Can generic knee joint models improve the measurement of osteoarthritic knee kinematics during squatting activity?

Clément, Julien; Dumas, Raphaël; Hagemeister, Nicola; Guise, Jacques A. de

doi:10.1080/10255842.2016.1202935

Cited by 17 publications

(14 citation statements)

References 29 publications

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“…When validated against reference data on asymptomatic subjects, the typical errors for the model-derived tibiofemoral rotations were between 1° and 22° and between 1 mm and 8 mm during squat, stair ascent, gait and running movements and the errors were maximal for internal-external rotation, anterior-posterior and proximal-distal displacements [51,54,55,57,81]. A detailed outline of the errors for the model-derived tibiofemoral kinematics can be found in [3].…”

Section: Validation Against Reference Datamentioning

confidence: 99%

Multibody Kinematics Optimization for the Estimation of Upper and Lower Limb Human Joint Kinematics: A Systematized Methodological Review

Begon

Andersen

Dumas

2018

Journal of Biomechanical Engineering

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Multibody kinematics optimization (MKO) aims to reduce soft tissue artefact (STA) and is a key step in musculoskeletal modeling. The objective of this review was to identify the numerical methods, their validation and performance for the estimation of the human joint kinematics using MKO. Seventy-four papers were extracted from a systematized search in five databases and cross-referencing. Model-derived kinematics were obtained using either constrained optimization or Kalman filtering to minimize the difference between measured (i.e., by skin markers, electromagnetic or inertial sensors) and model-derived positions and/or orientations. While hinge, universal, and spherical joints prevail, advanced models (e.g., parallel and four-bar mechanisms, elastic joint) have been introduced, mainly for the knee and shoulder joints. Models and methods were evaluated using: (i) simulated data based, however, on oversimplified STA and joint models; (ii) reconstruction residual errors, ranging from 4 mm to 40 mm; (iii) sensitivity analyses which highlighted the effect (up to 36 deg and 12 mm) of model geometrical parameters, joint models, and computational methods; (iv) comparison with other approaches (i.e., single body kinematics optimization and nonoptimized kinematics); (v) repeatability studies that showed low intra- and inter-observer variability; and (vi) validation against ground-truth bone kinematics (with errors between 1 deg and 22 deg for tibiofemoral rotations and between 3 deg and 10 deg for glenohumeral rotations). Moreover, MKO was applied to various movements (e.g., walking, running, arm elevation). Additional validations, especially for the upper limb, should be undertaken and we recommend a more systematic approach for the evaluation of MKO. In addition, further model development, scaling, and personalization methods are required to better estimate the secondary degrees-of-freedom (DoF).

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Section: Validation Against Reference Datamentioning

confidence: 99%

Multibody Kinematics Optimization for the Estimation of Upper and Lower Limb Human Joint Kinematics: A Systematized Methodological Review

Begon

Andersen

Dumas

2018

Journal of Biomechanical Engineering

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“…Each joint model was assessed by considering its biofidelity to functional anatomy. However, in the context of STA reduction, joint constraints do not only have to be anatomically biofidelic but also have to 1) be easily customisable to each participant including those with musculoskeletal disorders (Clément et al, 2016) and 2) to reduce STA. Subjects' anthropometry fitting can easily be performed by adjusting each segment length based on geometrical measurements for simple upper limb models.…”

Section: Personalisation Of Upper Limb Kinematic Modelmentioning

confidence: 99%

Kinematic models of the upper limb joints for multibody kinematics optimisation: An overview

Duprey

Naaïm

Moissenet³

et al. 2017

Journal of Biomechanics

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Soft tissue artefact (STA), i.e. the motion of the skin, fat and muscles gliding on the underlying bone, may lead to a marker position error reaching up to 8.7cm for the particular case of the scapula. Multibody kinematics optimisation (MKO) is one of the most efficient approaches used to reduce STA. It consists in minimising the distance between the positions of experimental markers on a subject skin and the simulated positions of the same markers embedded on a kinematic model. However, the efficiency of MKO directly relies on the chosen kinematic model. This paper proposes an overview of the different upper limb models available in the literature and a discussion about their applicability to MKO. The advantages of each joint model with respect to its biofidelity to functional anatomy are detailed both for the shoulder and the forearm areas. Models capabilities of personalisation and of adaptation to pathological cases are also discussed. Concerning model efficiency in terms of STA reduction in MKO algorithms, a lack of quantitative assessment in the literature is noted. In priority, future studies should concern the evaluation and quantification of STA reduction depending on upper limb joint constraints

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“…The spherical joint, the most common representation of the knee in MBO (Charlton et al, 2004;Lu and O'Connor, 1999;Ojeda et al, 2014), allows all rotational movements but no translation. These models provide, in most cases, a rather inadequate 3D representation of the physiological movement of the knee (Andersen et al, 2010;Clément et al, 2017). Parallel mechanisms have also been used (Duprey et al, 2010;Gasparutto et al, 2015;Valente et al, 2015), the principle of which relies on compound joints representing an assembly of simple mechanical linkages.…”

Section: Introductionmentioning

confidence: 99%

“…Based on a number of studies assessing MBO, it may be concluded that no fully satisfactory knee joint model has been found yet (Andersen et al, 2010;Clément et al, 2017;Gasparutto et al, 2015;Richard et al, 2016). However, each of these assessment studies was performed on a single motor task (i.e., level walking, stepping-up, running or squatting).…”

Section: Introductionmentioning

confidence: 99%

Comparative assessment of knee joint models used in multi-body kinematics optimisation for soft tissue artefact compensation

Richard

Cappozzo

Dumas

2017

Journal of Biomechanics

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Estimating joint kinematics from skin-marker trajectories recorded using stereophotogrammetry is complicated by soft tissue artefact (STA), an inexorable source of error. One solution is to use a bone pose estimator based on multi-body kinematics optimisation (MKO) embedding joint constraints to compensate for STA. However, there is some debate over the effectiveness of this method. The present study aimed to quantitatively assess the degree of agreement between reference (i.e., artefact-free) knee joint kinematics and the same kinematics estimated using MKO embedding six different knee joint models. The following motor tasks were assessed: level walking, hopping, cutting, running, sit-to-stand, and step-up. Reference knee kinematics was taken from pin-marker or biplane fluoroscopic data acquired concurrently with skin-marker data, made available by the respective authors. For each motor task, Bland-Altman analysis revealed that the performance of MKO varied according to the joint model used, with a wide discrepancy in results across degrees of freedom (DoFs), models and motor tasks (with a bias between -10.2° and 13.2° and between -10.2mm and 7.2mm, and with a confidence interval up to ±14.8° and ±11.1mm, for rotation and displacement, respectively). It can be concluded that, while MKO might occasionally improve kinematics estimation, as implemented to date it does not represent a reliable solution to the STA issue.

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Can generic knee joint models improve the measurement of osteoarthritic knee kinematics during squatting activity?

Cited by 17 publications

References 29 publications

Multibody Kinematics Optimization for the Estimation of Upper and Lower Limb Human Joint Kinematics: A Systematized Methodological Review

Multibody Kinematics Optimization for the Estimation of Upper and Lower Limb Human Joint Kinematics: A Systematized Methodological Review

Kinematic models of the upper limb joints for multibody kinematics optimisation: An overview

Comparative assessment of knee joint models used in multi-body kinematics optimisation for soft tissue artefact compensation

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