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, Alexandre; Richardson, Glen, & Mezghani, Neila (2018). Knee Kinematics Feature Selection for Surgical and Nonsurgical Arthroplasty Candidate Characterization. In 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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Item Type:	Papers in Conference Proceedings
Refereed:	Yes
Status:	Published
Abstract:	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.
Depositor:	Mezghani, Neila
Owner / Manager:	Neila Mezghani
Deposited:	12 Feb 2018 18:50
Last Modified:	25 Oct 2019 18:09

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