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We proposed a 2D-mesh representation of the deltoid muscle to improve a realism of forces and moments predictions in a multibody shoulder model. Our 2D-mesh model was qualitatively compared to a commonly used via-point model during an arm elevation in the scapular plane and to previous in-vitro studies in terms of deltoid moment arms. The most notable improvement was observed for the moment arms of the anterior deltoid, which shows better agreement with in-vitro studies. Consequently, joint reaction force above 90° of arm elevation was more consistent with in-vivo data, validating the 2D-mesh representation of the deltoid muscle.

It is not clear whether exercise therapy significantly improves knee biomechanics during gait in osteoarthritis (OA) patients. This study aimed to determine whether targeted exercises based on a knee kinesiography exam improve biomechanical markers (BMs) compared with conventional primary care (CPC) management.This was a secondary analysis of a cluster randomized controlled trial in which patients were assigned to one of three groups: (1) Control (CPC), (2) Exercise, and (3) ExerciseEducation. Fourteen known BMs in knee OA patients were assessed. The primary outcome was the global evolution ratio (GER), which was calculated as the sum of improved BMs over the sum of deteriorated BMs 6 months after baseline assessment. GER scores were categorized with three different sets of cut-off values into clinical levels: (a) Deteriorated, (b) Stabilized, and (c) Improved. Ordinal logistic regressions were performed on the per-protocol population to determine whether there was a relationship between group assignment and GER levels.Of the 221 eligible participants, 163 were included. Two different regression models showed that patients from Group 3 (ExerciseEducation) were 2.5-times more likely to be in an upper GER level (i.e., Stabilized or Improved) than patients from the control group (both odds ratio (OR) 2.46, Wald ΧResults suggest that targeted exercises can improve biomechanical markers in knee OA patients compared with CPC treatment. Further studies are needed to confirm these findings and refine the biomechanical markers to address to maximize patients' clinical outcomes.

Objective: An important clinical gap reported by primary care physicians (PCPs) in managing knee osteoarthritis patients is the lack of validated tools to help them guide conservative treatment dec...

Background Total knee arthroplasty (TKA) is the treatment of choice for end-stage knee osteoarthritis. Postoperative static knee alignment has been recognized as a key component of successful surgery. A correction toward the kinematics of a native knee is expected after TKA, with an aim for neutral mechanical alignment. The evolution of frontal plane knee kinematics is not well understood. Methods Nineteen patients awaiting TKA were recruited. Three-dimensional knee kinematics during treadmill gait were assessed pre-operatively, 12 months after surgery, and compared to a control group of 17 asymptomatic participants. Results Mean radiographic mechanical alignment was corrected from 5.4° ± 5.0 (Standard Deviation) varus pre-operatively to 0.1° ± 2.0 (Standard Deviation) valgus postoperatively (P = 0.002). Mean stance coronal plane alignment decreased from 6.7° ± 4.0 (Standard Deviation) varus per-operatively to 2.1° ± 3.8 (Standard Deviation) postoperatively (P = 0.001). Correlation between radiographic mechanical axis angle and dynamic frontal plane alignment during gait, before and after surgery, was weak (pre-operative R = 0.41; postoperative R = 0.13) compared to control (R = 0.88). In the sagittal plane, TKA patients maintained their pre-operative stiff knee gait adaptation. Postoperative transverse plane kinematics suggested restoration of external tibial rotation during swing after TKA compared to control (Pre-operative 3.1°, postoperative 6.8°, control 7.1°, P = 0.05). Conclusion The lack of correlation between static and dynamic alignment suggests that static radiographic coronal alignment of the knee does not accurately predict dynamic behavior. In the sagittal plane, pre-operative gait adaptations were still present 12 months after surgery, supporting the need for a functional assessment to guide postoperative rehabilitation following TKA.

Bien que le concept d’innovation responsable (IR) gagne en popularite, aucune synthese d’etudes empiriques n’existe pour informer son developpement. Cet article presente les resultats d’une meta-ethnographie dont l’objectif etait de modeliser pourquoi et comment differentes IR ayant une incidence sur les determinants de la sante avaient ete developpees. Dix-sept etudes qualitatives, publiees entre 2000 et 2018, ont ete analysees afin d’elaborer ce modele. Ce dernier suggere que les IR sont orientees vers un bien commun, mais que les acteurs cherchent aussi par ces projets a satisfaire leurs interets propres. Les processus de developpement des IR impliquent des activites de nature manageriale, cognitive-technologique et normative-politique qui permettent de prendre des decisions pragmatiques et de creer un espace protecteur pour ces IR. Cette etude confirme la pertinence de plusieurs notions theoriques de l’IR, mais identifie egalement des aspects qui echappent aux logiques normatives qui prevalent actuellement dans la litterature. Codes JEL : O31, O350

Objectives The way new health technologies are being developed and brought to market undermines the sustainability of health systems around the world and limits the emergence of innovations that could generate greater system-level benefits. While Responsible Research and Innovation (RRI) offers relevant principles to address this policy problem, there are no tools to assess whether an innovation qualifies as a Responsible Innovation in Health (RIH). Drawing on RRI and health policy research, we developed a RIH Tool that entails a three-step process: screening, assessment and rating. Methods To critically evaluate and improve the constructs of the Tool, we conducted an international Delphi study with experts (n = 19) in RRl, biomedical engineering, bioethics and Health Technology Assessment who were asked to examine: (1) the inclusion and exclusion criteria that should be used to identify whether an innovation may potentially qualify as a RIH (screening); (2) the responsibility dimensions and attributes that should be measured in more detail (assessment); and (3) the scoring system that should be applied (rating). Results A large number of insightful comments was shared by experts (221 comments in Round 1; 69 in Round 2) and, after the second round, consensus was achieved for 16 of the 20 survey questions pertaining to the importance, clarity and appropriateness of the constructs. Conclusion Further development of this Tool will help to bridge an important knowledge and policy gap by enlightening the decisions made at an early stage by innovation stakeholders, such as investors, technology developers, research funding agencies and policymakers.

A large amount of data including joint kinematics, joint kinetics, clinical and functional measurements constitutes the clinical gait analysis basis which is a process whereby quantitative gait information are collected to aid in clinical decision-making. Therefore, better understanding the relationship between the biomechanical and clinical data for the knee osteoarthritis (OA) patient is for a relevant importance. It’s the purpose of this paper, which aims to analyze and visualize the correlation structure between biomechanical characteristics and clinical symptoms, and thus to provide an additional knowledge from the coupling of these parameters that will be useful for the pathology assessment of knee-joint disease in the end-staged knee OA patients. We perform two multivariate statistical approaches, first, a Canonical Correlation Analysis (CCA) to assess the multivariate association and, second, a graphical- based representation of the multivariate correlation to better understand the association between these multivariate data. Results show the usefulness of using such multivariate approaches to highlight association and specific correlation structure between the features and to extract meaningful information.

This paper aims to analyze the correlation structure between the kinematic and clinical parameters of an end-staged knee osteoarthritis population. The kinematic data are a set of characteristics derived from 3D knee kinematic patterns. The clinical parameters include the answers of a clinical questionnaire and the patient&rsquo, s demographic characteristics. The proposed method performs, first, a regularized canonical correlation analysis (RCCA) to evaluate the multivariate relationship between the clinical and kinematic datasets, and second, a combined visualization method to better understand the relationships between these multivariate data. Results show the efficiency of using different and complementary visual representation tools to highlight hidden relationships and find insights in data.

The purpose of this study is to perform data pre-processing to identify, for a subject, robust representative knee kinematic patterns from a set of three-dimensional (3D) curves, recorded during gait. In this study, we identify a representative gait of a given subject using the within-subject variability evaluation for outliers’ removal and reliable curves’ selection. The proposed pre-processing method encompasses steps of gait events detection, normalization, outlier detection and cycles’ selection. In order to measure the reliability of the subjects’ curves before and after pre-processing, we computed the intra-class correlation (ICC) estimates and their 95% confidence intervals for knee kinematics of a multicentric dataset of 226 asymptomatic subjects and knee osteoarthrosis (OA). The experimental results show that the proposed pre-processing method allows to identify representative knee kinematic patterns.

International audience; Background: The magnetic resonance imaging (MRI) parameters used to diagnose rotator cuff tears are weakly correlated to shoulder function. Our hypothesis was that adding 3-dimensional morphologic parameters resulting from biplanar radiographs (3DXR parameters) to the MRI parameters would improve this correlation.Methods: We assessed 52 patients with rotator cuff tears with an EOS Imaging radiographic examination, MRI study, and clinical evaluation of the shoulder, as well as the Constant score. The bones of the 52 shoulders were reconstructed 3-dimensionally, and eleven 3DXR parameters were automatically extracted. First, the trueness and reliability of these parameters were evaluated. Then, bivariate correlations between each parameter and the Constant score were made. A linear regression model was subsequently built to correlate the 11 parameters and 5 MRI findings with shoulder function at diagnosis, as assessed by the Constant score.Results: The parameters showed good trueness and reliability of most 3DXR parameters. Supraspinatus tear extension, muscle atrophy, and the distance between the greater and deltoid tuberosities were the only parameters with a statistically significant correlation to a lower Constant score (P < .05) in the bivariate study. These correlations were either weak or negligible. A regression model was successfully built with one MRI parameter and four 3DXR parameters. Correlation to function increased from 16.7% to 43.3% with this model.Conclusion: For patients with rotator cuff tears, the combination of MRI and 3DXR parameters of the shoulder in a linear regression model improves the correlation with the Constant score (shoulder function) at diagnosis.

One of the main motivations for classifying knee kinematic signals, namely the variation during a locomotion gait cycle of the angles the knee makes with respect to the three-dimensional (3D) planes of flexion/extension, abduction/adduction, and internal/external rotation, is to assist diagnosis of knee pathologies. These signals are informative but high dimensional, and highly variable, which has posed difficulties that have been addressed by machine learning algorithms. The purpose of this study is to investigate classification of knee kinematic signals through the entire gait using deep neural networks. The signals are first pre-processed to identify representative patterns, which are then used for deep learning of discriminative classifiers. This paper describes an efficient means of distinguishing between knee osteoarthrisis patients and asymptomatic participants, and our methods and experiments which validate it.

Objective The aim of this study was to determine the relationship between rotator cuff tear (RCT) morphologic parameters and muscle atrophy and fatty infiltration, and patient-reported outcome measures, in patients with symptomatic full-thickness RCT. Methods Rotator cuff tear location, length, width, thickness, and musculotendinous junction position were assessed in 57 magnetic resonance imaging scans and correlated to the outcome measures using multivariate regression analysis. Results Supraspinatus tendon tear length (odds ratio [OR], 2.218; 95% confidence interval [CI], 1.460-3.370), supraspinatus musculotendinous junction position (OR, 2.037; 95% CI, 1.322-3.137), and infraspinatus tendon tear width (OR, 2.371; 95% CI, 1.218-4.615) were identified as the strongest determinants of supraspinatus muscle atrophy, supraspinatus muscle fatty infiltration, and infraspinatus muscle fatty infiltration, respectively. Conclusions The extent of supraspinatus tendon and musculotendinous junction retraction influences the development of supraspinatus muscle atrophy and fatty infiltration, whereas the extent of infraspinatus tendon tear width influences the development of infraspinatus muscle fatty infiltration. Morphologic parameters defining RCT at magnetic resonance imaging did not correlate with clinical shoulder function scores.

Objective To investigate, as a discovery phase, if 3D knee kinematics assessment parameters can serve as mechanical biomarkers, more specifically as diagnostic biomarker and burden of disease biomarkers , as defined in the Burden of Disease, Investigative, Prognostic, Efficacy of Intervention and Diagnostic classification scheme for osteoarthritis (OA) ( Altman et al., 1986 ). These biomarkers consist of a set of biomechanical parameters discerned from 3D knee kinematic patterns, namely, flexion/extension, abduction/adduction, and tibial internal/external rotation measurements, during gait recording. Methods 100 medial compartment knee OA patients and 40 asymptomatic control subjects participated in this study. OA patients were categorized according to disease severity, by the Kellgren and Lawrence grading system. The proposed biomarkers were identified by incremental parameter selection in a regression tree of cross-sectional data. Biomarker effectiveness was evaluated by receiver operating characteristic curve analysis, namely, the area under the curve (AUC), sensitivity and specificity. Results Diagnostic biomarkers were defined by a set of 3 abduction/adduction kinematics parameters. The performance of these biomarkers reached 85% for the AUC, 80% for sensitivity and 90% for specificity; the likelihood ratio was 8%. Burden of disease biomarkers were defined by a 3-decision tree, with sets of kinematics parameters selected from all 3 movement planes. Conclusion The results demonstrate, as part of a discovery phase, that sets of 3D knee kinematic parameters have the potential to serve as diagnostic and burden of disease biomarkers of medial compartment knee OA.

Achieving a neutral static Hip-Knee-Ankle angle (sHKA) measured on radiographs has been considered a factor of success for total knee arthroplasty (TKA). However, recent studies have shown that sHKA seems to have no effect on TKA survivorship. sHKA is not representative of the dynamic loading occurring during gait, unlike the dynamic HKA (dHKA).The primary objective was to see if the sHKA is predictive of the dynamic HKA (dHKA). A secondary objective was to document to what degree the dHKA changes during gait.We analysed 3D knee kinematics during gait of a cohort of 90 healthy individuals with the KneeKG™ system. dHKA was calculated and compared with sHKA. Knees were considered "Stable" if the dHKA remained in valgus or varus for greater than 95% of the corresponding phase, and "Changer" otherwise. Patient characteristics of the Stable and Changer knees were compared to find associated factors.Absolute variation of dHKA during gait was 10.9 ± 5.3° for the whole cohort. The variation was less for the varus knees (10.3 ± 4.8°), than for the valgus knees (12.8 ± 6.1°, p = 0.008). We found low to moderate correlations (r = 0.266 to 0.553, p 0.001) between sHKA and dHKA values for varus knees and no significant correlation for valgus knees. Twenty two percent (36/165) of the knees were considered Changers. The proportion of knees that were Changers was 15% of the varus versus 39% of the valgus (p 0.001).Lower limb radiographic measures of coronal alignment have limited value for predicting dynamic measures of alignment during gait.

Background Inertial motion capture (IMC) is rapidly gaining in popularity to evaluate gait in clinical settings. Previous examinations of IMC knee kinematics were often limited to the sagittal plane and IMC calibration has not been thoroughly investigated. Research question The objective was to validate IMC 3D knee kinematics calibrated with a double-pose during gait with reference to optical motion capture (OMC). The hypotheses are that IMC can estimate adequately knee kinematics and that both systems will detect similarly the changes with gait speed. Methods Twenty-four healthy participants walked on the treadmill at gait speed of 0.6, 0.8, 1.0 and 1.2 m/s. Knee kinematics were obtained simultaneously with two magnetic and inertial measurement units and passive markers fixed on the KneeKG system. OMC was calibrated with a functional anatomical approach and the IMC with a double-pose. Results Root mean square differences of the two systems yielded 3-6° for knee flexion, adduction and external rotation. Knee kinematics were more similar during the stance phase than the swing phase. Gait speed showed a significant progressive effect on the three knee angles that was similarly detected by the two systems. Significance IMC 3D knee kinematics can be obtained independently with a simple calibration and only two magnetic and inertial measurement units at an acceptable level of error especially during stance.

Occupational or daily-life upper-limb tasks can lead to incapacitating musculoskeletal disorders (MSDs), especially when the shoulder is recruited in repetitive or demanding tasks (overhead tasks, lifting high loadings). Preventing MSD risk requires that shoulder skeletal kinematics and muscle and joint loadings be estimated. Digital human modeling (DHM) can help provide such biomechanical measurements, difficult to obtain in vivo. Measuring the movement of the scapula (gliding freely on the thorax) and the wide range of motion (ROM) of the glenohumeral GH joint (GHJ) is the first challenge, because of soft-tissue artifact. Other problems are modeling the trajectories of pluriarticular muscles over this wide ROM and the fact that GH joint stability is mainly ensured by muscle cocontraction because of the low joint congruence. This chapter describes the difficulties and advanced methods of musculoskeletal modeling and shoulder measurement. Case studies of shoulder occupational tasks involving experiments and DHM are presented.

Measuring knee biomechanics provides valuable clinical information for defining patient-specific treatment options, including patient-oriented physical exercise programs. It can be done by a knee kinesiography test measuring the three-dimensional rotation angles (3D kinematics) during walking, thus providing objective knowledge about knee function in dynamic and weight-bearing conditions. The purpose of this study was to assess whether 3D kinematics can be efficiently used to predict the impact of a physical exercise program on the condition of knee osteoarthritis (OA) patients. The prediction was based on 3D knee kinematic data, namely flexion/extension, adduction/abduction and external/internal rotation angles collected during a treadmill walking session at baseline. These measurements are quantifiable information suitable to develop automatic and objective methods for personalized computer-aided treatment systems. The dataset included 221 patients who followed a personalized therapeutic physical exercise program for 6 months and were then assigned to one of two classes, Improved condition (I) and not-Improved condition (nI). A 10% improvement in pain was needed at the 6-month follow-up compared to baseline to be in the improved group. The developed model was able to predict I and nI with 84.4% accuracy for men and 75.5% for women using a decision tree classifier trained with 3D knee kinematic data taken at baseline and a 10-fold validation procedure. The models showed that men with an impaired control of their varus thrust and a higher pain level at baseline, and women with a greater amplitude of internal tibia rotation were more likely to report improvements in their pain level after 6 months of exercises. Results support the effectiveness of decision trees and the relevance of 3D kinematic data to objectively predict knee OA patients&rsquo, response to a treatment consisting of a physical exercise program.

This article explores how health innovation designers articulate care and responsibility when designing new health technologies. Towards this end, we draw on Tronto's ethic of care framework and Responsible Research and Innovation (RRI) scholarship to analyse interviews with Canadian health innovators (n = 31). Our findings clarify how respondents: 1) direct their attention to needs and ways to improve care; 2) mobilise their skill set to take care of problems; 3) engage in what we call ‘care-making’ practices by prioritising key material qualities; and 4) operationalise responsiveness to caregivers and care-receivers through user-centred design. We discuss the inclusion of health innovation designers within the care relationship as ‘care-makers’ as well as the tensions underlying their ways of caring and their conflicting responsibilities.

OBJECTIVES To assess the prevalence of sonographic visualization of the rotator cable in patients with symptomatic full-thickness rotator cuff tears and asymptomatic controls and to correlate rotator cable visualization with tear size, muscular fatty infiltration and atrophy, and the functional outcome in the patients with rotator cuff tears. METHODS Fifty-seven patients with rotator cuff tears and 30 asymptomatic volunteers underwent shoulder sonography for prospective assessment of the rotator cable and rotator cuff tear and responded to 2 functional outcome questionnaires (shortened Disabilities of the Arm, Shoulder, and Hand [QuickDASH] and Constant). In the patients with rotator cuff tears, appropriate tests were used to correlate rotator cable visualization with the tear size, functional outcome, muscular fatty infiltration, and atrophy. RESULTS The patients with rotator cuff tears included 25 women and 32 men (mean age,57 years; range, 39-67 years), and the volunteers included 13 women and 17 men (mean age, 56 years; range, 35-64 years). The rotator cable was identified in 77% (23 of 30) of controls and 23% (13 of 57) of patients with rotator cuff tears. In the patients, nonvisualization of the rotator cable correlated with larger tears (P < 0.001) and higher grades of supraspinatus atrophy (P = .049) and fatty infiltration (P = .022). There was no significant correlation with functional outcome scores (QuickDASH, P = .989; Constant, P = .073) or infraspinatus fatty infiltration (P = .065). CONCLUSIONS Nonvisualization of the rotator cable was more prevalent in patients with symptomatic rotator cuff tears than asymptomatic controls and was associated with a larger tear size and greater supraspinatus fatty infiltration and atrophy. Diligent assessment of the supraspinatus muscle should be done in patients with rotator cuff tears without a visible rotator cable, as the integrity of these anatomic structures may be interdependent.

Knee joint kinematics derived from multi-body optimisation (MBO) still requires evaluation. The objective of this study was to corroborate model-derived kinematics of osteoarthritic knees obtained using four generic knee joint models used in musculoskeletal modelling – spherical, hinge, degree-of-freedom coupling curves and parallel mechanism – against reference knee kinematics measured by stereo-radiography. Root mean square errors ranged from 0.7° to 23.4° for knee rotations and from 0.6 to 9.0 mm for knee displacements. Model-derived knee kinematics computed from generic knee joint models was inaccurate. Future developments and experiments should improve the reliability of osteoarthritic knee models in MBO and musculoskeletal modelling.

Background:Various implants of total knee arthroplasty (TKA) are used in clinical practice and each presents specific design characteristics. No implant managed this day to reproduce perfectly the biomechanics of the natural knee during gait.Objectives:We therefore asked whether (1) differences in tridimensional (3D) kinematic data during gait could be observed in two different designs of TKA on the same patients, (2) if those gait kinematic data are comparable with those of asymptomatic knees and (3) if difference in clinical subjective scores can be observed between the two TKA designs on the same patient.Methods:We performed knee kinematic analysis on 15 patients (30 TKAs) with two different TKA implant designs (Nexgen, Zimmer and Triathlon, Stryker) on each knee and on 25 asymptomatic subjects (35 knees). Clinical evaluation included range of motion, weight bearing radiographs, questionnaire of joint perception, KOOS, WOMAC and SF-12.Results:Comparison between TKAs and asymptomatic knees revealed that asymptomatic knees had significantly less knee flexion at initial contact (p< 0.04) and more flexion for most of the swing phase (pbetween 0.004 and 0.04). Asymptomatic knees also had less varus at loading response, during stance phase and during most of the swing phase (pbetween 0.001 - 0.05). Transverse plane analysis showed a tendency for asymptomatic knees to be more in internal rotation during stance phase (p0.02 - 0.04). Comparing both TKA designs, NexgenTMimplant had significantly more flexion at the end of swing phase (p= 0.04) compared to knees with the TriathlonTMimplant. In frontal plane, from initial contact to maximum mid stance angle and between the mean mid stance angle and initial contact NexgenTMTKA had significantly more adduction (varus,p=0.02 – 0.03). Clinical scores of both TKAs did not have significant difference.Conclusions:TKA with the tested implants did not reproduce natural knee kinematics during gait. In our cohort of patients, TKA implant design translated in limited kinematics differences during gait and on clinical results.

Background Biomechanical and clinical parameters contribute very closely to functional evaluations of the knee joint. To better understand knee osteoarthritis joint function, the association between a set of knee biomechanical data and a set of clinical parameters of an osteoarthritis population (OA) is investigated in this study. Methods The biomechanical data used here are a set of characteristics derived from 3D knee kinematic patterns: flexion/extension, abduction/adduction, and tibial internal/external rotation measurements, all determined during gait recording. The clinical parameters include a KOOS questionnaire and the patient’s demographic characteristics. Canonical correlation analysis (CCA) is used (1) to evaluate the multivariate relationship between biomechanical data and clinical parameter sets, and (2) to cluster the most correlated parameters. Multivariate models were created within the identified clusters to determine the effect of each parameter’s subset on the other. The analyses were performed on a large database containing 166 OA patients. Results The CCA results showed meaningful correlations that gave rise to three different clusters. Multivariate linear models were found explaining the subjective clinical parameters by evaluating the biomechanical data contained within each cluster. Conclusion The results showed that a multivariate analysis of the clinical symptoms and the biomechanical characteristics of knee joint function allowed a better understanding of their relationships.

The purpose of this study is to investigate data clustering to determine representative patterns in three-dimensional (3D) knee kinematic data measurements. Kinematic data are high-dimensional vectors to describe the temporal variations of the three fundamental angles of knee rotation during a walking cycle, namely the abduction/adduction angle, with respect to the frontal plane, the flexion/extension angle, with respect to the sagittal plane, and internal/external angle, with respect to the transverse plane. To offset the curse of dimensionality, inherent to high dimensional data pattern analysis, the method reduces dimensionality by isometric mapping without affecting information content. The data thus simplified is then clustered by the DBSCAN algorithm. The method has been tested on a large database of 165 healthy knee kinematic data measurements. Clusters are validated in terms of the silhouette index, the Dunn index, and connectivity. Results show that a two-cluster characterization of the kinematic knee data in each plane is quite effective. A further clinical investigation shows that the men and women knee patterns are balanced between the two clusters and, for 80% of participants, the right and left knees are in the same cluster.

Cette etude visait a verifier l’utilite clinique de l’introduction de la genougraphie pour la prise en charge de patients souffrant d’arthrose du genou en soins de premiere ligne. La genougraphie est une technologie permettant de mesurer la cinematique tridimensionnelle du genou a la marche sur un tapis roulant et d’identifier des facteurs mecaniques a risque de progression de l’arthrose du genou. Combinee a un examen musculosquelettique, la genougraphie permet de proposer un plan de prise en charge au patient, incluant des ortheses specifiques et des exercices a faire a la maison, ciblant la correction des marqueurs mecaniques a risque. L’etude a porte sur 449 patients recrutes dans 87 cliniques de medecine familiales. Les cliniques etaient randomisees en trois bras de l’etude : un premier groupe recevait les recommandations de prise en charge de la pratique medicale courante ; un deuxieme groupe passait le test de la genougraphie et son medecin recevait les recommandations ; un troisieme groupe recevait en plus une seance d’education sur sa maladie et une explication des exercices a faire. Les resultats montrent que les deux groupes pris en charge avec la genougraphie constataient une amelioration de la fonction de leur genou (diminution de la douleur et des symptomes, augmentation des activites de la vie quotidienne) par rapport au groupe controle. De plus, les deux groupes adheraient aux exercices qui leurs etaient recommandes. L’introduction d’une mesure biomecanique pour cibler des deficits mecaniques a la marche et personnaliser les approches de traitement conservateur semble avoir un impact positif sur la condition des patients.

Kinematic alignment technique for TKA aims to restore the individual knee anatomy and ligament tension, to restore native knee kinematics. The aim of this study was to compare parameters of kinematics during gait (knee flexion–extension, adduction–abduction, internal–external tibial rotation and walking speed) of TKA patients operated by either kinematic alignment or mechanical alignment technique with a group of healthy controls. The hypothesis was that the kinematic parameters of kinematically aligned TKAs would more closely resemble that of healthy controls than mechanically aligned TKAs. This was a retrospective case–control study. Eighteen kinematically aligned TKAs were matched by gender, age, operating surgeon and prosthesis to 18 mechanically aligned TKAs. Post-operative 3D knee kinematics analysis, performed with an optoelectronic knee assessment device (KneeKG®), was compared between mechanical alignment TKA patients, kinematic alignment TKA patients and healthy controls. Radiographic measures and clinical scores were also compared between the two TKA groups. The kinematic alignment group showed no significant knee kinematic differences compared to healthy knees in sagittal plane range of motion, maximum flexion, abduction–adduction curves or knee external tibial rotation. Conversely, the mechanical alignment group displayed several significant knee kinematic differences to the healthy group: less sagittal plane range of motion (49.1° vs. 54.0°, p = 0.020), decreased maximum flexion (52.3° vs. 57.5°, p = 0.002), increased adduction angle (2.0–7.5° vs. − 2.8–3.0°, p

Knee osteoarthritis alters joint stability but its kinematics during functional weight-bearing tasks remain unclear. We propose and validate an assessment technique for the quantification of knee alignment and stability in patients during a short single leg stance task.Three-dimensional knee kinematics were acquired non-invasively from 31 knee osteoarthritis patients (subdivided as moderate or severe) and 15 asymptomatic individuals during six short single-leg stance tasks. Data of participants achieving ≥3 trials were retained. From flexion-extension signals, a data treatment method compared the average between-trial root-mean-square error (RMSE) across trial triplets, and the average within-trial range of movement (RoM) for two data windows. From secondary knee motions (ab/adduction and int/external rotations, anteroposterior and mediolateral translations), we extracted measures characterizing alignments (mean), largest deviations (maximum, minimum), and extent of micro-adjustments (RoM, length of knee excursion). Their sensitivity to disease and severity was determined using an ANOVA, and between-trial repeatability using ICCNinety-four percent of patients achieved ≥3 trials. The retained trial triplet and window reduced the RMSE (2.15 to 1.54) and RoM (4.9° to 1.77°) for flexion-extension. Mean, minimum, and maximum measures were sensitive to disease for anteroposterior translations, and to severity for ab/adduction (P 0.05). High repeatability was found for those measures (ICC ≥0.84). RoM and length of knee excursion, although sensitive to disease for anteroposterior translations, had lower ICC.The proposed technique is feasible and exposed measures of knee alignment sensitive to knee osteoarthritis, for instance, an anterior femoral shift and an increased adduction malalignment with greater severity.

Up to 20% of total knee arthroplasty patients remain unsatisfied post-surgery, and a large proportion of them report anterior knee pain. This study aims to verify whether patients who experience anterior knee pain after total knee arthroplasty (TKA) will exhibit kinematic characteristics similar to those associated with patellofemoral syndrome, including in the frontal and transverse planes. Using four different assessment methods [radiological, patient-reported outcome, musculoskeletal assessment with functional performance testing, and a 3D kinematic assessment during gait], the clinical and 3D knee kinematic profiles of three groups were compared: a painful and an asymptomatic TKA group and a healthy control group. All three groups underwent a three-dimensional kinematic knee assessment while walking on a treadmill. Prosthetic component rotation was assessed through a CT scan measurement performed by one experienced radiologist. Flexion/extension, ab/adduction, and tibial internal rotation curves were compared, and significant differences were highlighted through ANCOVA analysis performed on SPSS. A total of 62 knees were evaluated, 24 asymptomatic, 21 painful, and 17 control. A dynamic flexion contracture during gait was observed in the painful group, which was associated with a lack of flexibility of the thigh muscles. Moreover, painful TKA cases exhibited a valgus alignment (− 1.5°) during stance, which increases the Q angle and lateralizes the patella. Finally, CT scan evaluation of painful total knee arthroplasty patients revealed that their combined components rotation was in slight internal rotation (− 1.4°, SD 7.0°). Painful TKA patients presented three well-known characteristics that tend to increase patellofemoral forces and that could be the cause of the unexplained pain: a stiff knee gait, a valgus alignment when walking, and combined TKA components slightly internally rotated.

Rigid attachment systems are one of the methods used to compensate for soft tissue artifact (STA) inherent in joint motion analyses.The goal of this study was to quantify STA of an exoskeleton design to reduce STA at the knee, and to assess the accuracy of 3D knee kinematics recorded with the exoskeleton in non-obese and obese subjects during quasi-static weight-bearing squatting activity using biplane radiography.Nine non-obese and eight obese subjects were recruited. The exoskeleton was calibrated on each subject before they performed a quasistatic squatting activity in the EOSThe results showed that STA observed at the femur was larger in non-obese subjects than in obese subjects in frontal rotation (p = 0.004), axial rotation (p = 0.000), medio-lateral displacement (p = 0.000) and antero-posterior displacement (p = 0.019), while STA observed at the tibia was lower in non-obese subjects than in obese subjects for the three rotations (p 0.05) and medio-lateral displacement (p = 0.015). Differences between the markers and bones knee kinematics increased with knee flexion and were similar in both groups, except for abduction-adduction: 4.9° for non-obese subjects against 2.3° for obese subjects (p = 0.011).This study demonstrated that STA at the femur and its impact on knee abduction-adduction using a specific exoskeleton were greater among non-obese subjects than obese subjects, which is encouraging for future biomechanical studies on pathologies such as osteoarthritis.

International audience; The aim of this study was to quantify the tibio-femoral contact point (CP) locations in healthy and osteoarthritic (OA) subjects during a weight-bearing squat using stand-alone biplanar X-ray images.Ten healthy and 9 severe OA subjects performed quasi-static squats. Bi-planar X-ray images were recorded at 0°, 15°, 30°, 45°, and 70° of knee flexion. A reconstruction/registration process was used to create 3D models of tibia, fibula, and femur from bi-planar X-rays and to measure their positions at each posture. A weighted centroid of proximity algorithm was used to calculate the tibio-femoral CP locations. The accuracy of the reconstruction/registration process in measuring the quasi-static kinematics and the contact parameters was evaluated in a validation study.The quasi-static kinematics data revealed that in OA knees, adduction angles were greater (p