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Knee Kinematics Feature Selection for Surgical and Nonsurgical Arthroplasty Candidate Characterization [r-libre/1391]

Ben Arous, Mohamed Amine; Dunbar, Mickel; Arfaoui, Shaima; Mitiche, Amar; Ouakrim, Youssef; Fuentes, Alxeandre; Richardson, Glen et Mezghani, Neila (2018). Knee Kinematics Feature Selection for Surgical and Nonsurgical Arthroplasty Candidate Characterization. Dans Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018), vol. 4 (p. 176-181). SCITEPRESS. ISBN 978-989-758-279-0

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  PDF - BIOSIGNALS_2018_20_CR.pdf
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Catégorie de document : Communications dans des actes de congrès/colloques
Évaluation par un comité de lecture : Oui
Étape de publication : Publié
Résumé : Keywords: Knee Kinematic, Biomechanical Data, Feature Selection, Complexity Measures, Arthroplasty. Abstract: The purpose of this study is to investigate a method to select a set of knee kinematic data fatures to characterize surgical vs nonsurgical arthroplasty subjects. The kinematic features are generated from 3D knee kinematic data patterns, namely, rotations of flexion-extension, abduction-adduction, and tibial internal-external recorded during a walking task on a dedicated treadmill. The discrimination features are selected using three types of statistical complexity measures: the Fisher discriminant ratio, volume of overlap region, and feature efficiency. The interclass distance measurements which the features thus selected induce demonstrate their effectiveness to characterize surgical and nonsurgical subjects for arthroplasty.
Déposant: Mezghani, Neila
Responsable : Neila Mezghani
Dépôt : 12 févr. 2018 18:50
Dernière modification : 12 févr. 2018 18:50

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