Joint kinematic calculation based on clinical direct kinematic versus inverse kinematic gait models

Kainz, H.; Modenese, L.; Lloyd, D. G.; Maine, S.; Walsh, H. P. J.; Carty, C. P.

Affiliations

¹School of Allied Health Sciences, Menzies Health Institute Queensland, Griffith University, Gold Coast, Australia

²Centre for Musculoskeletal Research, Menzies Health Institute Queensland, Griffith University, Gold Coast, Australia

³Queensland Children's Motion Analysis Service, Queensland Paediatric Rehabilitation Service, Children's Health Queensland Hospital and Health Services, Brisbane, Australia

⁴Department of Mechanical Engineering, University of Sheffield, United Kingdom

⁵INSIGNEO Institute for in silico Medicine, The University of Sheffield, United King

Abstract

Most clinical gait laboratories use the conventional gait analysis model. This model uses a computational method called Direct Kinematics (DK) to calculate joint kinematics. In contrast, musculoskeletal modelling approaches use Inverse Kinematics (IK) to obtain joint angles. IK allows additional analysis (e.g. muscle-tendon length estimates), which may provide valuable information for clinical decision-making in people with movement disorders.

The twofold aims of the current study were: (1) to compare joint kinematics obtained by a clinical DK model (Vicon Plug-in-Gait) with those produced by a widely used IK model (available with the OpenSim distribution), and (2) to evaluate the difference in joint kinematics that can be solely attributed to the different computational methods (DK versus IK), anatomical models and marker sets by using MRI based models.

Eight children with cerebral palsy were recruited and presented for gait and MRI data collection sessions. Differences in joint kinematics up to 13° were found between the Plug-in-Gait and the gait 2392 OpenSim model. The majority of these differences (94.4%) were attributed to differences in the anatomical models, which included different anatomical segment frames and joint constraints. Different computational methods (DK versus IK) were responsible for only 2.7% of the differences. We recommend using the same anatomical model for kinematic and musculoskeletal analysis to ensure consistency between the obtained joint angles and musculoskeletal estimates.

Links

DOI: 10.1016/j.jbiomech.2016.03.052

PubMed: 27139005

WoS: 000377731200033

History

Accepted: 2016-03-28

Cited Works (23)

Year	Entry
2000	Piazza SJ, Cavanagh PR. Measurement of the screw-home motion of the knee is sensitive to errors in axis alignment. J Biomech. August 2000;33(8):1029-1034.
2006	Damsgaard M, Rasmussen J, Christensen ST, Surma E, de Zee M. Analysis of musculoskeletal systems in the AnyBody modeling system. Simul Model Pract Theory. November 2006;14(8):1100-1111.
2005	Reinbolt JA, Schutte JF, Fregly BJ, Koh BI, Haftka RT, George AD, Mitchell KH. Determination of patient-specific multi-joint kinematic models through two-level optimization. J Biomech. March 2005;38(3):621-626.
1983	Grood ES, Suntay WJ. A joint coordinate system for the clinical description of three-dimensional motions: application to the knee. J Biomech Eng. May 1983;105(2):136-144.
1993	Söderkvist I, Wedin P-Å. Determining the movements of the skeleton using well-configured markers. J Biomech. December 1993;26(12):1473-1477.
2000	Arnold AS, Salinas S, Hakawa DJ, Delp SL. Accuracy of muscle moment arms estimated from MRI-based musculoskeletal models of the lower extremity. Comput Aided Surg. 2000;5(2):108-119.
2007	Harrington ME, Zavatsky AB, Lawson SEM, Yuan Z, Theologis TN. Prediction of the hip joint centre in adults, children, and patients with cerebral palsy based on magnetic resonance imaging. J Biomech. 2007;40(3):595-602.
2016	Modenese L, Ceseracciu E, Reggiani M, Lloyd DG. Estimation of musculotendon parameters for scaled and subject specific musculoskeletal models using an optimization technique. J Biomech. January 25, 2016;49(2):141-148.
1991	Davis RB III, Õunpuu S, Tyburski D, Gage JR. A gait analysis data collection and reduction technique. Hum Mov Sci. October 1991;10(5):575-587.
2009	Andersen MS, Damsgaard M, Rasmussen J. Kinematic analysis of over-determinate biomechanical systems. Comput Methods Biomech Biomed Eng. August 2009;12(4):371-384.
2008	Schwartz MH, Rozumalski A, Trost JP. The effect of walking speed on the gait of typically developing children. J Biomech. 2008;41(8):1639-1650.
2007	Delp SL, Anderson FC, Arnold AS, Loan P, Habib A, John CT, Guendelman E, Thelen DG. OpenSim: open-source software to create and analyze dynamic simulations of movement. IEEE Trans Biomed Eng. November 2007;54(11):1940-1950.
2002	Wu G, Siegler S, Allard P, Kirtley C, Leardini A, Rosenbaum D, Whittle M, D'Lima DD, Cristofolini L, Witte H, Schmid O, Stokes I. ISB recommendation on definitions of joint coordinate system of various joints for the reporting of human joint motion, I: ankle, hip, and spine. J Biomech. 2002;35(4):543-548.
1989	Yamaguchi GT, Zajac FE. A planar model of the knee joint to characterize the knee extensor mechanism. J Biomech. 1989;22(1):1-10.
2005	Cappozzo A, Della Croce U, Leardini A, Chiari L. Human movement analysis using stereophotogrammetry, I: theoretical background. Gait Post. February 2005;21(2):186-196.
2005	Leardini A, Chiari L, Della Croce U, Cappozzo A. Human movement analysis using stereophotogrammetry, III: soft tissue artifact assessment and compensation. Gait Post. February 2005;21(2):212-225.
1999	Lu T-W, O’Connor JJ. Bone position estimation from skin marker co-ordinates using global optimisation with joint constraints. J Biomech. February 1999;32(2):129-134.
2010	Duprey S, Cheze L, Dumas R. Influence of joint constraints on lower limb kinematics estimation from skin markers using global optimization. J Biomech. 2010;43(14):2858-2862.
2010	Andersen MS, Benoit DL, Damsgaard M, Ramsey DK, Rasmussen J. Do kinematic models reduce the effects of soft tissue artefacts in skin marker-based motion analysis? an in vivo study of knee kinematics. J Biomech. January 19, 2010;43(2):268-273.
2006	Benoit DL, Ramsey DK, Lamontagne M, Xu L, Wretenberg P, Renström P. Effect of skin movement artifact on knee kinematics during gait and cutting motions measured in vivo. Gait Post. October 2006;24(2):152-164.
1990	Delp SL, Loan JP, Hoy MG, Zajac FE, Topp EL, Rosen JM. An interactive graphics-based model of the lower extremity to study orthopaedic surgical procedures. IEEE Trans Biomed Eng. 1990;37(8):757-767.
1990	Kadaba MP, Ramakrishnan HK, Wootten ME. Measurement of lower extremity kinematics during level walking. J Orthop Res. May 1990;8(3):383-392.
2005	Chiari L, Della Croce U, Leardini A, Cappozzo A. Human movement analysis using stereophotogrammetry, II: instrumental errors. Gait Post. February 2005;21(2):197-211.

Cited By (6)

Year	Entry
2018	Modenese L, Montefiori E, Wang A, Wesarg S, Viceconti M, Mazzà C. Investigation of the dependence of joint contact forces on musculotendon parameters using a codified workflow for image-based modelling. J Biomech. May 17, 2018;73:108-118.
2021	Modenese L, Renault J-B. Automatic generation of personalised skeletal models of the lower limb from three-dimensional bone geometries. J Biomech. February 12, 2021;116:110186.
2023	Slowik JS, Davico G, Viceconti M. Comparison of a single-view image-based system to a multi-camera marker-based system for human static pose estimation. J Biomech. October 2023;159:111746.
2023	Princelle D, Davico G, Viceconti M. Comparative validation of two patient-specific modelling pipelines for predicting knee joint forces during level walking. J Biomech. October 2023;159:111758.
2024	Yu P, Cen X, Mei Q, Wang A, Gu Y, Fernandez J. Differences in intra-foot movement strategies during locomotive tasks among chronic ankle instability, copers and healthy individuals. J Biomech. January 2024;162:111865.
2017	Schloemer SA. Differences in Lower Extremity Muscle Function and Coordination During Gait Between Older and Young Adults [PhD thesis]. The Ohio State University; 2017.