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    A first approach on fault detection and isolation for cardiovascular anomalies detection

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    Type
    Conference Paper
    Authors
    Ledezma, Fernando
    Laleg-Kirati, Taous-Meriem cc
    KAUST Department
    Computational Bioscience Research Center (CBRC)
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Electrical Engineering Program
    Mechanical Engineering Program
    Date
    2015-07
    Permanent link to this record
    http://hdl.handle.net/10754/594153
    
    Metadata
    Show full item record
    Abstract
    In this paper, we use an extended version of the cardiovascular system's state space model presented by [1] and propose a fault detection and isolation methodology to study the problem of detecting cardiovascular anomalies that can originate from variations in physiological parameters and deviations in the performance of the heart's mitral and aortic valves. An observer-based approach is discussed as the basis of the method. The approach contemplates a bank of Extended Kalman Filters to achieve joint estimation of the model's states and parameters and to detect malfunctions in the valves' performance. © 2015 American Automatic Control Council.
    Citation
    Diaz Ledezma F, Laleg-Kirati TM (2015) A first approach on fault detection and isolation for cardiovascular anomalies detection. 2015 American Control Conference (ACC). Available: http://dx.doi.org/10.1109/acc.2015.7172246.
    Sponsors
    American Automatic Control Council (AACC)
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    2015 American Control Conference (ACC)
    Conference/Event name
    2015 American Control Conference, ACC 2015
    DOI
    10.1109/acc.2015.7172246
    ae974a485f413a2113503eed53cd6c53
    10.1109/acc.2015.7172246
    Scopus Count
    Collections
    Conference Papers; Electrical and Computer Engineering Program; Mechanical Engineering Program; Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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