Extracting diagnostic gait signatures for cerebral palsy patients

H. Lakany

    Research output: Contribution to journalArticlepeer-review


    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.
    Original languageEnglish
    Pages (from-to)31
    JournalGait and Posture
    Issue numberSupplement 2
    Publication statusPublished - Oct 2003
    EventEuropean Society of Movement Analysis for Adults and Children - Marseille, France
    Duration: 10 Sep 2003 → …


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


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