An application of principal component analysis for lower body kinematics between loaded and unloaded walking

Minhyung Lee, Michael Roan, Benjamin Smith

Research output: Contribution to journalArticlepeer-review

42 Scopus citations

Abstract

Load carriage is a very common daily activity at home and in the workplace. Generally, the load is in the form of an external load carried by an individual, it could also be the excessive body mass carried by an overweight individual. To quantify the effects of carrying extra weight, whether in the form of an external load or excess body mass, motion capture data were generated for a diverse subject set. This consisted of twenty-three subjects generating one hundred fifteen trials for each loading condition. This study applied principal component analysis (PCA) to motion capture data in order to analyze the lower body gait patterns for four loading conditions: normal weight unloaded, normal weight loaded, overweight unloaded and overweight loaded. PCA has been shown to be a powerful tool for analyzing complex gait data. In this analysis, it is shown that in order to quantify the effects of external loads and/or for both normal weight and overweight subjects, the first principal component (PC1) is needed. For the work in this paper, PCs were generated from lower body joint angle data. The PC1 of the hip angle and PC1 of the ankle angle are shown to be an indicator of external load and BMI effects on temporal gait data.

Original languageEnglish (US)
Pages (from-to)2226-2230
Number of pages5
JournalJournal of Biomechanics
Volume42
Issue number14
DOIs
StatePublished - Oct 16 2009

All Science Journal Classification (ASJC) codes

  • Biophysics
  • Biomedical Engineering
  • Orthopedics and Sports Medicine
  • Rehabilitation

Fingerprint

Dive into the research topics of 'An application of principal component analysis for lower body kinematics between loaded and unloaded walking'. Together they form a unique fingerprint.

Cite this