Probabilistic Evaluation of Predicted Force Sensitivity to Muscle Attachment and Glenohumeral Stability Uncertainty

The Amputated Limb Gluteus Medius is Biomechanically Disadvantaged in Patients with Unilateral Transfemoral Amputation

Patients with transfemoral amputation (TFA) are at an increased risk of secondary musculoskeleteal comorbidities, primarily due to asymmetric joint loading. Amputated limb muscle weakness is also prevalent in the TFA population, yet all factors that contribute to muscle strength and thus joint loading are not well understood. Our objective was to bilaterally compare gluteus medius (GMED) muscle factors (volume, fatty infiltration, moment arm) that all contribute to joint loading in patients with TFA. Quantitative magnetic resonance (MR) images of the hip were collected from eight participants with unilateral TFA (2M/6F; age: 47.3 ± 14.7 y/o; BMI: 25.4 ± 5.3 kg/m2; time since amputation: 20.6 ± 15.0 years) and used to calculate normalized GMED muscle volume and fatty infiltration. Six participants participated in an instrumented gait analysis session that collected whole-body kinematics during overground walking. Subject-specific musculoskeletal models were used to calculate bilateral GMED (anterior, middle, posterior) moment arms and frontal plane hip joint angles across three gait cycles. Differences in volume, fatty infiltration, hip adduction-abduction angle, and peak moment arms were compared between limbs using paired Cohen's d effect sizes. Volume was smaller by 36.3 ± 18.8% (d = 1.7) and fatty infiltration was greater by 6.4 ± 7.8% (d = 0.8) in the amputated limb GMED compared to the intact limb. The amputated limb GMED abduction moment arms were smaller compared to the intact limb for both overground walking (anterior: d = 0.9; middle: d = 0.1.2) and during normal range of motion (anterior: d = 0.8; middle: d = 0.8) while bilateral hip adduction-abduction angles were similar during overground walking (d = 0.5). These results indicate that in patients with TFA, the amputated limb GMED is biomechanically disadvantaged compared to the intact limb, which may contribute to the etiology of secondary comorbidities. This population might benefit from movement retraining to lengthen the amputated limb GMED abduction moment arm during gait.

Individuals with rotator cuff tears unsuccessfully treated with exercise therapy have less inferiorly oriented net muscle forces during scapular plane abduction

Exercise therapy for individuals with rotator cuff tears fails in approximately 25.0 % of cases. One reason for failure of exercise therapy may be the inability to strengthen and balance the muscle forces crossing the glenohumeral joint that act to center the humeral head on the glenoid. The objective of the current study was to compare the magnitude and orientation of the net muscle force pre- and post-exercise therapy between subjects successfully and unsuccessfully (e.g. eventually underwent surgery) treated with a 12-week individualized exercise therapy program. Twelve computational musculoskeletal models (n = 6 successful, n = 6 unsuccessful) were developed in OpenSim (v4.0) that incorporated subject specific tear characteristics, muscle peak isometric force, in-vivo kinematics and bony morphology. The models were driven with experimental kinematics and the magnitude and orientation of the net muscle force was determined during scapular plane abduction at pre- and post-exercise therapy timepoints. Subjects unsuccessfully treated had less inferiorly oriented net muscle forces pre- and post-exercise therapy compared to subjects successfully treated (p = 0.039 & 0.045, respectively). No differences were observed in the magnitude of the net muscle force (p > 0.05). The current study developed novel computational musculoskeletal models with subject specific inputs capable of distinguishing between subjects successfully and unsuccessfully treated with exercise therapy. A less inferiorly oriented net muscle force in subjects unsuccessfully treated may increase the risk of superior migration leading to impingement. Adjustments to exercise therapy programs may be warranted to avoid surgery in subjects at risk of unsuccessful treatment.

A comparative probabilistic analysis of human and chimpanzee rotator cuff functional capacity

Computational musculoskeletal modeling represents a valuable approach to examining biological systems in physical anthropology. Probabilistic modeling builds on computational musculoskeletal models by associating mathematical distributions of specific musculoskeletal features within known ranges of biological variability with functional outcomes. The purpose of this study was to determine if overlap in rotator cuff muscle force predictions would occur between species during the performance of an evolutionarily relevant horizontal bimanual arm suspension task. This necessitated creating novel probabilistic models of the human and chimpanzee glenohumeral joint through augmentation of previously published deterministic models. Glenohumeral musculoskeletal features of anthropological interest were probabilistically modeled to produce distributions of predicted human and chimpanzee rotator cuff muscle force that were representative of the specific anatomical manipulations. Musculoskeletal features modeled probabilistically included rotator cuff origins and deltoid insertion, glenoid inclination, and joint stability. Predicted human rotator cuff muscle force distributions were mostly limited to alternating between infraspinatus and teres minor, with both 100% and 0% muscle force predicted for both muscles. The chimpanzee model predicted low-to-moderate muscle force across all rotator cuff muscles. Rotator cuff muscle force predictions were most sensitive to changes of muscle origins and insertions. Results indicate that functional rotator cuff overlap is unlikely between chimpanzees and humans without greater modifications of the glenohumeral musculoskeletal phenotypes. The results also highlight the low efficacy of the human upper extremity in overhead, weight-bearing tasks, and propensity for rotator cuff injury.

Between Two Rocks and in a Hard Place: Reflecting on the Biomechanical Basis of Shoulder Occupational Musculoskeletal Disorders

OBJECTIVE

The aim was to review the biomechanical origins of occupational shoulder damage, while considering the complexity of shoulder mechanics and musculoskeletal consequences of diverse task demands.

BACKGROUND

Accessible measures of physical exposures are the primary focus of occupational shoulder assessments and analyses. This approach has led to guidelines and intervention strategies that are often inadequate for mitigating shoulder disorders amongst the complexity of modern workplace demands. Integration of complex shoulder mechanics into occupational assessments, analyses, and interventions is critical for reducing occupational shoulder injury risk.

METHOD

This narrative review describes shoulder biomechanics in the context of common injury mechanisms and consequent injuries, with a particular focus on subacromial impingement syndrome. Several modulators of shoulder injury risk are reviewed, including fatigue, overhead work, office ergonomics considerations, and pushing and pulling task configurations.

RESULTS

Relationships between work requirements, muscular demands, fatigue, and biomechanical tissue loads exist. This review highlights that consideration of specific workplace factors should be integrated with our knowledge of the intricate arrangement and interpersonal variability of the shoulder complex to proactively evaluate occupational shoulder demands and exposures.

CONCLUSION

A standard method for evaluating shoulder muscle exposures during workplace tasks does not exist. An integrated approach is critical for improved work design and prevention of shoulder tissue damage and accompanying disability.

APPLICATION

This review is particularly relevant for researchers and practitioners, providing guidance for work design and evaluation for shoulder injury prevention by understanding the importance of the unique and complex mechanics of the shoulder.

Model of the Performance Based on Artificial Intelligence-Fuzzy Logic Description of Physical Activity

The aim of the study was to build a fuzzy model of lower limb peak torque in an isokinetic mode. The study involved 93 male participants (28 male deaf soccer players, 19 hearing soccer players and 46 deaf untraining male). A fuzzy computational model of different levels of physical activity with a focus on the lower limbs was constructed. The proposed fuzzy model assessing lower limb peak torque in an isokinetic mode demonstrated its effectiveness. The novelty of our research lies in the use of hierarchical fuzzy logic to extract computational rules from data provided explicitly and then to determine the corresponding physiological and pathological mechanisms. The contribution of our research lies in complementing the methods for describing physiology, pathology and rehabilitation with fuzzy parameters, including the so-called dynamic norm embedded in the model.

Gaussian Process Autoregression for Joint Angle Prediction Based on sEMG Signals

There is uncertainty in the neuromusculoskeletal system, and deterministic models cannot describe this significant presence of uncertainty, affecting the accuracy of model predictions. In this paper, a knee joint angle prediction model based on surface electromyography (sEMG) signals is proposed. To address the instability of EMG signals and the uncertainty of the neuromusculoskeletal system, a non-parametric probabilistic model is developed using a Gaussian process model combined with the physiological properties of muscle activation. Since the neuromusculoskeletal system is a dynamic system, the Gaussian process model is further combined with a non-linear autoregressive with eXogenous inputs (NARX) model to create a Gaussian process autoregression model. In this paper, the normalized root mean square error (NRMSE) and the correlation coefficient (CC) are compared between the joint angle prediction results of the Gaussian process autoregressive model prediction and the actual joint angle under three test scenarios: speed-dependent, multi-speed and speed-independent. The mean of NRMSE and the mean of CC for all test scenarios in the healthy subjects dataset and the hemiplegic patients dataset outperform the results of the Gaussian process model, with significant differences (p < 0.05 and p < 0.05, p < 0.05 and p < 0.05). From the perspective of uncertainty, a non-parametric probabilistic model for joint angle prediction is established by using Gaussian process autoregressive model to achieve accurate prediction of human movement.

Morphometric analysis of vastus medialis oblique muscle and its influence on anterior knee pain

Healthy knees require full range squatting movements. Vastus medialis (VM) muscle regulates and adjusts the extensor apparatus that influences the patellofemoral function. This work was designed to investigate the anatomy and morphometry of vastus medialis oblique (VMO) muscle by widely used imaging techniques and investigate how VMO muscle participates in anterior knee pain. Ten dissected cadaveric specimens were examined, focusing on fiber orientations, origin, insertions and nerve supply of VMO muscle. Magnetic resonance imaging and ultrasound of VMO muscle were recorded. Anatomical cross-sectional areas of VMO muscle were determined in painless and painful knees and statistically analyzed. In cadaveric specimens, there was distinct separation between VM longus and VMO (change in fiber angle or fibro-fascial plane). VMO inserted directly into the medial proximal margin of the patella, capsule of the knee joint and continuous with the patellar tendon. Separate branch of femoral nerve run along the anteromedial border of the muscle. Anatomical cross-sectional area was significantly decreased in painful knee by -17.2%±11.0% at lower end of shaft of femur, -21.1%±6.0% at upper border of patella, -36.7%±11.0% at mid-patellar level. VMO is distinct muscle within quadriceps femoris group. VMO muscle would track the patella medially and participate in last phase of knee extension. Assessment of the VMO muscle anatomical cross-sectional area by ultrasonography may constitute promising and reliable tool to evaluate patellofemoral pain syndrome staging.

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.

Glenohumeral stabilizing roles of the scapulohumeral muscles: Implications of muscle geometry

Dynamic stability provided by muscles is integral for function and integrity of the glenohumeral joint. Although the high degree of inter-individual variation that exists in musculoskeletal geometry is associated with shoulder injuries, there is limited research associating the effects of muscle geometry on the potential stabilizing capacities of shoulder muscles. The purpose of this investigation was to evaluate the stabilizing functions of the scapulohumeral muscles using computational modeling and to quantify the sensitivity of muscle stabilizing roles to changes in muscle geometry. Muscle stability ratios in the superior/inferior and anterior/posterior directions were computed as the ratio between the muscle's shear components relative to compression throughout arm elevation in the scapular plane. Muscle attachment locations on the clavicle, scapula, and humerus were iteratively adjusted using Monte Carlo simulations. Consistent with previous experimental studies, the rotator cuff muscles were identified as the primary stabilizers of the glenohumeral joint; whereas the deltoids and coracobrachialis have a strong potential for superiorly translating the humerus at low elevation angles. Variations in the stability ratios due to altered muscle geometry were muscle- and angle-specific. In general, the highest variation was observed for the subscapularis and deltoids (at low elevation angles), while the remaining rotator cuff muscles largely maintained their capacity to provide compressive stabilizing forces at the glenohumeral joint. Changes in muscle stability ratios may affect dynamic stability of the humerus that could differentially predispose individuals to greater risk for injury.

Fast Forward-Dynamics Tracking Simulation: Application to Upper Limb and Shoulder Modeling

OBJECTIVE

Musculoskeletal simulation can be used to estimate muscle forces in clinical movement studies. However, such simulations typically only target movement measurements and are not applicable to force exertion tasks which are commonly used in rehabilitation therapy. Simulations can also produce nonphysiological joint forces or be too slow for real-time clinical applications, such as rehabilitation with real-time feedback. The objective of this study is to propose and evaluate a new formulation of forward-dynamics assisted tracking simulation that incorporates measured reaction forces as targets or constraints without any additional computational cost.

METHODS

We illustrate our method with idealized proof-of-concept models and evaluate it with two upper limb cases: Tracking of hand reaction forces during an isometric force-generation task and constraining glenohumeral joint reaction forces for stability during arm elevation.

RESULTS

We show that the addition of reaction force optimization terms within our simulations generates plausible muscle force predictions for these tasks, which are strongly related to reaction forces in addition to movement. Execution times for all models tested were not different when run with or without the reaction force optimization term, ensuring that the simulations are fast enough for real-time clinical applications.

CONCLUSION

Our novel reaction force optimization term leads to more realistic shoulder reaction forces, without any additional computational costs.

SIGNIFICANCE

Our formulation is not only valuable for shoulder simulations, but could be used in various clinical situations (e.g., for different joints and rehabilitation therapy tasks) where the direction and/or magnitude of reaction forces are of interest.

Structure, function, and control of the human musculoskeletal network

The human body is a complex organism, the gross mechanical properties of which are enabled by an interconnected musculoskeletal network controlled by the nervous system. The nature of musculoskeletal interconnection facilitates stability, voluntary movement, and robustness to injury. However, a fundamental understanding of this network and its control by neural systems has remained elusive. Here we address this gap in knowledge by utilizing medical databases and mathematical modeling to reveal the organizational structure, predicted function, and neural control of the musculoskeletal system. We constructed a highly simplified whole-body musculoskeletal network in which single muscles connect to multiple bones via both origin and insertion points. We demonstrated that, using this simplified model, a muscle's role in this network could offer a theoretical prediction of the susceptibility of surrounding components to secondary injury. Finally, we illustrated that sets of muscles cluster into network communities that mimic the organization of control modules in primary motor cortex. This novel formalism for describing interactions between the muscular and skeletal systems serves as a foundation to develop and test therapeutic responses to injury, inspiring future advances in clinical treatments.

Using a Bayesian Network to Predict L5/S1 Spinal Compression Force from Posture, Hand Load, Anthropometry, and Disc Injury Status

Stochastic biomechanical modeling has become a useful tool most commonly implemented using Monte Carlo simulation, advanced mean value theorem, or Markov chain modeling. Bayesian networks are a novel method for probabilistic modeling in artificial intelligence, risk modeling, and machine learning. The purpose of this study was to evaluate the suitability of Bayesian networks for biomechanical modeling using a static biomechanical model of spinal forces during lifting. A 20-node Bayesian network model was used to implement a well-established static two-dimensional biomechanical model for predicting L5/S1 compression and shear forces. The model was also implemented as a Monte Carlo simulation in MATLAB. Mean L5/S1 spinal compression force estimates differed by 0.8%, and shear force estimates were the same. The model was extended to incorporate evidence about disc injury, which can modify the prior probability estimates to provide posterior probability estimates of spinal compression force. An example showed that changing disc injury status from false to true increased the estimate of mean L5/S1 compression force by 14.7%. This work shows that Bayesian networks can be used to implement a whole-body biomechanical model used in occupational biomechanics and incorporate disc injury.