Muscular synergism--I. On criteria for load sharing between synergistic muscles

Predicting preferred motorcycle riding postures to support human factors/ergonomic trade-off analyses within a multi-objective optimisation-based digital human model

Digital human models (DHM) can predict how users might interact with new vehicle geometry during early-stage design, an important precursor to conducting trade-off analyses. However, predicting human postures requires assumptions about which performance criteria best predict realistic postures. Focusing on the design of motorcycles, we do not know what performance criteria drive preferred riding postures. Addressing this gap, we aimed to identify which performance criteria and corresponding weightings best predicted preferred motorcycle riding postures when using a DHM. To address our aim, we surveyed the literature to find experimental data specifying joint angles that correspond to preferred riding postures. We then deployed a response surface methodology to determine which performance criteria and weightings optimally predicted the preferred riding postures when using a DHM. Weighting the minimisation of the discomfort performance criteria (an aggregate of joint range of motion, displacement from neutral and joint torque) best predicted preferred motorcycle riding postures.

Exploring Optimal Objective Function Weightings to Predict Lifting Postures Under Unfatigued and Fatigued States

OBJECTIVE

To explore whether the optimal objective function weightings change when using a digital human model (DHM) to predict origin and destination lifting postures under unfatigued and fatigued states.

BACKGROUND

The ability to predict human postures can depend on state-based influences (e.g., fatigue). Altering objective function weightings within a predictive DHM could improve the ability to predict tasks specific lifting postures under unique fatigue states.

METHOD

A multi-objective optimization-based DHM was used to predict origin and destination lifting postures for ten anthropometrically scaled avatars by using different objective functions weighting combinations. Predicted and measured postures were compared to determine the root mean squared error. A response surface methodology was used to identify the optimal objective function weightings, which was found by generating the posture that minimized error between measured and predicted lifting postures. The resultant weightings were compared to determine if the optimal objective function weightings changed for different lifting postures or fatigue states.

RESULTS

Discomfort and total joint torque weightings were affected by posture (origin/destination) and fatigue state (unfatigued/fatigued); however, post-hoc differences between fatigue states and lifting postures were not sufficiently large to be detected. Weighting the discomfort objective function alone tended to predict postures that generalized well to both postures and fatigue states.

CONCLUSION

Lift postures were optimal predicted using the minimization of discomfort objective function regardless of fatigue state.

APPLICATION

Weighting the discomfort objective can predict unfatigued postures, but more research is needed to understand the optimal objective function weightings to predict postures during a fatigued state.

The Effect of the Nordic Hamstring Exercise on Muscle Activity: A Multichannel Electromyography Randomized Controlled Trial

The aim of this study was to evaluate the effect of a Nordic hamstring exercise intervention on biceps femoris long head, semitendinosus, and semimembranosus muscle's activity and relative contributions through multichannel electromyography. Twenty-four injury-free male basketball players (mean age 20 [3] y) were randomly assigned to a 12-week intervention (n = 13) or control group (n = 11). The primary outcome measures were normalized muscle activity (percentage of maximal voluntary isometric contraction, %MVIC) and relative contribution of hamstring muscles over 12 weeks. No effects were found on any of the primary outcome measures. Between-group differences over 12 weeks were 2.7%MVIC (95% confidence interval 95% CI, -0.7 to 6.1) for the biceps femoris long head, 3.4%MVIC (95% CI, -1.4 to 8.2) for the semitendinosus, and 0.8%MVIC (95% CI, -3.0 to 4.6) for the semimembranosus, P = .366. Between-group differences over 12 weeks were 1.0% relative contribution (%con; 95% CI, -3.0 to 5.1) for the biceps femoris long head, 2.2% relative contribution (95% CI, -2.8 to 7.2) for the semitendinosus, and -3.3% relative contribution (95% CI, -6.4 to -0.1) for the semimembranosus P = .258. A positive value implies a higher value for the Nordic group. A Nordic hamstring exercise intervention did not affect the level of muscle activity and relative contribution of hamstring muscles in performance of the Nordic hamstring exercise.

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.

Biomechanical modeling for the estimation of muscle forces: toward a common language in biomechanics, medical engineering, and neurosciences

Different research fields, such as biomechanics, medical engineering or neurosciences take part in the development of biomechanical models allowing for the estimation of individual muscle forces involved in motor action. The heterogeneity of the terminology used to describe these models according to the research field is a source of confusion and can hamper collaboration between the different fields. This paper proposes a common language based on lexical disambiguation and a synthesis of the terms used in the literature in order to facilitate the understanding of the different elements of biomechanical modeling for force estimation, without questioning the relevance of the terms used in each field or the different model components or their interest. We suggest that the description should start with an indication of whether the muscle force estimation problem is solved following the physiological movement control (from the nervous drive to the muscle force production) or in the opposite direction. Next, the suitability of the model for force production estimation at a given time or for monitoring over time should be specified. Authors should pay particular attention to the method description used to find solutions, specifying whether this is done during or after data collection, with possible method adaptations during processing. Finally, the presence of additional data must be specified by indicating whether they are used to drive, assist, or calibrate the model. Describing and classifying models in this way will facilitate the use and application in all fields where the estimation of muscle forces is of real, direct, and concrete interest.

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.

Activity distribution among the hamstring muscles during high-speed running: A descriptive multichannel surface EMG study

PURPOSE

This study assessed activity distribution among the hamstring muscles during high-speed running. The objective was to compare within and between muscle activity, relative contribution and hip and knee joint angles at peak muscle activity during high-speed running.

METHODS

Through multichannel electromyography, we measured muscle activity in male basketball players during high-speed running on a treadmill at 15 locations: five for biceps femoris long head, four for semitendinosus, and six for semimembranosus. Muscle activity was calculated for each location within each hamstring muscle individually for each percent of a stride cycle.

RESULTS

Twenty-nine non-injured basketball players were included (mean age: 17 ± 1 years; mass, 85 ± 9 kg; height, 193 ± 9 cm). Heterogeneous activity was found for all individual hamstring muscles across multiple events of the stride cycle. In the late-swing phase, muscle activity and relative contribution of the semimembranosus was significantly higher than of the semitendinosus. There was no significant difference in hip and knee joint angles at instant of peak muscle activity, assessed locally within individual hamstring muscles, as well as in general over the whole hamstring muscle.

CONCLUSION

Hamstring muscles were most active in the late-swing phase during high-speed running. In this phase, the semimembranosus was most active and the semitendinosus was least active. Within the biceps femoris long head, the most proximal region was significantly more active in the late-swing phase, compared to other muscle regions. For each muscle and location, peak muscle activity occurred at similar hip and knee joint angles.

Activity Distribution Among the Hamstring Muscles During the Nordic Hamstring Exercise: A Multichannel Surface Electromyography Study

This study assessed activity distribution among the hamstring muscles during the Nordic hamstring exercise (NHE). The objective was to compare muscle activity between and within muscles during the NHE to add insights in its underlying protective mechanism. Through multichannel electromyography, we measured muscle activity in male basketball players during the NHE. Electromyography was assessed at 15 locations: 5 for biceps femoris long head, 4 for semitendinosus, and 6 for semimembranosus. For each percent of the eccentric phase of the NHE, muscle activity was calculated for each electrode location within each hamstring muscle individually. To quantify whole muscle head activity, means and variances across electrodes within each muscle were calculated. Thirty-five noninjured participants were included (mean age, 18 [2] y; mass, 87 [12] kg; height, 192 [9] cm). Heterogeneous muscle activity was found between 38% and 62% and over the whole eccentric contraction phase within the semitendinosus and the semimembranosus, respectively. Muscle activity of the semitendinosus was significantly higher than that of the biceps femoris long head. During the NHE, the relative contribution of the semitendinosus is the highest among hamstring muscles. Its strong contribution may compensate for the biceps femoris long head, the most commonly injured hamstring muscle head.

Fusion of Wearable Kinetic and Kinematic Sensors to Estimate Triceps Surae Work during Outdoor Locomotion on Slopes

Muscle–tendon power output is commonly assessed in the laboratory through the work loop, a paired analysis of muscle force and length during a cyclic task. Work-loop analysis of muscle–tendon function in out-of-lab conditions has been elusive due to methodological limitations. In this work, we combined kinetic and kinematic measures from shear wave tensiometry and inertial measurement units, respectively, to establish a wearable system for estimating work and power output from the soleus and gastrocnemius muscles during outdoor locomotion. Across 11 healthy young adults, we amassed 4777 strides of walking on slopes from −10° to +10°. Results showed that soleus work scales with incline, while gastrocnemius work is relatively insensitive to incline. These findings agree with previous results from laboratory-based studies while expanding technological capabilities by enabling wearable analysis of muscle–tendon kinetics. Applying this system in additional settings and activities could improve biomechanical knowledge and evaluation of protocols in scenarios such as rehabilitation, device design, athletics, and military training.

Quantification of muscle coordination underlying basic shoulder movements using muscle synergy extraction

Numerous muscles around the shoulder joint are required to work in a coordinated manner, even when a basic shoulder movement is executed. Muscle synergy can be utilized as an index to determine muscle coordination. The purpose of the present study was to investigate the muscle coordination among different shoulder muscles underlying basic shoulder movements based on muscle synergy. Thirteen men performed 14 multiplanar shoulder movements; five movements were associated with elevation and lowering, while five were associated with horizontal abduction and adduction. The four additional movements were simple rotations at different positions. Muscle activity was measured from 12 muscle portions using surface electromyography. Using the dimensionality reduction technique, synergies were extracted first for each movement separately ("separate" synergies), and then for the global dataset (containing all movements; "global" synergies). The least number that provided 90% of the variance accounted for was selected as the optimal number of synergies. For each subject, approximately two separate synergies and approximately six global synergies with small residual values were extracted from the separate and global electromyography datasets, respectively. Specific patterns of these muscle synergies in each task were observed during each movement. In the cross-validation method, six global synergies explained 88.0 ± 1.3% of the global dataset. These findings indicate that muscle activities underlying basic shoulder movements are expressed as six units, and these units could be proxies for shoulder muscle coordination.

Development of a Full Flexion 3D Musculoskeletal Model of the Knee Considering Intersegmental Contact During High Knee Flexion Movements

A musculoskeletal model of the right lower limb was developed to estimate 3D tibial contact forces in high knee flexion postures. This model determined the effect of intersegmental contact between thigh-calf and heel-gluteal structures on tibial contact forces. This model includes direct tracking and 3D orientation of intersegmental contact force, femoral translations from in vivo studies, wrapping of knee extensor musculature, and a novel optimization constraint for multielement muscle groups. Model verification consisted of calculating the error between estimated tibial compressive forces and direct measurements from the Grand Knee Challenge during movements to ∼120° of knee flexion as no high knee flexion data are available. Tibial compression estimates strongly fit implant data during walking (R2 = .83) and squatting (R2 = .93) with a root mean squared difference of .47 and .16 body weight, respectively. Incorporating intersegmental contact significantly reduced model estimates of peak tibial anterior-posterior shear and increased peak medial-lateral shear during the static phase of high knee flexion movements by an average of .33 and .07 body weight, respectively. This model supports prior work in that intersegmental contact is a critical parameter when estimating tibial contact forces in high knee flexion movements across a range of culturally and occupationally relevant postures.

Development of a comparative chimpanzee musculoskeletal glenohumeral model: implications for human function

Modern human shoulder function is affected by the evolutionary adaptations that have occurred to ensure survival and prosperity of the species. Robust examination of behavioral shoulder performance and injury risk can be holistically improved through an interdisciplinary approach that integrates anthropology and biomechanics. Coordination of these fields can allow different perspectives to contribute to a more complete interpretation of biomechanics of the modern human shoulder. The purpose of this study was to develop a novel biomechanical and comparative chimpanzee glenohumeral model, designed to parallel an existing human glenohumeral model, and compare predicted musculoskeletal outputs between the two models. The chimpanzee glenohumeral model consists of three modules - an external torque module, a musculoskeletal geometric module and an internal muscle force prediction module. Together, these modules use postural kinematics, subject-specific anthropometrics, a novel shoulder rhythm, glenohumeral stability ratios, hand forces, musculoskeletal geometry and an optimization routine to estimate joint reaction forces and moments, subacromial space dimensions, and muscle and tissue forces. Using static postural data of a horizontal bimanual suspension task, predicted muscle forces and subacromial space were compared between chimpanzees and humans. Compared with chimpanzees, the human model predicted a 2 mm narrower subacromial space, deltoid muscle forces that were often double those of chimpanzees and a strong reliance on infraspinatus and teres minor (60-100% maximal force) over other rotator cuff muscles. These results agree with previous work on inter-species differences that inform basic human rotator cuff function and pathology.

Effects of knee flexor submaximal isometric contraction until exhaustion on semitendinosus and biceps femoris long head shear modulus in healthy individuals

This study examined whether a knee flexor isometric contraction at 20% of maximal voluntary isometric contraction until exhaustion would alter the biceps femoris long head (BFlh) and semitendinosus (ST) active stiffness, assessed using ultrasound-based shear wave elastography. Twelve healthy individuals participated in 2 sessions separated by 7 days. Time to exhaustion was similar in both sessions (day 1: 443.8 ± 192.5 s; day 2: 474.6 ± 131.7 s; p = 0.323). At the start of the fatigue task, the ST showed greater active stiffness than the BFlh (p < 0.001), with no differences between days (p = 0.08). The ST active stiffness then decreased from 40% of the task time to exhaustion (− 2.2 to − 13.3%, p = 0.027) until the end of the task (− 16.1 to − 22.9%, p = 0.012), while no significant changes were noted in the BFlh (p = 0.771). Immediately after the fatigue task, a decrease in active stiffness was observed in the ST (− 11.8 to − 17.8%, p < 0.001), but not in the BFlh (p = 0.551). Results were consistent between the 2 testing sessions (p = 0.07–0.959). The present results indicate that fatigue alters the hamstring active stiffness pattern.

Do Muscle Synergies Improve Optimization Prediction of Muscle Activations During Gait?

Determination of muscle forces during motion can help to understand motor control, assess pathological movement, diagnose neuromuscular disorders, or estimate joint loads. Difficulty of in vivo measurement made computational analysis become a common alternative in which, as several muscles serve each degree of freedom, the muscle redundancy problem must be solved. Unlike static optimization (SO), synergy optimization (SynO) couples muscle activations across all time frames, thereby altering estimated muscle co-contraction. This study explores whether the use of a muscle synergy structure within an SO framework improves prediction of muscle activations during walking. A motion/force/electromyography (EMG) gait analysis was performed on five healthy subjects. A musculoskeletal model of the right leg actuated by 43 Hill-type muscles was scaled to each subject and used to calculate joint moments, muscle–tendon kinematics, and moment arms. Muscle activations were then estimated using SynO with two to six synergies and traditional SO, and these estimates were compared with EMG measurements. Synergy optimization neither improved SO prediction of experimental activation patterns nor provided SO exact matching of joint moments. Finally, synergy analysis was performed on SO estimated activations, being found that the reconstructed activations produced poor matching of experimental activations and joint moments. As conclusion, it can be said that, although SynO did not improve prediction of muscle activations during gait, its reduced dimensional control space could be beneficial for applications such as functional electrical stimulation or motion control and prediction.

Joint moments and contact forces in the foot during walking

The net force and moment of a joint have been widely used to understand joint disease in the foot. Meanwhile, it does not reflect the physiological forces on muscles and contact surfaces. The objective of the study is to estimate active moments by muscles, passive moments by connective tissues and joint contact forces in the foot joints during walking. Joint kinematics and external forces of ten healthy subjects (all males, 24.7 ± 1.2 years) were acquired during walking. The data were entered into the five-segment musculoskeletal foot model to calculate muscle forces and joint contact forces of the foot joints using an inverse dynamics-based optimization. Joint reaction forces and active, passive and net moments of each joint were calculated from muscle and ligament forces. The maximum joint reaction forces were 8.72, 4.31, 2.65, and 3.41 body weight (BW) for the ankle, Chopart's, Lisfranc and metatarsophalangeal joints, respectively. Active and passive moments along with net moments were also obtained. The maximum net moments were 8.6, 8.4, 5.4 and 0.8%BW∙HT, respectively. While the trend of net moment was very similar between the four joints, the magnitudes and directions of the active and passive moments varied between joints. The active and passive moments during walking could reveal the roles of muscles and ligaments in each of the foot joints, which was not obvious in the net moment. This method may help narrow down the source of joint problems if applied to clinical studies.

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.

MUSCLE FORCE MAGNITUDES IN THE HUMAN LEG FOR ISOMETRIC EXERCISES WITH VARIOUS RESULTANT FORCE DIRECTIONS AND JOINT ANGLES

Using a gradient-based numerical optimization routine, the force magnitudes required of 10 major sagittal plane leg muscles to create a constant magnitude isometric resultant force against a fixed surface at the toe directed anteriorly, posteriorly, superiorly, and inferiorly were quantitatively predicted for three sets of joint angles: a straight leg configuration, with the knee flexed, and with both the hip and knee flexed. Comparisons over the conditions studied for each individual system muscle found that the maximum variation occurred in knee and hip extensor forces (up to two orders of magnitude). Comparisons within the set of active muscles for each studied condition identified dominant muscles and muscle functions. All anteriorly-directed and posteriorly-directed resultants required a small number of muscles with common functions (mainly knee or hip extensors) and large force magnitudes (O(1000[Formula: see text]N)). In contrast, a large number of muscles, with wide-ranging synergistic and antagonistic functions, acting across multiple joints with relatively small magnitudes (O(100[Formula: see text]N)) were needed to create the superiorly-directed resultant with flexed hip and knee. With good correlation to experimentally measured trends in the interrelationships between leg joint angles and isometric forces, the systematic muscle force prediction and analysis presented in this work can be used to guide the design of targeted muscle strengthening exercises and study of muscle-specific injury.

An integrated biomechanical modeling approach to the ergonomic evaluation of drywall installation

Three different methodologies: work sampling, computer simulation and biomechanical modeling, were integrated to study the physical demands of drywall installation. PATH (Posture, Activity, Tools, and Handling), a work-sampling based method, was used to quantify the percent of time that the drywall installers were conducting different activities with different body segment (trunk, arm, and leg) postures. Utilizing Monte-Carlo simulation to convert the categorical PATH data into continuous variables as inputs for the biomechanical models, the required muscle contraction forces and joint reaction forces at the low back (L4/L5) and shoulder (glenohumeral and sternoclavicular joints) were estimated for a typical eight-hour workday. To demonstrate the robustness of this modeling approach, a sensitivity analysis was conducted to examine the impact of some quantitative assumptions that have been made to facilitate the modeling approach. The results indicated that the modeling approach seemed to be the most sensitive to both the distribution of work cycles for a typical eight-hour workday and the distribution and values of Euler angles that are used to determine the "shoulder rhythm." Other assumptions including the distribution of trunk postures did not appear to have a significant impact on the model outputs. It was concluded that the integrated approach might provide an applicable examination of physical loads during the non-routine construction work, especially for those operations/tasks that have certain patterns/sequences for the workers to follow.

Development and implementation of a coupled computational muscle force optimization bone shape adaptation modeling method

Improved methods to analyze and compare the muscle-based influences that drive bone strength adaptation can aid in the understanding of the wide array of experimental observations about the effectiveness of various mechanical countermeasures to losses in bone strength that result from age, disuse, and reduced gravity environments. The coupling of gradient-based and gradientless numerical optimization routines with finite element methods in this work results in a modeling technique that determines the individual magnitudes of the muscle forces acting in a multisegment musculoskeletal system and predicts the improvement in the stress state uniformity and, therefore, strength, of a targeted bone through simulated local cortical material accretion and resorption. With a performance-based stopping criteria, no experimentally based or system-based parameters, and designed to include the direct and indirect effects of muscles attached to the targeted bone as well as to its neighbors, shape and strength alterations resulting from a wide range of boundary conditions can be consistently quantified. As demonstrated in a representative parametric study, the developed technique effectively provides a clearer foundation for the study of the relationships between muscle forces and the induced changes in bone strength. Its use can lead to the better control of such adaptive phenomena.

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.

The Spatial Dependency of Shoulder Muscle Demands for Seated Lateral Hand Force Exertions

As the modern workplace is dominated by submaximal repetitive tasks, knowledge of the effect of task location is important to ensure workers are unexposed to potentially injurious demands imposed by repetitive work in awkward or sustained postures. The purpose of this investigation was to develop a three-dimensional spatial map of the muscle activity for the right upper extremity during laterally directed submaximal force exertions. Electromyographic (EMG) activity was recorded from fourteen muscles surrounding the shoulder complex as the participants exerted 40N of force in two directions (leftward, rightward) at 70 defined locations. Hand position in both push directions strongly influenced total and certain individual muscle demands as identified by repeated measures analysis of variance (P< .001). During rightward exertions individual muscle activation varied from 1 to 21% MVE and during leftward exertions it varied from 1 to 27% MVE with hand location. Continuous prediction equations for muscular demands based on three-dimensional spatial parameters were created with explained variance ranging from 25 to 73%. The study provides novel information for evaluating existing and proactive workplace designs, and may help identify preferred geometric placements of lateral exertions in occupational settings to lower muscular demands, potentially mitigating fatigue and associated musculoskeletal risks.

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.

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.

Spatial dependency of shoulder muscle demands in horizontal pushing and pulling

Pushing and pulling account for nearly half of all manual material handling tasks. The purpose of this investigation was to develop a 3-D spatial muscle activity map for the right upper extremity during pushing and pulling tasks. Nineteen males performed 140 ramped directional hand exertions (70 push; 70 pull) at locations along three axes aligned with the anatomical planes. Electromyography (EMG) of 14 sites on the right upper extremity was recorded. Two directional 3-way repeated measures ANOVAs assessed the influence of hand position on EMG. Hand position and exertion direction influenced total and individual muscle demand. During pulling exertions, all three hand location parameters influenced total muscle activity (p < 0.001) and similarly in pushing exertions (p < 0.002), though less pronounced than in pulling. Data were used to create equations to predict the muscle activity of untested hand locations for novel work design scenarios.

Robustness of muscle synergies underlying three-dimensional force generation at the hand in healthy humans

Previous studies using advanced matrix factorization techniques have shown that the coordination of human voluntary limb movements may be accomplished using combinations of a small number of intermuscular coordination patterns, or muscle synergies. However, the potential use of muscle synergies for isometric force generation has been evaluated mostly using correlational methods. The results of such studies suggest that fixed relationships between the activations of pairs of muscles are relatively rare. There is also emerging evidence that the nervous system uses independent strategies to control movement and force generation, which suggests that one cannot conclude a priori that isometric force generation is accomplished by combining muscle synergies, as shown in movement control. In this study, we used non-negative matrix factorization to evaluate the ability of a few muscle synergies to reconstruct the activation patterns of human arm muscles underlying the generation of three-dimensional (3-D) isometric forces at the hand. Surface electromyographic (EMG) data were recorded from eight key elbow and shoulder muscles during 3-D force target-matching protocols performed across a range of load levels and hand positions. Four synergies were sufficient to explain, on average, 95% of the variance in EMG datasets. Furthermore, we found that muscle synergy composition was conserved across biomechanical task conditions, experimental protocols, and subjects. Our findings are consistent with the view that the nervous system can generate isometric forces by assembling a combination of a small number of muscle synergies, differentially weighted according to task constraints.

Analytical and numerical analysis of inverse optimization problems: conditions of uniqueness and computational methods

One of the key problems of motor control is the redundancy problem, in particular how the central nervous system (CNS) chooses an action out of infinitely many possible. A promising way to address this question is to assume that the choice is made based on optimization of a certain cost function. A number of cost functions have been proposed in the literature to explain performance in different motor tasks: from force sharing in grasping to path planning in walking. However, the problem of uniqueness of the cost function(s) was not addressed until recently. In this article, we analyze two methods of finding additive cost functions in inverse optimization problems with linear constraints, so-called linear-additive inverse optimization problems. These methods are based on the Uniqueness Theorem for inverse optimization problems that we proved recently (Terekhov et al., J Math Biol 61(3):423-453, 2010). Using synthetic data, we show that both methods allow for determining the cost function. We analyze the influence of noise on the both methods. Finally, we show how a violation of the conditions of the Uniqueness Theorem may lead to incorrect solutions of the inverse optimization problem.

A musculoskeletal foot model for clinical gait analysis

Several full body musculoskeletal models have been developed for research applications and these models may potentially be developed into useful clinical tools to assess gait pathologies. Existing full-body musculoskeletal models treat the foot as a single segment and ignore the motions of the intrinsic joints of the foot. This assumption limits the use of such models in clinical cases with significant foot deformities. Therefore, a three-segment musculoskeletal model of the foot was developed to match the segmentation of a recently developed multi-segment kinematic foot model. All the muscles and ligaments of the foot spanning the modeled joints were included. Muscle pathways were adjusted with an optimization routine to minimize the difference between the muscle flexion-extension moment arms from the model and moment arms reported in literature. The model was driven by walking data from five normal pediatric subjects (aged 10.6+/-1.57 years) and muscle forces and activation levels required to produce joint motions were calculated using an inverse dynamic analysis approach. Due to the close proximity of markers on the foot, small marker placement error during motion data collection may lead to significant differences in musculoskeletal model outcomes. Therefore, an optimization routine was developed to enforce joint constraints, optimally scale each segment length and adjust marker positions. To evaluate the model outcomes, the muscle activation patterns during walking were compared with electromyography (EMG) activation patterns reported in the literature. Model-generated muscle activation patterns were observed to be similar to the EMG activation patterns.

A procedure for estimating the relevant forces in the human knee using a four-bar mechanism

Knee injuries, especially those that affect the cruciate and lateral ligaments, are one of the most serious and frequent pathologies that affect the lower human extremity. Hence, the aim of this study is to develop a dynamic model for the lower extremity capable of estimating forces, forces in the cruciate and collateral ligaments and those normal to the articular cartilage, generated in the knee. The proposed model considers a four-bar mechanism in the knee, a spherical joint in the pelvis and a revolute one in the ankle. The four-bar mechanism is obtained by a synthesis process. The dynamic model includes the inertial properties of the femur, tibia, patella and the foot, the ground reaction force and the most important muscles in the knee. Muscle forces are estimated using an optimisation technique. Results from the application of the model on a real human task are presented.

A task-specific validation of homogeneous non-linear optimisation approaches

In biomechanics, musculoskeletal models are typically redundant. This situation is referred to as the distribution problem. Often, static, non-linear optimisation methods of the form "min: phi(f) subject to mechanical and muscular constraints" have been used to extract a unique set of muscle forces. Here, we present a method for validating this class of non-linear optimisation approaches where the homogeneous cost function, phi(f), is used to solve the distribution problem. We show that the predicted muscle forces for different loading conditions are scaled versions of each other if the joint loading conditions are just scaled versions. Therefore, we can calculate the theoretical muscle forces for different experimental conditions based on the measured muscle forces and joint loadings taken from one experimental condition and assuming that all input into the optimisation (e.g., moment arms, muscle attachment sites, size, fibre type distribution) and the optimisation approach are perfectly correct. Thus predictions of muscle force for other experimental conditions are accurate if the optimisation approach is appropriate, independent of the musculoskeletal geometry and other input required for the optimisation procedure. By comparing the muscle forces predicted in this way to the actual muscle forces obtained experimentally, we conclude that convex homogeneous non-linear optimisation approaches cannot predict individual muscle forces properly, as force-sharing among synergistic muscles obtained experimentally are not just scaled versions of joint loading, not even in a first approximation.

Applicability of the coactivation method in assessing synergies of the scapular stabilizing muscles

HYPOTHESIS

This study investigated the feasibility of quantifying the coactivation levels in the evaluation of synergisms of the scapular stabilizing muscles during the elevation and lowering of the arms. This method, which quantifies the overlapping area of the normalized electromyographic (EMG) activity, could be applicable in assessing such muscular synergies.

MATERIALS AND METHODS

Both shoulders of 10 healthy volunteers were assessed. The coactivation of 3 synergic muscular groups (upper, middle and lower trapezius; upper trapezius and serratus anterior; middle trapezius and serratus anterior) and the isolated electromyographic activity of each muscle were analyzed.

RESULTS

Analysis of variance revealed that the coactivation values between the synergic groups were different from the isolated levels of each respective muscle for both movements (24.42 < F < 40.12; df=6; p < 0.001). The coactivation values of all groups during elevation were different from those during the lowering of the arms (13.31 <F < 959.92; df=1; p <or= 0.002), with progressive increases in EMG activity during the elevation and decreases during the lowering of the arms.

CONCLUSION

The significant differences in EMG activity between the isolated and the coactivation methods indicated that the coactivation method was adequate to assess the scapular muscular synergies.

Arm load magnitude affects selective shoulder muscle activation

For isometric tasks, shoulder muscle forces are assumed to scale linearly with the external arm load magnitude, i.e., muscle force ratios are constant. Inverse dynamic modeling generally predicts such linear scaling behavior, with a critical role for the arbitrary load sharing criteria, i.e., the "cost function". We tested the linearity of the relation between external load magnitude exerted on the humerus and shoulder muscle activation. Six isometric force levels ranging from 17 to 100% of maximal arm force were exerted in 24 directions in a plane perpendicular to the longitudinal axis of the humerus. The direction of maximum muscle activation, the experimentally observed so called Principal Action (PA), was determined for each force magnitude in 12 healthy subjects. This experiment was also simulated with the Delft Shoulder and Elbow Model (DSEM) using two cost functions: (1) minimizing muscle stress and (2) a compound, energy related cost function. PA, both experimental (PA(exp)) and simulated (PA(sim)), was expected not to change with arm forces magnitudes. PA(exp) of the mm. trapezius pars descendens, deltoideus pars medialis and teres major changed substantially as a function of external force magnitude, indicating external load dependency of shoulder muscle activation. In DSEM simulations, using the stress cost function, small non-linearities in the muscle force-external load dependency were observed, originating from gravitational forces working on clavicular and scapular bone masses. More pronounced non-linearities were introduced by using the compound energy related cost function, but no similarity was observed between PA(exp) and PA(sim).

A novel two-stage framework for musculoskeletal dynamic modeling: an application to multifingered hand movement

In this paper, we present a new computational framework for biodynamic modeling of human movement. The framework decouples the conventional dynamic modeling process into two stages: in the first stage, two-component "agonist-antagonist" torque actuators under hypothesized and testable parametric control drive the forward dynamics, and parameters are identified by tracking both kinematics and kinetics; the second stage completes the mapping from the muscle-tendon forces to the predicted joint torques. An empirical test using multifinger grasping movement data was conducted to illustrate the application of the proposed framework and showed that the model reproduced the measurement accurately in both kinematics and kinetics. The torque components exhibited consistent spatial-temporal patterns across joints, digits, and subjects. The muscle-tendon forces computed based on the model-predicted kinematics and kinetics had the peak values within the same order of magnitude as in vivo data reported in the literature. The potential to predict was also demonstrated as we applied the control parameters of one subject to another and achieved close matches.

Experimental evaluation of a computational shoulder musculoskeletal model

BACKGROUND

Many evaluations of shoulder biomechanical models have focused on static exertions in constrained postures, but few have considered tasks that are more complex. This study examines model performance in load delivery tasks for a range of target locations.

METHODS

The study evaluated an optimization-based muscle force prediction model used to assess dynamic load transfer tasks. Model predictions were compared with experimental electromyographic data for two task phases: (1) static hold and (2) dynamic reach.

FINDINGS

Predictions correlated positively over all subjects with electromyographic data for prime movers (deltoid [r=0.53]; infraspinatus [r=0.63]; biceps [r=0.61]), though variations in the correlation existed across subjects and tasks. Conversely, the model predicted electromyographic activity of secondary muscles somewhat less accurately. The model also predicted inactivity for electromyographic inactive muscles.

INTERPRETATION

The model provides important insights into activity levels muscles that most actively respond to external moments during manual load transfer tasks.

Expertise-dependent modulation of muscular and non-muscular torques in multi-joint arm movements during piano keystroke

The problem of skill-level-dependent modulation in the joint dynamics of multi-joint arm movements is addressed in this study using piano keystroke performed by expert and novice piano players. Using the measured kinematic and key-force data, the time varying net, gravitational, motion-dependent interaction (INT), key-reaction (REA), and muscular (MUS) torques at the shoulder, elbow, wrist, and metacarpophalangeal (MP) joints were computed using inverse dynamics techniques. INTs generated at the elbow and wrist joints, but not those at the MP joint, were greater for the experts as compared with the novices. REA at the MP joint, but not at the other joints, was less for the experts as compared with the novices. The MUSs at the MP, wrist, and elbow joints were smaller, and that at the shoulder joint was larger for the experts as compared with the novices. The experts also had a lesser inter-strike variability of key striking force and key descending velocity as compared with the novices. These findings indicated that the relationship among the INT, REA, and MUS occurring at the joints of the upper-extremity differed between the expert and novice piano players, suggesting that the organization of multi-joint arm movement is modulated by long-term motor training toward facilitating both physiological efficiency and movement accuracy.

An integer programming model for optimizing shoulder rehabilitation

Strength restoration is one goal of shoulder rehabilitation following rotator cuff repair surgery. However, the time spent in a physical rehabilitation setting is limited. The objective of this study was to develop a novel mathematical formulation for determining the optimal shoulder rehabilitation exercise protocol to restore normal shoulder strength given a time-constrained rehabilitation session. Strength gain was modeled using a linear dose-response function and biomechanical parameters of the shoulder musculature. Two different objective functions were tested: (1) one based on a least squares support vector machine using healthy and pathologic shoulder strengths (normative objective function), and (2) one which seeks to match the strength of the contralateral shoulder (contralateral objective function). The normative objective function was subject-independent and the optimal protocol consisted of four sets each of adduction and external rotation. The contralateral objective function was subject-specific and the typical optimal protocol consisted of various set combinations of abduction and internal and external rotation. These results are only partially consistent with current practice. Improvement of the current model is dependent on a better understanding of strength training adaptation and shoulder rehabilitation.