Extracting a diagnostic gait signature

Heba Lakany

    Research output: Contribution to journalArticlepeer-review

    64 Citations (Scopus)


    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)1627-1637
    Number of pages11
    JournalPattern Recognition
    Issue number5
    Publication statusPublished - May 2008


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


    Dive into the research topics of 'Extracting a diagnostic gait signature'. Together they form a unique fingerprint.

    Cite this