Aims. This cross-sectional study aimed to investigate the in vivo ankle kinetic alterations in patients with concomitant chronic ankle instability (CAI) and osteochondral lesion of the talus (OLT), which may offer opportunities for clinician intervention in treatment and rehabilitation. Methods. A total of 16 subjects with CAI (eight without OLT and eight with OLT) and eight healthy subjects underwent gait analysis in a stair descent setting. Inverse dynamic analysis was applied to ground reaction forces and marker trajectories using the AnyBody Modeling System. One-dimensional statistical parametric mapping was performed to compare ankle joint reaction force and joint moment curve among groups. Results. The patients with OLT showed significantly increased dorsiflexion moment in the ankle joint compared with healthy subjects during 38.2% to 40.9% of the gait cycle, and increased eversion moment in the ankle joint compared with patients without OLT during 25.5% to 27.6% of the gait cycle. Compared with healthy subjects, the patients with OLT showed increased anterior force during 42% to 43% of the gait cycle, and maximal medial force (p = 0.005, ηp2 = 0.399). Conclusion. The patients with concomitant CAI and OLT exhibit increased dorsiflexion and eversion moment, as well as increased anterior and medial ankle joint reaction force during stair descent, compared with patients with CAI but without OLT and healthy subjects, respectively. Thus, a rehabilitative regimen targeting excessive ankle dorsiflexion and eversion moment may help to reduce ankle joint loading. Cite this article: Bone Joint Res 2024;13(12):716–724

Introduction. This research aims to enhance the control of intricate musculoskeletal spine models, a critical tool for comprehending both healthy and pathological spinal conditions. State-of-the-art musculoskeletal spine models incorporate segments for all vertebra, each possessing 3 degrees-of-freedom (DOF). Manually defining the posture with this amount of DOFs presents a significant challenge. The prevalent method of equally distributing the spine's overall rotation among the vertebrae often proves to be an inadequate assumption, particularly when dealing with the entire spine. Method. We have engineered a comprehensive non-linear spine rhythm and the requisite tools for its implementation in widely utilized musculoskeletal modelling software (1). The rhythm controls lateral bending, axial rotation, and flexion/extension. The mathematical and implementation details of the rhythm are beyond this abstract, but it's noteworthy that the implementation accommodates non-linear rhythms. This means, for example, that one set of rhythm coefficients is used for flexion and another for extension. The rhythm coefficients, which distinguish the movement along the spine, were derived from a review of spine literature. The values for spine and vertebra range-of-motion (ROM) vary significantly in published studies, and no complete dataset was found in any single study. Consequently, the rhythm presented here is a composite, designed to provide the most consistent and average set of rhythm coefficients. Result. The novel spine rhythm simplifies the control of detailed spine models, accommodating varying amounts of input data. It allows for the specification of only the overall motion or the posture at a more detailed level (i.e., lumbar, thoracic, neck). The tools and rhythm coefficients are publicly available on GitHub. Conclusion. The innovative spine rhythm enhances the usability of cutting-edge spine models. For flexion/extension of the spine, it introduces a non-linear rhythm, exhibiting distinct behaviour between flexion and extension - a feature not previously observed in musculoskeletal spine models. 1) The AnyBody Modeling System

Aims

The aim of this study was to explore parents’ experience of their child’s recovery, and their thoughts about their decision to enrol their child in a randomized controlled trial (RCT) of surgery versus non-surgical casting for a displaced distal radius fracture.

The tendency towards using inertial sensors for remote monitoring of the patients at home is increasing. One of the most important characteristics of the sensors is sampling rate. Higher sampling rate results in higher resolution of the sampled signal and lower amount of noise. However, higher sampling frequency comes with a cost. The main aim of our study was to determine the validity of measurements performed by low sampling frequency (12.5 Hz) accelerometers (SENS) in patients with knee osteoarthritis compared to standard sensor-based motion capture system (Xsens). We also determined the test-retest reliability of SENS accelerometers. Participants were patients with unilateral knee osteoarthritis. Gait analysis was performed simultaneously by using Xsens and SENS sensors during two repetitions of over-ground walking at a self-selected speed. Gait data from Xsens were used as an input for AnyBody musculoskeletal modeling software to measure the accelerations at the exact location of two defined virtual sensors in the model (VirtualSENS). After preprocessing, the signals from SENS and VirtualSENS were compared in different coordinate axes in time and frequency domains. ICC for SENS data from first and second trials were calculated to assess the repeatability of the measurements. We included 32 patients (18 females) with median age 70.1[48.1 – 85.4]. Mean height and weight of the patients were 173.2 ± 9.6 cm and 84.2 ± 14.7 kg respectively. The correlation between accelerations in time domain measured by SENS and VirtualSENS in different axes was r = 0.94 in y-axis (anteroposterior), r = 0.91 in x-axis (vertical), r = 0.83 in z-axis (mediolateral), and r = 0.89 for the magnitude vector. In frequency domain, the value and the power of fundamental frequencies (F. 0. ) of SENS and VirtualSENS signals demonstrated strong correlation (r = 0.98 and r = 0.99 respectively). The result of test-retest evaluation showed excellent repeatability for acceleration measurement by SENS sensors. ICC was between 0.89 to 0.94 for different coordinate axes. Low sampling frequency accelerometers can provide valid and reliable measurements especially for home monitoring of the patients, in which handling big data and sensors cost and battery lifetime are among important issues

Introduction and Objective. The human body is designed to walk in an efficient way. As energy can be stored in elastic structures, it is no surprise that the strongest elastic structure of the human body, the iliofemoral ligament (IFL), is located in the lower limb. Numerous popular surgical hip interventions, however, affect the structural integrity of the hip capsule and there is a growing evidence that surgical repair of the capsule improves the surgical outcome. Though, the exact contribution of the iliofemoral ligament in energy efficient hip function remains unelucidated. Therefore, the objective of this study was to evaluate the influence of the IFL on energy efficient ambulation. Materials and Methods. In order to assess the potential passive contribution of the IFL to energy efficient ambulation, we simulated walking using the large public dataset (n=50) from Schreiber in a the AnyBody musculoskeletal modeling environment with and without the inclusion of the IFL. The work required from the psoas, iliacus, sartorius, quadriceps and gluteal muscles was evaluated in both situations. Considering the large uncertainty on ligament properties a parameter study was included. Results. A significant reduction in the active component of all hip flexors was observed when the IFL is intact. The required muscle work was found to be reduced by as much as 48% (CI: 29–62%), 61% (CI: 35–84%) and 38% (CI: 2–69%) for the psoas, iliacus, and sartorius muscle respectively. The IFL inclusion has no major effect on the required work from the quadriceps and the gluteal muscle group. The energy storage in the IFL is largest at maximal hip extension and the contribution to forward motion is the largest at the start of the swing phase. Conclusions. The iliofemoral ligament seems to be a crucial structure in energy efficient walking. The findings support need for meticulous reconstruction of the capsule ligament in case of surgical damage

Aims

A multicentre, randomized, clinician-led, pragmatic, parallel-group orthopaedic trial of two surgical procedures was set up to obtain high-quality evidence of effectiveness. However, the trial faced recruitment challenges and struggled to maintain recruitment rates over 30%, although this is not unusual for surgical trials. We conducted a qualitative study with the aim of gathering information about recruitment practices to identify barriers to patient consent and participation to an orthopaedic trial.

To date, the fixation of proximal humeral fractures with angular stable locking plates is still insufficient with mechanical failure rates of 18% to 35%. The PHILOS plate (DePuy Synthes, Switzerland) is one of the most used implants. However, this plate has not been demonstrated to be optimal; the closely symmetric plate design and the largely heterogeneous bone mineral density (BMD) distribution of the humeral head suggest that the primary implant stability may be improved by optimizing the screw orientations. Finite element (FE) analysis allows testing of various implant configurations repeatedly to find the optimal design. The aim of this study was to evaluate whether computational optimization of the orientation of the PHILOS plate locking screws using a validated FE methodology can improve the predicted primary implant stability. The FE models of nineteen low-density (humeral head BMD range: 73.5 – 139.5 mg/cm3) left proximal humeri of 10 male and 9 female elderly donors (mean ± SD age: 83 ± 8.8 years) were created from high-resolution peripheral computer tomography images (XtremeCT, Scanco Medical, Switzerland), using a previously developed and validated computational osteosynthesis framework. To simulate an unstable mal-reduced 3-part fracture (AO/OTA 11-B3.2), the samples were virtually osteotomized and fixed with the PHILOS plate, using six proximal screws (rows A, B and E) according to the surgical guide. Three physiological loading modes with forces taken from musculoskeletal models (AnyBody, AnyBody Technology A/S, Denmark) were applied. The FE analyses were performed with Abaqus/Standard (Simulia, USA). The average principal compressive strain was evaluated in cylindrical bone regions around the screw tips; since this parameter was shown to be correlated with the experimental number of cycles to screw cut-out failure (R2 = 0.90). In a parametric analysis, the orientation of each of the six proximal screws was varied by steps of 5 in a 5×5 grid, while keeping the screw head positions constant. Unfeasible configurations were discarded. 5280 simulations were performed by repeating the procedure for each sample and loading case. The best screw configuration was defined as the one achieving the largest overall reduction in peri-screw bone strain in comparison with the PHILOS plate. With the final optimized configuration, the angle of each screw could be improved, exhibiting significantly smaller average bone strain around the screw tips (range of reduction: 0.4% – 38.3%, mean ± SD: 18.49% ± 9.56%). The used simulation approach may help to improve the fixation of complex proximal humerus fractures, especially for the target populations of patients at high risk of failure

Aims

Brachial plexus injury (BPI) is an often devastating injury that affects patients physically and emotionally. The vast majority of the published literature is based on surgeon-graded assessment of motor outcomes, but the patient experience after BPI is not well understood. Our aim was to better understand overall life satisfaction after BPI, with the goal of identifying areas that can be addressed in future delivery of care.

Aims

Fixation of osteoporotic proximal humerus fractures remains challenging even with state-of-the-art locking plates. Despite the demonstrated biomechanical benefit of screw tip augmentation with bone cement, the clinical findings have remained unclear, potentially as the optimal augmentation combinations are unknown. The aim of this study was to systematically evaluate the biomechanical benefits of the augmentation options in a humeral locking plate using finite element analysis (FEA).

Introduction. Gait laboratory measurement of whole-body kinematics and ground reaction forces during a wide range of activities is frequently performed in joint replacement patient diagnosis, monitoring, and rehabilitation programs. These data are commonly processed in musculoskeletal modeling platforms such as OpenSim and Anybody to estimate muscle and joint reaction forces during activity. However, the processing required to obtain musculoskeletal estimates can be time consuming, requires significant expertise, and thus seriously limits the patient populations studied. Accordingly, the purpose of this study was to evaluate the potential of deep learning methods for estimating muscle and joint reaction forces over time given kinematic data, height, weight, and ground reaction forces for total knee replacement (TKR) patients performing activities of daily living (ADLs). Methods. 70 TKR patients were fitted with 32 reflective markers used to define anatomical landmarks for 3D motion capture. Patients were instructed to perform a range of tasks including gait, step-down and sit-to-stand. Gait was performed at a self-selected pace, step down from an 8” step height, and sit-to-stand using a chair height of 17”. Tasks were performed over a force platform while force data was collected at 2000 Hz and a 14 camera motion capture system collected at 100 Hz. The resulting data was processed in OpenSim to estimate joint reaction and muscle forces in the hip and knee using static optimization. The full set of data consisted of 135 instances from 70 patients with 63 sit-to-stands, 15 right-sided step downs, 14 left-sided step downs, and 43 gait sequences. Two classes of neural networks (NNs), a recurrent neural network (RNN) and temporal convolutional neural network (TCN), were trained to predict activity classification from joint angle, ground reaction force, and anthropometrics. The NNs were trained to predict muscle and joint reaction forces over time from the same input metrics. The 135 instances were split into 100 instances for training, 15 for validation, and 20 for testing. Results. The RNN and TCN yielded classification accuracies of 90% and 100% on the test set. Correlation coefficients between ground truth and predictions from the test set ranged from 0.81–0.95 for the RNN, depending on the activity. Predictions from both NNs were qualitatively assessed. Both NNs were able to effectively learn relationships between the input and output variables. Discussion. The objective of the study was to develop and evaluate deep learning methods for predicting patient mechanics from standard gait lab data. The resulting models classified activities with excellent performance, and showed promise for predicting exact values for loading metrics for a range of different activities. These results indicate potential for real-time prediction of musculoskeletal metrics with application in patient diagnostics and rehabilitation. For any figures or tables, please contact authors directly

Objectives

The aim of this study was to investigate the biomechanical effect of the anterolateral ligament (ALL), anterior cruciate ligament (ACL), or both ALL and ACL on kinematics under dynamic loading conditions using dynamic simulation subject-specific knee models.

Introduction. Fretting corrosion at the taper interface of modular connections can be studied using Finite Element (FE) analyses. However, the loading conditions in FE studies are often simplified, or based on generic activity patterns. Using musculoskeletal modeling, subject-specific muscle and joint forces can be calculated, which can then be applied to a FE model for wear predictions. The objective of the current study was to investigate the effect of incorporating more detailed activity patterns on fretting simulations of modular connections. Methods. Using a six-camera motion capture system, synchronized force plates, and 45 optical markers placed on 6 different subjects, data was recorded for three different activities: walking at a comfortable speed, chair rise, and stair climbing. Musculoskeletal models, using the Twente Lower Extremity Model 2.0 implemented in the AnyBody modeling System™ (AnyBody Technology A/S, Aalborg, Denmark; figure1), were used to determine the hip joint forces. Hip forces for the subject with the lowest and highest peak force, as well as averaged hip forces were then applied to an FE model of a modular taper connection (Biomet Type-1 taper with a Ti6Al4V Magnum +9 mm adaptor; Figure 2). During the FE simulations, the taper geometry was updated iteratively to account for material removal due to wear. The wear depth was calculated based on Archard's Law, using contact pressures, micromotions, and a wear factor, which was determined from accelerated fretting experiments. Results. The forces for the comfortable walking speed had the highest peak forces for the maximum peak subject, with a maximum peak force of 3644 N, followed by walking up stairs, with a similar maximum peak force of 3626 N. The chair rise had a lower maximum peak force of 2240 N (−38.5%). The simulated volumetric wear followed the trends seen in the peaks of the predicted hip joint forces, with the largest wear volumes predicted for a comfortable walking speed, followed by the stairs up activity and the chair rise (Figure 3). The subjects with the highest peak forces produced the most volumetric wear in all cases. However, the lowest peak subject had a higher volumetric wear for the stairs up case than the average subject. Discussion. This study explored the effect of subject-specific variations in hip joint loads on taper fretting. The results indicate that taper wear was predominantly affected by the magnitudes of the peak forces, rather than by the orientation of the force. A more comprehensive study, capturing the full spectrum of patient variability, can help identifying parameters that accelerate fretting corrosion. Such a study should also incorporate other sources of variability, including surgical factors such as implant orientation, sizing, and offset. These factors also affect hip joint forces, and can be evaluated in musculoskeletal models such as presented here

Introduction. One of the known mechanisms which could contribute to the failure of total hip replacements (THR) is edge contact. Failures associated with edge contact include rim damage and lysis due to altered loading and torques. Recent study on four THR patients showed that the inclusion of pelvic motions in a contact model increased the risk of edge contact in some patients. The aim of current study was to determine whether pelvic motions have the same effect on contact location for a larger patient cohort and determine the contribution of each of the pelvic rotations to this effect. Methods. Gait data was acquired from five male and five female unilateral THR patients using a ten camera Vicon system (Oxford Metrics, UK) interfaced with twin force plates (AMTI) and using a CAST marker set. All patients had good surgical outcomes, confirmed by patient-reported outcomes and were considered well-functioning, based on elective walking speed. Joint contact forces and pelvic motions were obtained from the AnyBody modelling system (AnyBody Technologies, DK). Only gait cycle regions with available force plate data were considered. A finite element model of a 32mm head on a featureless hemispherical polyethylene cup, 0.5mm radial clearance, was used to obtain the contact area from the contact force. A bespoke computational tool was used to analyse patients' gait profiles with and without pelvic motions. The risk of edge contact was measured as a “centre proximity angle” between the cup pole and centre of the contact area, and “edge proximity angle” between the cup pole and the furthest contact area point away from the pole. Pelvic tilt, drop and internal-external rotation were considered one at a time and in combinations. Results. In eight out of 10 patients, the addition of pelvic motions decreased the risk of edge contact during toe-off. There was up to 6° reduction in the proximity angles when pelvic motions were introduced to the gait cycle. In six out of 10 patients, the addition of pelvic motions resulted in an increase in the risk of edge contact during heel-strike with up to 6° increase in the proximity angles. For all patients where these effects were seen, sagittal pelvic tilt was a substantial contributor. Conclusion. The results of this study suggest that pelvic motion play an important role in contact location in THR bearings during loading phase. Both static and dynamic pelvic tilt contribute to the variability in the risk of edge contact. Further tests on larger patient cohorts are required to confirm the trends observed. The outcomes of this study suggest that pre-clinical mechanical and tribological testing of THRs should consider the role of pelvic motion. The outcomes also have implications for establishing surgical positioning safe zones, which are currently based only on risk of dislocation and severe impingement

Introduction. A deep squat (DS) is a challenging motion at the level of the hip joint generating substantial reaction forces (HJRF). During DS, the hip flexion angle approximates the functional range of hip motion. In some hip morphologies this femoroacetabular conflict has been shown to occur as early as 80° of hip flexion. So far in-vivo HJRF measurements have been limited to instrumented hip implants in a limited number of older patients performing incomplete squats (< 50° hip flexion and < 80° knee flexion). Clearly, young adults have a different kinetical profile with hip and knee flexion ranges going well over 100 degrees. Since hip loading data on this subgroup of the population is lacking and performing invasive measurements would be unfeasible, this study aimed to report a personalised numerical model solution based on inverse dynamics to calculate realistic in silico HJRF values during DS. M&M. Fifty athletic males (18–25 years old) were prospectively recruited for motion and morphological analysis. DS motion capture (MoCap) acquisitions and MRI scans of the lower extremities with gait lab marker positions were obtained. The AnyBody Modelling System (v6.1.1) was used to implement a novel personalisation workflow of the AnyMoCap template model. Bone geometries, semi-automatically segmented from MRI, and corresponding markers were incorporated into the template human model by an automated nonlinear morphing. Furthermore, a state-of-the-art TLEM 2.0 dataset, included in the Anybody Managed Model Repository (v2.0), was used in the template model. The subject-specific MoCap trials were processed to compute squat motion by resolving an overdeterminate kinematics problem. Inverse dynamics analyses were carried out to compute muscle and joint reaction forces in the entire body. Resulting hip joint loads were validated with measured in-vivo data from Knee bend trials in the OrthoLoad library. Additionally, anterior pelvic tilt, hip and knee joint angles were computed. Results. A preliminary set of results (20 out of 50 subjects) was analysed. The average HJRF was 3.42 times bodyweight at the peak of DS (95% confidence interval: 2.99 – 3.85%BW). Maximal hip and knee flexion angles were 113° (109.7°–116.8°) and 116° (109.4 – 123.0°) respectively. The anterior pelvic tilt demonstrated a biphasic profile with peak value of 33° (28.1° – 38.4°). Discussion. A non-invasive and highly personalised alternative for determining hip loading was presented. Consistently higher HJR forces during DS in young adults were demonstrated as opposed to the Orthoload dataset. Similarly, knee and hip flexion angles were much higher, which could support the increase in HJRF. We can conclude that DS hip kinetics in young adults clearly differ from the typical total hip arthroplasty population

Introduction. There are over one-half million total knee replacement (TKR) procedures performed each year in the United States and is projected to increase to over 3.48 million by 2030. Concurrent with the increase in TKR procedures is a trend of younger patients receiving knee implants (under the age of 65). These younger patients are known to have a 5% lower implant survival rate at 8 years post-op compared to older patients (65+ years), and they are also known to live more active lifestyles that place higher demands on the durability and functional performance of the TKR device. Conventional TKR designs increase articular conformity to increase stability, but these articular constraints decrease patient range of knee motion, often limiting key measures of femoral rollback, A/P motion, and deep knee flexion. Without this articular constraint however, many patients report TKR “instability” during activities such as walking and stair descent, which can significantly impede confidence of movement. Therefore there is a need for a TKR system that can offer enhanced stability while also maintaining active ranges of motion. Materials and Methods. A novel knee arthroplasty system was designed that uses synthetic ligament systems that can be surgically replaced, to provide ligamentous stability and natural motion to increase the functional performance of the implant. Using an anatomical knee model from the AnyBody software, a computational model that incorporated ligaments into an existing Journey II TKR was developed. Using the software ligaments were modeled and given biomechanical properties developed from equations from literature. Simulated A/P drawer tests and knee flexion test were analyzed for 2,916 possible cruciate ligament location and length combinations to determine the effects on the A/P stability of the TKR. A physical model was constructed, and the design was verified by performing 110 N A/P drawer tests under 710 N of simulated body weight. Results and Discussion. As ACL insertion location moved posteriorly on the femur, it was found to decrease ACL ligament strain, enabling a higher range of flexion. In general, as ACL and PCL length increased, the A/P laxity of the TKR system increased linearly. Range of motion was found to be more dependent on ligament attachment location, and laxity was more dependent on ligament length. In this work, TKR stability was clearly affected by changes in synthetic ligament length and location. When comparing the laxity between a TKR with and without ligaments, the TKR with synthetic ligaments experienced significantly less displacement than a TKR without synthetic ligaments as seen in Figure 1. Conclusions. This study shows that the stability of a TKR can be increased while maintaining range of motion by incorporating synthetic ligaments into this design. The effectiveness of the ligaments was clearly dependent on two factors: length and location, with incorrect lengths and locations significantly impairing ranges of motion. These results verify that a knee replacement can incorporate synthetic ligaments, and that with calibrated location and lengths, they can significantly influence stability and possible kinematic performance of the TKR system, and potentially influencing long-term functional outcomes. For any figures or tables, please contact the authors directly

Introduction. A deep squat (DS) is a challenging motion at the level of the hip joint generating substantial reaction forces (HJRF). As a closed chain exercise, it has great value in rehabilitation and muscle strengthening of hip and knee. During DS, the hip flexion angle approximates the functional range of hip motion risking femoroacetabular impingement in some morphologies. In-vivo HJRF measurements have been limited to instrumented implants in a limited number of older patients performing incomplete squats (< 50° hip flexion and < 80° knee flexion). On the other hand, total hip arthroplasty is being increasingly performed in a younger and higher demanding patient population. These patients clearly have a different kinetical profile with hip and knee flexion ranges going well over 100 degrees. Since measurements of HJRF with instrumented prostheses in healthy subjects would be ethically unfeasible, this study aims to report a personalised numerical solution based on inverse dynamics to calculate realistic in-silico HJRF values during DS. Material and methods. Thirty-five healthy males (18–25 years old) were prospectively recruited for motion and morphological analysis. DS motion capture (MoCap) acquisitions and MRI scans with gait lab marker positions were obtained. The AnyBody Modelling System (v6.1.1) was used to implement a novel personalisation workflow of the AnyMoCap template model. Bone geometries, semi-automatically segmented from MRI, and corresponding markers were incorporated into the template human model by an automated procedure. A state of-the-art TLEM 2.0 dataset, included in the Anybody Managed Model Repository (v2.0), was used in the template model. The subject-specific MoCap trials were processed to compute kinematics of DS, muscle and joint reaction forces in the entire body. Resulting hip joint loads were compared with in-vivo data from OrthoLoad dataset. Additionally, hip and knee joint angles were computed. Results. An average HJRF of 274%BW (251.5 – 297.9%BW; 95% confidence interval) was calculated at the peak of DS. The HJRF on the pelvis was directed superior, medial and posterior throughout the DS. Peak knee and hip flexion angles were 112° (108.1° – 116.5°) and 107° (104.6° – 109.4°) on average. Discussion and conclusions. A comprehensive approach to construct an accurate personalised musculoskeletal model from subject-specific MoCap data, bone geometries, and palpatory landmarks was presented. Consistently higher HJR forces during DS in young adults were demonstrated as opposed to the Orthoload dataset. Similarly, knee and hip flexion angles were much higher, which could cause the increase in HJRF. It can be concluded that DS kinetics in young adults differ from the typical total hip arthroplasty population. These models will enable further in-silico joint biomechanics studies, and could serve the purpose of a virtual test bed for implant design

Aims

The aim of this study was to explore the patients’ experience of recovery from open fracture of the lower limb in acute care.

Background. A new knee simulator has been developed at Ghent University. This simulator provides the unique opportunity of evaluating the knee kinematics during activities of daily living. The simulator therefore controls the position of the ankle in the sagittal plane while keeping the hip at a fixed position. This approach provides full kinematic freedom to the knee. To evaluate and validate the performance of the simulator, the development of and comparison with a numerical simulation model is discussed in this paper. Methods. Both a two and three dimensional simulation model have been developed using the AnyBody Modelling System (AMS). In the two dimensional model, the knee joint is represented by a hinge. Similarly, the ankle and hip joint are represented by a hinge joint and a variable amplitude quadriceps and hamstrings force is applied. In line with this simulation model, a hinge model was created that could be mounted in the UGent knee simulator to evaluate the performance of the simulated model. The hinge model thereby performs a cyclic motion under varying simulated muscle loads while recording the ankle reaction forces. In addition to the two dimensional model, a three dimensional model has been developed. More specifically, a model is built of a sawbone leg holding a posterior stabilised single radius total knee implant. The physical sawbone model contains simplified medial and lateral collateral ligaments. In line with the boundary conditions of the UGent knee simulator, the simulated hip contains a single rotational degree of freedom and the ankle holds four degrees of freedom (three rotations, single translation). In the simulations, the knee is modelled using the force-dependent kinematics (FDK) method built in the AMS. This leaves the knee with six degrees of freedom that are controlled by the ligament tension in combination with the applied quadriceps load and shape of the implant. The physical sawbone model goes through five cycles in the UGent simulator using while recording the kinematics of the femur and tibia using a set of markers rigidly attached to the femur and tibia bone. The position of the implant with respect to the markers was evaluated by CT-scanning the sawbone model. Results and Discussion. In a first step, the reaction forces at the ankle in the 2D model were evaluated. The difference between the simulated and measured reaction force is limited and can be explained from a slight variation of the attachment point of the simulated muscle loads. For the 3D model, the kinematic patterns have been evaluated for both the simulation and physical model using Grood & Suntay definitions. The kinematic parameters display realistic trends, however, no exact match has been obtained for all parameters so far. The latter might be attributed to a number of simplifications in the simulation model as well as elastic deformation of the physical sawbone model. Conclusion. A three dimensional model of a knee implant in the UGent Knee Simulator has been developed. The simulated kinematic patterns appear realistic though no exact match with the measured patterns has been obtained. Future research will therefore focus on the development of a more realistic experimental and numerical model

Introduction. Total knee arthroplasty (TKA) is a well proven surgical procedure. Squat and gait motions are common activities in daily life. However, squat motion is known as most dissatisfying motion in activities in daily life after total knee arthroplasty (TKA). Dissatisfaction after TKA might refer to muscle co-contraction between quadriceps and hamstrings. The purposed of this study was to develop squat and gait simulation model and analyses the contact mechanics and quadriceps and hamstring muscle stability. We hypothesized that squat model shows larger contact forces and lower hamstring to quadriceps force ratio than gait model. Materials and Methods. Squat motion and gait model were simulated in musculoskeletal simulation software (AnyBody Modeling System, AnyBody Technology, Denmark). Subject-specific bone models used in the simulation were reconstructed from CT images by Mimics (Materialize, Belgium). The lower extremity model was constructed with pelvis, femur, tibia, foot segments and total knee replacement components: femoral component, tibial insert, tibial tray, and patella component [Fig.1]. The muscle model was consisted of 160 muscle elements. The TKR components used in this study are PS-type LOSPA Primary Knee System (Corentec Co., Ltd, Republic of Korea). Force-dependent kinematics method was used in the simulation. The model was simulated to squat from 15° to 100° knee flexion, in 100 frames. Gait simulation model was based on motion capture and force-plate system. Motion capture and force-plate data were from grand challenge competition dataset. Results / Discussion. Patellofemoral contact forces ranged from 0.18 to 3.78 percent body weight (%BW) and from 0.00 to 1.36 %BW during squat motion and gait cycle, respectively. Patellofemoral contact forces calculated at 30°, 60°, and 90° flexion during squat motion were 0.53, 1.93, and 3.22 %BW, respectively. Wallace et al. also reported patellofemoral contact forces at 30°, 60°, and 90° flexion, which were 0.31, 1.33, 2.45 %BW during squat motion. Our results showed similar results from other studies, however the squat model overestimated the patellofemoral contact forces. Contact stiffness in the simulation model might affected the overestimated contact forces. Hamstring to quadriceps force ratio ranged from 0.32 to 1.88 for squat model, and from 0.00 to 2.54 for gait model. As our hypothesis, squat motion showed larger patellofemoral contact forces. Also, mean hamstring to quadriceps force ratio of squat model were about half than the mean hamstring to quadriceps force ratio of gait model. From the results, possibility exists that unbalanced force of quadriceps and hamstring can affect dissatisfaction after TKA while squat motion is the most dissatisfying motion after TKA. However, muscle stability is not the only factor that can affect dissatisfaction after TKA. In future study, more biomechanical parameters should be evaluated to find meaningful dissatisfying factor after TKA. Conclusion. In conclusion, TKA musculoskeletal models of squat and gait motion were constructed and patellofemoral contact force / hamstring to quadriceps force ratio were evaluated. Patellofemoral mechanics were validated by comparison of previous study. Additional studies are needed to find dissatisfying factor after TKA