The relationship between two different mechanical cost functions and muscle oxygen consumption

Influence of the rotator cuff tear pattern in shoulder stability after arthroscopic superior capsule reconstruction: a computational analysis

OBJECTIVES

To assess the ability of the arthroscopic superior capsule reconstruction (SCR) in restoring glenohumeral stability in the presence of different preoperative patterns of irreparable rotator cuff tears (RCTs).

METHODS

A computational musculoskeletal (MSK) model of the upper limb was used to simulate isolated SCR and to estimate the stability of the shoulder. Four patterns of preoperative irreparable RCTs were modeled: Supraspinatus (SSP); SSP ​+ ​Subscapularis (SSC); SSP ​+ ​Infraspinatus (ISP); and SSP ​+ ​SSC ​+ ​ISP. The muscles involved in the irreparable RCT were removed from the MSK model to simulate an irreparable full-thickness tear. In the MSK model, the muscle and joint forces were estimated for a set of upper limb positions, from four types of motions (abduction in the frontal plane, forward flexion in the sagittal plane, reaching behind the back, and combing the hair) collected in a biomechanics laboratory, through inverse dynamic analysis. The stability of the shoulder was estimated based on the tangential and compressive components of the glenohumeral joint reaction force. The comparison of pre- and post-operative conditions, for the four patterns of irreparable RCTs, with the healthy condition, was performed using ANOVA and Tukey's tests (statistical level of p ​< ​0.05).

RESULTS

In the setting of an isolated irreparable SSP tear, SCR statistically significantly improved stability compared with the preoperative condition (p ​< ​0.001). For the irreparable SSP ​+ ​SSC pattern, a statistically significant loss in stability was observed (p ​< ​0.001) when SCR was applied. For the irreparable SSP ​+ ​ISP and SSP ​+ ​SSC ​+ ​ISP patterns, the postoperative condition increased shoulder stability, compared to the preoperative condition; however, the improvement was not statistically significantly different.

CONCLUSION

Isolated SCR for irreparable RCTs extending beyond the SSP does not statistically significantly improve the stability of the glenohumeral joint.

LEVEL OF EVIDENCE

Level IV.

How mechanics of individual muscle-tendon units define knee and ankle joint function in health and cerebral palsy-a narrative review

This study reviews the relationship between muscle-tendon biomechanics and joint function, with a particular focus on how cerebral palsy (CP) affects this relationship. In healthy individuals, muscle size is a critical determinant of strength, with muscle volume, cross-sectional area, and moment arm correlating with knee and ankle joint torque for different isometric/isokinetic contractions. However, in CP, impaired muscle growth contributes to joint pathophysiology even though only a limited number of studies have investigated the impact of deficits in muscle size on pathological joint function. As muscles are the primary factors determining joint torque, in this review two main approaches used for muscle force quantification are discussed. The direct quantification of individual muscle forces from their relevant tendons through intraoperative approaches holds a high potential for characterizing healthy and diseased muscles but poses challenges due to the invasive nature of the technique. On the other hand, musculoskeletal models, using an inverse dynamic approach, can predict muscle forces, but rely on several assumptions and have inherent limitations. Neither technique has become established in routine clinical practice. Nevertheless, identifying the relative contribution of each muscle to the overall joint moment would be key for diagnosis and formulating efficient treatment strategies for patients with CP. This review emphasizes the necessity of implementing the intraoperative approach into general surgical practice, particularly for joint correction operations in diverse patient groups. Obtaining in vivo data directly would enhance musculoskeletal models, providing more accurate force estimations. This integrated approach can improve the clinicians' decision-making process and advance treatment strategies by predicting changes at the muscle and joint levels before interventions, thus, holding the potential to significantly enhance clinical outcomes.

Modeling Human Suboptimal Control: A Review

This review paper provides an overview of the approaches to model neuromuscular control, focusing on methods to identify nonoptimal control strategies typical of populations with neuromuscular disorders or children. Where possible, the authors tightened the description of the methods to the mechanisms behind the underlying biomechanical and physiological rationale. They start by describing the first and most simplified approach, the reductionist approach, which splits the role of the nervous and musculoskeletal systems. Static optimization and dynamic optimization methods and electromyography-based approaches are summarized to highlight their limitations and understand (the need for) their developments over time. Then, the authors look at the more recent stochastic approach, introduced to explore the space of plausible neural solutions, thus implementing the uncontrolled manifold theory, according to which the central nervous system only controls specific motions and tasks to limit energy consumption while allowing for some degree of adaptability to perturbations. Finally, they explore the literature covering the explicit modeling of the coupling between the nervous system (acting as controller) and the musculoskeletal system (the actuator), which may be employed to overcome the split characterizing the reductionist approach.

Neuromuscular control: from a biomechanist's perspective

Understanding neural control of movement necessitates a collaborative approach between many disciplines, including biomechanics, neuroscience, and motor control. Biomechanics grounds us to the laws of physics that our musculoskeletal system must obey. Neuroscience reveals the inner workings of our nervous system that functions to control our body. Motor control investigates the coordinated motor behaviours we display when interacting with our environment. The combined efforts across the many disciplines aimed at understanding human movement has resulted in a rich and rapidly growing body of literature overflowing with theories, models, and experimental paradigms. As a result, gathering knowledge and drawing connections between the overlapping but seemingly disparate fields can be an overwhelming endeavour. This review paper evolved as a need for us to learn of the diverse perspectives underlying current understanding of neuromuscular control. The purpose of our review paper is to integrate ideas from biomechanics, neuroscience, and motor control to better understand how we voluntarily control our muscles. As biomechanists, we approach this paper starting from a biomechanical modelling framework. We first define the theoretical solutions (i.e., muscle activity patterns) that an individual could feasibly use to complete a motor task. The theoretical solutions will be compared to experimental findings and reveal that individuals display structured muscle activity patterns that do not span the entire theoretical solution space. Prevalent neuromuscular control theories will be discussed in length, highlighting optimality, probabilistic principles, and neuromechanical constraints, that may guide individuals to families of muscle activity solutions within what is theoretically possible. Our intention is for this paper to serve as a primer for the neuromuscular control scientific community by introducing and integrating many of the ideas common across disciplines today, as well as inspire future work to improve the representation of neural control in biomechanical models.

The reserve of joint torque determines movement coordination

Humans coordinate biomechanical degrees of freedom to perform tasks at minimum cost. When reaching a target from a seated position, the trunk-arm-forearm coordination moves the hand to the well-defined spatial goal, while typically minimising hand jerk and trunk motion. However, due to fatigue or stroke, people visibly move the trunk more, and it is unclear what cost can account for this. Here we show that people recruit their trunk when the torque at the shoulder is too close to the maximum. We asked 26 healthy participants to reach a target while seated and we found that the trunk contribution to hand displacement increases from 11 to 27% when an additional load is handled. By flexing and rotating the trunk, participants spontaneously increase the reserve of anti-gravitational torque at the shoulder from 25 to 40% of maximal voluntary torque. Our findings provide hints on how to include the reserve of torque in the cost function of optimal control models of human coordination in healthy fatigued persons or in stroke victims.

EMG-Assisted Algorithm to Account for Shoulder Muscles Co-Contraction in Overhead Manual Handling

Glenohumeral stability is essential for a healthy function of the shoulder. It is ensured partly by the scapulohumeral muscular balance. Accordingly, modelling muscle interactions is a key factor in the understanding of occupational pathologies, and the development of ergonomic interventions. While static optimization is commonly used to estimate muscle activations, it tends to underestimate the role of shoulder’s antagonist muscles. The purpose of this study was to implement experimental electromyographic (EMG) data to predict muscle activations that could account for the stabilizing role of the shoulder muscles. Kinematics and EMG were recorded from 36 participants while lifting a box from hip to eye level. Muscle activations and glenohumeral joint reactions were estimated using an EMG-assisted algorithm and compared to those obtained using static optimization with a generic and calibrated model. Muscle activations predicted with the EMG-assisted method were generally larger. Additionally, more interactions between the different rotator cuff muscles, as well as between primer actuators and stabilizers, were predicted with the EMG-assisted method. Finally, glenohumeral forces calculated from a calibrated model remained within the boundaries of the glenoid stability cone. These findings suggest that EMG-assisted methods could account for scapulohumeral muscle co-contraction, and thus their contribution to the glenohumeral stability.

Forces acting on the clavicle during shoulder abduction, forward humeral flexion and activities of daily living

BACKGROUND

The forces acting on the human clavicle in vivo are difficult if not impossible to measure. The goal of this study is to quantify the forces acting on the human clavicle during shoulder abduction, forward humeral elevation and three activities of daily living using the Delft Shoulder and Elbow Model.

METHODS

The Delft Shoulder and Elbow Model and a computed tomography scan of a clavicle were used to calculate the forces and moments acting on the entire clavicle and on three planes within the middle third of the clavicle during the simulated movements.

FINDINGS

The largest resultant force simulated across the clavicle was 126 N during abduction. Maximum resultant moments of 2.4 Nm were identified during both abduction and forward humeral elevation. The highest forces in the middle third of the clavicle were of a compressive nature along the longitudinal axis of the clavicle, increasing to 97 N during forward humeral elevation and 91 N during abduction. Forces in opposite direction along the y-axis were identified on either side of the conoid ligament. The three simulated activities of daily living had similar ranges of forces and moments irrespective of the sagittal plane in which these activities were performed.

INTERPRETATION

Peak forces occurred at different locations on the middle third of the clavicle during different movements. The results create an understanding of the forces and their distribution across the clavicle during activities of daily living. These data may be helpful in the development of clavicular fixation devices.

LEVEL OF EVIDENCE

Biomechanical study.

Estimates for energy expenditure in free-living animals using acceleration proxies: A reappraisal

It is fundamentally important for many animal ecologists to quantify the costs of animal activities, although it is not straightforward to do so. The recording of triaxial acceleration by animal-attached devices has been proposed as a way forward for this, with the specific suggestion that dynamic body acceleration (DBA) be used as a proxy for movement-based power. Dynamic body acceleration has now been validated frequently, both in the laboratory and in the field, although the literature still shows that some aspects of DBA theory and practice are misunderstood. Here, we examine the theory behind DBA and employ modelling approaches to assess factors that affect the link between DBA and energy expenditure, from the deployment of the tag, through to the calibration of DBA with energy use in laboratory and field settings. Using data from a range of species and movement modes, we illustrate that vectorial and additive DBA metrics are proportional to each other. Either can be used as a proxy for energy and summed to estimate total energy expended over a given period, or divided by time to give a proxy for movement-related metabolic power. Nonetheless, we highlight how the ability of DBA to predict metabolic rate declines as the contribution of non-movement-related factors, such as heat production, increases. Overall, DBA seems to be a substantive proxy for movement-based power but consideration of other movement-related metrics, such as the static body acceleration and the rate of change of body pitch and roll, may enable researchers to refine movement-based metabolic costs, particularly in animals where movement is not characterized by marked changes in body acceleration.

Assessment of the energy-related cost function over a range of walking speeds

Cost funtions are needed for calculation of muscle forces in musculoskeletal models. The behavior of the energy-related cost function, proposed by Praagman et al. (J Biomech 39(4):758-765, 2006. https://doi.org/10.1016/j.jbiomech.2004.11.034 ) (CFP), can be used as an optimization criteria in musculoskeletal models for studying gait. In particular, in this work, its performance is compared against two empirical phenomenological models at different walking speed conditions. Also, the sensitivity of the CFP function to model parameters, such as muscle mass, maximal isometric muscle force, optimal muscle fiber length and maximum muscle velocity of the contractile element, was analyzed. The obtained results showed that CFP presents different behavior (in terms of the normalized root-mean-squared deviation (NRMSD) and the coefficient of multiple correlation (CMC)) for different muscles. Also, it provided estimates with median of NRMSD between 0.176 and 0.299 and median of CMC between 0.703 and 0.865 both metrics for slow, free and fast walking speed, which could be considered as acceptable results. Furthermore, the results indicated that CFP is insensitive to changes in muscle mass and relatively sensitive to maximal isometric muscle force. However, CFP presented a noisy behavior on estimations of muscle energy rate for some muscle as compared to phenomenological models. Finally, estimations by CFP during gait are within the values obtained by the empirical phenomenological models.

Estimating the Maximum Isometric Force Generating Capacity of Wheelchair Racing Athletes for Simulation Purposes

For the wheelchair racing population, it is uncertain whether musculoskeletal models using the maximum isometric force generating capacity of non-athletic, able-bodied individuals, are appropriate, as few anthropometric parameters for wheelchair athletes are reported in the literature. In this study, a sensitivity analysis was performed in OpenSim, whereby the maximum isometric force generating capacity of muscles was adjusted in 25% increments to literature defined values between scaling factors of 0.25x to 4.0x for two elite athletes, at three speeds representative of race conditions. Convergence of the solution was used to assess the results. Artificially weakening a model presented unrealistic values, and artificially strengthening a model excessively (4.0x) demonstrated physiologically invalid muscle force values. The ideal scaling factors were 1.5x and 1.75x for each of the athletes, respectively, as was assessed through convergence of the solution. This was similar to the relative difference in limb masses between dual energy X-Ray absorptiometry (DXA) data and anthropometric data in the literature (1.49x and 1.70x), suggesting that DXA may be used to estimate the required scaling factors. The reliability of simulations for elite wheelchair racing athletes can be improved by appropriately increasing the maximum isometric force generating capacity of muscles.

Changes in propulsion technique and shoulder complex loading following low-intensity wheelchair practice in novices

Background

Up to 80% of wheelchair users are affected by shoulder pain. The Clinical Practice Guidelines for preservation of upper limb function following spinal cord injury suggest that using a proper wheelchair propulsion technique could minimize the shoulder injury risk. Yet, the exact relationship between the wheelchair propulsion technique and shoulder load is not well understood.

Objective

This study aimed to examine the changes in shoulder loading accompanying the typical changes in propulsion technique following 80 min of low-intensity wheelchair practice distributed over 3 weeks.

Methods

Seven able-bodied participants performed the pre- and the post-test and 56 min of visual feedback-based low-intensity wheelchair propulsion practice. Kinematics and kinetics of propulsion technique were recorded during the pre- and the post-test. A musculoskeletal model was used to calculate muscle force and glenohumeral reaction force.

Results

Participants decreased push frequency (51→36 pushes/min, p = 0.04) and increased contact angle (68→94°, p = 0.02) between the pre- and the post-test. The excursion of the upper arm increased, approaching significance (297→342 mm, p = 0.06). Range of motion of the hand, trunk and shoulder remained unchanged. The mean glenohumeral reaction force per cycle decreased by 13%, approaching significance (268→232 N, p = 0.06).

Conclusions

Despite homogenous changes in propulsion technique, the kinematic solution to the task varied among the participants. Participants exhibited two glenohumeral reaction force distribution patterns: 1) Two individuals developed high force at the onset of the push, leading to increased peak and mean glenohumeral forces 2) Five individuals distributed the force more evenly over the cycle, lowering both peak and mean glenohumeral forces.

How sensitive are predicted muscle and knee contact forces to normalization factors and polynomial order in the muscle recruitment criterion formulation?

Musculoskeletal modeling is an important tool to estimate knee loads. In these models, anatomical muscles are frequently sub-divided to account for wide origin/insertion areas. The specific sub-division has been shown to affect some muscle recruitment criteria and it has been suggested that normalization factors should be incorporated into models. The primary aim of this study was to investigate the effect of different muscle normalization factors in the muscle recruitment criterion and polynomial order on the estimated muscle and total, medial and lateral knee contact forces during gait. These were evaluated on three different musculoskeletal models with increasing levels of patient-specificity and knee joint model complexity for one subject from the Grand Challenge data set and evaluated against measured forces. The results showed that the introduction of the muscle normalization factors affected the estimated forces and that this effect was most pronounced when a polynomial of order two was applied. Additionally, mainly the second contact force peak was affected. Secondary investigations revealed that the predicted forces can vary substantially as a function of the knee flexor and extensor muscle strength with over one body weight difference in predicted total compressive force between 100% and 40% of the strength. Additionally, the predicted second peak during gait was found to be sensitive to the position of the pelvic skin marker positions in the model. These results imply that caution should be taken when a normalization factor is introduced to account for sub-divided muscles especially for second-order recruitment criteria.

B. G, João F. Influence of the Musculotendon Dynamics on the Muscle Force-Sharing Problem of the Shoulder—A Fully Inverse Dynamics Approach

Most dynamic simulations are based on inverse dynamics, being the time-dependent physiological nature of the muscle properties rarely considered due to numerical challenges. Since the influence of muscle physiology on the consistency of inverse dynamics simulations remains unclear, the purpose of the present study is to evaluate the computational efficiency and biological validity of four musculotendon models that differ in the simulation of the muscle activation and contraction dynamics. Inverse dynamic analyses are performed using a spatial musculoskeletal model of the upper limb. The muscle force-sharing problem is solved for five repetitions of unloaded and loaded motions of shoulder abduction and shoulder flexion. The performance of the musculotendon models is evaluated by comparing muscle activation predictions with electromyography (EMG) signals, measured synchronously with motion for 11 muscles, and the glenohumeral joint reaction forces estimated numerically with those measured in vivo. The results show similar muscle activations for all muscle models. Overall, high cross-correlations are computed between muscle activations and the EMG signals measured for all movements analyzed, which provides confidence in the results. The glenohumeral joint reaction forces estimated compare well with those measured in vivo, but the influence of the muscle dynamics is found to be negligible. In conclusion, for slow-speed, standard movements of the upper limb, as those studied here, the activation and musculotendon contraction dynamics can be neglected in inverse dynamic analyses without compromising the prediction of muscle and joint reaction forces.

sEMG-assisted inverse modelling of 3D lip movement: a feasibility study towards person-specific modelling

We propose a surface-electromyographic (sEMG) assisted inverse-modelling (IM) approach for a biomechanical model of the face to obtain realistic person-specific muscle activations (MA) by tracking movements as well as innervation trajectories. We obtained sEMG data of facial muscles and 3D positions of lip markers in six volunteers and, using a generic finite element (FE) face model in ArtiSynth, performed inverse static optimisation with and without sEMG tracking on both simulation data and experimental data. IM with simulated data and experimental data without sEMG data showed good correlations of tracked positions (0.93 and 0.67) and poor correlations of MA (0.27 and 0.20). When utilising the sEMG-assisted IM approach, MA correlations increased drastically (0.83 and 0.59) without sacrificing performance in position correlations (0.92 and 0.70). RMS errors show similar trends with an error of 0.15 in MA and of 1.10 mm in position. Therefore, we conclude that we were able to demonstrate the feasibility of an sEMG-assisted inverse modelling algorithm for the perioral region. This approach may help to solve the ambiguity problem in inverse modelling and may be useful, for instance, in future applications for preoperatively predicting treatment-related function loss.

Introduction to Force-Dependent Kinematics: Theory and Application to Mandible Modeling

Knowledge of the muscle, ligament, and joint forces is important when planning orthopedic surgeries. Since these quantities cannot be measured in vivo under normal circumstances, the best alternative is to estimate them using musculoskeletal models. These models typically assume idealized joints, which are sufficient for general investigations but insufficient if the joint in focus is far from an idealized joint. The purpose of this study was to provide the mathematical details of a novel musculoskeletal modeling approach, called force-dependent kinematics (FDK), capable of simultaneously computing muscle, ligament, and joint forces as well as internal joint displacements governed by contact surfaces and ligament structures. The method was implemented into the anybody modeling system and used to develop a subject-specific mandible model, which was compared to a point-on-plane (POP) model and validated against joint kinematics measured with a custom-built brace during unloaded emulated chewing, open and close, and protrusion movements. Generally, both joint models estimated the joint kinematics well with the POP model performing slightly better (root-mean-square-deviation (RMSD) of less than 0.75 mm for the POP model and 1.7 mm for the FDK model). However, substantial differences were observed when comparing the estimated joint forces (RMSD up to 24.7 N), demonstrating the dependency on the joint model. Although the presented mandible model still contains room for improvements, this study shows the capabilities of the FDK methodology for creating joint models that take the geometry and joint elasticity into account.

Running Economy from a Muscle Energetics Perspective

The economy of running has traditionally been quantified from the mass-specific oxygen uptake; however, because fuel substrate usage varies with exercise intensity, it is more accurate to express running economy in units of metabolic energy. Fundamentally, the understanding of the major factors that influence the energy cost of running (Erun) can be obtained with this approach. Erun is determined by the energy needed for skeletal muscle contraction. Here, we approach the study of Erun from that perspective. The amount of energy needed for skeletal muscle contraction is dependent on the force, duration, shortening, shortening velocity, and length of the muscle. These factors therefore dictate the energy cost of running. It is understood that some determinants of the energy cost of running are not trainable: environmental factors, surface characteristics, and certain anthropometric features. Other factors affecting Erun are altered by training: other anthropometric features, muscle and tendon properties, and running mechanics. Here, the key features that dictate the energy cost during distance running are reviewed in the context of skeletal muscle energetics.

An entropy-assisted musculoskeletal shoulder model

Optimization combined with a musculoskeletal shoulder model has been used to estimate mechanical loading of musculoskeletal elements around the shoulder. Traditionally, the objective function is to minimize the summation of the total activities of the muscles with forces, moments, and stability constraints. Such an objective function, however, tends to neglect the antagonist muscle co-contraction. In this study, an objective function including an entropy term is proposed to address muscle co-contractions. A musculoskeletal shoulder model is developed to apply the proposed objective function. To find the optimal weight for the entropy term, an experiment was conducted. In the experiment, participants generated various 3-D shoulder moments in six shoulder postures. The surface EMG of 8 shoulder muscles was measured and compared with the predicted muscle activities based on the proposed objective function using Bhattacharyya distance and concordance ratio under different weight of the entropy term. The results show that a small weight of the entropy term can improve the predictability of the model in terms of muscle activities. Such a result suggests that the concept of entropy could be helpful for further understanding the mechanism of muscle co-contractions as well as developing a shoulder biomechanical model with greater validity.

The biomechanical effect of clavicular shortening on shoulder muscle function, a simulation study

BACKGROUND

Malunion of the clavicle with shortening after mid shaft fractures can give rise to long-term residual complaints. The cause of these complaints is as yet unclear.

METHODS

In this study we analysed data of an earlier experimental cadaveric study on changes of shoulder biomechanics with progressive shortening of the clavicle. The data was used in a musculoskeletal computer model to examine the effect of clavicle shortening on muscle function, expressed as maximal muscle moments for abduction and internal rotation.

FINDINGS

Clavicle shortening results in changes of maximal muscle moments around the shoulder girdle. The mean values at 3.6cm of shortening of maximal muscle moment changes are 16% decreased around the sterno-clavicular joint decreased for both ab- and adduction, 37% increased around the acromion-clavicular joint for adduction and 32% decrease for internal rotation around the gleno-humeral joint in resting position.

INTERPRETATION

Shortening of the clavicle affects muscle function in the shoulder in a computer model. This may explain for the residual complaints after short malunion with shortening.

LEVEL OF EVIDENCE

Basic Science Study. Biomechanics. Cadaveric data and computer model.

Subject-specific geometrical detail rather than cost function formulation affects hip loading calculation

This study assessed the relative importance of introducing an increasing level of medical image-based subject-specific detail in bone and muscle geometry in the musculoskeletal model, on calculated hip contact forces during gait. These forces were compared to introducing minimization of hip contact forces in the optimization criterion. With an increasing level of subject-specific detail, specifically MRI-based geometry and wrapping surfaces representing the hip capsule, hip contact forces decreased and were more comparable to contact forces measured using instrumented prostheses (average difference of 0.69 BW at the first peak compared to 1.04 BW for the generic model). Inclusion of subject-specific wrapping surfaces in the model had a greater effect than altering the cost function definition.

Brain-controlled muscle stimulation for the restoration of motor function

Loss of the ability to move, as a consequence of spinal cord injury or neuromuscular disorder, has devastating consequences for the paralyzed individual, and great economic consequences for society. Functional electrical stimulation (FES) offers one means to restore some mobility to these individuals, improving not only their autonomy, but potentially their general health and well-being as well. FES uses electrical stimulation to cause the paralyzed muscles to contract. Existing clinical systems require the stimulation to be preprogrammed, with the patient typically using residual voluntary movement of another body part to trigger and control the patterned stimulation. The rapid development of neural interfacing in the past decade offers the promise of dramatically improved control for these patients, potentially allowing continuous control of FES through signals recorded from motor cortex, as the patient attempts to control the paralyzed body part. While application of these 'brain-machine interfaces' (BMIs) has undergone dramatic development for control of computer cursors and even robotic limbs, their use as an interface for FES has been much more limited. In this review, we consider both FES and BMI technologies and discuss the prospect for combining the two to provide important new options for paralyzed individuals.

Computational reverse shoulder prosthesis model: Experimental data and verification

The reverse shoulder prosthesis aims to restore the stability and function of pathological shoulders, but the biomechanical aspects of the geometrical changes induced by the implant are yet to be fully understood. Considering a large-scale musculoskeletal model of the upper limb, the aim of this study is to evaluate how the Delta reverse shoulder prosthesis influences the biomechanical behavior of the shoulder joint. In this study, the kinematic data of an unloaded abduction in the frontal plane and an unloaded forward flexion in the sagittal plane were experimentally acquired through video-imaging for a control group, composed of 10 healthy shoulders, and a reverse shoulder group, composed of 3 reverse shoulders. Synchronously, the EMG data of 7 superficial muscles were also collected. The muscle force sharing problem was solved through the minimization of the metabolic energy consumption. The evaluation of the shoulder kinematics shows an increase in the lateral rotation of the scapula in the reverse shoulder group, and an increase in the contribution of the scapulothoracic joint to the shoulder joint. Regarding the muscle force sharing problem, the musculoskeletal model estimates an increased activity of the deltoid, teres minor, clavicular fibers of the pectoralis major, and coracobrachialis muscles in the reverse shoulder group. The comparison between the muscle forces predicted and the EMG data acquired revealed a good correlation, which provides further confidence in the model. Overall, the shoulder joint reaction force was lower in the reverse shoulder group than in the control group.

The effect of scaling physiological cross-sectional area on musculoskeletal model predictions

Personalisation of model parameters is likely to improve biomechanical model predictions and could allow models to be used for subject- or patient-specific applications. This study evaluates the effect of personalising physiological cross-sectional areas (PCSA) in a large-scale musculoskeletal model of the upper extremity. Muscle volumes obtained from MRI were used to scale PCSAs of five subjects, for whom the maximum forces they could exert in six different directions on a handle held by the hand were also recorded. The effect of PCSA scaling was evaluated by calculating the lowest maximum muscle stress (σmax, a constant for human skeletal muscle) required by the model to reproduce these forces. When the original cadaver-based PCSA-values were used, strongly different between-subject σmax-values were found (σmax=106.1±39.9 N cm(-2)). A relatively simple, uniform scaling routine reduced this variation substantially (σmax=69.4±9.4 N cm(-2)) and led to similar results to when a more detailed, muscle-specific scaling routine was used (σmax=71.2±10.8 N cm(-2)). Using subject-specific PCSA values to simulate an shoulder abduction task changed muscle force predictions for the subscapularis and the pectoralis major on average by 33% and 21%, respectively, but was <10% for all other muscles. The glenohumeral (GH) joint contact force changed less than 1.5% as a result of scaling. We conclude that individualisation of the model's strength can most easily be done by scaling PCSA with a single factor that can be derived from muscle volume data or, alternatively, from maximum force measurements. However, since PCSA scaling only marginally changed muscle and joint contact force predictions for submaximal tasks, the need for PCSA scaling remains debatable.

Stochastic modelling of muscle recruitment during activity

Muscle forces can be selected from a space of muscle recruitment strategies that produce stable motion and variable muscle and joint forces. However, current optimization methods provide only a single muscle recruitment strategy. We modelled the spectrum of muscle recruitment strategies while walking. The equilibrium equations at the joints, muscle constraints, static optimization solutions and 15-channel electromyography (EMG) recordings for seven walking cycles were taken from earlier studies. The spectrum of muscle forces was calculated using Bayesian statistics and Markov chain Monte Carlo (MCMC) methods, whereas EMG-driven muscle forces were calculated using EMG-driven modelling. We calculated the differences between the spectrum and EMG-driven muscle force for 1-15 input EMGs, and we identified the muscle strategy that best matched the recorded EMG pattern. The best-fit strategy, static optimization solution and EMG-driven force data were compared using correlation analysis. Possible and plausible muscle forces were defined as within physiological boundaries and within EMG boundaries. Possible muscle and joint forces were calculated by constraining the muscle forces between zero and the peak muscle force. Plausible muscle forces were constrained within six selected EMG boundaries. The spectrum to EMG-driven force difference increased from 40 to 108 N for 1-15 EMG inputs. The best-fit muscle strategy better described the EMG-driven pattern (R (2) = 0.94; RMSE = 19 N) than the static optimization solution (R (2) = 0.38; RMSE = 61 N). Possible forces for 27 of 34 muscles varied between zero and the peak muscle force, inducing a peak hip force of 11.3 body-weights. Plausible muscle forces closely matched the selected EMG patterns; no effect of the EMG constraint was observed on the remaining muscle force ranges. The model can be used to study alternative muscle recruitment strategies in both physiological and pathophysiological neuromotor conditions.

Early motor learning changes in upper-limb dynamics and shoulder complex loading during handrim wheelchair propulsion

Background

To propel in an energy-efficient manner, handrim wheelchair users must learn to control the bimanually applied forces onto the rims, preserving both speed and direction of locomotion. Previous studies have found an increase in mechanical efficiency due to motor learning associated with changes in propulsion technique, but it is unclear in what way the propulsion technique impacts the load on the shoulder complex. The purpose of this study was to evaluate mechanical efficiency, propulsion technique and load on the shoulder complex during the initial stage of motor learning.

Methods

15 naive able-bodied participants received 12-minutes uninstructed wheelchair practice on a motor driven treadmill, consisting of three 4-minute blocks separated by two minutes rest. Practice was performed at a fixed belt speed (v = 1.1 m/s) and constant low-intensity power output (0.2 W/kg). Energy consumption, kinematics and kinetics of propulsion technique were continuously measured. The Delft Shoulder Model was used to calculate net joint moments, muscle activity and glenohumeral reaction force.

Results

With practice mechanical efficiency increased and propulsion technique changed, reflected by a reduced push frequency and increased work per push, performed over a larger contact angle, with more tangentially applied force and reduced power losses before and after each push. Contrary to our expectations, the above mentioned propulsion technique changes were found together with an increased load on the shoulder complex reflected by higher net moments, a higher total muscle power and higher peak and mean glenohumeral reaction forces.

Conclusions

It appears that the early stages of motor learning in handrim wheelchair propulsion are indeed associated with improved technique and efficiency due to optimization of the kinematics and dynamics of the upper extremity. This process goes at the cost of an increased muscular effort and mechanical loading of the shoulder complex. This seems to be associated with an unchanged stable function of the trunk and could be due to the early learning phase where participants still have to learn to effectively use the full movement amplitude available within the wheelchair-user combination. Apparently whole body energy efficiency has priority over mechanical loading in the early stages of learning to propel a handrim wheelchair.

Muscle optimization techniques impact the magnitude of calculated hip joint contact forces

In musculoskeletal modelling, several optimization techniques are used to calculate muscle forces, which strongly influence resultant hip contact forces (HCF). The goal of this study was to calculate muscle forces using four different optimization techniques, i.e., two different static optimization techniques, computed muscle control (CMC) and the physiological inverse approach (PIA). We investigated their subsequent effects on HCFs during gait and sit to stand and found that at the first peak in gait at 15-20% of the gait cycle, CMC calculated the highest HCFs (median 3.9 times peak GRF (pGRF)). When comparing calculated HCFs to experimental HCFs reported in literature, the former were up to 238% larger. Both static optimization techniques produced lower HCFs (median 3.0 and 3.1 pGRF), while PIA included muscle dynamics without an excessive increase in HCF (median 3.2 pGRF). The increased HCFs in CMC were potentially caused by higher muscle forces resulting from co-contraction of agonists and antagonists around the hip. Alternatively, these higher HCFs may be caused by the slightly poorer tracking of the net joint moment by the muscle moments calculated by CMC. We conclude that the use of different optimization techniques affects calculated HCFs, and static optimization approached experimental values best.

Patient-specific bone modeling and analysis: the role of integration and automation in clinical adoption

Patient-specific analysis of bones is considered an important tool for diagnosis and treatment of skeletal diseases and for clinical research aimed at understanding the etiology of skeletal diseases and the effects of different types of treatment on their progress. In this article, we discuss how integration of several important components enables accurate and cost-effective patient-specific bone analysis, focusing primarily on patient-specific finite element (FE) modeling of bones. First, the different components are briefly reviewed. Then, two important aspects of patient-specific FE modeling, namely integration of modeling components and automation of modeling approaches, are discussed. We conclude with a section on validation of patient-specific modeling results, possible applications of patient-specific modeling procedures, current limitations of the modeling approaches, and possible areas for future research.

Estimation of muscle forces in gait using a simulation of the electromyographic activity and numerical optimization

Clinical gait analysis provides great contributions to the understanding of gait patterns. However, a complete distribution of muscle forces throughout the gait cycle is a current challenge for many researchers. Two techniques are often used to estimate muscle forces: inverse dynamics with static optimization and computer muscle control that uses forward dynamics to minimize tracking. The first method often involves limitations due to changing muscle dynamics and possible signal artefacts that depend on day-to-day variation in the position of electromyographic (EMG) electrodes. Nevertheless, in clinical gait analysis, the method of inverse dynamics is a fundamental and commonly used computational procedure to calculate the force and torque reactions at various body joints. Our aim was to develop a generic musculoskeletal model that could be able to be applied in the clinical setting. The musculoskeletal model of the lower limb presents a simulation for the EMG data to address the common limitations of these techniques. This model presents a new point of view from the inverse dynamics used on clinical gait analysis, including the EMG information, and shows a similar performance to another model available in the OpenSim software. The main problem of these methods to achieve a correct muscle coordination is the lack of complete EMG data for all muscles modelled. We present a technique that simulates the EMG activity and presents a good correlation with the muscle forces throughout the gait cycle. Also, this method showed great similarities whit the real EMG data recorded from the subjects doing the same movement.

Multi-objective optimisation for musculoskeletal modelling: application to a planar elbow model

One of the open issues in musculoskeletal modelling remains the choice of the objective function that is used to solve the muscular redundancy problem. Some authors have recently proposed to introduce joint reaction forces in the objective function, and the question of the weights associated with musculo-tendon forces and joint reaction forces arose. This question typically deals with a multi-objective optimisation problem. The aim of this study is to illustrate, on a planar elbow model, the ensemble of optimal solutions (i.e. Pareto front) and the solution of a global objective method that represent different compromises between musculo-tendon forces, joint compression force, and joint shear force. The solutions of the global objective method, based either on the minimisation of the sum of the squared musculo-tendon forces alone or on the minimisation of the squared joint compression force and shear force together, are in the same range. Minimising either the squared joint compression force or shear force alone leads to extreme force values. The exploration of the compromises between these forces illustrates the existence of major interactions between the muscular and joint structures. Indeed, the joint reaction forces relate to the projection of the sum of the musculo-tendon forces. An illustration of these interactions, due to the projection relation, is that the Pareto front is not a large surface, like in a typical three-objective optimisation, but almost a curve. These interactions, and the possibility to take them into account by a multi-objective optimisation, seem essential for the application of musculoskeletal modelling to joint pathologies.

A comparison of muscle energy models for simulating human walking in three dimensions

The popular Hill model for muscle activation and contractile dynamics has been extended with several different formulations for predicting the metabolic energy expenditure of human muscle actions. These extended models differ considerably in their approach to computing energy expenditure, particularly in their treatment of active lengthening and eccentric work, but their predictive abilities have never been compared. In this study, we compared the predictions of five different Hill-based muscle energy models in 3D forward dynamics simulations of normal human walking. In a data-tracking simulation that minimized muscle fatigue, the energy models predicted metabolic costs that varied over a three-fold range (2.45-7.15 J/m/kg), with the distinction arising from whether or not eccentric work was subtracted from the net heat rate in the calculation of the muscle metabolic rate. In predictive simulations that optimized neuromuscular control to minimize the metabolic cost, all five models predicted similar speeds, step lengths, and stance phase durations. However, some of the models predicted a hip circumduction strategy to minimize metabolic cost, while others did not, and the accuracy of the predicted knee and ankle angles and ground reaction forces also depended on the energy model used. The results highlights the need to clarify how eccentric work should be treated when calculating muscle energy expenditure, the difficulty in predicting realistic metabolic costs in simulated walking even with a detailed 3D musculoskeletal model, the potential for using such models to predict energetically-optimal gait modifications, and the room for improvement in existing muscle energy models and locomotion simulation frameworks.

Multibody System of the Upper Limb Including a Reverse Shoulder Prosthesis

The reverse shoulder replacement, recommended for the treatment of several shoulder pathologies such as cuff tear arthropathy and fractures in elderly people, changes the biomechanics of the shoulder when compared to the normal anatomy. Although several musculoskeletal models of the upper limb have been presented to study the shoulder joint, only a few of them focus on the biomechanics of the reverse shoulder. This work presents a biomechanical model of the upper limb, including a reverse shoulder prosthesis, to evaluate the impact of the variation of the joint geometry and position on the biomechanical function of the shoulder. The biomechanical model of the reverse shoulder is based on a musculoskeletal model of the upper limb, which is modified to account for the properties of the DELTA® reverse prosthesis. Considering two biomechanical models, which simulate the anatomical and reverse shoulder joints, the changes in muscle lengths, muscle moment arms, and muscle and joint reaction forces are evaluated. The muscle force sharing problem is solved for motions of unloaded abduction in the coronal plane and unloaded anterior flexion in the sagittal plane, acquired using video-imaging, through the minimization of an objective function related to muscle metabolic energy consumption. After the replacement of the shoulder joint, significant changes in the length of the pectoralis major, latissimus dorsi, deltoid, teres major, teres minor, coracobrachialis, and biceps brachii muscles are observed for a reference position considered for the upper limb. The shortening of the teres major and teres minor is the most critical since they become unable to produce active force in this position. Substantial changes of muscle moment arms are also observed, which are consistent with the literature. As expected, there is a significant increase of the deltoid moment arms and more fibers are able to elevate the arm. The solutions to the muscle force sharing problem support the biomechanical advantages attributed to the reverse shoulder design and show an increase in activity from the deltoid, teres minor, and coracobrachialis muscles. The glenohumeral joint reaction forces estimated for the reverse shoulder are up to 15% lower than those in the normal shoulder anatomy. The data presented here complements previous publications, which, all together, allow researchers to build a biomechanical model of the upper limb including a reverse shoulder prosthesis.

Clinical applications of musculoskeletal modelling for the shoulder and upper limb

Musculoskeletal models have been developed to estimate internal loading on the human skeleton, which cannot directly be measured in vivo, from external measurements like kinematics and external forces. Such models of the shoulder and upper extremity have been used for a variety of purposes, ranging from understanding basic shoulder biomechanics to assisting in preoperative planning. In this review, we provide an overview of the most commonly used large-scale shoulder and upper extremity models and categorise the applications of these models according to the type of questions their users aimed to answer. We found that the most explored feature of a model is the possibility to predict the effect of a structural adaptation on functional outcome, for instance, to simulate a tendon transfer preoperatively. Recent studies have focused on minimising the mismatch in morphology between the model, often derived from cadaver studies, and the subject that is analysed. However, only a subset of the parameters that describe the model's geometry and, perhaps most importantly, the musculotendon properties can be obtained in vivo. Because most parameters are somehow interrelated, the others should be scaled to prevent inconsistencies in the model's structure, but it is not known exactly how. Although considerable effort is put into adding complexity to models, for example, by making them subject-specific, we have found little evidence of their superiority over current models. The current trend in development towards individualised, more complex models needs to be justified by demonstrating their ability to answer questions that cannot already be answered by existing models.

Musculoskeletal shoulder models: A technical review and proposals for research foci

Musculoskeletal shoulder models allow non-invasive prediction of parameters that cannot be measured, particularly the loading applied to morphological structures and neurological control. This insight improves treatment and avoidance of pathology and performance evaluation and optimisation. A lack of appropriate validation and knowledge of model parameters’ accuracy may cause reduced clinical success for these models. Instrumented implants have recently been used to validate musculoskeletal models, adding important information to the literature. This development along with increasing prevalence of shoulder models necessitates a fresh review of available models and their utility. The practical uses of models are described. Accuracy of model inputs, modelling techniques and model sensitivity is the main technical review undertaken. Collection and comparison of these parameters are vital to understanding disagreement between model outputs. Trends in shoulder modelling are highlighted: validation through instrumented prostheses, increasing openness and strictly constrained, optimised, measured kinematics. Future directions are recommended: validation through focus on model sub-sections, increased subject specificity with imaging techniques determining muscle and body segment parameters and through different scaling and kinematics optimisation approaches.

The influence of simulated rotator cuff tears on the risk for impingement in handbike and handrim wheelchair propulsion

BACKGROUND

Rotator cuff tears strongly affect the biomechanics of the shoulder joint in their role to regulate the joint contact force needed to prevent the joint from dislocation. The aim of this study was to investigate the influence of simulated progressed rotator cuff tears on the (in)stability of the glenohumeral joint and the risk for impingement during wheelchair and handbike propulsion.

METHODS

The Delft Shoulder and Elbow Model was used to calculate the magnitude of the glenohumeral joint reaction force and the objective function J, which is an indication of the effort needed to complete the task. Full-thickness tears were simulated by virtually removing muscles from the model.

FINDINGS

With larger cuff tears the joint reaction force was higher and more superiorly directed. Also extra muscle force was necessary to balance the external force such that the glenohumeral joint did not dislocate.

INTERPRETATION

A tear of only the supraspinatus leads only to a minor increase in muscle forces and a minor shift of the force on the glenoid, indicating that it is possible to function well with a torn supraspinatus muscle. A massive tear shifts the direction of the joint reaction force to the superior border of the glenoid, increasing the risk for impingement.

Glenohumeral stability during a hand-positioning task in previously injured shoulders

This study aimed to compare glenohumeral stability during functional tasks in subjects with previous dislocation injury against non-injured controls. Six subjects with previous injury and six controls were asked to complete hand-positioning tasks against external forces applied in six directions. Arm kinematics, muscle activations and hand forces were measured and used as input to an inverse-dynamic model of the shoulder that optimised muscle forces to solve the load-sharing problem. Glenohumeral stability was calculated using the direction of the joint reaction force vector in the glenoid. The simulations showed that GH stability was significantly lower in the previously injured group compared to the controls, and that the direction of exerted forces had a significant effect on GH stability, with the hand pushing away from the body and medially producing significantly lower stability. GH stability was significantly lower in the previously injured group for all six force directions, even though all participants were back to normal activities and reported no symptoms from their injuries.

PREDICTION OF MUSCLE FORCES USING STATIC OPTIMIZATION FOR DIFFERENT CONTRACTILE CONDITIONS

In this study, we introduced a novel cost function for the prediction of individual muscle forces for a one degree-of-freedom musculoskeletal system. Unlike previous models, the new approach incorporates the instantaneous contractile conditions represented by the force-length and force-velocity relationships and accounts for physiological properties such as fiber type distribution and physiological cross-sectional area (PCSA) in the cost function. Using this cost function, it is possible to predict experimentally observed features of force-sharing among synergistic muscles that cannot be predicted using the classical approaches. Specifically, the new approach allows for predictions of force-sharing loops of agonistic muscles in one degree-of-freedom systems and for simultaneous increases in force in one muscle and decreases in a corresponding agonist. We concluded that the incorporation of the contractile conditions in the weighting of cost functions provides a natural way to incorporate observed force-sharing features in synergistic muscles that have eluded satisfactory description.

Transformation methods for estimation of subject-specific scapular muscle attachment sites

The parameters that describe the soft tissue structures are among the most important anatomical parameters for subject-specific biomechanical modelling. In this paper, we study one of the soft tissue parameters, namely muscle attachment sites. Two new methods are proposed for transformation of the muscle attachment sites of any reference scapula to any destination scapula based on four palpable bony landmarks. The proposed methods as well as one previously proposed method have been applied for transformation of muscle attachment sites of one reference scapula to seven other scapulae. The transformation errors are compared among the three methods. Both proposed methods yield significantly less (p < 0.05) prediction error as compared to the currently available method. Furthermore, we investigate whether there exists a reference scapula that performs significantly better than other scapulae when used for transformation of muscle attachment sites. Seven different scapulae were used as reference scapula and their resulting transformation errors were compared with each other. In the considered statistical population, no such a thing as an ideal scapula was found. There was, however, one outlier scapula that performed significantly worse than the other scapulae when used as a reference. The effect of perturbations in both muscle attachment sites and other muscle properties is studied by comparing muscle force predictions of a musculoskeletal model between perturbed and non-perturbed versions of the model. It is found that 10 mm variations in muscle attachments have more significant effect on muscle force predictions than 10% variations in any of the other four analysed muscle properties.

RELATIVE CONTRIBUTION OF DIFFERENT MUSCLE ENERGY CONSUMPTION PROCESSES IN AN ENERGY-BASED MUSCLE LOAD SHARING COST FUNCTION

The aim of this study is to quantify the relative contributions of two muscle energy consumption processes (the detachment of cross-bridges and calcium-pumping) incorporated in a recently developed muscle load sharing cost function, namely the energy-based criterion, by using in vivo measured glenohumeral-joint reaction forces (GH-JRFs). Motion data and in vivo GH-JRFs were recorded for four patients carrying an instrumented shoulder implant while performing abduction and forward flexion motions up to their maximum possible arm elevations. Motion data were used as the input to the delft shoulder and elbow model for the estimation of GH-JRFs. The widely used stress as well as the energy-based cost functions were adopted as the load sharing criteria. For the energy-based criterion, simulations were run for a wide range of different weight parameters (determining the relative contribution of the two energy processes) in the neighborhood of the previously assumed parameters for each subject and motion. The model-predicted and in vivo-measured GH-JRFs were compared for all model simulations. Application of the energy-based criterion with new identified parameters resulted in significant (two-tailed p < 0.05, post-hoc power ~ 0.3) improvement (on average ~20%) of the model-predicted GH-JRFs at the maximal arm elevation compared to when using either the stress or the pre-assumed form of the energy-based criterion. About 25% of the total energy consumption was calculated for the calcium-pumping process at maximal muscle activation level when using the new parameters. This value was comparable to the corresponding ones reported in the previous literature. The identified parameters are recommended to be used instead of their predecessors.

The effect of crank position and backrest inclination on shoulder load and mechanical efficiency during handcycling

Handbikes come in different models and setups, but only limited knowledge is available on the handbike-user interface. The aim of this study was to identify optimal handbike setups, assuming that in such a setup mechanical efficiency is high, while shoulder load is low. Thirteen subjects with a spinal cord injury (paraplegia) performed handcycling with different handbike setups at constant power output: four crank positions (two distances, two heights) and four backrest inclinations. The O2-consumption, kinetics, and kinematics were measured to calculate mechanical efficiency and shoulder load (glenohumeral contact force, net shoulder moments, and rotator cuff force). The analysis showed that more upright backrest positions resulted in lower shoulder load compared with the most reclined position [glenohumeral contact force (260 vs 335 N), supraspinatus (14.4% vs 18.2%), and infraspinatus force (5.4% vs 9.8%)], while there was no difference in efficiency. Except for a reduction in subscapularis force at the distant position, no differences in shoulder load or efficiency were found between crank positions. Recreational handbike users, who want to improve their physical capacity in a shoulder-friendly way, should set up their handbike with a more upright backrest position and a distant crank placement.

Personalized neuromusculoskeletal modeling to improve treatment of mobility impairments: a perspective from European research sites

Mobility impairments due to injury or disease have a significant impact on quality of life. Consequently, development of effective treatments to restore or replace lost function is an important societal challenge. In current clinical practice, a treatment plan is often selected from a standard menu of options rather than customized to the unique characteristics of the patient. Furthermore, the treatment selection process is normally based on subjective clinical experience rather than objective prediction of post-treatment function. The net result is treatment methods that are less effective than desired at restoring lost function. This paper discusses the possible use of personalized neuromusculoskeletal computer models to improve customization, objectivity, and ultimately effectiveness of treatments for mobility impairments. The discussion is based on information gathered from academic and industrial research sites throughout Europe, and both clinical and technical aspects of personalized neuromusculoskeletal modeling are explored. On the clinical front, we discuss the purpose and process of personalized neuromusculoskeletal modeling, the application of personalized models to clinical problems, and gaps in clinical application. On the technical front, we discuss current capabilities of personalized neuromusculoskeletal models along with technical gaps that limit future clinical application. We conclude by summarizing recommendations for future research efforts that would allow personalized neuromusculoskeletal models to make the greatest impact possible on treatment design for mobility impairments.