Extracting diagnostic gait signatures for cerebral palsy patients

    Research output: Contribution to journalArticle

    Abstract

    This research addresses the question of the existence of prominent diagnostic signatures for human walking extracted from kinematics gait data. The proposed method is based on transforming the joint motion trajectories using wavelets to extract spatio-temporal features which are then fed as input to a vector quantiser; a self-organising map for classification of walking patterns of individuals with and without pathology. We show that our proposed algorithm is successful in extracting features that successfully discriminate between individuals with and without locomotion impairment.
    LanguageEnglish
    Pages31
    JournalGait and Posture
    Volume18
    Issue numberSupplement 2
    DOIs
    Publication statusPublished - Oct 2003
    EventEuropean Society of Movement Analysis for Adults and Children - Marseille, France
    Duration: 10 Sep 2003 → …

    Fingerprint

    Cerebral Palsy
    Gait
    Walking
    Locomotion
    Biomechanical Phenomena
    Joints
    Pathology
    Research

    Keywords

    • human locomotion
    • gait analysis
    • feature extraction
    • self-organising maps
    • diagnostic signatures

    Cite this

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    abstract = "This research addresses the question of the existence of prominent diagnostic signatures for human walking extracted from kinematics gait data. The proposed method is based on transforming the joint motion trajectories using wavelets to extract spatio-temporal features which are then fed as input to a vector quantiser; a self-organising map for classification of walking patterns of individuals with and without pathology. We show that our proposed algorithm is successful in extracting features that successfully discriminate between individuals with and without locomotion impairment.",
    keywords = "human locomotion, gait analysis, feature extraction, self-organising maps, diagnostic signatures",
    author = "H. Lakany",
    note = "ESMAC Abstracts. Gait & Posture. Volume 18, Supplement 2, October 2003, Pages 80-123",
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    Extracting diagnostic gait signatures for cerebral palsy patients. / Lakany, H.

    In: Gait and Posture, Vol. 18, No. Supplement 2, 10.2003, p. 31.

    Research output: Contribution to journalArticle

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    KW - gait analysis

    KW - feature extraction

    KW - self-organising maps

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