Accuracy and Reliability of Marker-Based Approaches to Scale the Pelvis, Thigh, and Shank Segments in Musculoskeletal Models.

Gait analysis together with musculoskeletal modeling is widely used for research. In the absence of medical images, surface marker locations are used to scale a generic model to the individual's anthropometry. Studies evaluating the accuracy and reliability of different scaling approaches in a pediatric and/or clinical population have not yet been conducted and, therefore, formed the aim of this study. Magnetic resonance images (MRI) and motion capture data were collected from 12 participants with cerebral palsy and 6 typically developed participants. Accuracy was assessed by comparing the scaled model's segment measures to the corresponding MRI measures, whereas reliability was assessed by comparing the model's segments scaled with the experimental marker locations from the first and second motion capture session. The inclusion of joint centers into the scaling process significantly increased the accuracy of thigh and shank segment length estimates compared to scaling with markers alone. Pelvis scaling approaches which included the pelvis depth measure led to the highest errors compared to the MRI measures. Reliability was similar between scaling approaches with mean ICC of 0.97. The pelvis should be scaled using pelvic width and height and the thigh and shank segment should be scaled using the proximal and distal joint centers.

[1]  Ayman Habib,et al.  OpenSim: Open-Source Software to Create and Analyze Dynamic Simulations of Movement , 2007, IEEE Transactions on Biomedical Engineering.

[2]  Marco Viceconti,et al.  Sensitivity of a subject-specific musculoskeletal model to the uncertainties on the joint axes location , 2015, Computer methods in biomechanics and biomedical engineering.

[3]  Dustin A. Bruening,et al.  A simple, anatomically based correction to the conventional ankle joint center. , 2008, Clinical biomechanics.

[4]  T. Theologis,et al.  Prediction of the hip joint centre in adults, children, and patients with cerebral palsy based on magnetic resonance imaging. , 2007, Journal of biomechanics.

[5]  A. Cappozzo,et al.  Pelvis and lower limb anatomical landmark calibration precision and its propagation to bone geometry and joint angles , 1999, Medical & Biological Engineering & Computing.

[6]  W C H Parr,et al.  Calculating the axes of rotation for the subtalar and talocrural joints using 3D bone reconstructions. , 2012, Journal of biomechanics.

[7]  Ilse Jonkers,et al.  Hip contact force in presence of aberrant bone geometry during normal and pathological gait , 2014, Journal of orthopaedic research : official publication of the Orthopaedic Research Society.

[8]  John Rasmussen,et al.  Scaling of musculoskeletal models from static and dynamic trials , 2015 .

[9]  D. Altman,et al.  Applying the right statistics: analyses of measurement studies , 2003, Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology.

[10]  Paul Suetens,et al.  Personalized MR-based musculoskeletal models compared to rescaled generic models in the presence of increased femoral anteversion: effect on hip moment arm lengths. , 2008, Gait & posture.

[11]  M. Pandy,et al.  Sensitivity of femoral strain calculations to anatomical scaling errors in musculoskeletal models of movement. , 2015, Journal of biomechanics.

[12]  F.E. Zajac,et al.  An interactive graphics-based model of the lower extremity to study orthopaedic surgical procedures , 1990, IEEE Transactions on Biomedical Engineering.

[13]  G Van der Perre,et al.  Subject-specific hip geometry and hip joint centre location affects calculated contact forces at the hip during gait. , 2009, Journal of biomechanics.

[14]  D. Downham,et al.  How to assess the reliability of measurements in rehabilitation. , 2005, American journal of physical medicine & rehabilitation.

[15]  L. S. Feldt,et al.  A Comparison of Five Methods for Estimating the Standard Error of Measurement at Specific Score Levels , 1985 .

[16]  D G Lloyd,et al.  Joint kinematic calculation based on clinical direct kinematic versus inverse kinematic gait models. , 2016, Journal of biomechanics.

[17]  David G Lloyd,et al.  Tibiofemoral Contact Forces in the Anterior Cruciate Ligament-Reconstructed Knee. , 2016, Medicine and science in sports and exercise.

[18]  Christopher P Carty,et al.  Muscle contributions to recovery from forward loss of balance by stepping. , 2014, Journal of biomechanics.

[19]  Ilse Jonkers,et al.  Computed tomography-based joint locations affect calculation of joint moments during gait when compared to scaling approaches , 2015, Computer methods in biomechanics and biomedical engineering.

[20]  Marcus G Pandy,et al.  Accuracy of generic musculoskeletal models in predicting the functional roles of muscles in human gait. , 2011, Journal of biomechanics.

[21]  Thor F Besier,et al.  Lower limb estimation from sparse landmarks using an articulated shape model. , 2016, Journal of biomechanics.

[22]  J. Fleiss,et al.  Intraclass correlations: uses in assessing rater reliability. , 1979, Psychological bulletin.

[23]  Jeffrey A Reinbolt,et al.  Crouched posture maximizes ground reaction forces generated by muscles. , 2012, Gait & posture.

[24]  Morgan Sangeux On the implementation of predictive methods to locate the hip joint centres. , 2015, Gait & posture.

[25]  David G. Lloyd,et al.  Estimation of the hip joint centre in human motion analysis: a systematic review. , 2015, Clinical biomechanics.

[26]  Christopher P Carty,et al.  The effect of femoral derotation osteotomy on transverse plane hip and pelvic kinematics in children with cerebral palsy: a systematic review and meta-analysis. , 2014, Gait & posture.