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Correlation of movement patterns via pattern recognition.

W C Whiting1, R F Zernicke

  • 1University of California, Los Angeles, CA, USA.

Journal of Motor Behavior
|June 1, 1982
PubMed
Summary
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This study introduces a novel pattern recognition method to quantify movement similarity. The technique accurately distinguishes between different lower limb movement patterns during walking and running.

Area of Science:

  • Biomechanics
  • Movement Analysis
  • Pattern Recognition

Background:

  • Quantitative analysis of human locomotion is crucial for understanding biomechanical patterns.
  • Existing methods may lack precision in discriminating subtle differences in movement trajectories.

Purpose of the Study:

  • To develop and evaluate a structural pattern recognition method for assessing movement pattern equivalence.
  • To quantitatively determine similarity between lower limb trajectories during locomotion.

Main Methods:

  • Utilized a chain encoding technique for analyzing lower limb trajectories.
  • Employed conjoint angular displacement and angular velocity patterns for kinematic data.
  • Applied cross-correlation analysis to assess geometric congruity of motor patterns.

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Main Results:

  • The method successfully provided numerical coefficients to quantify movement pattern similarity.
  • Correlations consistently discriminated between similar and dissimilar limb movement patterns across different speeds.
  • Demonstrated effectiveness in both within- and between-subject analyses.

Conclusions:

  • The proposed structural pattern recognition method offers a reliable quantitative approach for movement analysis.
  • This technique can effectively differentiate kinematic patterns during various locomotion speeds.
  • Applicable for objective assessment of motor pattern similarity in biomechanics research.