Interpreting streaming biosignals: in search of best approaches to augmenting mobile health monitoring with machine learning for adaptive clinical decision support

Valerie M. Jones, R.J. Mendes Batista, Richard G.A. Bults, Harm op den Akker, I.A. Widya, Hermanus J. Hermens, M.H.A. Huis in 't Veld, Thijs Tönis, T. Tonis, Miriam Marie Rosé Vollenbroek-Hutten

    Research output: Contribution to conferencePaper

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    We investigate Body Area Networks for ambulant patient monitoring. As well as sensing physiological parameters, BAN applications may provide feedback to patients. Automating formulation of feedback requires realtime analysis and interpretation of streaming biosignals and other context and knowledge sources. We illustrate with two prototype applications: the first is designed to detect epileptic seizures and support appropriate intervention. The second is a decision support application aiding weight management; the goal is to promote health and prevent chronic illnesses associated with overweight/obesity. We begin to explore extending these and other m-health applications with generic AI-based decision support and machine learning. Monitoring success of different behavioural change strategies could provide a basis for machine learning, enabling adaptive clinical decision support by personalising and adapting strategies to individuals and their changing needs. Data mining applied to BAN data aggregated from large numbers of patients opens up possibilities for discovery of new clinical knowledge.
    Original languageEnglish
    Number of pages12
    Publication statusPublished - 2011
    EventWorkshop on Learning from Medical Data Streams, LEMEDS 2011 - Bled, Slovenia
    Duration: 6 Jul 20116 Jul 2011


    WorkshopWorkshop on Learning from Medical Data Streams, LEMEDS 2011
    Abbreviated titleLEMEDS



    • METIS-279172
    • IR-77943
    • Machine Learning
    • Ambulant monitoring
    • medical data streams
    • Clinical Decision Support
    • Patient monitoring
    • EWI-20458
    • Body Area Networks

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