Human gait analysis using SOM

H. Lakany

Research output: Chapter in Book/Report/Conference proceedingConference contribution book


This paper addresses the problem of analysing kinematic gait data which has been collected using 3D motion capture equipment that uses IR-reflective markers place on the joints on the lower extremities of the subject’s body. The data comprises motion trajectories of the different joints and it included normal and pathological subjects. The analysis of motion trajectories is done by combining the wavelet transform for feature extraction and a Kohonen self-organising map (SOM) for classification of walking patterns. Rules are then extracted from the SOM after self-organisation to determine the salient features characterising each cluster. As well as differentiating it from others. It is shown and experimentally verified that salient features do exist within the internal structure of the kinematic data from which diagnostic signatures are elicited. Existence of such features could be used by clinicians in the orthopaedic field.
Original languageEnglish
Title of host publicationAdvances in Self-Organising Maps
Place of PublicationLondon
Number of pages10
ISBN (Print)1852335114
Publication statusPublished - 27 Jun 2001
EventAdvances in Self-Organising Maps, Third Workshop on Self-Organising Maps - Lincoln , United Kingdom
Duration: 13 Jun 200115 Jun 2001


ConferenceAdvances in Self-Organising Maps, Third Workshop on Self-Organising Maps
Country/TerritoryUnited Kingdom


  • gait analysis
  • self organized feature maps
  • human movement


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