Publications
74 results found
Caillet A, Phillips ATM, Farina D, et al., 2022, Mathematical relationships between spinal motoneuron properties, eLife, Vol: 11, ISSN: 2050-084X
Our understanding of the behaviour of spinal alpha-motoneurons (MNs) in mammals partly relies on our knowledge of the relationships between MN membrane properties, such as MN size, resistance, rheobase, capacitance, time constant, axonal conduction velocity and afterhyperpolarization period. We reprocessed the data from 40 experimental studies in adult cat, rat and mouse MN preparations, to empirically derive a set of quantitative mathematical relationships between these MN electrophysiological and anatomical properties. This validated mathematical framework, which supports past findings that the MN membrane properties are all related to each other and clarifies the nature of their associations, is besides consistent with the Henneman’s size principle and Rall’s cable theory. The derived mathematical relationships provide a convenient tool for neuroscientists and experimenters to complete experimental datasets, to explore relationships between pairs of MN properties never concurrently observed in previous experiments, or to investigate inter-mammalian-species variations in MN membrane properties. Using this mathematical framework, modelers can build profiles of inter-consistent MN-specific properties to scale pools of MN models, with consequences on the accuracy and the interpretability of the simulations.
Bicer M, Phillips A, Modenese L, 2022, Generative deep learning applied to biomechanics: creating an infinite number of realistic walking data for modelling and data augmentation purposes, 9th World Congress of Biomechanics
Our work using generative deep learning models to generate synthetic human movement data to augment existing datasets was presented at the 9th World Congress of Biomechanics.
Bicer M, Phillips ATM, Modenese L, 2022, Altering the strength of the muscles crossing the lower limb joints only affects knee joint reaction forces, GAIT & POSTURE, Vol: 95, Pages: 210-216, ISSN: 0966-6362
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- Citations: 2
Caillet AH, Phillips ATM, Farina D, et al., 2022, Estimation of the firing behaviour of a complete motoneuron pool by combining electromyography signal decomposition and realistic motoneuron modelling
<jats:title>Abstract</jats:title><jats:p>Our understanding of the firing behaviour of motoneuron (MN) pools during human voluntary muscle contractions is currently limited to electrophysiological findings from animal experiments extrapolated to humans, mathematical models of MN pools not validated for human data, and experimental results obtained from decomposition of electromyographical (EMG) signals. These approaches are limited in accuracy or provide information on only small partitions of the MN population. Here, we propose a method based on the combination of high-density EMG (HDEMG) data and realistic modelling for predicting the behaviour of entire pools of motoneurons in humans. The method builds on a physiologically realistic model of a MN pool which predicts, from the experimental spike trains of a smaller number of individual MNs identified from decomposed HDEMG signals, the unknown recruitment and firing activity of the remaining unidentified MNs in the complete MN pool. The MN pool model is described as a cohort of single-compartment leaky fire- and-integrate (LIF) models of MNs scaled by a physiologically realistic distribution of MN electrophysiological properties and driven by a spinal synaptic input, both derived from decomposed HDEMG data. The MN spike trains and effective neural drive to muscle, predicted with this method, have been successfully validated experimentally. A representative application of the method in MN-driven neuromuscular modelling is also presented. The proposed approach provides a validated tool for neuroscientists, experimentalists, and modelers to infer the firing activity of MNs that cannot be observed experimentally, investigate the neuromechanics of human MN pools, support future experimental investigations, and advance neuromuscular modelling for investigating the neural strategies controlling human voluntary contractions.</jats:p><jats:sec><jats:title>Author Summary</jats:title>&
Modenese L, Caillet A, Phillips A, et al., 2022, A novel neuromechanical model for predicting muscle force from motoneuron spike trains, 27th Congress of the European Society of Biomechanics
Caillet A, Phillips ATM, Farina D, et al., 2022, Prediction of the firing behaviour of the motoneuron population for motoneuron-driven muscle modelling, 9th World Congress of Biomechanics
Diamond LE, Barrett RS, Modenese L, et al., 2021, Editorial: Neuromechanics of Hip Osteoarthritis, FRONTIERS IN SPORTS AND ACTIVE LIVING, Vol: 3
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- Citations: 1
Maine S, Ngo-Nguyen C, Barzan M, et al., 2021, Bisect offset ratio and cartilaginous sulcus angle are good combined predictors of recurrent patellar dislocation in children and adolescents, Journal of ISAKOS, Vol: 6, Pages: 265-270, ISSN: 2059-7754
Caillet AHD, Phillips ATM, Farina D, et al., 2021, Mathematical Relationships between Spinal Motoneuron Properties, Publisher: Cold Spring Harbor Laboratory
<jats:p>Our understanding of the behaviour of alpha-motoneurons (MNs) in mammals partly relies on our knowledge of the relationships between MN membrane properties, such as MN size, resistance, rheobase, capacitance, time constant, axonal conduction velocity and afterhyperpolarization period. Based on scattered but converging evidence, current experimental studies and review papers qualitatively assumed that some of these MN properties are related. In this systematic meta-analysis, we reprocessed the data from 40 experimental studies in adult cat, rat and mouse MN preparations in vivo to empirically derive mathematical relations between experimentally measured MN electrophysiological and anatomical properties. These mathematical relationships provide the first validated framework of MN-specific morphometric and electrophysiological properties that reproduce published experimental mammal data in vivo. These relationships moreover support the classic description of a MN as a membrane equivalent electrical circuit and describe for the first time the association between MN size and MN membrane capacitance and time constant. The obtained relationships finally indicate that motor units are recruited in order of increasing MN size, muscle unit size, MN rheobase, unit force recruitment thresholds and tetanic forces, but underlines that MN size and recruitment order may not be related to motor unit type.</jats:p>
Curreli C, Di Puccio F, Davico G, et al., 2021, Using musculoskeletal models to estimate in vivo total knee replacement kinematics and loads: effect of differences between models, Frontiers in Bioengineering and Biotechnology, Vol: 9, Pages: 1-10, ISSN: 2296-4185
Total knee replacement (TKR) is one of the most performed orthopedic surgeries to treat knee joint diseases in the elderly population. Although the survivorship of knee implants may extend beyond two decades, the poor outcome rate remains considerable. A recent computational approach used to better understand failure modes and improve TKR outcomes is based on the combination of musculoskeletal (MSK) and finite element models. This combined multiscale modeling approach is a promising strategy in the field of computational biomechanics; however, some critical aspects need to be investigated. In particular, the identification and quantification of the uncertainties related to the boundary conditions used as inputs to the finite element model due to a different definition of the MSK model are crucial. Therefore, the aim of this study is to investigate this problem, which is relevant for the model credibility assessment process. Three different generic MSK models available in the OpenSim platform were used to simulate gait, based on the experimental data from the fifth edition of the “Grand Challenge Competitions to Predict in vivo Knee Loads.” The outputs of the MSK analyses were compared in terms of relative kinematics of the knee implant components and joint reaction (JR) forces and moments acting on the tibial insert. Additionally, the estimated knee JRs were compared with those measured by the instrumented knee implant so that the “global goodness of fit” was quantified for each model. Our results indicated that the different kinematic definitions of the knee joint and the muscle model implemented in the different MSK models influenced both the motion and the load history of the artificial joint. This study demonstrates the importance of examining the influence of the model assumptions on the output results and represents the first step for future studies that will investigate how the uncertainties in the MSK models propagate on disease-speci
Caillet A, Phillips ATM, Farina D, et al., 2021, Development of a high-density EMG-driven Hill-type muscle model, XXVII Congress of the International Society of Biomechanics, Publisher: International Society of Biomechanics
Bicer M, Phillips ATM, Modenese L, 2021, Changing the strength of muscles crossing single lower limb joints only affects knee joint reaction forces, ESBiomech 2021
Our work investigating effects of muscle strenghts on joint reaction force estimations was presented at the 26th Congress of the European Society of Biomechanics.
Modenese L, Barzan M, Carty CP, 2021, Dependency of lower limb joint reaction forces on femoral version, Gait and Posture, Vol: 88, Pages: 318-321, ISSN: 0966-6362
BackgroundMusculoskeletal (MSK) models based on literature data are meant to represent a generic anatomy and are a popular tool employed by biomechanists to estimate the internal loads occurring in the lower limb joints, such as joint reaction forces (JRFs). However, since these models are normally just linearly scaled to an individual’s anthropometry, it is unclear how their estimations would be affected by the personalization of key features of the MSK anatomy, one of which is the femoral version angle.Research QuestionHow are the lower limb JRF magnitudes computed through a generic MSK model affected by changes in the femoral version?MethodsWe developed a bone-deformation tool in MATLAB (shared at https://simtk.org/projects/bone_deformity) and used it to create a set of seven OpenSim models spanning from 2˚ femoral retroversion to 40˚ anteversion. We used these models to simulate the gait of an elderly individual with an instrumented prosthesis implanted at their knee joint (5th Grand Challenge dataset) and quantified both the changes in JRFs magnitude due to varying the skeletal anatomy and their accuracy against the correspondent in vivo measurements at the knee joint.ResultsHip and knee JRF magnitudes were affected by the femoral version with variations from the unmodified generic model up to 17.9 ± 4.5% at the hip and 43.4 ± 27.1% at the knee joint. The ankle joint was unaffected by the femoral geometry. The MSK models providing the most accurate knee JRFs (root mean squared error: 0.370 ± 0.068 body weight, coefficient of determination: 0.757 ± 0.104, peak error range: 0.09−0.42 body weight) were those with femoral anteversion angle closer to that measured on the segmented bone of the individual.SignificanceFemoral version substantially affects hip and knee JRFs estimated with generic MSK models, suggesting that personalizing key MSK anatomical features might be necessary for accurate estimation of JRFs with these mode
Modenese L, Barzan M, Carty CP, 2021, Dependency of lower limb joint reaction forces on femoral anteversion, Publisher: Cold Spring Harbor Laboratory
Background Musculoskeletal (MSK) models based on literature data are meant to represent a generic anatomy and are a popular tool employed by biomechanists to estimate the internal loads occurring in the lower limb joints, such as joint reaction forces (JRFs). However, since these models are normally just linearly scaled to an individual’s anthropometry, it is unclear how their estimations would be affected by the personalization of key features of the MSK anatomy, one of which is the femoral anteversion angle.Research Question How are the lower limb JRF magnitudes computed through a generic MSK model affected by changes in the femoral anteversion?Methods We developed a bone-deformation tool in MATLAB (https://simtk.org/projects/bone_deformity) and used it to create a set of seven OpenSim models spanning from 2° femoral retroversion to 40° anteversion. We used these models to simulate the gait of an elderly individual with an instrumented prosthesis implanted at their knee joint (5th Grand Challenge dataset) and quantified both the changes in JRFs magnitude due to varying the skeletal anatomy and their accuracy against the correspondent in vivo measurements at the knee joint.Results Hip and knee JRF magnitudes were affected by the femoral anteversion with variations from the unmodified generic model up to 11.7±5.5% at the hip and 42.6±31.0% at the knee joint. The ankle joint was unaffected by the femoral geometry. The MSK models providing the most accurate knee JRFs (root mean squared error: 0.370±0.069 body weight, coefficient of determination: 0.764±0.104, largest peak error: 0.36±0.16 body weight) were those with the femoral anteversion angle closer to that measured on the segmented bone of the individual.Significance Femoral anteversion substantially affects hip and knee JRFs estimated with generic MSK models, suggesting that personalizing key MSK anatomical features might be necessary for accurate estimation of JR
Modenese L, Renault J-B, 2021, Automatic generation of personalised skeletal models of the lower limb from three-dimensional bone geometries, Journal of Biomechanics, Vol: 116, Pages: 1-11, ISSN: 0021-9290
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 evaluated against four manually created lower limb models finding remarkable agreement in the computed joint parameters, well within human operator repeatability. The coordinate systems origins were identified with maximum differences between 0.5 mm (hip joint) and 5.9 mm (subtalar joint), while the joint axes presented discrepancies between 1° (knee joint) to 11° (subtalar joint). To prove the robustness of the methodology, the models were built from four 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, together with upcoming progress in medical image segmentation techniques, will promote the use of personalised models in larger-scale studies than those hitherto undertaken.
Modenese L, 2021, modenaxe/msk-STAPLE: beta2
nice printouts and loggerrewritten joint creation functionsAdded two advanced examples (custom degrees of freedom joints and merging models)few bug fixes
Modenese L, Renault J-B, 2020, Automatic Generation of Personalised Skeletal Models of the Lower Limb from Three-Dimensional Bone Geometries
This repository contains the data, models and the MATLAB scripts to inspect and reproduce the results and figures of the associate publication available at https://doi.org/10.1016/j.jbiomech.2020.110186.A detailed description of the individual scripts and datasets is available at the GitHub repository: https://github.com/modenaxe/auto-lowerlimb-models-paper.
Saxby DJ, Killen BA, Pizzolato C, et al., 2020, Machine learning methods to support personalized neuromusculoskeletal modelling, BIOMECHANICS AND MODELING IN MECHANOBIOLOGY, Vol: 19, Pages: 1169-1185, ISSN: 1617-7959
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- Citations: 42
Modenese L, Renault J-B, 2020, Automatic Generation of Personalised Skeletal Models of the Lower Limb from Three-Dimensional Bone Geometries
<jats:title>Abstract</jats:title><jats:p>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 evaluated against four manually created lower limb models finding remarkable agreement in the computed joint parameters, well within human operator repeatability. The coordinate systems origins were identified with maximum differences between 0.5 mm (hip joint) and 5.9 mm (subtalar joint), while the joint axes presented discrepancies between 1° (knee joint) to 11° (subtalar joint). To prove the robustness of the methodology, the models were built from four 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, together with upcoming progress in medical image segmentation techniques, will promote the use of personalised models in larger-scale studies than those hitherto undertaken.</jats:p>
Modenese L, 2020, modenaxe/dog-breed-classifier: submitted version
modenaxe/dog-breed-classifier: submitted version
Modenese L, Kohout J, 2020, Automated Generation of Three-Dimensional Complex Muscle Geometries for Use in Personalised Musculoskeletal Models, ANNALS OF BIOMEDICAL ENGINEERING, Vol: 48, Pages: 1793-1804, ISSN: 0090-6964
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- Citations: 31
Benemerito I, Modenese L, Montefiori E, et al., 2020, An extended discrete element method for the estimation of contact pressure at the ankle joint during stance phase, Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine, Vol: 234, Pages: 507-516, ISSN: 0954-4119
Abnormalities in the ankle contact pressure are related to the onset of osteoarthritis. In vivo measurements are not possible with currently available techniques, so computational methods such as the finite element analysis (FEA) are often used instead. The discrete element method (DEM), a computationally efficient alternative to time-consuming FEA, has also been used to predict the joint contact pressure. It describes the articular cartilage as a bed of independent springs, assuming a linearly elastic behaviour and absence of relative motion between the bones. In this study, we present the extended DEM (EDEM) which is able to track the motion of talus over time. The method was used, with input data from a subject-specific musculoskeletal model, to predict the contact pressure in the ankle joint during gait. Results from EDEM were also compared with outputs from conventional DEM. Predicted values of contact area were larger in EDEM than they were in DEM (4.67 and 4.18 cm2, respectively). Peak values of contact pressure, attained at the toe-off, were 7.3 MPa for EDEM and 6.92 MPa for DEM. Values predicted from EDEM fell well within the ranges reported in the literature. Overall, the motion of the talus had more effect on the extension and shape of the pressure distribution than it had on the magnitude of the pressure. The results indicated that EDEM is a valid methodology for the prediction of ankle contact pressure during daily activities.
van Veen B, Montefiori E, Modenese L, et al., 2019, Muscle recruitment strategies can reduce joint loading during level walking, Journal of Biomechanics, Vol: 97, ISSN: 0021-9290
Joint inflammation, with consequent cartilage damage and pain, typically reduces functionality and affects activities of daily life in a variety of musculoskeletal diseases. Since mechanical loading is an important determinant of the disease process, a possible conservative treatment is the unloading of joints. In principle, a neuromuscular rehabilitation program aimed to promote alternative muscle recruitments could reduce the loads on the lower-limb joints during walking. The extent of joint load reduction one could expect from this approach remains unknown. Furthermore, assuming significant reductions of the load on the affected joint can be achieved, it is unclear whether, and to what extent, the other joints will be overloaded. Using subject-specific musculoskeletal models of four different participants, we computed the muscle recruitment strategies that minimised the hip, knee and ankle contact force, and predicted the contact forces such strategies induced at the other joints. Significant reductions of the peak force and impulse at the knee and hip were obtained, while only a minimal effect was found at the ankle joint. Adversely, the peak force and the impulse in non-targeted joints increased when aiming to minimize the load in an adjacent joint. These results confirm the potential of alternative muscle recruitment strategies to reduce the loading at the knee and the hip, but not at the ankle. Therefore, neuromuscular rehabilitation can be targeted to reduce the loading at affected joints but must be considered carefully in patients with multiple joints affected due to the potential adverse effects in non-targeted joints.
Montefiori E, Modenese L, Di Marco R, et al., 2019, Linking joint impairment and gait biomechanics in patients with juvenile idiopathic arthritis, Annual Review of Biomedical Engineering, Vol: 47, Pages: 2155-2167, ISSN: 1523-9829
Juvenile Idiopathic Arthritis (JIA) is a paediatric musculoskeletal disease of unknown aetiology, leading to walking alterations when the lower-limb joints are involved. Diagnosis of JIA is mostly clinical. Imaging can quantify impairments associated to inflammation and joint damage. However, treatment planning could be better supported using dynamic information, such as joint contact forces (JCFs). To this purpose, we used a musculoskeletal model to predict JCFs and investigate how JCFs varied as a result of joint impairment in eighteen children with JIA. Gait analysis data and magnetic resonance images (MRI) were used to develop patient-specific lower-limb musculoskeletal models, which were evaluated for operator-dependent variability (< 3.6°, 0.05 N kg-1 and 0.5 BW for joint angles, moments, and JCFs, respectively). Gait alterations and JCF patterns showed high between-subjects variability reflecting the pathology heterogeneity in the cohort. Higher joint impairment, assessed with MRI-based evaluation, was weakly associated to overall joint overloading. A stronger correlation was observed between impairment of one limb and overload of the contralateral limb, suggesting risky compensatory strategies being adopted, especially at the knee level. This suggests that knee overloading during gait might be a good predictor of disease progression and gait biomechanics should be used to inform treatment planning.
Barzan M, Modenese L, Carty CP, et al., 2019, Development and validation of subject-specific pediatric multibody knee kinematic models with ligamentous constraints, Journal of Biomechanics, Vol: 93, Pages: 194-203, ISSN: 0021-9290
Computational knee models that replicate the joint motion are important tools to discern difficult-to-measure functional joint biomechanics. Numerous knee kinematic models of different complexity, with either generic or subject-specific anatomy, have been presented and used to predict three-dimensional tibiofemoral (TFJ) and patellofemoral (PFJ) joint kinematics of cadavers or healthy adults, but not pediatric populations.The aims of this study were: (i) to develop subject-specific TFJ and PFJ kinematic models, with TFJ models having either rigid or extensible ligament constraints, for eight healthy pediatric participants and (ii) to validate the estimated joint and ligament kinematics against in vivo kinematics measured from magnetic resonance imaging (MRI) at four TFJ flexion angles.Three different TFJ models were created from MRIs and used to solve the TFJ kinematics: (i) 5-rigid-link parallel mechanism with rigid surface contact and isometric anterior cruciate (ACL), posterior cruciate (PCL) and medial collateral (MCL) ligaments (Δ, (ii) 6-link parallel mechanism with minimized ACL, PCL, MCL and lateral collateral ligament (LCL) length changes (Δ and (iii) 6-link parallel mechanism with prescribed ACL, PCL, MCL and LCL length variations (Δ). Each model’s geometrical parameters were optimized using a Multiple Objective Particle Swarm algorithm.When compared to MRI-measured data, Δ and Δ performed the best, with average root mean square errors below 6.93° and 4.23 mm for TFJ and PFJ angles and displacements, respectively, and below 2.01 mm for ligament lengths (<4.32% ligament strain). Therefore, within these error ranges, Δ and Δ can be used to estimate three-dimensional pediatric TFJ, PFJ and ligament kinematics and can be incorporated into lower-limb models to estimate joint kinematics and kinetics during dynamic tasks.
Montefiori E, Modenese L, Di Marco R, et al., 2019, An image-based kinematic model of the tibiotalar and subtalar joints and its application to gait analysis in children with Juvenile Idiopathic Arthritis, Journal of Biomechanics, Vol: 85, Pages: 27-36, ISSN: 0021-9290
In vivo estimates of tibiotalar and the subtalar joint kinematics can unveil unique information about gait biomechanics, especially in the presence of musculoskeletal disorders affecting the foot and ankle complex. Previous literature investigated the ankle kinematics on ex vivo data sets, but little has been reported for natural walking, and even less for pathological and juvenile populations. This paper proposes an MRI-based morphological fitting methodology for the personalised definition of the tibiotalar and the subtalar joint axes during gait, and investigated its application to characterise the ankle kinematics in twenty patients affected by Juvenile Idiopathic Arthritis (JIA). The estimated joint axes were in line with in vivo and ex vivo literature data and joint kinematics variation subsequent to inter-operator variability was in the order of 1°. The model allowed to investigate, for the first time in patients with JIA, the functional response to joint impairment. The joint kinematics highlighted changes over time that were consistent with changes in the patient's clinical pattern and notably varied from patient to patient. The heterogeneous and patient-specific nature of the effects of JIA was confirmed by the absence of a correlation between a semi-quantitative MRI-based impairment score and a variety of investigated joint kinematics indexes. In conclusion, this study showed the feasibility of using MRI and morphological fitting to identify the tibiotalar and subtalar joint axes in a non-invasive patient-specific manner. The proposed methodology represents an innovative and reliable approach to the analysis of the ankle joint kinematics in pathological juvenile populations.
Saxby DJ, Bryant AL, Van Ginckel A, et al., 2019, Greater magnitude tibiofemoral contact forces are associated with reduced prevalence of osteochondral pathologies 2-3 years following anterior cruciate ligament reconstruction, Knee Surgery, Sports Traumatology, Arthroscopy, Vol: 27, Pages: 707-715, ISSN: 0942-2056
PURPOSE: External loading of osteoarthritic and healthy knees correlates with current and future osteochondral tissue state. These relationships have not been examined following anterior cruciate ligament reconstruction. We hypothesised greater magnitude tibiofemoral contact forces were related to increased prevalence of osteochondral pathologies, and these relationships were exacerbated by concomitant meniscal injury. METHODS: This was a cross-sectional study of 100 individuals (29.7 ± 6.5 years, 78.1 ± 14.4 kg) examined 2-3 years following hamstring tendon anterior cruciate ligament reconstruction. Thirty-eight participants had concurrent meniscal pathology (30.6 ± 6.6 years, 83.3 ± 14.3 kg), which included treated and untreated meniscal injury, and 62 participants (29.8 ± 6.4 years, 74.9 ± 13.3 kg) were free of meniscal pathology. Magnetic resonance imaging of reconstructed knees was used to assess prevalence of tibiofemoral osteochondral pathologies (i.e., cartilage defects and bone marrow lesions). A calibrated electromyogram-driven neuromusculoskeletal model was used to predict medial and lateral tibiofemoral compartment contact forces from gait analysis data. Relationships between contact forces and osteochondral pathology prevalence were assessed using logistic regression models. RESULTS: In patients with reconstructed knees free from meniscal pathology, greater medial contact forces were related to reduced prevalence of medial cartilage defects (odds ratio (OR) = 0.7, Wald χ2(2) = 7.9, 95% confidence interval (CI) = 0.50-95, p = 0.02) and medial bone marrow lesions (OR = 0.8, Wald χ2(2) = 4.2, 95% CI = 0.7-0.99, p = 0.04). No significant relationships were
Tagliapietra L, Modenese L, Ceseracciu E, et al., 2018, Validation of a model-based inverse kinematics approach based on wearable inertial sensors, Computer Methods in Biomechanics and Biomedical Engineering, Vol: 21, Pages: 834-844, ISSN: 1025-5842
Wearable inertial measurement units (IMUs) are a promising solution to human motion estimation. Using IMUs 3D orientations, a model-driven inverse kinematics methodology to estimate joint angles is presented. Estimated joint angles were validated against encoder-measured kinematics (robot) and against marker-based kinematics (passive mechanism). Results are promising, with RMS angular errors respectively lower than 3 and 6 deg over a minimum range of motion of 50 deg (robot) and 160 deg (passive mechanism). Moreover, a noise robustness analysis revealed that the model-driven approach reduces the effects of experimental noises, making the proposed technique particularly suitable for application in human motion analysis.
Montefiori E, Modenese L, Di Marco R, et al., 2018, O 104 - MRI-based musculoskeletal models for the quantification of gait in children with Juvenile Idiopathic Arthritis, Gait and Posture, Vol: 65, Pages: 216-218, ISSN: 0966-6362
Juvenile Idiopathic Arthritis (JIA) is a paediatric disease of unknown aetiology potentially leading to biomechanical alterations due to local damage of joints. After assessing its reliability, a patient-specific musculoskeletal model of the lower limb was used to investigate the link between joint loading and disease activity in a cohort of JIA children with ankle involvement. We observed a common strategy aiming at protecting the affected ankles with consequent overloading of hip and knee. When quantified at patient specific level, this strategy might allow to identify those cases where a localised steroid injection might not be sufficient to induce remission.
Ng KCG, Mantovani G, Modenese L, et al., 2018, Altered walking and muscle patterns reduce hip contact forces in individuals with symptomatic cam femoroacetabular impingement, American Journal of Sports Medicine, Vol: 46, Pages: 2615-2623, ISSN: 0363-5465
Background:Cam-type femoroacetabular impingement (FAI) is a causative factor for hip pain and early hip osteoarthritis. Although cam FAI can alter hip joint biomechanics, it is unclear what role muscle forces play and how they affect the hip joint loading.Purpose/Hypothesis:The purpose was to examine the muscle contributions and hip contact forces in individuals with symptomatic cam FAI during level walking. Patients with symptomatic cam FAI would demonstrate different muscle and hip contact forces during gait.Study Design:Controlled laboratory study.Methods:Eighteen patients with symptomatic cam FAI were matched for age and body mass index with 18 control participants. Each participant’s walking kinematics and kinetics were recorded throughout a gait cycle (ipsilateral foot-strike to ipsilateral foot-off) by use of a motion capture system and force plates. Muscle and hip contact forces were subsequently computed by use of a musculoskeletal modeling program and static optimization methods.Results:The FAI group walked slower and with shorter steps, demonstrating reduced joint motions and moments during contralateral foot-strike, compared with the control group. The FAI group showed reduced psoas major (median, 1.1 newtons per bodyweight [N/BW]; interquartile range [IQR], 1.0-1.5 N/BW) and iliacus forces (median, 1.2 N/BW; IQR, 1.0-1.6 N/BW), during contralateral foot-strike, compared with the control group (median, 1.6 N/BW; IQR, 1.3-1.6 N/BW, P = .004; and median, 1.5 N/BW; IQR, 1.3-1.6 N/BW, P = .03, respectively), which resulted in lower hip contact forces in the anterior (P = .026), superior (P = .02), and medial directions (P = .038). The 3 vectors produced a resultant peak force at the anterosuperior aspect of the acetabulum for both groups, with the FAI group demonstrating a substantially lower magnitude.Conclusion:FAI participants altered their walking kinematics and kinetics, especially during contralateral foot-strike, as a protective mechanism, which
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