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Tracking Knee Joint Functional Axes through Tikhonov Filtering and Plucker Coordinates | OMICS International | Abstract

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Research Article

Tracking Knee Joint Functional Axes through Tikhonov Filtering and Plucker Coordinates

Wangdo Kim1, Yoon Hyuk Kim2, António P Veloso1 and Sean S Kohles3*
1Univ Tecn Lisboa, Fac Motricidade Humana, CIPER, LBMF. Estrada da Costa, P-1499-002 Lisbon, Portugal
2Department of Mechanical Engineering, Kyung Hee University, Yongin, 446-701, Korea
3Regenerative Bioengineering Laboratory, Departments of Mechanical and Materials Engineering and Biology, Portland State University, Portland, OR, USA
Corresponding Author : Sean S Kohles, PhD
Adjunct Professor
Departments of Mechanical and Materials Engineering and Biology
Portland State University, P.O. Box 751
Portland, OR, USA, 97207-0751
Tel: 503-516-7528
Received December 26, 2012; Accepted February 27, 2013; Published March 01, 2013
Citation: Kim W, Kim YH, Veloso AP, Kohles SS (2013) Tracking Knee Joint Functional Axes through Tikhonov Filtering and Plűcker Coordinates. J Nov Physiother S4:001. doi: 10.4172/2165-7025.S4-001
Copyright: © 2013 Kim W, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Researchers have reported several compensation methods to estimate bone and joint position from a cluster of skin-mounted markers as influenced by Soft Tissue Artifacts (STA). Tikhonov Regularization Filtering (TRF) as a means to estimate Instantaneous Screw Axes (ISA) was introduced here as a means to reduce the displacement of a rigid body to its simplest geometric form. Recent studies have suggested that the ISA of the knee, i.e., Knee Functional Axes (KFA), might be closely connected to the estimation of constraint forces such as those due to medial and lateral connective tissues. The estimations of ISAs were known to be highly sensitive to noisy data, which may be mathematically ill-posed, requiring smoothing such as that conducted by regularization. The main contribution in this work was to establish the reciprocal connection between the KFA and Ground Reaction Forces (GRF) as a means to estimate joint constraint forces. Presented results compare the computational performance with published kinetic and kinematic joint data generated from an instrumented total knee replacement. Implications of these preliminary findings with respect to dynamic alignment as a functional anatomic metric are discussed.