OpenSim: open-source software to create and analyze dynamic simulations of movement

A Data-Driven Approach to Estimate Human Center of Mass State During Perturbed Locomotion Using Simulated Wearable Sensors

Center of mass (COM) state, specifically in a local reference frame (i.e., relative to center of pressure), is an important variable for controlling and quantifying bipedal locomotion. However, this metric is not easily attainable in real time during human locomotion experiments. This information could be valuable when controlling wearable robotic exoskeletons, specifically for stability augmentation where knowledge of COM state could enable step placement planners similar to bipedal robots. Here, we explored the ability of simulated wearable sensor-driven models to rapidly estimate COM state during steady state and perturbed walking, spanning delayed estimates (i.e., estimating past state) to anticipated estimates (i.e., estimating future state). We used various simulated inertial measurement unit (IMU) sensor configurations typically found on lower limb exoskeletons and a temporal convolutional network (TCN) model throughout this analysis. We found comparable COM estimation capabilities across hip, knee, and ankle exoskeleton sensor configurations, where device type did not significantly influence error. We also found that anticipating COM state during perturbations induced a significant increase in error proportional to anticipation time. Delaying COM state estimates significantly increased accuracy for velocity estimates but not position estimates. All tested conditions resulted in models with R2 > 0.85, with a majority resulting in R2 > 0.95, emphasizing the viability of this approach. Broadly, this preliminary work using simulated IMUs supports the efficacy of wearable sensor-driven deep learning approaches to provide real-time COM state estimates for lower limb exoskeleton control or other wearable sensor-based applications, such as mobile data collection or use in real-time biofeedback.

Meta-heuristic optimization algorithms based feature selection for joint moment prediction of sit-to-stand movement using machine learning algorithms

The sit-to-stand (STS) movement is fundamental in daily activities, involving coordinated motion of the lower extremities and trunk, which leads to the generation of joint moments based on joint angles and limb properties. Traditional methods for determining joint moments often involve sensors or complex mathematical approaches, posing limitations in terms of movement restrictions or expertise requirements. Machine learning (ML) algorithms have emerged as promising tools for joint moment estimation, but the challenge lies in efficiently selecting relevant features from diverse datasets, especially in clinical research settings. This study aims to address this challenge by leveraging metaheuristic optimization algorithms to predict joint moments during STS using minimal input data. Motion analysis data from 20 participants with varied mass and inertia properties are utilized, and joint angles are computed alongside simulations of joint moments. Feature selection is performed using the Manta Ray Foraging Optimization (MRFO), Marine Predators Algorithm (MPA), and Equilibrium Optimizer (EO) algorithms. Subsequently, Decision Tree Regression (DTR), Random Forest Regression (RFR), Extra Tree Regression (ETR), and eXtreme Gradient Boosting Regression (XGBoost Regression) ML algorithms are deployed for joint moment prediction. The results reveal EO-ETR as the most effective algorithm for ankle, knee, and neck joint moment prediction, while MPA-ETR exhibits superior performance for hip joint prediction. This approach demonstrates potential for enhancing accuracy in joint moment estimation with minimal feature input, offering implications for biomechanical research and clinical applications.

Exoskeletons vs. exosuits: A comparative analysis using biological-based computer simulation

BACKGROUND

Interest in the design of gait assistance devices has experienced significant growth in recent years. Among various uses of assistive devices, those aimed at supporting the elderly have gained importance due to the rising population of this age group.

METHODS

This study aims to compare the efficacy of two types of assistive devices through musculoskeletal simulations. One case is an ideal device, simulating the motor actuation as it would be in a rigid exoskeleton, and, cable-assisted devices, simulating the assistance of an exosuit. The simulations were based on data obtained from 9 subjects. OpenSim, an open-source software, was employed to conduct the simulations.

RESULTS

Our findings indicate that the cable-assisted device outperforms the traditional exoskeleton by achieving a more significant reduction in the metabolic cost with relatively lower assistance power.

CONCLUSION

Cable-assisted gait assistance devices have shown comparable results to traditional exoskeletons, with the added advantage of improved performance through reduced power requirements.

Influence of Walking Over Unexpected Uneven Terrain on Joint Loading for Individuals With Transtibial Amputation

Individuals with transtibial amputation (TTA) experience asymmetric lower-limb loading which can lead to joint pain and injuries. However, it is unclear how walking over unexpected uneven terrain affects their loading patterns. This study sought to use modeling and simulation to determine how peak joint contact forces and impulses change for individuals with unilateral TTA during an uneven step and subsequent recovery step and how those patterns compare to able-bodied individuals. We expected residual limb loading during the uneven step and intact limb loading during the recovery step would increase relative to flush walking. Further, individuals with TTA would experience larger loading increases compared to able-bodied individuals. Simulations of individuals with TTA showed during the uneven step, changes in joint loading occurred at all joints except the prosthetic ankle relative to flush walking. During the recovery step, intact limb joint loading increased in early stance relative to flush walking. Simulations of able-bodied individuals showed large increases in ankle joint loading for both surface conditions. Overall, increases in early stance knee joint loading were larger for those with TTA compared to able-bodied individuals during both steps. These results suggest that individuals with TTA experience altered joint loading patterns when stepping on uneven terrain. Future work should investigate whether an adapting ankle-foot prosthesis can mitigate these changes to reduce injury risk.

Smartphone videos-driven musculoskeletal multibody dynamics modelling workflow to estimate the lower limb joint contact forces and ground reaction forces

The estimation of joint contact forces in musculoskeletal multibody dynamics models typically requires the use of expensive and time-consuming technologies, such as reflective marker-based motion capture (Mocap) system. In this study, we aim to propose a more accessible and cost-effective solution that utilizes the dual smartphone videos (SPV)-driven musculoskeletal multibody dynamics modeling workflow to estimate the lower limb mechanics. Twelve participants were recruited to collect marker trajectory data, force plate data, and motion videos during walking and running. The smartphone videos were initially analyzed using the OpenCap platform to identify key joint points and anatomical markers. The markers were used as inputs for the musculoskeletal multibody dynamics model to calculate the lower limb joint kinematics, joint contact forces, and ground reaction forces, which were then evaluated by the Mocap-based workflow. The root mean square error (RMSE), mean absolute deviation (MAD), and Pearson correlation coefficient (ρ) were adopted to evaluate the results. Excellent or strong Pearson correlations were observed in most lower limb joint angles (ρ = 0.74 ~ 0.94). The averaged MADs and RMSEs for the joint angles were 1.93 ~ 6.56° and 2.14 ~ 7.08°, respectively. Excellent or strong Pearson correlations were observed in most lower limb joint contact forces and ground reaction forces (ρ = 0.78 ~ 0.92). The averaged MADs and RMSEs for the joint lower limb joint contact forces were 0.18 ~ 1.07 bodyweight (BW) and 0.28 ~ 1.32 BW, respectively. Overall, the proposed smartphone video-driven musculoskeletal multibody dynamics simulation workflow demonstrated reliable accuracy in predicting lower limb mechanics and ground reaction forces, which has the potential to expedite gait dynamics analysis in a clinical setting.

Effects of Fatigue and Unanticipated Factors on Knee Joint Biomechanics in Female Basketball Players during Cutting

(1) This study examined the impact of fatigue and unanticipated factors on knee biomechanics during sidestep cutting and lateral shuffling in female basketball players, assessing the potential for non-contact anterior cruciate ligament (ACL) injuries. (2) Twenty-four female basketball players underwent fatigue induction and unanticipated change of direction tests, and kinematic and kinetic parameters were collected before and after fatigue with a Vicon motion capture system and Kistler ground reaction force (GRF) sensor. (3) Analysis using two-way repeated-measures ANOVA showed no significant interaction between fatigue and unanticipated factors on joint kinematics and kinetics. Unanticipated conditions significantly increased the knee joint flexion and extension angle (p < 0.01), decreased the knee flexion moment under anticipated conditions, and increased the knee valgus moment after fatigue (p ≤ 0.05). One-dimensional statistical parametric mapping (SPM1d) results indicated significant differences in GRF during sidestep cutting and knee inversion and rotation moments during lateral shuffling post-fatigue. (4) Unanticipated factors had a greater impact on knee load patterns, raising ACL injury risk. Fatigue and unanticipated factors were independent risk factors and should be considered separately in training programs to prevent lower limb injuries.

Impact of different landing heights on the contact force in the medial tibiofemoral compartment and the surrounding muscle force characteristics in drop jumps

This study explored the impact of landing height on the tibiofemoral joint's medial compartment force (MCF) during drop jumps to help athletes prevent knee injury. Experienced male participants (N = 16) performed drop jumps with landing heights from 0.15 m to 0.75 m. Kinematic/kinetic parameters were collected using a motion capture system and a three-dimensional force platform. The Med-Lat Knee model was used to calculate biomechanical indicators of the knee joint, and data were analyzed using one-way analysis of variance and one-dimensional statistical parametric mapping (SPM1d). Findings indicated that landing height significantly affected the anterior-posterior and vertical MCF, flexion-extension torque, internal-external rotation torque, and vertical ground reaction force (p<0.05)-all increasing with elevated landing height-and significantly impacted the generated force of the vastus medialis, vastus lateralis, and vastus intermedius (p<0.05). SPM1d analysis confirmed these results within specific time intervals. Thus, both the knee moment and the MCF exhibited similar coordinated changes during drop jumps, indicating that these may be adaptive movement strategy. The impact of varying drop jump heights on muscle groups around the knee joint varied suggests that different heights induce specific muscular responses and improve muscle coordination to prevent knee joint injuries.

Variable-stiffness prosthesis improves biomechanics of walking across speeds compared to a passive device

Ankle push-off power plays an important role in healthy walking, contributing to center-of-mass acceleration, swing leg dynamics, and accounting for 45% of total leg power. The majority of existing passive energy storage and return prostheses for people with below-knee (transtibial) amputation are stiffer than the biological ankle, particularly at slower walking speeds. Additionally, passive devices provide insufficient levels of energy return and push-off power, negatively impacting biomechanics of gait. Here, we present a clinical study evaluating the kinematics and kinetics of walking with a microprocessor-controlled, variable-stiffness ankle-foot prosthesis (945 g) compared to a standard low-mass passive prosthesis (Ottobock Taleo, 463 g) with 7 study participants having unilateral transtibial amputation. By modulating prosthesis stiffness under computer control across walking speeds, we demonstrate that there exists a stiffness that increases prosthetic-side energy return, peak power, and center-of-mass push-off work, and decreases contralateral limb peak ground reaction force compared to the standard passive prosthesis across all evaluated walking speeds. We demonstrate a significant increase in center-of-mass push-off work of 26.1%, 26.2%, 29.6% and 29.9% at 0.75 m/s, 1.0 m/s, 1.25 m/s, and 1.5 m/s, respectively, and a significant decrease in contralateral limb ground reaction force of 3.1%, 3.9%, and 3.2% at 1.0 m/s, 1.25 m/s, and 1.5 m/s, respectively. This study demonstrates the potential for a quasi-passive microprocessor-controlled variable-stiffness prosthesis to increase push-off power and energy return during gait at a range of walking speeds compared to a passive device of a fixed stiffness.

An OpenSim thoracolumbar spine model applying a bottom-up modelling approach is similar to a top-down approach

The kinetic demands of the spine can be assessed using a top-down (TD) or bottom-up (BU) approach, which start calculations from the either the hands or from the feet, respectively. Biomechanists have traditionally favored a BU approach, though existing modeling approaches encourage a TD approach. Regardless of the approach the demands should be similar, provided the external forces and linked segment parameters are equivalently measured and modeled. Demonstrating a level of agreement between the two approaches can help evaluate a model. Further, having both approaches can be advantageous when data is inaccurate or unavailable for one. The purpose of this study was to compare the internal moments and forces at multiple lumbar and thoracic intervertebral joint (IVJ) levels during lifting tasks from an established OpenSim thoracolumbar spine model that applies a TD approach and a similar model modified to adopt a BU approach. Kinematics and external forces were recorded from twelve participants during sagittal and lateral lifts of different lifting speeds and crate masses. For both approaches IVJ kinetics were estimated using a standard OpenSim modeling pipeline. The BU and TD approach IVJ joint moments generally agreed both temporally (R2 = .94 ± .17) and in magnitude (RMSE=6.2 ± 3.5 Nm) of the primary planes of movement. There were however some temporal fit exceptions for off axes moments with low magnitudes (i.e., < 10 Nm). Bland-Altman plots also indicated acceptable agreement for IVJ peak forces (BU-TD difference of 12 ± 111 and 8 ± 31 N in compression and resultant shear, respectfully). These results support the application of the BU approach and the assigned linked segment parameters of the model. The new BU model is available on the SimTK site (https://simtk.org/projects/spine_ribcage).

An Extended Neck Position is Likely to Produce Cervical Spine Injuries Through Buckling in Accidental Head-First Impacts During Rugby Tackling

Catastrophic cervical spine injuries in rugby often occur during tackling. The underlying mechanisms leading to these injuries remain unclear, with neck hyperflexion and buckling both proposed as the causative factor in the injury prevention literature. The aim of this study was to evaluate the effect of pre-impact head-neck posture on intervertebral neck loads and motions during a head-first rugby tackle. Using a validated, subject-specific musculoskeletal model of a rugby player, and computer simulations driven by in vivo and in vitro data, we examined the dynamic response of the cervical spine under such impact conditions. The simulations demonstrated that the initial head-neck sagittal-plane posture affected intervertebral loads and kinematics, with an extended neck resulting in buckling and supraphysiologic intervertebral shear and flexion loads and motions, typical of bilateral facet dislocation injuries. In contrast, an initially flexed neck increased axial compression forces and flexion angles without exceeding intervertebral physiological limits. These findings provide objective evidence that can inform injury prevention strategies or rugby law changes to improve the safety of the game of rugby.

Efficient musculoskeletal annotation using free-form deformation

Traditionally, constructing training datasets for automatic muscle segmentation from medical images involved skilled operators, leading to high labor costs and limited scalability. To address this issue, we developed a tool that enables efficient annotation by non-experts and assessed its effectiveness for training an automatic segmentation network. Our system allows users to deform a template three-dimensional (3D) anatomical model to fit a target magnetic-resonance image using free-form deformation with independent control points for axial, sagittal, and coronal directions. This method simplifies the annotation process by allowing non-experts to intuitively adjust the model, enabling simultaneous annotation of all muscles in the template. We evaluated the quality of the tool-assisted segmentation performed by non-experts, which achieved a Dice coefficient greater than 0.75 compared to expert segmentation, without significant errors such as mislabeling adjacent muscles or omitting musculature. An automatic segmentation network trained with datasets created using this tool demonstrated performance comparable to or superior to that of networks trained with expert-generated datasets. This innovative tool significantly reduces the time and labor costs associated with dataset creation for automatic muscle segmentation, potentially revolutionizing medical image annotation and accelerating the development of deep learning-based segmentation networks in various clinical applications.

Clustering analysis across different speeds reveals two distinct running techniques with no differences in running economy

Establishing the links between running technique and economy remains elusive due to high inter-individual variability. Clustering runners by technique may enable tailored training recommendations, yet it is unclear if different techniques are equally economical and whether clusters are speed-dependent. This study aimed to identify clusters of runners based on technique and to compare cluster kinematics and running economy. Additionally, we examined the agreement of clustering partitions of the same runners at different speeds. Trunk and lower-body kinematics were captured from 84 trained runners at different speeds on a treadmill. We used Principal Component Analysis for dimensionality reduction and agglomerative hierarchical clustering to identify groups of runners with a similar technique, and we evaluated cluster agreement across speeds. Clustering runners at different speeds independently produced different partitions, suggesting single speed clustering can fail to capture the full speed profile of a runner. The two clusters identified using data from the whole range of speeds showed differences in pelvis tilt and duty factor. In agreement with self-optimisation theories, there were no differences in running economy, and no differences in participants' characteristics between clusters. Considering inter-individual technique variability may enhance the efficacy of training designs as opposed to 'one size fits all' approaches.

Estimation of joint torque in dynamic activities using wearable A-mode ultrasound

The human body constantly experiences mechanical loading. However, quantifying internal loads within the musculoskeletal system remains challenging, especially during unconstrained dynamic activities. Conventional measures are constrained to laboratory settings, and existing wearable approaches lack muscle specificity or validation during dynamic movement. Here, we present a strategy for estimating corresponding joint torque from muscles with different architectures during various dynamic activities using wearable A-mode ultrasound. We first introduce a method to track changes in muscle thickness using single-element ultrasonic transducers. We then estimate elbow and knee torque with errors less than 7.6% and coefficients of determination (R2) greater than 0.92 during controlled isokinetic contractions. Finally, we demonstrate wearable joint torque estimation during dynamic real-world tasks, including weightlifting, cycling, and both treadmill and outdoor locomotion. The capability to assess joint torque during unconstrained real-world activities can provide new insights into muscle function and movement biomechanics, with potential applications in injury prevention and rehabilitation.

Effect of changes in motor skill induced by educational video program to decrease lower-limb joint load during cutting maneuvers: based on musculoskeletal modeling

BACKGROUND

This study investigated the effects of changes in motor skills from an educational video program on the kinematic and kinetic variables of the lower extremity joints and knee ligament load.

METHODS

Twenty male participants (age: 22.2 ± 2.60 y; height: 1.70 ± 6.2 m; weight: 65.4 ± 7.01 kg; BMI: 23.32 ± 2.49 [Formula: see text]) were instructed to run at 4.5 ± 0.2 m/s from a 5 m distance posterior to the force plate, land their foot on the force plate, and perform the cutting maneuver on the left. The educational video program for cutting maneuvers consisted of preparatory posture, foot landing orientation, gaze and trunk directions, soft landing, and eversion angle. The measured variables were the angle, angular velocity of lower extremity joints, ground reaction force (GRF), moment, and anterior cruciate ligament (ACL) and medial collateral ligament (MCL) forces through musculoskeletal modeling.

RESULTS

After the video feedback, the hip joint angles increased in flexion, abduction, and external rotation (p < 0.05), and the angular velocity increased in extension (p < 0.05). The ankle joint angles increased in dorsiflexion (p < 0.05), and the angular velocity decreased in dorsiflexion (p < 0.05) but increased in abduction (p < 0.05). The GRF increased in the anterior-posterior and medial-lateral directions and decreased vertically (p < 0.05). The hip joint moments decreased in extension and external rotation (p < 0.05) but increased in adduction (p < 0.05). The knee joint moments were decreased in extension, adduction, and external rotation (p < 0.05). The abduction moment of the ankle joint decreased (p < 0.001). There were differences in the support zone corresponding to 64‒87% of the hip frontal moment (p < 0.001) and 32‒100% of the hip horizontal moment (p < 0.001) and differences corresponding to 32‒100% of the knee frontal moment and 21‒100% of the knee horizontal moment (p < 0.001). The GRF varied in the support zone at 44‒95% in the medial-lateral direction and at 17‒43% and 73‒100% in the vertical direction (p < 0.001).

CONCLUSIONS

Injury prevention feedback reduced the load on the lower extremity joints during cutting maneuvers, which reduced the knee ligament load, mainly on the MCL.

A Biomechanical Comparison Between a High and Low Barbell Placement on Net Joint Moments, Kinematics, Muscle Forces, and Muscle-Specific Moments in 3 Repetition Maximum Back Squats

ABSTRACT

Larsen, S, de Zee, M, Kristiansen, EL, and van den Tillaar, R. A biomechanical comparison between a high and low barbell placement on net joint moments, kinematics, muscle forces, and muscle-specific moments in 3 repetition maximum back squats. J Strength Cond Res 38(7): 1221-1230, 2024-This study aimed to investigate the impact of a high barbell vs. low barbell placement on net joint moments, muscle forces, and muscle-specific moments in the lower extremity joints and muscles during maximum back squats. Twelve recreationally trained men (age = 25.3 ± 2.9 years, height = 1.79 ± 7.7 m, and body mass = 82.8 ± 6.9 kg) volunteered for the study. A marker-based motion capture system and force plate data were used to calculate the net joint moments, and individual muscle forces were estimated using static optimization. Muscle forces were multiplied by their corresponding internal moment arms to determine muscle-specific moments. Statistical parametric mapping was used to analyze the effect of barbell placement as time-series data during the concentric phase. The 3 repetition maximum barbell load lifted by the subjects was 129.1 ± 13.4 kg and 130.2 ± 12.7 kg in the high bar and low bar, which were not significantly different from each other. Moreover, no significant differences were observed in net joint moments, muscle forces, or muscle-specific moments for the hip, knee, or ankle joint between the low- and high bar placements. The findings of this study suggest that barbell placement plays a minor role in lower extremity muscle forces and moment-specific moments when stance width is standardized, and barbell load lifted does not differ between barbell placements among recreationally resistance-trained men during maximal back squats. Therefore, the choice of barbell placement should be based on individual preference and comfort.

Hindfoot kinematics and kinetics - A combined in vivo and in silico analysis approach

BACKGROUND

The complex anatomical structure of the foot-ankle imposes challenges to accurately quantify detailed hindfoot kinematics and estimate musculoskeletal loading parameters. Most systems used to capture or estimate dynamic joint function oversimplify the anatomical structure by reducing its complexity.

RESEARCH QUESTION

Can four dimensional computed tomography (4D CT) imaging in combination with an innovative foot manipulator capture in vivo hindfoot kinematics during a simulated stance phase of walking and can talocrural and subtalar articular joint mechanics be estimated based on a detailed in silico musculoskeletal foot-ankle model.

METHODS

A foot manipulator imposed plantar/dorsiflexion and inversion/eversion representing a healthy stance phase of gait in 12 healthy participants while simultaneously acquiring 4D CT images. Participant-specific 3D hindfoot rotations and translations were calculated based on bone-specific anatomical coordinate systems. Articular cartilage contact area and contact pressure of the talocrural and subtalar joints were estimated using an extended foot-ankle model updated with an elastic foundation contact model upon prescribing the participant-specific rotations measured in the 4D CT measurement.

RESULTS

Plantar/dorsiflexion predominantly occurred at the talocrural joint (RoM 15.9±3.9°), while inversion/eversion (RoM 5.9±3.9°) occurred mostly at the subtalar joint, with the contact area being larger at the subtalar than at the talocrural joint. Contact pressure was evenly distributed between the talocrural and subtalar joint at the beginning of the simulated stance phase but was then redistributed from the talocrural to the subtalar joint with increasing dorsiflexion.

SIGNIFICANCE

In a clinical case study, the healthy participants were compared with four patients after surgically treaded intra-articular calcaneal fracture. The proposed workflow was able to detect small but meaningful differences in hindfoot kinematics and kinetics, indicative of remaining hindfoot pathomechanics that may influence the onset and progression of degenerative joint diseases.

NeuroMotion: Open-source platform with neuromechanical and deep network modules to generate surface EMG signals during voluntary movement

Neuromechanical studies investigate how the nervous system interacts with the musculoskeletal (MSK) system to generate volitional movements. Such studies have been supported by simulation models that provide insights into variables that cannot be measured experimentally and allow a large number of conditions to be tested before the experimental analysis. However, current simulation models of electromyography (EMG), a core physiological signal in neuromechanical analyses, remain either limited in accuracy and conditions or are computationally heavy to apply. Here, we provide a computational platform to enable future work to overcome these limitations by presenting NeuroMotion, an open-source simulator that can modularly test a variety of approaches to the full-spectrum synthesis of EMG signals during voluntary movements. We demonstrate NeuroMotion using three sample modules. The first module is an upper-limb MSK model with OpenSim API to estimate the muscle fibre lengths and muscle activations during movements. The second module is BioMime, a deep neural network-based EMG generator that receives nonstationary physiological parameter inputs, like the afore-estimated muscle fibre lengths, and efficiently outputs motor unit action potentials (MUAPs). The third module is a motor unit pool model that transforms the muscle activations into discharge timings of motor units. The discharge timings are convolved with the output of BioMime to simulate EMG signals during the movement. We first show how MUAP waveforms change during different levels of physiological parameter variations and different movements. We then show that the synthetic EMG signals during two-degree-of-freedom hand and wrist movements can be used to augment experimental data for regressing joint angles. Ridge regressors trained on the synthetic dataset were directly used to predict joint angles from experimental data. In this way, NeuroMotion was able to generate full-spectrum EMG for the first use-case of human forearm electrophysiology during voluntary hand, wrist, and forearm movements. All intermediate variables are available, which allows the user to study cause-effect relationships in the complex neuromechanical system, fast iterate algorithms before collecting experimental data, and validate algorithms that estimate non-measurable parameters in experiments. We expect this modular platform will enable validation of generative EMG models, complement experimental approaches and empower neuromechanical research.

ArborSim: Articulated, branching, OpenSim routing for constructing models of multi-jointed appendages with complex muscle-tendon architecture

Computational models of musculoskeletal systems are essential tools for understanding how muscles, tendons, bones, and actuation signals generate motion. In particular, the OpenSim family of models has facilitated a wide range of studies on diverse human motions, clinical studies of gait, and even non-human locomotion. However, biological structures with many joints, such as fingers, necks, tails, and spines, have been a longstanding challenge to the OpenSim modeling community, especially because these structures comprise numerous bones and are frequently actuated by extrinsic muscles that span multiple joints-often more than three-and act through a complex network of branching tendons. Existing model building software, typically optimized for limb structures, makes it difficult to build OpenSim models that accurately reflect these intricacies. Here, we introduce ArborSim, customized software that efficiently creates musculoskeletal models of highly jointed structures and can build branched muscle-tendon architectures. We used ArborSim to construct toy models of articulated structures to determine which morphological features make a structure most sensitive to branching. By comparing the joint kinematics of models constructed with branched and parallel muscle-tendon units, we found that among various parameters-the number of tendon branches, the number of joints between branches, and the ratio of muscle fiber length to muscle tendon unit length-the number of tendon branches and the number of joints between branches are most sensitive to branching modeling method. Notably, the differences between these models showed no predictable pattern with increased complexity. As the proportion of muscle increased, the kinematic differences between branched and parallel models units also increased. Our findings suggest that stress and strain interactions between distal tendon branches and proximal tendon and muscle greatly affect the overall kinematics of a musculoskeletal system. By incorporating complex muscle-tendon branching into OpenSim models using ArborSim, we can gain deeper insight into the interactions between the axial and appendicular skeleton, model the evolution and function of diverse animal tails, and understand the mechanics of more complex motions and tasks.

Effects of overweight and obesity on lower limb walking characteristics from joint kinematics to muscle activations

BACKGROUND

Obesity is a crucial factor that increases the risk of initiating and advancing knee osteoarthritis. However, it remains unclear how obesity directly impacts the biomechanical experience of the lower limb joints, potentially triggering or exacerbating joint degeneration. This study investigated the interactive effects of BMI augmentation on lower limb kinematics, kinetics, and muscle activations during walking.

METHODOLOGY

A group of 60 participants underwent a three-dimensional gait analysis. These individuals were categorized into three groups based on their body mass index (BMI): those with a BMI below 25 were classified as having a healthy weight, those with a BMI between 25 and 30 were categorized as overweight, and those with a BMI exceeding 30 were considered obese. This study analyzed the gait of 60 participants categorized by BMI. During walking trials, they recorded ground reaction forces electromyography of leg muscles like the gastrocnemii, hamstrings, and quadriceps. Lower limb joint angles and net moments were also calculated. Statistical mapping identified variations in kinematic, kinetic, and muscle activation patterns across the stance phase between BMI groups.

RESULTS

The results displayed distinct biomechanical patterns in obese individuals. Notably, there was a significant increase in flexion observed in the hip and knee joints (P < 0.001) during the initial stance phase and an increase in hip and knee adduction angles and moments throughout the entire stance phase (P < 0.001). Additionally, muscle activations underwent significant changes (P < 0.01), with a positive correlation noted with the BMI factor. This correlation was most pronounced during the early stance phase for the quadriceps and hamstring muscles and the late stance phase for the gastrocnemius.

CONCLUSION

These findings represent a comprehensive picture that contributes to understanding how excess weight and obesity influence joint biomechanics, highlighting the associated risk of joint osteoarthritis.

An articulated shape model to predict paediatric lower limb bone geometry using sparse landmarks

Creating musculoskeletal models in a paediatric population currently involves either creating an image-based model from medical imaging data or a generic model using linear scaling. Image-based models provide a high level of accuracy but are time-consuming and costly to implement, on the other hand, linear scaling of an adult template musculoskeletal model is faster and common practice, but the output errors are significantly higher. An articulated shape model incorporates pose and shape to predict geometry for use in musculoskeletal models based on existing information from a population to provide both a fast and accurate method. From a population of 333 children aged 4-18 years old, we have developed an articulated shape model of paediatric lower limb bones to predict bone geometry from eight bone landmarks commonly used for motion capture. Bone surface root mean squared errors were found to be 2.63 ± 0.90 mm, 1.97 ± 0.61 mm, and 1.72 ± 0.51 mm for the pelvis, femur, and tibia/fibula, respectively. Linear scaling produced bone surface errors of 4.79 ± 1.39 mm, 4.38 ± 0.72 mm, and 4.39 ± 0.86 mm for the pelvis, femur, and tibia/fibula, respectively. Clinical bone measurement errors were low across all bones predicted using the articulated shape model, which outperformed linear scaling for all measurements. However, the model failed to accurately capture torsional measures (femoral anteversion and tibial torsion). Overall, the articulated shape model was shown to be a fast and accurate method to predict lower limb bone geometry in a paediatric population, superior to linear scaling.

Simulation-driven design of smart gloves for gesture recognition

Smart gloves are in high demand for entertainment, manufacturing, and rehabilitation. However, designing smart gloves has been complex and costly due to trial and error. We propose an open simulation platform for designing smart gloves, including optimal sensor placement and deep learning models for gesture recognition, with reduced costs and manual effort. Our pipeline starts with 3D hand pose extraction from videos and extends to the refinement and conversion of the poses into hand joint angles based on inverse kinematics, the sensor placement optimization based on hand joint analysis, and the training of deep learning models using simulated sensor data. In comparison to the existing platforms that always require precise motion data as input, our platform takes monocular videos, which can be captured with widely available smartphones or web cameras, as input and integrates novel approaches to minimize the impact of the errors induced by imprecise motion extraction from videos. Moreover, our platform enables more efficient sensor placement selection. We demonstrate how the pipeline works and how it delivers a sensible design for smart gloves in a real-life case study. We also evaluate the performance of each building block and its impact on the reliability of the generated design.

Pelvic Tilt in Adults With Cerebral Palsy and Its Relationship With Prior Hamstrings Lengthening

BACKGROUND

Current studies assessing the change in pelvic tilt for ambulatory patients with cerebral palsy (CP) after surgical hamstring lengthening (SHL) lack a comparison cohort without prior SHL and are limited to younger patients. This study presents gait data of middle-aged adults with CP, primarily focusing on the pelvis, and compares pelvic tilt, trunk tilt, and knee flexion between those with and without prior SHL.

MATERIALS AND METHODS

A consecutive series of 54 adults with CP, a mean age of 36±13 years, and Gross Motor Function Classification System (GMFCS) levels I-III were included. Thirty-two (59%) had SHL performed at a mean age of 8±5 years. Three-dimensional gait analysis data prospectively collected at a mean of 28±14 years postoperatively were retrospectively analyzed. Chi-square tests were used to compare demographic and surgical history data and statistical parameter mapping was used to compare knee flexion during stance and pelvic and trunk tilts during the gait cycle between SHL and SHL-naive groups.

RESULTS

Age, GMFCS level, sex, race, topography, and ethnicity were not different between the groups (P=.217-.612). Anterior pelvic tilt throughout gait was significantly greater in the SHL group compared with the SHL-naive group (63%-87%; P=.033). This difference was augmented after accounting for other surgical history and revision SHL (0%-32%, P=.019; and 46%-93%, P=.007).

CONCLUSION

Within a cohort of adults with CP, GMFCS levels I-III, and a mean age of 36 years, those with a history of SHL, performed a mean of 28 years prior to 3-dimensional gait analysis, walked with increased anterior pelvic tilt compared with those without a history of SHL. [Orthopedics. 202x;4x(x):xx-xx.].

Squatting biomechanics following physiotherapist-led care or hip arthroscopy for femoroacetabular impingement syndrome: a secondary analysis from a randomised controlled trial

Background

Femoroacetabular impingement syndrome (FAIS) can cause hip pain and chondrolabral damage that may be managed non-operatively or surgically. Squatting motions require large degrees of hip flexion and underpin many daily and sporting tasks but may cause hip impingement and provoke pain. Differential effects of physiotherapist-led care and arthroscopy on biomechanics during squatting have not been examined previously. This study explored differences in 12-month changes in kinematics and moments during squatting between patients with FAIS treated with a physiotherapist-led intervention (Personalised Hip Therapy, PHT) and arthroscopy.

Methods

A subsample (n = 36) of participants with FAIS enrolled in a multi-centre, pragmatic, two-arm superiority randomised controlled trial underwent three-dimensional motion analysis during squatting at baseline and 12-months following random allocation to PHT (n = 17) or arthroscopy (n = 19). Changes in time-series and peak trunk, pelvis, and hip biomechanics, and squat velocity and maximum depth were explored between treatment groups.

Results

No significant differences in 12-month changes were detected between PHT and arthroscopy groups. Compared to baseline, the arthroscopy group squatted slower at follow-up (descent: mean difference -0.04 m∙s-1 (95%CI [-0.09 to 0.01]); ascent: -0.05 m∙s-1 [-0.11 to 0.01]%). No differences in squat depth were detected between or within groups. After adjusting for speed, trunk flexion was greater in both treatment groups at follow-up compared to baseline (descent: PHT 7.50° [-14.02 to -0.98]%; ascent: PHT 7.29° [-14.69 to 0.12]%, arthroscopy 16.32° [-32.95 to 0.30]%). Compared to baseline, both treatment groups exhibited reduced anterior pelvic tilt (descent: PHT 8.30° [0.21-16.39]%, arthroscopy -10.95° [-5.54 to 16.34]%; ascent: PHT -7.98° [-0.38 to 16.35]%, arthroscopy -10.82° [3.82-17.81]%), hip flexion (descent: PHT -11.86° [1.67-22.05]%, arthroscopy -16.78° [8.55-22.01]%; ascent: PHT -12.86° [1.30-24.42]%, arthroscopy -16.53° [6.72-26.35]%), and knee flexion (descent: PHT -6.62° [0.56- 12.67]%; ascent: PHT -8.24° [2.38-14.10]%, arthroscopy -8.00° [-0.02 to 16.03]%). Compared to baseline, the PHT group exhibited more plantarflexion during squat ascent at follow-up (-3.58° [-0.12 to 7.29]%). Compared to baseline, both groups exhibited lower external hip flexion moments at follow-up (descent: PHT -0.55 N∙m/BW∙HT[%] [0.05-1.05]%, arthroscopy -0.84 N∙m/BW∙HT[%] [0.06-1.61]%; ascent: PHT -0.464 N∙m/BW∙HT[%] [-0.002 to 0.93]%, arthroscopy -0.90 N∙m/BW∙HT[%] [0.13-1.67]%).

Conclusion

Exploratory data suggest at 12-months follow-up, neither PHT or hip arthroscopy are superior at eliciting changes in trunk, pelvis, or lower-limb biomechanics. Both treatments may induce changes in kinematics and moments, however the implications of these changes are unknown.

Trial registration details

Australia New Zealand Clinical Trials Registry reference: ACTRN12615001177549. Trial registered 2/11/2015.

Effects of bench press technique variations on musculoskeletal shoulder loads and potential injury risk

While shoulder injuries resulting from the bench press exercise are commonly reported, no biomechanical evidence for lowering injury risk is currently available. Therefore, the aim of the present study was to compare musculoskeletal shoulder loads and potential injury risk during several bench press variations. Ten experienced strength athletes performed 21 technical variations of the barbell bench press, including variations in grip width of 1,1.5 and 2 bi-acromial widths (BAW), shoulder abduction angles of 45°, 70° and 90°, and scapula poses including neutral, retracted, and released conditions. Motions and forces were recorded by an opto-electronic measurement system and an instrumented barbell. An OpenSim musculoskeletal shoulder model was employed to estimate joint reaction forces in the glenohumeral and acromioclavicular joints. Time-series of joint reaction forces were compared between techniques by statistical non-parametric mapping. Results showed that narrower grip widths of < 1.5 BAW decreased acromioclavicular compression (p < 0.05), which may decrease the risk for distal clavicular osteolysis. Moreover, scapula retraction, as well as a grip width of < 1.5 BAW (p < 0.05), decreased glenohumeral posterior shear force components and rotator cuff activity and may decrease the risk for glenohumeral instability and rotator cuff injuries. Furthermore, results showed that mediolaterally exerted barbell force components varied considerably between athletes and largely affected shoulder reaction forces. It can be concluded that the grip width, scapula pose and mediolateral exerted barbell forces during the bench press influence musculoskeletal shoulder loads and the potential injury risk. Results of this study can contribute to safer bench press training guidelines.

Increased knee flexion in participants with cerebral palsy results in altered stresses at the distal femoral growth plate compared to a typically developing cohort

INTRODUCTION

Femoral deformities are highly prevalent in children with cerebral palsy (CP) and can have a severe impact on patients' gait abilities. While the mechanical stress regime within the distal femoral growth plate remains underexplored, understanding it is crucial given bone's adaptive response to mechanical stimuli. We quantified stresses at the distal femoral growth plate to deepen our understanding of the relationship between healthy and pathological gait patterns, internal loading, and femoral growth patterns.

METHODS

This study included three-dimensional motion capture data and magnetic resonance images of 13 typically developing children and twelve participants with cerebral palsy. Employing a multi-scale mechanobiological approach, integrating musculoskeletal simulations and subject-specific finite element analysis, we investigated the orientation of the distal femoral growth plate and the stresses within it. Limbs of participants with CP were grouped depending on their knee flexion kinematics during stance phase as this potentially changes the stresses induced by knee and patellofemoral joint contact forces.

RESULTS

Despite similar growth plate orientation across groups, significant differences were observed in the shape and distribution of growth values. Higher growth rates were noted in the anterior compartment in CP limbs with high knee flexion while CP limbs with normal knee flexion showed high similarity to the group of healthy participants.

DISCUSSION

Results indicate that the knee flexion angle during the stance phase is of high relevance for typical bone growth at the distal femur. The evaluated growth rates reveal plausible results, as long-term promoted growth in the anterior compartment leads to anterior bending of the femur which was confirmed for the group with high knee flexion through analyses of the femoral geometry. The framework for these multi-scale simulations has been made accessible on GitHub, empowering peers to conduct similar mechanobiological studies. Advancing our understanding of femoral bone development could ultimately support clinical decision-making.

Classification of Fashion Models' Walking Styles Using Publicly Available Data, Pose Detection Technology, and Multivariate Analysis: From Past to Current Trendy Walking Styles

Understanding past and current trends is crucial in the fashion industry to forecast future market demands. This study quantifies and reports the characteristics of the trendy walking styles of fashion models during real-world runway performances using three cutting-edge technologies: (a) publicly available video resources, (b) human pose detection technology, and (c) multivariate human-movement analysis techniques. The skeletal coordinates of the whole body during one gait cycle, extracted from publicly available video resources of 69 fashion models, underwent principal component analysis to reduce the dimensionality of the data. Then, hierarchical cluster analysis was used to classify the data. The results revealed that (1) the gaits of the fashion models analyzed in this study could be classified into five clusters, (2) there were significant differences in the median years in which the shows were held between the clusters, and (3) reconstructed stick-figure animations representing the walking styles of each cluster indicate that an exaggerated leg-crossing gait has become less common over recent years. Accordingly, we concluded that the level of leg crossing while walking is one of the major changes in trendy walking styles, from the past to the present, directed by the world's leading brands.

The effect of body weight on the knee joint biomechanics based on subject-specific finite element-musculoskeletal approach

Knee osteoarthritis (OA) and obesity are major public health concerns that are closely intertwined. This intimate relationship was documented by considering obesity as the most significant preventable risk factor associated with knee OA. To date, however, the effects of obesity on the knee joint's passive-active structure and cartilage loading have been inconclusive. Hence, this study investigates the intricate relationship between obesity and knee OA, centering on the biomechanical changes in knee joint active and passive reactions during the stance phase of gait. Using a subject-specific musculoskeletal and finite element approach, muscle forces, ligament stresses, and articular cartilage contact stresses were analyzed among 60 individuals with different body mass indices (BMI) classified under healthy weight, overweight, and obese categories. Our predicted results showed that obesity significantly influenced knee joint mechanical reaction, increasing muscle activations, ligament loading, and articular cartilage contact stresses, particularly during key instances of the gait cycle-first and second peak loading instances. The study underscores the critical role of excessive body weight in exacerbating knee joint stress distribution and cartilage damage. Hence, the insights gained provide a valuable biomechanical perspective on the interaction between body weight and knee joint health, offering a clinical utility in assessing the risks associated with obesity and knee OA.

Rethinking Exoskeleton Simulation-Based Design: The Effect of Using Different Cost Functions

Designing an exoskeleton that can improve user capabilities is a challenging task, and most designs rely on experiments to achieve this goal. A different approach is to use simulation-based designs to determine optimal device parameters. Most of these simulations use full trajectory tracking limb kinematics during a natural gait as a reference. However, exoskeletons typically change the natural gait kinematics of the user. Other types of simulations assume that human gait is optimized for a cost function that combines several objectives, such as the cost of transport, injury prevention, and stabilization. In this study, we use a 2D OpenSim model consisting of 10 degrees of freedom and considering 18 muscles, together with the Moco optimization tool, to investigate the differences between these two approaches with respect to running with a passive knee exoskeleton. Utilizing this model, we test the effect of a full trajectory tracking objective with different weights (representing the importance of the objective in the optimization cost function) and show that when using weights that are typically used in the literature, there is no deviation from the experimental data. Next, we develop a multi-objective cost function with foot clearance term based on peak knee angle during swing, that achieves trajectories similar (RMSE=7.4 deg) to experimental running data. Finally, we investigate the effect of different parameters in the design of a clutch-based passive knee exoskeleton (1.5 kg at each leg) and find that a design that utilizes a 2.5 Nm/deg spring achieves an improvement of up to 8% in net metabolic energy. Our results show that tracking objectives in the cost function, even with a low weight, hinders the simulation's ability to change the gait trajectory. Thus, there is a need for other predictive simulation methods for exoskeletons.

Asymmetry in kinematics of dominant/nondominant lower limbs in central and lateral positioned college and sub-elite soccer players

Change of direction, stops, and pivots are among the most common non-contact movements associated with anterior cruciate ligament (ACL) injuries in soccer. By observing these dynamic movements, clinicians recognize abnormal kinematic patterns that contribute to ACL tears such as increased knee valgus or reduced knee flexion. Different motions and physical demands are observed across playing positions, which may result in varied lower limb kinematic patterns. In the present study, 28 college and sub-elite soccer players performed four dynamic motions (change of direction with and without ball, header, and instep kick) with the goal of examining the effect of on-field positioning, leg dominance, and gender in lower body kinematics. Motion capture software monitored joint angles in the knee, hip, and ankle. A three-way ANOVA showed significant differences in each category. Remarkably, centrally positioned players displayed significantly greater knee adduction (5° difference, p = 0.013), hip flexion (9° difference, p = 0.034), hip adduction (7° difference, p = 0.016), and dorsiflexion (12° difference, p = 0.022) when performing the instep kick in comparison to their laterally positioned counterparts. These findings suggest that central players tend to exhibit a greater range of motion when performing an instep kicking task compared to laterally positioned players. At a competitive level, this discrepancy could potentially lead to differences in lower limb muscle development among on-field positions. Accordingly, it is suggested to implement position-specific prevention programs to address these asymmetries in lower limb kinematics, which can help mitigate dangerous kinematic patterns and consequently reduce the risk of ACL injury in soccer players.

E, MacInnis MJ, Nigg BM. Counterweight mass influences single-leg cycling biomechanics

INTRODUCTION

Single-leg cycling is a commonly used intervention in exercise physiology that has applications in exercise training and rehabilitation. The addition of a counterweight to the contralateral pedal helps single-leg cycling mimic cycling patterns of double-leg cycling. To date, no research has tested (a) the influence of a wide range of counterweight masses on a person's cycling biomechanics and (b) the optimal counterweight mass to emulate double-leg cycling.

OBJECTIVES

The purpose of this study was to determine the effects of varying counterweights on the kinematics (joint angles) and kinetics (joint moments, work) of cycling using a 3D analysis.

METHODS

Twelve participants cycled at 50W or 100W with different counterweight masses (0 to 30 lbs, 2.5 lbs increments), while we analyzed the pedal force data, joint angles, joint moments, and joint power of the lower limb using 3D motion capture and 3D instrumented pedals to create participant-specific musculoskeletal models.

RESULTS

The results showed that no single-leg cycling condition truly emulated double-leg cycling with respect to all measured variables, namely pedal forces (p ≤ 0.05), joint angles (p ≤ 0.05), joint moments(p ≤ 0.05), and joint powers (p ≤ 0.05), but higher counterweights resulted in single-leg cycling that was statistically similar (p > 0.05), but descriptively, asymptotically approached the biomechanics of double-leg cycling.

CONCLUSION

We suggest that a 20-lb counterweight is a conservative estimate of the counterweight required for using single-leg cycling in exercise physiology studies, but further modifications are needed to the cycle ergometer for the biomechanics of single-leg cycling to match those of double-leg cycling.

Sensitivity of knee cartilage biomechanics in finite element analysis to selected Musculoskeletal models

Knee joint kinematics and kinetics analyzed by musculoskeletal (MS) modeling are often utilized in finite element (FE) models, estimating tissue-level mechanical responses. We compared knee cartilage stresses, strains, and centers of pressure of FE models driven by two widely used MS models, implemented in AnyBody and OpenSim. Minor discrepancies in the results were observed between the models. AnyBody-driven FE models showed slightly higher stresses in the medial tibial cartilage, while OpenSim-driven FE models estimated more anterior and lateral center of pressure. Recognizing these differences in the MS-FE models is important to ensure reliable analysis of cartilage mechanics and failure and simulation of rehabilitation.

An alpha- to gamma-motoneurone collateral can mitigate velocity-dependent stretch reflexes during voluntary movement: A computational study

The primary motor cortex does not uniquely or directly produce alpha motoneurone (α-MN) drive to muscles during voluntary movement. Rather, α-MN drive emerges from the synthesis and competition among excitatory and inhibitory inputs from multiple descending tracts, spinal interneurons, sensory inputs, and proprioceptive afferents. One such fundamental input is velocity-dependent stretch reflexes in lengthening muscles, which should be inhibited to enable voluntary movement. It remains an open question, however, the extent to which unmodulated stretch reflexes disrupt voluntary movement, and whether and how they are inhibited in limbs with numerous multi-articular muscles. We used a computational model of a Rhesus Macaque arm to simulate movements with feedforward α-MN commands only, and with added velocity-dependent stretch reflex feedback. We found that velocity-dependent stretch reflex caused movement-specific, typically large and variable disruptions to arm movements. These disruptions were greatly reduced when modulating velocity-dependent stretch reflex feedback (i) as per the commonly proposed (but yet to be clarified) idealized alpha-gamma (α-γ) co-activation or (ii) an alternative α-MN collateral projection to homonymous γ-MNs. We conclude that such α-MN collaterals are a physiologically tenable, but previously unrecognized, propriospinal circuit in the mammalian fusimotor system. These collaterals could still collaborate with α-γ co-activation, and the few skeletofusimotor fibers (β-MNs) in mammals, to create a flexible fusimotor ecosystem to enable voluntary movement. By locally and automatically regulating the highly nonlinear neuro-musculo-skeletal mechanics of the limb, these collaterals could be a critical low-level enabler of learning, adaptation, and performance via higher-level brainstem, cerebellar and cortical mechanisms.

Prediction of Achilles Tendon Force During Common Motor Tasks From Markerless Video

Remodeling of the Achilles tendon (AT) is partly driven by its mechanical environment. AT force can be estimated with neuromusculoskeletal (NMSK) modeling; however, the complex experimental setup required to perform the analyses confines use to the laboratory. We developed task-specific long short-term memory (LSTM) neural networks that employ markerless video data to predict the AT force during walking, running, countermovement jump, single-leg landing, and single-leg heel rise. The task-specific LSTM models were trained on pose estimation keypoints and corresponding AT force data from 16 subjects, calculated via an established NMSK modeling pipeline, and cross-validated using a leave-one-subject-out approach. As proof-of-concept, new motion data of one participant was collected with two smartphones and used to predict AT forces. The task-specific LSTM models predicted the time-series AT force using synthesized pose estimation data with root mean square error (RMSE) ≤ 526 N, normalized RMSE (nRMSE) ≤ 0.21 , R 2 ≥ 0.81 . Walking task resulted the most accurate with RMSE = 189±62 N; nRMSE = 0.11±0.03 , R 2 = 0.92±0.04 . AT force predicted with smartphones video data was physiologically plausible, agreeing in timing and magnitude with established force profiles. This study demonstrated the feasibility of using low-cost solutions to deploy complex biomechanical analyses outside the laboratory.

Impedance-based biomechanical method for robust inverse kinematics from noisy data

This paper presents a novel method for solving the inverse kinematic problem of capturing human reaching movements using a dynamic biomechanical model. The model consists of rigid segments connected by joints and actuated by markers. The method was validated against a rotation matrix-based method using motion capture data recorded during reaching movements performed by healthy human volunteers. The results showed that the proposed method achieved low errors in joint angles and compensated for noise in motion capture data. The angles were comparable to those calculated using the standard marker-based method. The proposed bioinspired method can be used in real-time medical applications for processing noisy marker data with occlusions.

Neuromuscular and trunk control mediate factors associated with injury in fatigued runners

This study aimed to determine how fatigue affects factors associated with injury, neuromuscular activity, and control in recreational runners. Previously identified injury risk factors were defined as peak vertical instantaneous loading rates (pVILR) for tibial stress fracture (TSF) and peak hip adduction (pHADD) for patellofemoral pain syndrome and iliotibial band syndrome. Kinematics, kinetics, and electromyography data were collected from 11 recreational runners throughout a fatiguing run. Three trials were collected in the first and final minutes of the run. Coactivation was quantified about the knee and ankle for the entire stance phase and anticipatory, weight acceptance (WA), and propulsion sub-phases of stance. Trunk control was quantified by the peak mediolateral lean, peak forward lean, and flexion range of motion (ROM). There were significant increases in pHADD and pVILR when fatigued. Significant decreases in coactivation around the knee were found over the entire stance phase, in the anticipatory phase, and WA phase. Coactivation decreased about the ankle during WA. Lateral trunk lean significantly increased when fatigued, but no significant changes were found in flexion ROM or lean. Mediation analyses showed changes in ankle coactivation during WA, and lateral trunk lean are significant influences on pVILR, a measure associated with TSF. Fatigue-induced adaptations of decreasing ankle coactivation during WA and increased lateral trunk lean may increase the likelihood of TSF. In this study, a fatiguing run influenced changes in control in recreational runners. Further investigation of causal fatigue-induced injuries is necessary to better understand the effects of coactivation and trunk control.

EMG-Constrained and Ultrasound-Informed Muscle-Tendon Parameter Estimation in Post-Stroke Hemiparesis

Secondary morphological and mechanical property changes in the muscle-tendon unit at the ankle joint are often observed in post-stroke individuals. These changes may alter the force generation capacity and affect daily activities such as locomotion. This work aimed to estimate subject-specific muscle-tendon parameters in individuals after stroke by solving the muscle redundancy problem using direct collocation optimal control methods based on experimental electromyography (EMG) signals and measured muscle fiber length. Subject-specific muscle-tendon parameters of the gastrocnemius, soleus, and tibialis anterior were estimated in seven post-stroke individuals and seven healthy controls. We found that the maximum isometric force, tendon stiffness and optimal fiber length in the post-stroke group were considerably lower than in the control group. We also computed the root mean square error between estimated and experimental values of muscle excitation and fiber length. The musculoskeletal model with estimated subject-specific muscle tendon parameters (from the muscle redundancy solver), yielded better muscle excitation and fiber length estimations than did scaled generic parameters. Our findings also showed that the muscle redundancy solver can estimate muscle-tendon parameters that produce force behavior in better accordance with the experimentally-measured value. These muscle-tendon parameters in the post-stroke individuals were physiologically meaningful and may shed light on treatment and/or rehabilitation planning.

Achilles Tendon Loading during Running Estimated Via Shear Wave Tensiometry: A Step Toward Wearable Kinetic Analysis

PURPOSE

Understanding muscle-tendon forces (e.g., triceps surae and Achilles tendon) during locomotion may aid in the assessment of human performance, injury risk, and rehabilitation progress. Shear wave tensiometry is a noninvasive technique for assessing in vivo tendon forces that has been recently adapted to a wearable technology. However, previous laboratory-based and outdoor tensiometry studies have not evaluated running. This study was undertaken to assess the capacity for shear wave tensiometry to produce valid measures of Achilles tendon loading during running at a range of speeds.

METHODS

Participants walked (1.34 m·s -1 ) and ran (2.68, 3.35, and 4.47 m·s -1 ) on an instrumented treadmill while shear wave tensiometers recorded Achilles tendon wave speeds simultaneously with whole-body kinematic and ground reaction force data. A simple isometric task allowed for the participant-specific conversion of Achilles tendon wave speeds to forces. Achilles tendon forces were compared with ankle torque measures obtained independently via inverse dynamics analyses. Differences in Achilles tendon wave speed, Achilles tendon force, and ankle torque across walking and running speeds were analyzed with linear mixed-effects models.

RESULTS

Achilles tendon wave speed, Achilles tendon force, and ankle torque exhibited similar temporal patterns across the stance phase of walking and running. Significant monotonic increases in peak Achilles tendon wave speed (56.0-83.8 m·s -1 ), Achilles tendon force (44.0-98.7 N·kg -1 ), and ankle torque (1.72-3.68 N·m·(kg -1 )) were observed with increasing locomotion speed (1.34-4.47 m·s -1 ). Tensiometry estimates of peak Achilles tendon force during running (8.2-10.1 body weights) were within the range of those estimated previously via indirect methods.

CONCLUSIONS

These results set the stage for using tensiometry to evaluate Achilles tendon loading during unobstructed athletic movements, such as running, performed in the field.

Inclusion of a skeletal model partly improves the reliability of lower limb joint angles derived from a markerless depth camera

A single depth camera provides a fast and easy approach to performing biomechanical assessments in a clinical setting; however, there are currently no established methods to reliably determine joint angles from these devices. The primary aim of this study was to compare joint angles as well as the between-day reliability of direct kinematics to model-constrained inverse kinematics recorded using a single markerless depth camera during a range of clinical and athletic movement assessments.A secondary aim was to determine the minimum number of trials required to maximize reliability. Eighteen healthy participants attended two testing sessions one week apart. Tasks included treadmill walking, treadmill running, single-leg squats, single-leg countermovement jumps, bilateral countermovement jumps, and drop vertical jumps. Keypoint data were processed using direct kinematics as well as in OpenSim using a full-body musculoskeletal model and inverse kinematics. Kinematic methods were compared using statistical parametric mapping and between-day reliability was calculated using intraclass correlation coefficients, mean absolute error, and minimal detectable change. Keypoint-derived inverse kinematics resulted in significantly smaller hip flexion (range = -9 to -2°), hip abduction (range = -3 to -2°), knee flexion (range = -5° to -2°), and greater dorsiflexion angles (range = 6-15°) than direct kinematics. Both markerless kinematic methods had high between-day reliability (inverse kinematics ICC 95 %CI = 0.83-0.90; direct kinematics ICC 95 %CI = 0.80-0.93). For certain tasks and joints, keypoint-derived inverse kinematics resulted in greater reliability (up to 0.47 ICC) and smaller minimal detectable changes (up to 13°) than direct kinematics. Performing 2-4 trials was sufficient to maximize reliability for most tasks. A single markerless depth camera can reliably measure lower limb joint angles, and skeletal model-constrained inverse kinematics improves lower limb joint angle reliability for certain tasks and joints.

Hip biomechanics in early recovery following fixation of intertrochanteric fractures: Results from a randomised controlled trial

Single and dual integrated screw femoral nails are both commonly used to treat intertrochanteric fractures. This study investigated if using single or dual integrated screw femoral nails result in different post-operative hip joint loading. In the presence of differences, we investigated potential contributing factors. Patients were randomised for treatment via single screw (Stryker, Gamma3) or dual-integrated screw nail (Smith and Nephew, Intertan). Pre-injury mobility levels were collected at enrolment. Hip radiographs and gait data were collected at six weeks (Gamma: 16; Intertan: 15) and six months (Gamma: 14; Intertan: 13) follow-up. The resultant hip joint reaction forces and abductor muscle forces were estimated using electromyography-assisted neuromusculoskeletal modelling during level walking gait. Our primary analysis focused on the resultant hip joint reaction force and abductor muscle forces. We compared between groups, across stance phase of walking gait, using statistical parametric mapping. At six weeks, the Intertan group showed a short (∼5% of stance phase) but substantial (33 % [0.3 × body weight] greater magnitude) resultant hip joint reaction force when compared to the Gamma group (P = 0.022). Higher gluteus medius forces (P = 0.009) were demonstrated in the Intertan group at six weeks. Harris Hip Scores followed the trend seen for the biomechanical outcomes with superior scores for the Intertan group at six weeks postoperative (P = 0.044). The use of dual-integrated screw femoral nails over single screw devices may allow for hip biomechanics more closely resembling normal hip function at earlier post-operative timepoints, but these appear to resolve by six months postoperative.

Hip contact forces can be predicted with a neural network using only synthesised key points and electromyography in people with hip osteoarthritis

OBJECTIVE

To develop and validate a neural network to estimate hip contact forces (HCF), and lower body kinematics and kinetics during walking in individuals with hip osteoarthritis (OA) using synthesised anatomical key points and electromyography. To assess the capability of the neural network to detect directional changes in HCF resulting from prescribed gait modifications.

DESIGN

A calibrated electromyography-informed neuromusculoskeletal model was used to compute lower body joint angles, moments, and HCF for 17 participants with mild-to-moderate hip OA. Anatomical key points (e.g., joint centres) were synthesised from marker trajectories and augmented with bias and noise expected from computer vision-based pose estimation systems. Temporal convolutional and long short-term memory neural networks (NN) were trained using leave-one-subject-out validation to predict neuromusculoskeletal modelling outputs from the synthesised key points and measured electromyography data from 5 hip-spanning muscles.

RESULTS

HCF was predicted with an average error of 13.4 ± 7.1% of peak force. Joint angles and moments were predicted with an average root-mean-square-error of 5.3 degrees and 0.10 Nm/kg, respectively. The NN could detect changes in peak HCF that occur due to gait modifications with good agreement with neuromusculoskeletal modelling (r2 = 0.72) and a minimum detectable change of 9.5%.

CONCLUSION

The developed neural network predicted HCF and lower body joint angles and moments in individuals with hip OA using noisy synthesised key point locations with acceptable errors. Changes in HCF magnitude due to gait modifications were predicted with high accuracy. These findings have important implications for implementation of load-modification based gait retraining interventions for people with hip OA in a natural environment (i.e., home, clinic).

Biomechanical improvements in gait following medial pivot knee implant surgery

BACKGROUND

Total knee replacements are used to improve function and reduce pain in patients with advanced osteoarthritis. The medially stabilising implant is designed to mimic a healthy knee. This study aims to provide a comprehensive analysis of the kinematics and kinetics of a medially stabilising knee implant, comparing it to a healthy control group, as well as to its pre-operative state and the contralateral limb.

METHODS

Sixteen total knee replacement patients and ten healthy participants were recruited. Patients underwent testing 4-6 weeks before surgery and repeated the same tests 12 months after surgery. Healthy participants completed the same tests at a single time point. All participants completed three walking trials: kinematics was captured with eight cameras; kinetics with in-ground force plates. Subject-specific musculoskeletal models were developed in OpenSim. Inverse kinematics and inverse dynamics were used to determine gait parameters. Joint angles and joint moments were evaluated using Statistical Parametric Mapping. Patient-reported outcome measures were also collected at both time points.

FINDINGS

Spatiotemporal results indicate significant differences in velocity and step length between pre-operative patients and control participants. Differences are observed in the adduction angles between the contralateral and ipsilateral limbs pre-operatively. Postoperatively, there was an increase in the 1st peak flexion moment, reduced adduction moment and reduced internal rotation moment. In PROMs, patients all report improvements in pain levels and high satisfaction levels following surgery.

INTERPRETATIONS

Following medial stabilising total knee arthroplasty, patients displayed improved clinical parameters and joint moments reflecting a shift towards more normal, healthy gait.

Determining a musculoskeletal system's pre-stretched state using continuum-mechanical forward modelling and joint range optimization

The subject-specific range of motion (RoM) of a musculoskeletal joint system is balanced by pre-tension levels of individual muscles, which affects their contraction capability. Such an inherent pre-tension or pre-stretch of muscles is not measureable with in vivo experiments. Using a 3D continuum mechanical forward simulation approach for motion analysis of the musculoskeletal system of the forearm with 3 flexor and 2 extensor muscles, we developed an optimization process to determine the muscle fibre pre-stretches for an initial arm position, which is given human dataset. We used RoM values of a healthy person to balance the motion in extension and flexion. The performed sensitivity study shows that the fibre pre-stretches of the m. brachialis, m. biceps brachii and m. triceps brachii with 91 % dominate the objective flexion ratio, while m. brachiradialis and m. anconeus amount 7.8 % and 1.2 % . Within the multi-dimensional space of the surrogate model, 3D sub-spaces of primary variables, namely the dominant muscles and the global objective, flexion ratio, exhibit a path of optimal solutions. Within this optimal path, the muscle fibre pre-stretch of two flexors demonstrate a negative correlation, while, in contrast, the primary extensor, m. triceps brachii correlates positively to each of the flexors. Comparing the global optimum with four other designs along the optimal path, we saw large deviations, e.g., up to 15∘ in motion and up to 40% in muscle force. This underlines the importance of accurate determination of fibre pre-stretch in muscles, especially, their role in pathological muscular disorders and surgical applications such as free muscle or tendon transfer.

A dynamic foot model for predictive simulations of human gait reveals causal relations between foot structure and whole-body mechanics

The unique structure of the human foot is seen as a crucial adaptation for bipedalism. The foot's arched shape enables stiffening the foot to withstand high loads when pushing off, without compromising foot flexibility. Experimental studies demonstrated that manipulating foot stiffness has considerable effects on gait. In clinical practice, altered foot structure is associated with pathological gait. Yet, experimentally manipulating individual foot properties (e.g. arch height or tendon and ligament stiffness) is hard and therefore our understanding of how foot structure influences gait mechanics is still limited. Predictive simulations are a powerful tool to explore causal relationships between musculoskeletal properties and whole-body gait. However, musculoskeletal models used in three-dimensional predictive simulations assume a rigid foot arch, limiting their use for studying how foot structure influences three-dimensional gait mechanics. Here, we developed a four-segment foot model with a longitudinal arch for use in predictive simulations. We identified three properties of the ankle-foot complex that are important to capture ankle and knee kinematics, soleus activation, and ankle power of healthy adults: (1) compliant Achilles tendon, (2) stiff heel pad, (3) the ability to stiffen the foot. The latter requires sufficient arch height and contributions of plantar fascia, and intrinsic and extrinsic foot muscles. A reduced ability to stiffen the foot results in walking patterns with reduced push-off power. Simulations based on our model also captured the effects of walking with anaesthetised intrinsic foot muscles or an insole limiting arch compression. The ability to reproduce these different experiments indicates that our foot model captures the main mechanical properties of the foot. The presented four-segment foot model is a potentially powerful tool to study the relationship between foot properties and gait mechanics and energetics in health and disease.

Current practices in clinical gait analysis in Europe: A comprehensive survey-based study from the European society for movement analysis in adults and children (ESMAC) standard initiative

BACKGROUND

Clinical gait analysis (CGA) is a systematic approach to comprehensively evaluate gait patterns, quantify impairments, plan targeted interventions, and evaluate the impact of interventions. However, international standards for CGA are currently lacking, resulting in various national initiatives. Standards are important to ensure safe and effective healthcare practices and to enable evidence-based clinical decision-making, facilitating interoperability, and reimbursement under national healthcare policies. Collaborative clinical and research work between European countries would benefit from common standards.

RESEARCH OBJECTIVE

This study aimed to review the current laboratory practices for CGA in Europe.

METHODS

A comprehensive survey was conducted by the European Society for Movement Analysis in Adults and Children (ESMAC), in close collaboration with the European national societies. The survey involved 97 gait laboratories across 16 countries. The survey assessed several aspects related to CGA, including equipment used, data collection, processing, and reporting methods.

RESULTS

There was a consensus between laboratories concerning the data collected during CGA. The Conventional Gait Model (CGM) was the most used biomechanical model for calculating kinematics and kinetics. Respondents also reported the use of video recording, 3D motion capture systems, force plates, and surface electromyography. While there was a consensus on the reporting of CGA data, variations were reported in training, documentation, data preprocessing and equipment maintenance practices.

SIGNIFICANCE

The findings of this study will serve as a foundation for the development of standardized guidelines for CGA in Europe.

Muscle and joint mechanics during maximum force biting following total temporomandibular joint replacement surgery

Total temporomandibular joint replacement (TMJR) surgery is the established treatment for severe temporomandibular joint disorders. While TMJR surgery is known to increase mouth-opening capacity, reduce pain and improve quality of life, little is known about post-surgical jaw function during activities of daily living such as biting and chewing. The aim of this study was to use subject-specific 3D bite force measurements to evaluate the magnitude and direction of joint loading in unilateral total TMJR patients and compare these data to those in healthy control subjects. An optoelectronic tracking system was used to measure jaw kinematics while biting a rubber sample for 5 unilateral total TMJR patients and 8 controls. Finite element simulations driven by the measured kinematics were employed to calculate the resultant bite force generated when compressing the rubber between teeth during biting tasks. Subject-specific musculoskeletal models were subsequently used to calculate muscle and TMJ loading. Unilateral total TMJR patients generated a bite force of 249.6 ± 24.4 N and 164.2 ± 62.3 N when biting on the contralateral and ipsilateral molars, respectively. In contrast, controls generated a bite force of 317.1 ± 206.6 N. Unilateral total TMJR patients biting on the contralateral molars had a significantly higher lateral TMJ force direction (median difference: 63.6°, p = 0.028) and a significantly lower ratio of working TMJ force to bite force (median difference: 0.17, p = 0.049) than controls. Results of this study may guide TMJ prosthesis design and evaluation of dental implants.

Cost function criteria using muscle synergies: Exploring the potential of muscle synergy hypothesis

BACKGROUND AND OBJECTIVE

Solving the redundant optimization problem for human muscles depends on the cost function. Choosing the appropriate cost function helps to address a specific problem. Muscle synergies are currently limited to those obtained by electromyography. Furthermore, debate continues regarding whether muscle synergy is derived or real. This study proposes new cost functions based on the muscle synergy hypothesis for solving the optimal muscle force output problem through musculoskeletal modeling.

METHODS

We propose two new computational cost functions involving muscle synergies, which are extracted from muscle activations predicted by musculoskeletal modelling rather than electromyography. In this study, we constructed a musculoskeletal model for simulation using the "Grand Challenge Competition to Predict In Vivo Knee Loads" dataset. Muscle synergies were obtained using non-negative matrix factorization. Two cost functions with muscle synergies were constructed by integrating the polynomial and min/max criterion. Two new functions were verified and validated in normal, smooth, and bouncy gaits.

RESULTS

The muscle synergies based on normal gaits were classified into four modules. The cosine similarities of the first three modules were all >0.9. In the normal and smooth gaits, the forces in most muscles predicted using the two new functions were within three standard deviations of the root mean square error for electromyographic comparisons. Predicted muscle force curves using the four methods as well as characteristic points (i.e., time points in the gait cycle when the significant difference was observed between normal and bouncy gaits) were obtained to validate their predictive capabilities.

CONCLUSIONS

This study constructed two new cost functions involving muscle synergies, verified and validated the ability, and explored the potential of muscle synergy hypothesis.

Combined translational and rotational perturbations of standing balance reveal contributions of reduced reciprocal inhibition to balance impairments in children with cerebral palsy

Balance impairments are common in cerebral palsy. When balance is perturbed by backward support surface translations, children with cerebral palsy have increased co-activation of the plantar flexors and tibialis anterior muscle as compared to typically developing children. However, it is unclear whether increased muscle co-activation is a compensation strategy to improve balance control or is a consequence of reduced reciprocal inhibition. During translational perturbations, increased joint stiffness due to co-activation might aid balance control by resisting movement of the body with respect to the feet. In contrast, during rotational perturbations, increased joint stiffness will hinder balance control as it couples body to platform rotation. Therefore, we expect increased muscle co-activation in response to rotational perturbations if co-activation is caused by reduced reciprocal inhibition but not if it is merely a compensation strategy. We perturbed standing balance by combined backward translational and toe-up rotational perturbations in 20 children with cerebral palsy and 20 typically developing children. Perturbations induced forward followed by backward movement of the center of mass. We evaluated reactive muscle activity and the relation between center of mass movement and reactive muscle activity using a linear feedback model based on center of mass kinematics. In typically developing children, perturbations induced plantar flexor balance correcting muscle activity followed by tibialis anterior balance correcting muscle activity, which was driven by center of mass movement. In children with cerebral palsy, the switch from plantar flexor to tibialis anterior activity was less pronounced than in typically developing children due to increased muscle co-activation of the plantar flexors and tibialis anterior throughout the response. Our results thus suggest that a reduction in reciprocal inhibition causes muscle co-activation in reactive standing balance in children with cerebral palsy.

Muscle synergy-informed neuromusculoskeletal modelling to estimate knee contact forces in children with cerebral palsy

Cerebral palsy (CP) includes a group of neurological conditions caused by damage to the developing brain, resulting in maladaptive alterations of muscle coordination and movement. Estimates of joint moments and contact forces during locomotion are important to establish the trajectory of disease progression and plan appropriate surgical interventions in children with CP. Joint moments and contact forces can be estimated using electromyogram (EMG)-informed neuromusculoskeletal models, but a reduced number of EMG sensors would facilitate translation of these computational methods to clinics. This study developed and evaluated a muscle synergy-informed neuromusculoskeletal modelling approach using EMG recordings from three to four muscles to estimate joint moments and knee contact forces of children with CP and typically developing (TD) children during walking. Using only three to four experimental EMG sensors attached to a single leg and leveraging an EMG database of walking data of TD children, the synergy-informed approach estimated total knee contact forces comparable to those estimated by EMG-assisted approaches that used 13 EMG sensors (children with CP, n = 3, R2 = 0.95 ± 0.01, RMSE = 0.40 ± 0.14 BW; TD controls, n = 3, R2 = 0.93 ± 0.07, RMSE = 0.19 ± 0.05 BW). The proposed synergy-informed neuromusculoskeletal modelling approach could enable rapid evaluation of joint biomechanics in children with unimpaired and impaired motor control within a clinical environment.

AST: An OpenSim-based tool for the automatic scaling of generic musculoskeletal models

BACKGROUND AND OBJECTIVES

The paper introduces a tool called Automatic Scaling Tool (AST) designed for improving and expediting musculoskeletal (MSK) simulations based on generic models in OpenSim. Scaling is a crucial initial step in MSK analyses, involving the correction of virtual marker locations on a model to align with actual experimental markers.

METHODS

The AST automates this process by iteratively adjusting virtual markers using scaling and inverse kinematics on a static trial. It evaluates the root mean square error (RMSE) and maximum marker error, implementing corrective actions until achieving the desired accuracy level. The tool determines whether to scale a segment with a marker-based or constant scaling factor based on checks on RMSE and segment scaling factors.

RESULTS

Testing on three generic MSK models demonstrated that the AST significantly outperformed manual scaling by an expert operator. The RMSE for static trials was one order of magnitude lower, and for gait tasks, it was five times lower (8.5 ± 0.76 mm vs. 44.5 ± 7.5 mm). The AST consistently achieved the desired level of accuracy in less than 100 iterations, providing reliable scaled MSK models within a relatively brief timeframe, ranging from minutes to hours depending on model complexity.

CONCLUSIONS

The paper concludes that AST can greatly benefit the biomechanical community by quickly and accurately scaling generic models, a critical first step in MSK analyses. Further validation through additional experimental datasets and generic models is proposed for future tests.

Synergy quality assessment of muscle modules for determining learning performance using a realistic musculoskeletal model

How our central nervous system efficiently controls our complex musculoskeletal system is still debated. The muscle synergy hypothesis is proposed to simplify this complex system by assuming the existence of functional neural modules that coordinate several muscles. Modularity based on muscle synergies can facilitate motor learning without compromising task performance. However, the effectiveness of modularity in motor control remains debated. This ambiguity can, in part, stem from overlooking that the performance of modularity depends on the mechanical aspects of modules of interest, such as the torque the modules exert. To address this issue, this study introduces two criteria to evaluate the quality of module sets based on commonly used performance metrics in motor learning studies: the accuracy of torque production and learning speed. One evaluates the regularity in the direction of mechanical torque the modules exert, while the other evaluates the evenness of its magnitude. For verification of our criteria, we simulated motor learning of torque production tasks in a realistic musculoskeletal system of the upper arm using feed-forward neural networks while changing the control conditions. We found that the proposed criteria successfully explain the tendency of learning performance in various control conditions. These result suggest that regularity in the direction of and evenness in magnitude of mechanical torque of utilized modules are significant factor for determining learning performance. Although the criteria were originally conceived for an error-based learning scheme, the approach to pursue which set of modules is better for motor control can have significant implications in other studies of modularity in general.