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    One-class support vector machine for joint variable selection and detection of postural balance degradation

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    Authors
    Amoud, Hassan
    Snoussi, Hichem
    Hewson, David
    Duchêne, Jacques
    Issue Date
    2009-12-31
    Subjects
    One Class classification
    feature selection
    detection
    support vector data description
    posture
    
    Metadata
    Show full item record
    Other Titles
    IFMBE Proceedings
    Abstract
    The study of the static posture is of great interest for the analysis of the deficit of the control of balance. A method of balance analysis is to use a platform of forces which makes it possible to extract displacement of the centre of pressure (COP). The parameters extracted from COP time series prove like variables keys to supervise the degradation of balance. However, the irrelevance and\or the redundancy of some of them make difficult an effective detection of degradation. The objective of this paper is the implementation of a method of detection (SVDD) and of a procedure of selection of the relevant parameters able to detect a degradation of balance. The selected criterion of selection is the maximization of the area AUC under the curve ROC.
    Citation
    Amoud H, Snoussi H, Hewson DJ, Duchene J (2009) 'One-class support vector machine for joint variable selection and detection of postural balance degradation', 4th European Conference of the International Federation for Medical and Biological Engineering - , Springer.
    Publisher
    Springer
    Journal
    5TH EUROPEAN CONFERENCE OF THE INTERNATIONAL FEDERATION FOR MEDICAL AND BIOLOGICAL ENGINEERING, PTS 1 AND 2
    URI
    http://hdl.handle.net/10547/623473
    DOI
    10.1007/978-3-540-89208-3_51
    Additional Links
    https://link.springer.com/chapter/10.1007/978-3-540-89208-3_51
    Type
    Conference papers, meetings and proceedings
    Language
    en
    ISSN
    1680-0737
    ae974a485f413a2113503eed53cd6c53
    10.1007/978-3-540-89208-3_51
    Scopus Count
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