Tibiofemoral contact forces during walking, running and sidestepping

Saxby, David J.; Modenese, Luca; Bryant, Adam; Gerus, Pauline; Killen, Bryce A.; Fortin, Karine; Wrigley, Tim V.; Bennell, Kim L; Cicuttini, Flavia Maria; Lloyd, David G.

doi:10.1016/j.gaitpost.2016.06.014

Cited by 119 publications

(129 citation statements)

References 38 publications

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“…The generic gait2392 OpenSim model [43] was first modified to allow calculation of external adduction/abduction moments about lateral and medial condyle contact points [40] and then scaled to fit the anthropometry of each participant. The hip joint centers were calculated using regression equations [54], while knee and ankle joint centers were calculated from markers on the femoral epicondyles and ankle malleoli, respectively.…”

Section: Methodsmentioning

confidence: 99%

“…The KAM has been positively correlated with the shape of MTFF during walking [7, 39], but this is not always the case [3, 4, 37, 40]. Studies based on instrumented tibiofemoral prostheses [41] have shown that decreases in the KAM do not necessarily result in decreases to MTFF [37], and that only small changes occurred in the MTFF for gait patterns designed 1to reduce KAM [42].…”

Section: Introductionmentioning

confidence: 99%

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Biofeedback for Gait Retraining Based on Real-Time Estimation of Tibiofemoral Joint Contact Forces

Pizzolato

Reggiani

Saxby

et al. 2017

IEEE Trans. Neural Syst. Rehabil. Eng.

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102

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Biofeedback assisted rehabilitation and intervention technologies have the potential to modify clinically relevant biomechanics. Gait retraining has been used to reduce the knee adduction moment, a surrogate of medial tibiofemoral joint loading often used in knee osteoarthritis research. In this study we present an electromyogram-driven neuromusculoskeletal model of the lower-limb to estimate, in real-time, the tibiofemoral joint loads. The model included 34 musculotendon units spanning the hip, knee, and ankle joints. Full-body inverse kinematics, inverse dynamics, and musculotendon kinematics were solved in real-time from motion capture and force plate data to estimate the knee medial tibiofemoral contact force (MTFF). We analyzed 5 healthy subjects while they were walking on an instrumented treadmill with visual biofeedback of their MTFF. Each subject was asked to modify their gait in order to vary the magnitude of their MTFF. All subjects were able to increase their MTFF, whereas only 3 subjects could decrease it, and only after receiving verbal suggestions about possible gait modification strategies. Results indicate the important role of knee muscle activation patterns in modulating the MTFF. While this study focused on the knee, the technology can be extended to examine the musculoskeletal tissue loads at different sites of the human body.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Biofeedback for Gait Retraining Based on Real-Time Estimation of Tibiofemoral Joint Contact Forces

Pizzolato

Reggiani

Saxby

et al. 2017

IEEE Trans. Neural Syst. Rehabil. Eng.

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102

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“…In recent years, user friendly musculoskeletal modelling software (e.g. OpenSim [2] and AnyBody [3]) has emerged that additionally enables calculation of muscle-tendon length [4], muscle moment arm [5] and joint contact forces [6]. The adoption of musculoskeletal modelling software for clinical 3DGA may provide additional data to identify musculoskeletal causes of dysfunction, thereby better informing the treatment decision-making process.…”

Section: Introductionmentioning

confidence: 99%

Reliability of four models for clinical gait analysis

et al. 2017

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Three-dimensional gait analysis (3DGA) has become a common clinical tool for treatment planning in children with cerebral palsy (CP). Many clinical gait laboratories use the conventional gait analysis model (e.g. Plug-in-Gait model), which uses Direct Kinematics (DK) for joint kinematic calculations, whereas, musculoskeletal models, mainly used for research, use Inverse Kinematics (IK). Musculoskeletal IK models have the advantage of enabling additional analyses which might improve the clinical decision-making in children with CP. Before any new model can be used in a clinical setting, its reliability has to be evaluated and compared to a commonly used clinical gait model (e.g. Plug-in-Gait model) which was the purpose of this study. Two testers performed 3DGA in eleven CP and seven typically developing participants on two occasions. Intra- and inter-tester standard deviations (SD) and standard error of measurement (SEM) were used to compare the reliability of two DK models (Plug-in-Gait and a six degrees-of-freedom model solved using Vicon software) and two IK models (two modifications of 'gait2392' solved using OpenSim). All models showed good reliability (mean SEM of 3.0° over all analysed models and joint angles). Variations in joint kinetics were less in typically developed than in CP participants. The modified 'gait2392' model which included all the joint rotations commonly reported in clinical 3DGA, showed reasonable reliable joint kinematic and kinetic estimates, and allows additional musculoskeletal analysis on surgically adjustable parameters, e.g. muscle-tendon lengths, and, therefore, is a suitable model for clinical gait analysis.

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“…Musculoskeletal models have proven to be powerful computational tools to study muscle function and internal forces in healthy (Hamner et al, 2010;Saxby et al, 2016) and clinical populations (Barber et al, 2017;Fox et al, 2018;Montefiori et al, 2019b). Recent technical progress in predictive simulation approaches Falisse et al, 2019) has enabled the investigation of if-then scenarios that could support planning and execution of physical interventions.…”

Section: Introductionmentioning

confidence: 99%

Automatic Generation of Personalised Skeletal Models of the Lower Limb from Three-Dimensional Bone Geometries

Modenese

Renault

2020

Preprint

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The generation of personalised and patient-specific musculoskeletal models is currently a cumbersome and time-consuming task that normally requires several processing hours and trained operators. We believe that this aspect discourages the use of computational models even when appropriate data are available and personalised biomechanical analysis would be beneficial. In this paper we present a computational tool that enables the fully automatic generation of skeletal models of the lower limb from three-dimensional bone geometries, normally obtained by segmentation of medical images. This tool was validated against four manually created lower limb models finding remarkable agreement in the computed joint parameters, well within human operator repeatability, with the only exception being the subtalar joint axis estimation, which was sensitive to the bone segmentation quality. To prove the robustness of the methodology, the models were built from datasets including both genders, anatomies ranging from juvenile to elderly and bone geometries reconstructed from high-quality computed tomography as well as lower-quality magnetic resonance imaging scans. The entire workflow, implemented in MATLAB scripting language, executed in seconds and required no operator intervention, creating lower extremity models ready to use for kinematic and kinetic analysis or as baselines for more advanced musculoskeletal modelling approaches, of which we provide some practical examples. We auspicate that this technical advancement will promote the use of personalised models in larger-scale studies than those hitherto undertaken.

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Tibiofemoral contact forces during walking, running and sidestepping

Cited by 119 publications

References 38 publications

Biofeedback for Gait Retraining Based on Real-Time Estimation of Tibiofemoral Joint Contact Forces

Biofeedback for Gait Retraining Based on Real-Time Estimation of Tibiofemoral Joint Contact Forces

Reliability of four models for clinical gait analysis

Automatic Generation of Personalised Skeletal Models of the Lower Limb from Three-Dimensional Bone Geometries

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