiquitous.2014.257974}
    }
    
  • Pari Delir Haghighi
    Averi Perera
    Maria Indrawan-Santiago
    Tuan Minh Huynh
    Year: 2014
    Situation-Aware Mobile Health Monitoring
    MOBIQUITOUS
    ICST
    DOI: 10.4108/icst.mobiquitous.2014.257974
Pari Delir Haghighi1,*, Averi Perera1, Maria Indrawan-Santiago1, Tuan Minh Huynh1
  • 1: Monash University
*Contact email: pari.delirhaghighi@monash.edu

Abstract

Recent advances in mobile computing coupled with the widespread availability of inexpensive mobile devices are the key motivating factors for the development of mobile health monitoring systems. However, to leverage the full potential of such systems for continuous and real time monitoring, there are a number of challenges that need to be addressed. This paper proposes a situation-aware mobile health monitoring framework that aims to increase not only the accuracy in identifying the occurring health conditions but also the cost-efficiency of running algorithms (e.g. the activity recognition classifier) using a situation-aware adaptation technique. The proposed framework integrates high level knowledge (i.e. user activity) with low level sensory data (e.g. heart rate) in situation reasoning and data fusion. Such holistic situational information can significantly improve accuracy of clinical decision making and self-management of chronic diseases. The implementation and evaluation of the framework for a health monitoring application is described.