Extracting a diagnostic gait signature

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...

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Bibliographic Details
Published inPattern recognition Vol. 41; no. 5; pp. 1627 - 1637
Main Author Lakany, Heba
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.05.2008
Subjects
Diagnostic signatures
Feature extraction
Gait analysis
Human locomotion
Self-organising maps
Human locomotion
Diagnostic signatures
Feature extraction
Gait analysis
Self-organising maps
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ISSN0031-3203
1873-5142
DOI10.1016/j.patcog.2007.11.004

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Summary: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.
ISSN:0031-3203
1873-5142
DOI:10.1016/j.patcog.2007.11.004