Literature DB >> 29948373

Comparison of Marker-Based and Stereo Radiography Knee Kinematics in Activities of Daily Living.

Donald R Hume1, Vasiliki Kefala1, Michael D Harris2,3, Kevin B Shelburne4.   

Abstract

Movement of the marker positions relative to the body segments obscures in vivo joint level motion. Alternatively, tracking bones from radiography images can provide precise motion of the bones at the knee but is impracticable for measurement of body segment motion. Consequently, researchers have combined marker-based knee flexion with kinematic splines to approximate the translations and rotations of the tibia relative to the femur. Yet, the accuracy of predicting six degree-of-freedom joint kinematics using kinematic splines has not been evaluated. The objectives of this study were to (1) compare knee kinematics measured with a marker-based motion capture system to kinematics acquired with high speed stereo radiography (HSSR) and describe the accuracy of marker-based motion to improve interpretation of results from these methods, and (2) use HSSR to define and evaluate a new set of knee joint kinematic splines based on the in vivo kinematics of a knee extension activity. Simultaneous measurements were recorded from eight healthy subjects using HSSR and marker-based motion capture. The marker positions were applied to three models of the lower extremity to calculate tibiofemoral kinematics and compared to kinematics acquired with HSSR. As demonstrated by normalized RMSE above 1.0, varus-valgus rotation (1.26), medial-lateral (1.26), anterior-posterior (2.03), and superior-inferior translations (4.39) were not accurately measured. Using kinematic splines improved predictions in varus-valgus (0.81) rotation, and medial-lateral (0.73), anterior-posterior (0.69), and superior-inferior (0.49) translations. Using splines to predict tibiofemoral kinematics as a function knee flexion can lead to improved accuracy over marker-based motion capture alone, however this technique was limited in reproducing subject-specific kinematics.

Entities:  

Keywords:  Fluoroscopy; Motion capture; Musculoskeletal modeling; Tibiofemoral

Mesh:

Year:  2018        PMID: 29948373      PMCID: PMC7757735          DOI: 10.1007/s10439-018-2068-9

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  33 in total

1.  A point cluster method for in vivo motion analysis: applied to a study of knee kinematics.

Authors:  T P Andriacchi; E J Alexander; M K Toney; C Dyrby; J Sum
Journal:  J Biomech Eng       Date:  1998-12       Impact factor: 2.097

2.  Feasibility of using orthogonal fluoroscopic images to measure in vivo joint kinematics.

Authors:  Guoan Li; Thomas H Wuerz; Louis E DeFrate
Journal:  J Biomech Eng       Date:  2004-04       Impact factor: 2.097

3.  Effect of skin movement artifact on knee kinematics during gait and cutting motions measured in vivo.

Authors:  Daniel L Benoit; Dan K Ramsey; Mario Lamontagne; Lanyi Xu; Per Wretenberg; Per Renström
Journal:  Gait Posture       Date:  2005-11-02       Impact factor: 2.840

4.  Validation of three-dimensional model-based tibio-femoral tracking during running.

Authors:  William Anderst; Roger Zauel; Jennifer Bishop; Erinn Demps; Scott Tashman
Journal:  Med Eng Phys       Date:  2008-04-23       Impact factor: 2.242

5.  Kinematics of a bicruciate-retaining total knee arthroplasty.

Authors:  Thomas J Heyse; Joshua Slane; Geert Peersman; Margo Dirckx; Arne van de Vyver; Philipp Dworschak; Susanne Fuchs-Winkelmann; Lennart Scheys
Journal:  Knee Surg Sports Traumatol Arthrosc       Date:  2017-01-11       Impact factor: 4.342

6.  The effects of knee brace hinge design and placement on joint mechanics.

Authors:  P S Walker; J S Rovick; D D Robertson
Journal:  J Biomech       Date:  1988       Impact factor: 2.712

7.  Motion analysis of Chinese normal knees during gait based on a novel portable system.

Authors:  Yu Zhang; Zilong Yao; Shaobai Wang; Wenhan Huang; Limin Ma; Huayang Huang; Hong Xia
Journal:  Gait Posture       Date:  2015-01-28       Impact factor: 2.840

8.  A model of the lower limb for analysis of human movement.

Authors:  Edith M Arnold; Samuel R Ward; Richard L Lieber; Scott L Delp
Journal:  Ann Biomed Eng       Date:  2009-12-03       Impact factor: 3.934

9.  The inaccuracy of surface-measured model-derived tibiofemoral kinematics.

Authors:  Kang Li; Liying Zheng; Scott Tashman; Xudong Zhang
Journal:  J Biomech       Date:  2012-09-08       Impact factor: 2.712

10.  Integrating dynamic stereo-radiography and surface-based motion data for subject-specific musculoskeletal dynamic modeling.

Authors:  Liying Zheng; Kang Li; Snehal Shetye; Xudong Zhang
Journal:  J Biomech       Date:  2014-08-15       Impact factor: 2.712

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  4 in total

1.  ReadySim: A computational framework for building explicit finite element musculoskeletal simulations directly from motion laboratory data.

Authors:  Donald R Hume; Paul J Rullkoetter; Kevin B Shelburne
Journal:  Int J Numer Method Biomed Eng       Date:  2020-09-01       Impact factor: 2.747

2.  Description of soft tissue artifacts and related consequences on hindlimb kinematics during canine gait.

Authors:  Cheng-Chung Lin; Shi-Nuan Wang; Ming Lu; Tzu-Yi Chao; Tung-Wu Lu; Ching-Ho Wu
Journal:  PeerJ       Date:  2020-06-26       Impact factor: 2.984

3.  Effects of Weight-Bearing on Tibiofemoral, Patellofemoral, and Patellar Tendon Kinematics in Older Adults.

Authors:  Vasiliki Kefala; Azhar A Ali; Landon D Hamilton; Erin M Mannen; Kevin B Shelburne
Journal:  Front Bioeng Biotechnol       Date:  2022-04-14

4.  Validation of a portable marker-based motion analysis system.

Authors:  Shaobai Wang; Xiaolong Zeng; Liang Huangfu; Zhenyan Xie; Limin Ma; Wenhan Huang; Yu Zhang
Journal:  J Orthop Surg Res       Date:  2021-07-03       Impact factor: 2.359

  4 in total

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