Literature DB >> 16430905

Alternative approach to modal gait analysis through the Karhunen-Loève decomposition: An application in the sagittal plane.

Luciano Santos Constantin Raptopoulos1, Max S Dutra, Fernando A de Noronha Castro Pinto, Armando Carlos de Pina Filho.   

Abstract

This article uses the Karhunen-Loève decomposition (KL) technique, also known as proper orthogonal decomposition (POD) or principal component analysis (PCA), to introduce the concept of gait mode, which can be used as a tool to identify gait differences among subjects or groups and to approximate gait curves. The KL is a statistical pattern analysis technique for finding dominant structures in an ensemble of data. This technique can be used to decompose a spatiotemporal signal into time-independent, orthogonal, spatial components and time-dependent amplitudes. This study demonstrates the existence of a common gait mode through the analysis of the kinematics of 57 young, healthy subjects, and how they can be used to identify different walking patterns, for instance differentiating male and female subjects.

Mesh:

Year:  2006        PMID: 16430905     DOI: 10.1016/j.jbiomech.2005.09.017

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  3 in total

1.  Analysis of multiple waveforms by means of functional principal component analysis: normal versus pathological patterns in sit-to-stand movement.

Authors:  Irene Epifanio; Carolina Avila; Alvaro Page; Carlos Atienza
Journal:  Med Biol Eng Comput       Date:  2008-04-08       Impact factor: 2.602

2.  Association between the gait pattern characteristics of older people and their two-step test scores.

Authors:  Yoshiyuki Kobayashi; Toru Ogata
Journal:  BMC Geriatr       Date:  2018-04-27       Impact factor: 3.921

3.  Kinematic characteristics during gait in frail older women identified by principal component analysis.

Authors:  Wakako Tsuchida; Yoshiyuki Kobayashi; Koh Inoue; Masanori Horie; Kumiko Yoshihara; Toshihiko Ooie
Journal:  Sci Rep       Date:  2022-01-31       Impact factor: 4.379

  3 in total

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