Mining Gait Pattern for Clinical Locomotion Diagnosis Based on Clustering Techniques

  • Guandong Xu
  • Yanchun Zhang
  • Rezaul Begg
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4093)


Scientific gait (walking) analysis provides valuable information about an individual’s locomotion function, in turn, to assist clinical diagnosis and prevention, such as assessing treatment for patients with impaired postural control and detecting risk of falls in elderly population. While several artificial intelligence (AI) paradigms are addressed for gait analysis, they usually utilize supervised techniques where subject groups are defineda priori. In this paper, we explore to investigate gait pattern mining with clustering-based approaches, in which k-means and hierarchical clustering algorithms are employed to derive gait pattern. After feature selection and data preparation, we conduct clustering on the constructed gait data model to build up pattern-based clusters. The centroids of clusters are then treated as the subject profiles to model the various kinds of gait pattern, e.g. normal or pathological. Experiments are undertaken to visualize the derived subject clusters, evaluate the quality of clustering paradigm in terms of silhouette and mean square error and compare the results with the discovery derived from hierarchy tree analysis. In addition, analysis conducted on test data demonstrates the usability of the proposed paradigm in clinical applications.


Cerebral Palsy Gait Analysis Stride Length Gait Pattern Gait Parameter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Guandong Xu
    • 1
  • Yanchun Zhang
    • 1
  • Rezaul Begg
    • 2
  1. 1.School of Computer Science and MathematicsVictoria UniversityAustralia
  2. 2.Centre for Ageing, Rehabilitation, Exercise & SportsVictoria UniversityAustralia

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