Identification of knee frontal plane kinematic patterns in normal gait by principal component analysis [r-libre/297]

Mezghani, Neila; Fuentes, Alexandre; Gaudreault, Nathaly; Mitiche, Amar; Aissaoui, Rachid; Hagemeister, Nicola et De Guise, Jacques A. (2013). Identification of knee frontal plane kinematic patterns in normal gait by principal component analysis. Journal of Mechanics in Medicine and Biology, 13 (3), 284-291. https://doi.org/10.1142/S0219519413500267

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Catégorie de document :	Articles de revues
Évaluation par un comité de lecture :	Oui
Étape de publication :	Publié
Résumé :	The purpose of this study was to identify meaningful gait patterns in knee frontal plane kinematics from a large population of asymptomatic individuals. The proposed method used principal component analysis (PCA). It first reduced the data dimensionality, without loss of relevant information, by projecting the original kinematic data onto a subspace of significant principal components (PCs). This was followed by a discriminant model to separate the individuals' gait into homogeneous groups. Four descriptive gait patterns were identified and validated by clustering silhouette width and statistical hypothesis testing. The first pattern was close to neutral during the stance phase and in adduction during the swing phase (Cluster 1). The second pattern was in abduction during the stance phase and tends into adduction during the swing phase (Cluster 2). The third pattern was close to neutral during the stance phase and in abduction during the swing phase (Cluster 3) and the fourth was in abduction during both the stance and the swing phase (Cluster 4). Read More: http://www.worldscientific.com/doi/abs/10.1142/S0219519413500267
Adresse de la version officielle :	http://www.worldscientific.com/doi/abs/10.1142/S02...
Déposant:	Mezghani, Neila
Responsable :	Neila Mezghani
Dépôt :	24 oct. 2014 16:37
Dernière modification :	29 oct. 2019 15:09

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