Model-based estimation of muscle forces exerted during movements

Dynamic injectable tissue adhesives with strong adhesion and rapid self-healing for regeneration of large muscle injury

Wounds often necessitate the use of instructive biomaterials to facilitate effective healing. Yet, consistently filling the wound and retaining the material in place presents notable challenges. Here, we develop a new class of injectable tissue adhesives by leveraging the dynamic crosslinking chemistry of Schiff base reactions. These adhesives demonstrate outstanding mechanical properties, especially in regard to stretchability and self-healing capacity, and biodegradability. Furthermore, they also form robust adhesion to biological tissues. Their therapeutic potential was evaluated in a rodent model of volumetric muscle loss (VML). Ultrasound imaging confirmed that the adhesives remained within the wound site, effectively filled the void, and degraded at a rate comparable to the healing process. Histological analysis indicated that the adhesives facilitated muscle fiber and blood vessel formation, and induced anti-inflammatory macrophages. Notably, the injured muscles of mice treated with the adhesives displayed increased weight and higher force generation than the control groups. This approach to adhesive design paves the way for the next generation of medical adhesives in tissue repair.

Estimation of the forces exerted on the limb long bones of a white rhinoceros (Ceratotherium simum) using musculoskeletal modelling and simulation

Heavy animals incur large forces on their limb bones, due to the transmission of body weight and ground reaction forces, and the contractions of the various muscles of the limbs. This is particularly true for rhinoceroses, the heaviest extant animals capable of galloping. Several studies have examined their musculoskeletal system and the forces their bones incur, but no detailed quantification has ever been attempted. Such quantification could help understand better the link between form and function in giant land animals. Here we constructed three-dimensional musculoskeletal models of the forelimb and hindlimb of Ceratotherium simum, the heaviest extant rhino species, and used static optimisation (inverse) simulations to estimate the forces applied on the bones when standing at rest, including magnitudes and directions. Overall, unsurprisingly, the most active muscles were antigravity muscles, which generate moments opposing body weight (thereby incurring the ground reaction force), and thus keep the joints extended, avoiding joint collapse via flexion. Some muscles have an antigravity action around several joints, and thus were found to be highly active, likely specialised in body weight support (ulnaris lateralis; digital flexors). The humerus was subjected to the greatest amount of forces in terms of total magnitude; forces on the humerus furthermore came from a great variety of directions. The radius was mainly subject to high-magnitude compressive joint reaction forces, but to little muscular tension, whereas the opposite pattern was observed for the ulna. The femur had a pattern similar to that of the humerus, and the tibia's pattern was intermediate, being subject to great compression in its caudal side but to great tension in its cranial side (i.e. bending). The fibula was subject to by far the lowest force magnitude. Overall, the forces estimated were consistent with the documented morphofunctional adaptations of C. simum's long bones, which have larger insertion areas for several muscles and a greater robusticity overall than those of lighter rhinos, likely reflecting the intense forces we estimated here. Our estimates of muscle and bone (joint) loading regimes for this giant tetrapod improve the understanding of the links between form and function in supportive tissues and could be extended to other aspects of bone morphology, such as microanatomy.

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

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

Bone morphology and physical characteristics of the pro-cyclist hip joint

PURPOSE

This study aimed to investigate the radiographic findings for the hip joint and hip range of motion in professional cyclists, and to determine their bone morphology and physical characteristics. The effects of physical characteristics on athletic performance were examined in terms of metabolic efficiency using simulation analysis.

METHODS

We performed a case-control research study on 22 hips in 11 male professional cyclists (average age 28.5, height 1.73 m, weight 77.6 kg). Thirty hips in 15 healthy male volunteers were selected as controls. As radiographic evaluations, acetabular dysplasia was assessed on standardized radiographs. During physical evaluations, the hip range of motion was examined. We used simulation analysis to investigate the metabolic efficiency in the different cycling forms.

RESULTS

The radiographic evaluations showed a significant difference in the incidence of acetabular dysplasia (p = 0.01): 59% (13/22 hips) in the pro-cyclist group versus 10% (3/30 hips) in the control group. The physical evaluations revealed significant differences in the hip internal rotation angle (p = 0.01), with greater ranges of internal rotation in the pro-cyclist group versus the control group. The simulation analyses showed that metabolism was reduced in the cycling form with hip internal rotation, especially in the lower extremities.

CONCLUSIONS

Pro-cyclists showed a high frequency of acetabular dysplasia and superior hip internal rotation. According to the cycling model analyses, hip internal rotation allowed pedaling with reduced metabolic power.

The ankle dorsiflexion kinetics demand to increase swing phase foot-ground clearance: implications for assistive device design and energy demands

BACKGROUND

The ankle is usually highly effective in modulating the swing foot's trajectory to ensure safe ground clearance but there are few reports of ankle kinetics and mechanical energy exchange during the gait cycle swing phase. Previous work has investigated ankle swing mechanics during normal walking but with developments in devices providing dorsiflexion assistance, it is now essential to understand the minimal kinetic requirements for increasing ankle dorsiflexion, particularly for devices employing energy harvesting or utilizing lighter and lower power energy sources or actuators.

METHODS

Using a real-time treadmill-walking biofeedback technique, swing phase ankle dorsiflexion was experimentally controlled to increase foot-ground clearance by 4 cm achieved via increased ankle dorsiflexion. Swing phase ankle moments and dorsiflexor muscle forces were estimated using AnyBody modeling system. It was hypothesized that increasing foot-ground clearance by 4 cm, employing only the ankle joint, would require significantly higher dorsiflexion moments and muscle forces than a normal walking control condition.

RESULTS

Results did not confirm significantly increased ankle moments with augmented dorsiflexion, with 0.02 N.m/kg at toe-off reducing to zero by the end of swing. Tibialis Anterior muscle force incremented significantly from 2 to 4 N/kg after toe-off, due to coactivation with the Soleus. To ensure an additional 4 cm mid swing foot-ground clearance, an estimated additional 0.003 Joules/kg is required to be released immediately after toe-off.

CONCLUSION

This study highlights the interplay between ankle moments, muscle forces, and energy demands during swing phase ankle dorsiflexion, offering insights for the design of ankle assistive technologies. External devices do not need to deliver significantly greater ankle moments to increase ankle dorsiflexion but, they should offer higher mechanical power to provide rapid bursts of energy to facilitate quick dorsiflexion transitions before reaching Minimum Foot Clearance event. Additionally, for ankle-related bio-inspired devices incorporating artificial muscles or humanoid robots that aim to replicate natural ankle biomechanics, the inclusion of supplementary Tibialis Anterior forces is crucial due to Tibialis Anterior and Soleus co-activation. These design strategies ensures that ankle assistive technologies are both effective and aligned with the biomechanical realities of human movement.

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

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

Advanced subject-specific neck musculoskeletal modeling unveils sex differences in muscle moment arm and cervical spine loading

Neck pain and injuries are growing healthcare burdens with women having a higher incidence rate and poorer treatment outcomes than males. A better understanding of sex differences in neck biomechanics, foundational for more targeted, effective prevention or treatment strategies, calls for more advanced subject-specific musculoskeletal modeling. Current neck musculoskeletal models are based on generic anatomy, lack subject specificity beyond anthropometric scaling, and are unable to accurately reproduce neck strengths exhibited in vivo without arbitrary muscle force scaling factors or residual torque actuators. In this work, subject-specific neck musculoskeletal models of 23 individuals (11 male, 12 female) were constructed by integrating multi-modality imaging and biomechanical measurements. Each model simulated maximal voluntary neck static exertions in three postures: neck flexion in a neutral posture, flexion in a 40° extended posture, and extension in a 40° flexed posture. Quantitative model validation showed close agreement between model-predicted muscle activation and EMG measurement. The models unveiled that (1) males have greater moment arms in one flexor muscle group and five extensor muscle groups, (2) females exhibited higher cervical spinal compression per unit exertion force in the flexed posture, and (3) the variability of compression force was much greater in females in all three exertions but most notably in the extension with a flexed "dropped head" position. These insights illuminated a plausible pathway from sex differences in neck biomechanics to sex disparities in the risk and prevalence of neck pain.

Muscle Strength Identification Based on Isokinetic Testing and Spine Musculoskeletal Modeling

Subject-specific spinal musculoskeletal modeling can help understand the spinal loading mechanism during human locomotion. However, existing literature lacks methods to identify the maximum isometric strength of individual spinal muscles. In this study, a muscle strength identification method combining isokinetic testing and musculoskeletal simulations was proposed, and the influence of muscle synergy and intra-abdominal pressure (IAP) on identified spinal muscle strength was further discussed. A multibody dynamic model of the spinal musculoskeletal system was established and controlled by a feedback controller. Muscle strength parameters were adjusted based on the measured isokinetic moments, and muscle synergy vectors and the IAP piston model were further introduced. The results of five healthy subjects showed that the proposed method successfully identified the subject-specific spinal flexor/extensor strength. Considering the synergistic activations of antagonist muscles improved the correlation between the simulated and measured spinal moments, and the introduction of IAP slightly increased the identified spinal extensor strength. The established method is beneficial for understanding spinal loading distributions for athletes and patients with sarcopenia.

Effects of static exercises on hip muscle fatigue and knee wobble assessed by surface electromyography and inertial measurement unit data

Hip muscle weakness can be a precursor to or a result of lower limb injuries. Assessment of hip muscle strength and muscle motor fatigue in the clinic is important for diagnosing and treating hip-related impairments. Muscle motor fatigue can be assessed with surface electromyography (sEMG), however sEMG requires specialized equipment and training. Inertial measurement units (IMUs) are wearable devices used to measure human motion, yet it remains unclear if they can be used as a low-cost alternative method to measure hip muscle fatigue. The goals of this work were to (1) identify which of five pre-selected exercises most consistently and effectively elicited muscle fatigue in the gluteus maximus, gluteus medius, and rectus femoris muscles and (2) determine the relationship between muscle fatigue using sEMG sensors and knee wobble using an IMU device. This work suggests that a wall sit and single leg knee raise activity fatigue the gluteus medius, gluteus maximus, and rectus femoris muscles most reliably (p < 0.05) and that the gluteus medius and gluteus maximus muscles were fatigued to a greater extent than the rectus femoris (p = 0.031 and p = 0.0023, respectively). Additionally, while acceleration data from a single IMU placed on the knee suggested that more knee wobble may be an indicator of muscle fatigue, this single IMU is not capable of reliably assessing fatigue level. These results suggest the wall sit activity could be used as simple, static exercise to elicit hip muscle fatigue in the clinic, and that assessment of knee wobble in addition to other IMU measures could potentially be used to infer muscle fatigue under controlled conditions. Future work examining the relationship between IMU data, muscle fatigue, and multi-limb dynamics should be explored to develop an accessible, low-cost, fast and standardized method to measure fatiguability of the hip muscles in the clinic.

Psoas force recruitment in full-body musculoskeletal movement simulations is restored with a geometrically informed cost function weighting

Simulations of musculoskeletal models are useful for estimating internal muscle and joint forces. However, predicted forces rely on optimization and modeling formulations. Geometric detail is important to predict muscle forces, and greater geometric complexity is required for muscles that have broad attachments or span many joints, as in the torso. However, the extent to which optimized muscle force recruitment is sensitive to these geometry choices is unclear. We developed level, uphill and downhill sloped walking simulations using a standard (uniformly weighted, "fatigue-like") cost function with lower limb and full-body musculoskeletal models to evaluate hip muscle recruitment with different geometric representations of the psoas muscle under walking conditions with varying hip moment demands. We also tested a novel cost function formulation where muscle activations were weighted according to the modeled geometric detail in the full-body model. Total psoas force was less and iliacus, rectus femoris, and other hip flexors' force was greater when psoas was modeled with greater geometric detail compared to other hip muscles for all slopes. The proposed weighting scheme restored hip muscle force recruitment without sacrificing detailed psoas geometry. In addition, we found that lumbar, but not hip, joint contact forces were influenced by psoas force recruitment. Our results demonstrate that static optimization dependent simulations using models comprised of muscles with different amounts of geometric detail bias force recruitment toward muscles with less geometric detail. Muscle activation weighting that accounts for differences in geometric complexity across muscles corrects for this recruitment bias.

Validity of muscle activation estimated with predicted ground reaction force in inverse dynamics based musculoskeletal simulation during gait

The inverse dynamics based musculoskeletal simulation needs ground reaction forces (GRF) as an external force input. GRF can be predicted from kinematic data. However, the validity of estimated muscle activation using the predicted GRF has remained unclear. Therefore, the purpose of this study was to determine the validity of estimated muscle activation with predicted GRF in the inverse dynamics based musculoskeletal simulation. To perform musculoskeletal simulations, an open-source motion capture dataset that contains gait data from 50 healthy subjects was used. CusToM was used for the musculoskeletal simulations. Two sets of inverse dynamics and static optimization were performed, one used predicted GRF (PRED) and another used experimentally measured GRF (EXP). Pearson's correlation was calculated to evaluate the similarity between EMG and estimated muscle activations for both PRED and EXP. To compare PRED and EXP, paired t-tests were used to compare the trial-wise muscle activation similarity and residuals. Relationships between joint moments and residuals were also tested. The overall muscle activation similarity was comparable in PRED (R = 0.477) and EXP (R = 0.475). The residuals were 2-4 times higher in EXP compared to PRED (P < 0.001). The hip flexion-extension moment was correlated to sagittal plane residual moment (R = 0.467). The muscle activations estimated using predicted GRF were comparable to that with measured GRF in the inverse dynamics based musculoskeletal simulation. Prediction of GRF helps to perform musculoskeletal simulations where the force plates are not available.

Female Lower Body Muscle Forces: A Musculoskeletal Modeling Comparison of Back Squats, Split Squats and Good Mornings

The aim of this study was to analyze lower leg muscle forces during strength exercises such as back squats, good mornings and split squats, with a particular emphasis on females. By focusing on females, who are more vulnerable to anterior cruciate ligament injuries, we aimed to better understand muscle engagement and its role in injury prevention. Eight participants were monitored during exercises with a barbell load of 25% of body weight and, during the back squat, an additional 50% load. The analysis was conducted using personalized musculoskeletal models, electromyography (EMG) and Vicon motion capture systems to assess various muscle groups, including the m. gluteus maximus and m. gluteus medius, as well as the hamstring and quadriceps muscles. The back squat produced the highest forces for the quadriceps muscles, particularly the rectus femoris (>25 N/kg), as well as in the back leg during the split squat (>15 N/kg). The gluteal muscles were most active during good mornings and in the front leg of the split squat, especially the m. gluteus maximus medial part (>20 N/kg). The hamstrings generated the highest muscle forces in the front leg of the split squat, with the greatest forces observed in the m. semimembranosus. Our research highlights how musculoskeletal modeling helps us to understand the relationship among muscles, joint angles and anterior cruciate ligament injury risks, especially in strength training females. The results emphasize the need for personalized exercise guidance and customized models to make strength training safer and more effective.

An Enhanced Spine Model Validated for Simulating Dynamic Lifting Tasks in OpenSim

A fully articulated thoracolumbar spine model had been previously developed in OpenSim and had been extensively validated against experimental data during various static tasks. In the present study, we enhanced this detailed musculoskeletal model by adding the role of passive structures and adding kinematic constraints to make it suitable for dynamic tasks. We validated the spinal forces estimated by this enhanced model during nine dynamic lifting/lowering tasks. Moreover, we recently developed and evaluated five approaches in OpenSim to model the external loads applied to the hands during lifting/lowering tasks, and in the present study, we assessed which approach results in more accurate spinal forces. Regardless of the external load modeling approach, the maximum forces predicted by our enhanced spine model across all tasks, as well as the pattern of estimated spinal forces within each task, showed strong correlations (r-values and cross-correlation coefficients > 0.9) with experimental data. Given the biofidelity of our enhanced model, its accessibility via the open-source OpenSim software, and the extent to which this model has been validated, we recommend it for applications requiring estimation of spinal forces during lifting/lowering tasks using multibody-based models and inverse dynamic analyses.

Effect of different postures and loads on joint motion and muscle activity in older adults during overhead retrieval

Introduction: Pain is a common health problem among older adults worldwide. Older adults tend to suffer from arm, lumbar, and back pain when using hanging cabinets. Methods: This study used surface electromyography to record muscle activity and a motion capture system to record joint motion to research effects of different loads and retrieval postures on muscle activity and joint range of motion when older adults retrieve objects from a high place, to provide optimised feedback for the design of hanging cabinet furniture. Results: We found that: 1) The activity of BB (Biceps brachii) on the side of the body interacting with the cabinet door was greater than that of UT (Upper trapezius) and BR (Brachial radius) when retrieving objects from a high place, the activity of UT on the side of the body interacting with a heavy object was greater than that of BB and BR. 2) The activity of UT decreases when the shoulder joint angle is greater than 90°, but the activity of BB increases as the angle increases. In contrast, increasing the object's mass causes the maximum load on the shoulder joint. 3) Among the different postures for overhead retrieval, alternating between the right and left hand is preferable for the overhead retrieval task. 4) Age had the most significant effect on overhead retrieval, followed by height (of person), and load changes were significantly different only at the experiment's left elbow joint and the L.BR. 5) Older adults took longer and exerted more effort to complete the task than younger adults, and static exercise in older adults may be more demanding on muscle activity in old age than powered exercise. Conclusion: These results help to optimise the design of hanging cabinet furniture. Regarding the height of hanging cabinets, 180 cm or less is required for regular retrieval movements if the human height is less than 150 cm. Concerning the depth of the hanging cabinets, different heights chose different comfort distances, which translated into the depth of the hanging cabinets; the greater the height, the greater the depth of the hanging cabinets to use.

Metabolic cost for isometric force scales nonlinearly and predicts how humans distribute forces across limbs

Muscles consume metabolic energy for force production and movement. A mathematical model of metabolic energy cost will be useful in predicting instantaneous costs during human exercise and in computing effort-minimizing movements via simulations. Previous in vivo data-derived models usually assumed either zero or linearly increasing cost with force, but a nonlinear relation could have significant metabolic or behavioural implications. Here, we show that metabolic cost scales nonlinearly with joint torque with an exponent of about 1.64, using calorimetric measurements of isometric squats. We then demonstrate that this metabolic nonlinearity is reflected in human behaviour: minimizing this nonlinear cost predicts how humans share forces between limbs in additional experiments involving arms and legs. This shows the utility of the nonlinear energy cost in predictive models and its generalizability across limbs. Finally, we show mathematical evidence that the same nonlinear metabolic objective may underlie force sharing at the muscle level.

Predicting Tissue Loads in Running from Inertial Measurement Units

BACKGROUND

Runners have high incidence of repetitive load injuries, and habitual runners often use smartwatches with embedded IMU sensors to track their performance and training. If accelerometer information from such IMUs can provide information about individual tissue loads, then running watches may be used to prevent injuries.

METHODS

We investigate a combined physics-based simulation and data-based method. A total of 285 running trials from 76 real runners are subjected to physics-based simulation to recover forces in the Achilles tendon and patella ligament, and the collected data are used to train and test a data-based model using elastic net and gradient boosting methods.

RESULTS

Correlations of up to 0.95 and 0.71 for the patella ligament and Achilles tendon forces, respectively, are obtained, but no single best predictive algorithm can be identified.

CONCLUSIONS

Prediction of tissues loads based on body-mounted IMUs appears promising but requires further investigation before deployment as a general option for users of running watches to reduce running-related injuries.

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.

Does enforcing glenohumeral joint stability matter? A new rapid muscle redundancy solver highlights the importance of non-superficial shoulder muscles

The complexity of the human shoulder girdle enables the large mobility of the upper extremity, but also introduces instability of the glenohumeral (GH) joint. Shoulder movements are generated by coordinating large superficial and deeper stabilizing muscles spanning numerous degrees-of-freedom. How shoulder muscles are coordinated to stabilize the movement of the GH joint remains widely unknown. Musculoskeletal simulations are powerful tools to gain insights into the actions of individual muscles and particularly of those that are difficult to measure. In this study, we analyze how enforcement of GH joint stability in a musculoskeletal model affects the estimates of individual muscle activity during shoulder movements. To estimate both muscle activity and GH stability from recorded shoulder movements, we developed a Rapid Muscle Redundancy (RMR) solver to include constraints on joint reaction forces (JRFs) from a musculoskeletal model. The RMR solver yields muscle activations and joint forces by minimizing the weighted sum of squared-activations, while matching experimental motion. We implemented three new features: first, computed muscle forces include active and passive fiber contributions; second, muscle activation rates are enforced to be physiological, and third, JRFs are efficiently formulated as linear functions of activations. Muscle activity from the RMR solver without GH stability was not different from the computed muscle control (CMC) algorithm and electromyography of superficial muscles. The efficiency of the solver enabled us to test over 3600 trials sampled within the uncertainty of the experimental movements to test the differences in muscle activity with and without GH joint stability enforced. We found that enforcing GH stability significantly increases the estimated activity of the rotator cuff muscles but not of most superficial muscles. Therefore, a comparison of shoulder model muscle activity to EMG measurements of superficial muscles alone is insufficient to validate the activity of rotator cuff muscles estimated from musculoskeletal models.

Influence of Force-Length Relationship and Task-Specific Constraints on Finger Force-Generating Capacities

Grip strength loss in extended and flexed wrist postures has been explained by reduced force-generating capacities of extrinsic finger flexor resulting from non-optimal length, owing to the force-length relationship. Recent works suggested that other muscles, especially wrist extensors, participate in this grip strength loss. The objective of this study was to clarify the role of the force-length relationship in finger force production. 18 participants performed maximal isometric finger force production during pinch grip (Pinch) and four-finger pressing (Press) tasks in four different wrist postures (extended, flexed, neutral, spontaneous). The maximum finger force (MFF), finger and wrist joint angles, as well as activation of four muscles were determined using dynamometry, motion capture, and electromyography. The force and length of the four muscles were estimated from joint angles and muscle activation using a musculoskeletal model. MFF decreased for flexed wrist during Pinch but remained stable across wrist postures during Press. The results suggested that the loss of pinch grip force in deviated wrist posture is partially related to force-length relationship of finger extensors. In opposition, MFF during Press was not influenced by the modulation of muscle capacities but was probably first limited by mechanical and neural factors related to finger interdependence.

Comparative validation of two patient-specific modelling pipelines for predicting knee joint forces during level walking

Over the past few years, the use of computer models and simulations tailored to the patient's physiology to assist clinical decision-making has increased enormously.While several pipelines to develop personalized models exist, their adoption on a large scale is still limited due to the required niche computational skillset and the lengthy operations required. Novel toolboxes, such as STAPLE, promise to streamline and expedite the development of image-based skeletal lower limb models. STAPLE-generated models can be rapidly generated, with minimal user input, and present similar joint kinematics and kinetics compared to models developed employing the established INSIGNEO pipeline. Yet, it is unclear how much the observed discrepancies scale up and affect joint contact force predictions. In this study, we compared image-based musculoskeletal models developed (i) with the INSIGNEO pipeline and (ii) with a semi-automated pipeline that combines STAPLE and nmsBuilder, and assessed their accuracy against experimental implant data.Our results showed that both pipelines predicted similar total knee joint contact forces between one another in terms of profiles and average values, characterized by a moderately high level of agreement with the experimental data. Nonetheless, the Student t-test revealed statistically significant differences between both pipelines. Of note, the STAPLE-based pipeline required considerably less time than the INSIGNEO pipeline to generate a musculoskeletal model (i.e., 60 vs 160 min). This is likely to open up opportunities for the use of personalized musculoskeletal models in clinical practice, where time is of the essence.

Tapping Into Skeletal Muscle Biomechanics for Design and Control of Lower Limb Exoskeletons: A Narrative Review

Lower limb exoskeletons and exosuits ("exos") are traditionally designed with a strong focus on mechatronics and actuation, whereas the "human side" is often disregarded or minimally modeled. Muscle biomechanics principles and skeletal muscle response to robot-delivered loads should be incorporated in design/control of exos. In this narrative review, we summarize the advances in literature with respect to the fusion of muscle biomechanics and lower limb exoskeletons. We report methods to measure muscle biomechanics directly and indirectly and summarize the studies that have incorporated muscle measures for improved design and control of intuitive lower limb exos. Finally, we delve into articles that have studied how the human-exo interaction influences muscle biomechanics during locomotion. To support neurorehabilitation and facilitate everyday use of wearable assistive technologies, we believe that future studies should investigate and predict how exoskeleton assistance strategies would structurally remodel skeletal muscle over time. Real-time mapping of the neuromechanical origin and generation of muscle force resulting in joint torques should be combined with musculoskeletal models to address time-varying parameters such as adaptation to exos and fatigue. Development of smarter predictive controllers that steer rather than assist biological components could result in a synchronized human-machine system that optimizes the biological and electromechanical performance of the combined system.

Muscle-driven forward dynamic active hybrid model of the lumbosacral spine: combined FEM and multibody simulation

Most spine models belong to either the musculoskeletal multibody (MB) or finite element (FE) method. Recently, coupling of MB and FE models has increasingly been used to combine advantages of both methods. Active hybrid FE-MB models, still rarely used in spine research, avoid the interface and convergence problems associated with model coupling. They provide the inherent ability to account for the full interplay of passive and active mechanisms for spinal stability. In this paper, we developed and validated a novel muscle-driven forward dynamic active hybrid FE-MB model of the lumbosacral spine (LSS) in ArtiSynth to simultaneously calculate muscle activation patterns, vertebral movements, and internal mechanical loads. The model consisted of the rigid vertebrae L1-S1 interconnected with hyperelastic fiber-reinforced FE intervertebral discs, ligaments, facet joints, and force actuators representing the muscles. Morphological muscle data were implemented via a semi-automated registration procedure. Four auxiliary bodies were utilized to describe non-linear muscle paths by wrapping and attaching the anterior abdominal muscles. This included an abdominal plate whose kinematics was optimized using motion capture data from upper body movements. Intra-abdominal pressure was calculated from the forces of the abdominal muscles compressing the abdominal cavity. For the muscle-driven approach, forward dynamics assisted data tracking was used to predict muscle activation patterns that generate spinal postures and balance the spine without prescribing accurate spinal kinematics. During calibration, the maximum specific muscle tension and spinal rhythms resulting from the model dynamics were evaluated. To validate the model, load cases were simulated from -10° extension to +30° flexion with weights up to 20 kg in both hands. The biomechanical model responses were compared with in vivo literature data of intradiscal pressures, intra-abdominal pressures, and muscle activities. The results demonstrated high agreement with this data and highlight the advantages of active hybrid modeling for the LSS. Overall, this new self-contained tool provides a robust and efficient estimation of LSS biomechanical responses under in vivo similar loads, for example, to improve pain treatment by spinal stabilization therapies.

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.

Estimating Joint Kinematics and Muscles Forces During Robotic Rehabilitation to Detect and Counteract Reduced Ankle Mobility

The paper presents a solution to detect active ankle joint movement while a patient undergoes therapy with a robotic lower limb rehabilitation device that neither restricts nor actively supports ankle dorsi- or plantarflexion. The presented method requires the addition of only two accelerometer sensors to the system as well as a musculoskeletal model of the lower limb. Using forward kinematics and inverse dynamics, it enables knee and ankle joint kinematic tracking in the sagittal plane and muscle force estimation. This is an extension of a previous work in which only hip joint tracking was possible and, thus, muscle force estimation was limited. The correlation results of the current validation study with 12 healthy subjects show high correlation (R=0.88±0.09) between the kinematics estimated with the proposed method and those calculated from a gold standard motion capture setup for all three joints (hip, knee, and ankle). The correlation results of the estimated m. tibialis anterior muscle force against electromyography measurements (R = 0.62±0.27) are promising and a first application to a patient data set shows potential for future clinical application.

Knee joint biomechanics and cartilage damage prediction during landing: A hybrid MD-FE-musculoskeletal modeling

Understanding the mechanics behind knee joint injuries and providing appropriate treatment is crucial for improving physical function, quality of life, and employability. In this study, we used a hybrid molecular dynamics-finite element-musculoskeletal model to determine the level of loads the knee can withstand when landing from different heights (20, 40, 60 cm), including the height at which cartilage damage occurs. The model was driven by kinematics-kinetics data of asymptomatic subjects at the peak loading instance of drop landing. Our analysis revealed that as landing height increased, the forces on the knee joint also increased, particularly in the vastus muscles and medial gastrocnemius. The patellar tendon experienced more stress than other ligaments, and the medial plateau supported most of the tibial cartilage contact forces and stresses. The load was mostly transmitted through cartilage-cartilage interaction and increased with landing height. The critical height of 126 cm, at which cartilage damage was initiated, was determined by extrapolating the collected data using an iterative approach. Damage initiation and propagation were mainly located in the superficial layers of the tibiofemoral and patellofemoral cartilage. Finally, this study provides valuable insights into the mechanisms of landing-associated cartilage damage and could help limit joint injuries and improve training programs.

A trained neural network model accurately predicts Achilles tendon stress during walking and running based on shear wave propagation

Shear wave tensiometry is a noninvasive technique for measuring tendon loading during activity based on the speed of a shear wave traveling along the tendon. Shear wave speed has been shown to modulate with axial stress, but calibration is required to obtain absolute measures of tendon loading. However, the current technique only makes use of wave speed, whereas other characteristics of the wave (e.g., amplitude, frequency content) may also vary with tendon loading. It is possible that these data could be used in addition to wave speed to circumvent the need for calibration. Given the potential complex relationships to tendon loading, and the lack of an analytical model to guide the use of these data, it is sensible to use a machine learning approach. Here, we used an ensemble neural network approach to predict inverse dynamics estimates of Achilles tendon stress from shear wave tensiometry data collected in a prior study. Neural network-predicted stresses were highly correlated with stance phase inverse dynamics estimates for walking (R2 = 0.89 ± 0.06) and running (R2 = 0.87 ± 0.11) data reserved for neural network model testing and not included in model training. Additionally, error between neural network-predicted and inverse dynamics-estimated stress was reasonable (walking: RMSD = 11 ± 2% of peak load; running: 25 ± 14%). Results of this pilot analysis suggest that a machine learning approach could reduce the reliance of shear wave tensiometry on calibration and expand its usability in many settings.

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.

Real-Time-Capable Muscle Force Estimation for Monitoring Robotic Rehabilitation Therapy in the Intensive Care Unit

In this paper, a method is proposed to enable real-time monitoring of muscle forces during robotic rehabilitation therapy in the ICU. This method is solely based on sensor information provided by the rehabilitation robot. In current clinical practice, monitoring primarily takes place in the later stages of rehabilitation, but it would also be highly beneficial during early stages. Musculoskeletal models have large, mostly unrealized potential to support and improve patient monitoring. The method presented in this paper is based on a state-of-the-art muscle-tendon path model, which is applied to the use case of the robotic rehabilitation device VEMOTION. The muscle force estimation is validated against surface electromyography measurements of lower limb muscles from 12 healthy volunteers The results show an overall correlation of R = 0.70 0.25 for the single-joint muscle m. iliopsoas, which has a ±major contribution to hip flexion. Given this correlation, the proposed model could be used for real-time monitoring of active patient participation.

The non-invasive evaluation technique of patellofemoral joint stress: a systematic literature review

Introduction: Patellofemoral joint stress (PFJS) is an important parameter for understanding the mechanism of patellofemoral joint pain, preventing patellofemoral joint injury, and evaluating the therapeutic efficacy of PFP rehabilitation programs. The purpose of this systematic review was to identify and categorize the non-invasive technique to evaluate the PFJS. Methods: Literature searches were conducted from January 2000 to October 2022 in electronic databases, namely, PubMed, Web of Science, and EBSCO (Medline, SPORTDiscus). This review includes studies that evaluated the patellofemoral joint reaction force (PJRF) or PFJS, with participants including both healthy individuals and those with patellofemoral joint pain, as well as cadavers with no organic changes. The study design includes cross-sectional studies, case-control studies, and randomized controlled trials. The JBI quality appraisal criteria tool was used to assess the risk of bias in the included studies. Results: In total, 5016 articles were identified in the database research and the citation network, and 69 studies were included in the review. Discussion: Researchers are still working to improve the accuracy of evaluation for PFJS by using a personalized model and optimizing quadriceps muscle strength calculations. In theory, the evaluation method of combining advanced computational and biplane fluoroscopy techniques has high accuracy in evaluating PFJS. The method should be further developed to establish the "gold standard" for PFJS evaluation. In practical applications, selecting appropriate methods and approaches based on theoretical considerations and ecological validity is essential.

Model-based estimation of muscle and ACL forces during turning maneuvers in alpine skiing

In alpine skiing, estimation of the muscle forces and joint loads such as the forces in the ACL of the knee are essential to quantify the loading pattern of the skier during turning maneuvers. Since direct measurement of these forces is generally not feasible, non-invasive methods based on musculoskeletal modeling should be considered. In alpine skiing, however, muscle forces and ACL forces have not been analyzed during turning maneuvers due to the lack of three dimensional musculoskeletal models. In the present study, a three dimensional musculoskeletal skier model was successfully applied to track experimental data of a professional skier. During the turning maneuver, the primary activated muscles groups of the outside leg, bearing the highest loads, were the gluteus maximus, vastus lateralis as well as the medial and lateral hamstrings. The main function of these muscles was to generate the required hip extension and knee extension moments. The gluteus maximus was also the main contributor to the hip abduction moment when the hip was highly flexed. Furthermore, the lateral hamstrings and gluteus maximus contributed to the hip external rotation moment in addition to the quadratus femoris. Peak ACL forces reached 211 N on the outside leg with the main contribution in the frontal plane due to an external knee abduction moment. Sagittal plane contributions were low due to consistently high knee flexion (> 60[Formula: see text]), substantial co-activation of the hamstrings and the ground reaction force pushing the anteriorly inclined tibia backwards with respect to the femur. In conclusion, the present musculoskeletal simulation model provides a detailed insight into the loading of a skier during turning maneuvers that might be used to analyze appropriate training loads or injury risk factors such as the speed or turn radius of the skier, changes of the equipment or neuromuscular control parameters.

Musculotendon Parameters in Lower Limb Models: Simplifications, Uncertainties, and Muscle Force Estimation Sensitivity

Musculotendon parameters are key factors in the Hill-type muscle contraction dynamics, determining the muscle force estimation accuracy of a musculoskeletal model. Their values are mostly derived from muscle architecture datasets, whose emergence has been a major impetus for model development. However, it is often not clear if such parameter update indeed improves simulation accuracy. Our goal is to explain to model users how these parameters are derived and how accurate they are, as well as to what extent errors in parameter values might influence force estimation. We examine in detail the derivation of musculotendon parameters in six muscle architecture datasets and four prominent OpenSim models of the lower limb, and then identify simplifications which could add uncertainties to the derived parameter values. Finally, we analyze the sensitivity of muscle force estimation to these parameters both numerically and analytically. Nine typical simplifications in parameter derivation are identified. Partial derivatives of the Hill-type contraction dynamics are derived. Tendon slack length is determined as the musculotendon parameter that muscle force estimation is most sensitive to, whereas pennation angle is the least impactful. Anatomical measurements alone are not enough to calibrate musculotendon parameters, and the improvement on muscle force estimation accuracy will be limited if the source muscle architecture datasets are the only main update. Model users may check if a dataset or model is free of concerning factors for their research or application requirements. The derived partial derivatives may be used as the gradient for musculotendon parameter calibration. For model development, we demonstrate that it is more promising to focus on other model parameters or components and seek alternative strategies to further increase simulation accuracy.

Can a Musculoskeletal Model Adapted to Knee Implant Geometry Improve Prediction of 3D Contact Forces and Moments?

Tibiofemoral contact loads are crucial parameters in the onset and progression of osteoarthrosis. While contact loads are frequently estimated from musculoskeletal models, their customization is often limited to scaling musculoskeletal geometry or adapting muscle lines. Moreover, studies have usually focused on superior-inferior contact force without investigating three-dimensional contact loads. Using experimental data from six patients with instrumented total knee arthroplasty (TKA), this study customized a lower limb musculoskeletal model to consider the positioning and the geometry of the implant at knee level. Static optimization was performed to estimate tibiofemoral contact forces and contact moments as well as musculotendinous forces. Predictions from both a generic and a customized model were compared to the instrumented implant measurements. Both models accurately predict superior-inferior (SI) force and abduction-adduction (AA) moment. Notably, the customization improves prediction of medial-lateral (ML) force and flexion-extension (FE) moments. However, there is subject-dependent variability in the prediction of anterior-posterior (AP) force. The customized models presented here predict loads on all joint axes and in most cases improve prediction. Unexpectedly, this improvement was more limited for patients with more rotated implants, suggesting a need for further model adaptations such as muscle wrapping or redefinition of hip and ankle joint centers and axes.

Machine Learning for Optical Motion Capture-Driven Musculoskeletal Modelling from Inertial Motion Capture Data

Marker-based Optical Motion Capture (OMC) systems and associated musculoskeletal (MSK) modelling predictions offer non-invasively obtainable insights into muscle and joint loading at an in vivo level, aiding clinical decision-making. However, an OMC system is lab-based, expensive, and requires a line of sight. Inertial Motion Capture (IMC) techniques are widely-used alternatives, which are portable, user-friendly, and relatively low-cost, although with lesser accuracy. Irrespective of the choice of motion capture technique, one typically uses an MSK model to obtain the kinematic and kinetic outputs, which is a computationally expensive tool increasingly well approximated by machine learning (ML) methods. Here, an ML approach is presented that maps experimentally recorded IMC input data to the human upper-extremity MSK model outputs computed from ('gold standard') OMC input data. Essentially, this proof-of-concept study aims to predict higher-quality MSK outputs from the much easier-to-obtain IMC data. We use OMC and IMC data simultaneously collected for the same subjects to train different ML architectures that predict OMC-driven MSK outputs from IMC measurements. In particular, we employed various neural network (NN) architectures, such as Feed-Forward Neural Networks (FFNNs) and Recurrent Neural Networks (RNNs) (vanilla, Long Short-Term Memory, and Gated Recurrent Unit) and a comprehensive search for the best-fit model in the hyperparameters space in both subject-exposed (SE) as well as subject-naive (SN) settings. We observed a comparable performance for both FFNN and RNN models, which have a high degree of agreement (ravg,SE,FFNN=0.90±0.19, ravg,SE,RNN=0.89±0.17, ravg,SN,FFNN=0.84±0.23, and ravg,SN,RNN=0.78±0.23) with the desired OMC-driven MSK estimates for held-out test data. The findings demonstrate that mapping IMC inputs to OMC-driven MSK outputs using ML models could be instrumental in transitioning MSK modelling from 'lab to field'.

Hip joint load prediction using inverse bone remodeling with homogenized FE models: Comparison to micro-FE and influence of material modeling strategy

BACKGROUND AND OBJECTIVE

Measuring physiological loading conditions in vivo can be challenging, as methods are invasive or pose a high modeling effort. However, the physiological loading of bones is also imprinted in the bone microstructure due to bone (re)modeling. This information can be retrieved by inverse bone remodeling (IBR). Recently, an IBR method based on micro-finite-element (µFE) modeling was translated to homogenized-FE (hFE) to decrease computational effort and tested on the distal radius. However, this bone has a relatively simple geometry and homogeneous microstructure. Therefore, the objective of this study was to assess the agreement of hFE-based IBR with µFE-based IBR to predict hip joint loading from the head of the femur; a bone with more complex loading as well as more heterogeneous microstructure.

METHODS

hFE-based IBR was applied to a set of 19 femoral heads using four different material mapping laws. One model with a single homogeneous material for both trabecular and cortical volume and three models with a separated cortex and either homogeneous, density-dependent inhomogeneous, or density and fabric-dependent orthotropic material. Three different evaluation regions (full bone, trabecular bone only, head region only) were defined, in which IBR was applied. µFE models were created for the same bones, and the agreement of the predicted hip joint loading history obtained from hFE and µFE models was evaluated. The loading history was discretized using four unit load cases.

RESULTS

The computational time for FE solving was decreased on average from 500 h to under 1 min (CPU time) when using hFE models instead of µFE models. Using more information in the material model in the hFE models led to a better prediction of hip joint loading history. Inhomogeneous and inhomogeneous orthotropic models gave the best agreement to µFE-based IBR (RMSE% <14%). The evaluation region only played a minor role.

CONCLUSIONS

hFE-based IBR was able to reconstruct the dominant joint loading of the femoral head in agreement with µFE-based IBR and required considerably lower computational effort. Results indicate that cortical and trabecular bone should be modeled separately and at least density-dependent inhomogeneous material properties should be used with hFE models of the femoral head to predict joint loading.

Comparison of a Scaled Cadaver-Based Musculoskeletal Model With a Clinical Upper Extremity Model

Reliably and accurately estimating joint/segmental kinematics from optical motion capture data has remained challenging. Studies objectively characterizing human movement patterns have typically involved inverse kinematics and inverse dynamics techniques. Subsequent research has included scaled cadaver-based musculoskeletal (MSK) modeling for noninvasively estimating joint and muscle loads. As one of the ways to enhance confidence in the validity of MSK model predictions, the kinematics from the preceding step that drives such a model needs to be checked for agreement or compared with established/widely used models. This study rigorously compares the upper extremity (UE) joint kinematics calculated by the Dutch Shoulder Model implemented in the AnyBody Managed Model Repository (involving multibody kinematics optimization (MKO)) with those estimated by the Vicon Plug-in Gait model (involving single-body kinematics optimization (SKO)). Ten subjects performed three trials of (different types of) reaching tasks in a three-dimensional marker-based optical motion capture laboratory setting. Joint angles, processed marker trajectories, and reconstruction residuals corresponding to both models were compared. Scatter plots and Bland-Altman plots were used to assess the agreement between the two model outputs. Results showed the largest differences between the two models for shoulder, followed by elbow and wrist, with all root-mean-squared differences less than 10 deg (although this limit might be unacceptable for clinical use). Strong-to-excellent Spearman's rank correlation coefficients were found between the two model outputs. The Bland-Altman plots showed a good agreement between most of the outputs. In conclusion, results indicate that these two models with different kinematic algorithms broadly agree with each other, albeit with few key differences.

Dynamics of Two-Link Musculoskeletal Chains during Fast Movements: Endpoint Force, Axial, and Shear Joint Reaction Forces

This study provides a dynamic model for a two-link musculoskeletal chain controlled by single-joint and two-joint muscles. The chain endpoint force, and the axial and shear components of the joint reaction forces, were expressed analytically as a function of the muscle forces or torques, the chain configuration, and the link angular velocities and accelerations. The model was applied to upper-limb ballistic push movements involving transverse plane shoulder flexion and elbow extension. The numerical simulation highlights that the shoulder flexion and elbow extension angular acceleration at the initial phase of the movement, and the elbow extension angular velocity and acceleration at the later phase of the movement, induce a proportional medial deviation in the endpoint force direction. The forearm angular velocity and acceleration selectively affect the value of the axial and shear components of the shoulder reaction force, depending on the chain configuration. The same goes for the upper arm and elbow. The combined contribution of the elbow extension angular velocity and acceleration may give rise to anterior shear force acting on the humerus and axial forearm traction force as high as 300 N. This information can help optimize the performance and estimate/control of the joint loads in ballistic sport activities and power-oriented resistance exercises.

High tibiofemoral contact and muscle forces during gait are associated with radiographic knee OA progression over 3 years

BACKGROUND

The objective of this study was to investigate differences in tibiofemoral joint contact forces between individuals with moderate medial OA who exhibit radiographic knee OA progression within 3 years versus those who do not, and to understand the relationship between model-predicted contact forces and net external moments for this population.

METHODS

27 individuals with moderate medial compartment knee OA underwent baseline instrumented gait analysis. OA progressors were defined as those who experienced at least a one grade increase in medial joint space narrowing at three years. An electromyography-driven musculoskeletal model was used to estimate muscle and tibiofemoral contact forces at baseline, which were compared between progressors and non-progressors using t-tests.

RESULTS

Seven individuals experienced radiographic OA progression by 3 years. Progressors walked with significantly higher peaks of medial and total tibiofemoral contact forces, and higher impulse of medial contact forces. Significant and high correlations were found between: first peaks of medial and total contact forces with first peak of the knee adduction moment (R² = 0.74; R² = 0.59); second peaks of medial and total knee contact forces with second peaks of knee adduction and flexion moments (R² = 0.71; R² = 0.68); medial knee contact force impulse with knee adduction moment impulse (R² = 0.76).

CONCLUSIONS

Higher tibiofemoral joint contact forces during walking were associated with three-year radiographic knee OA progression based on medial joint space narrowing. These results support the need for strategies that reduce compressive knee contact forces through the reduction of adduction and flexion moments during walking.

Association between sagittal alignment and loads at the adjacent segment in the fused spine: a combined clinical and musculoskeletal modeling study of 205 patients with adult spinal deformity

PURPOSE

Sagittal malalignment is a risk factor for mechanical complications after surgery for adult spinal deformity (ASD). Spinal loads, modulated by sagittal alignment, may explain this relationship. The aims of this study were to investigate the relationships between: (1) postoperative changes in loads at the proximal segment and realignment, and (2) absolute postoperative loads and postoperative alignment measures.

METHODS

A previously validated musculoskeletal model of the whole spine was applied to study a clinical sample of 205 patients with ASD. Based on clinical and radiographic data, pre-and postoperative patient-specific alignments were simulated to predict loads at the proximal segment adjacent to the spinal fusion.

RESULTS

Weak-to-moderate associations were found between pre-to-postop changes in lumbar lordosis, LL (r =  - 0.23, r =  - 0.43; p < 0.001), global tilt, GT (r = 0.26, r = 0.38; p < 0.001) and the Global Alignment and Proportion score, GAP (r = 0.26, r = 0.37; p < 0.001), and changes in compressive and shear forces at the proximal segment. GAP score parameters, thoracic kyphosis measurements and the slope of upper instrumented vertebra were associated with changes in shear. In patients with T10-pelvis fusion, moderate-to-strong associations were found between postoperative sagittal alignment measures and compressive and shear loads, with GT showing the strongest correlations (r = 0.75, r = 0.73, p < 0.001).

CONCLUSIONS

Spinal loads were estimated for patient-specific full spinal alignment profiles in a large cohort of patients with ASD pre-and postoperatively. Loads on the proximal segments were greater in association with sagittal malalignment and malorientation of proximal vertebra. Future work should explore whether they provide a causative mechanism explaining the associated risk of proximal junction complications.

Elbow joint biomechanics during ADL focusing on total elbow arthroplasty - a scoping review

BACKGROUND

Overloading is hypothesized to be one of the failure mechanisms following total elbow arthroplasty (TEA). It is unclear whether the current post-operative loading instruction is compliant with reported failure mechanisms. Aim is therefore to evaluate the elbow joint load during activities of daily living (ADL) and compare these loads with reported failure limits from retrieval and finite element studies.

METHODS

A scoping review of studies until 23 November 2021 investigating elbow joint load during ADL were identified by searching PubMed/Medline and Web of Science. Studies were eligible when: (1) reporting on the elbow joint load in native elbows or elbows with an elbow arthroplasty in adults; (2) full-text article was available.

RESULTS

Twenty-eight studies with a total of 256 participants were included. Methodological quality was low in 3, moderate in 22 and high in 3 studies. Studies were categorized as 1) close to the body and 2) further away from the body. Tasks were then subdivided into: 1) cyclic flexion/extension, 2) push-up, 3) reaching, 4) self-care, 5) work. Mean flexion-extension joint load was 17 Nm, mean varus-valgus joint load 9 Nm, mean pronation-supination joint load 8 Nm and mean bone-on-bone contact force 337 N.

CONCLUSION

The results of our scoping review give a first overview of the current knowledge on elbow joint loads during ADL. Surprisingly, the current literature is not sufficient to formulate a postoperative instruction for elbow joint loading, which is compliant with failure limits of the prosthesis. In addition, our current instruction does not appear to be evidence-based. Our recommendations offer a starting point to assist clinicians in providing informed decisions about post-operative instructions for their patients.

Shear wave elastography characterizes passive and active mechanical properties of biceps brachii muscle in vivo

Mechanical characterization of individual muscles in their in vivo environment is not well studied. Shear wave elastography (SWE) as a non-invasive technique was shown to be promising in quantifying the local mechanical properties of skeletal muscles. This study aimed to investigate the mechanics of the biceps brachii muscle (BB) derived from SWE in relation to elbow joint position and contraction intensity during isometric contraction. 14 healthy, young subjects participated in the study and five different joint positions (60°-180° elbow angle) were investigated. Shear elastic modulus and surface electromyography (sEMG) of the BB and elbow torque were measured simultaneously, both in passive (i.e., resting) and active states during slow, sub-maximal isometric ramp contractions up to 25%, 50%, and 75% of the maximum voluntary contraction. At passive state, the shear elastic modulus of the BB increased with increasing elbow angle (p < 0.001). Maximum elbow flexion torque was produced at 60° and it decreased with increasing elbow angle (p = 0.001). During sub-maximal contractions, both elbow angle (p < 0.001) and contraction intensity (p < 0.001) had significant effects on the shear elastic modulus but only contraction intensity (p < 0.001) affected sEMG amplitude of the BB. Although torque was decreased at extended elbow positions (150°, 180°), higher active shear elastic modulus of BB muscle was found compared to flexed positions (60°, 90°). Linear regression of the BB sEMG amplitude over elbow torque showed good agreement for all joint positions (R² between 0.69 and 0.89) while the linear agreement between shear elastic modulus of BB and elbow torque differed between flexed (R² = 0.70 at 60° and R² = 0.79 at 90°) and extended positions (with the lowest R² = 0.57 at 150°). We conclude that using SWE, we can detect length-dependent mechanical changes of BB both in passive and active states. More importantly, SWE can be used to characterize active muscle properties in vivo. The present findings have critical importance for developing muscle stiffness as a measure of individual muscle force to validate muscle models and using SWE in clinical diagnostics.

Prediction of in vivo hip contact forces during common activities of daily living using a segment-based musculoskeletal model

Background: Quantifying in vivo hip muscle and contact forces during activities of daily living (ADL) provides valuable information for diagnosis and treatment of hip-related disorders. The objective of this study was to utilize Freebody, a segment-based musculoskeletal model, for the prediction of hip contact forces using a novel objective function during seven common ADLs and validate its performance against the publicly available HIP98 dataset. Methods: Marker data, ground reaction forces, and hip contact forces during slow, normal, and fast walking, stair ascent and descent, and standing up and sitting down were extracted for 3 subjects from the HIP98 dataset. A musculoskeletal anatomical dataset was scaled to match the dimensions of each subject, and muscle and hip contact forces were estimated by minimizing a novel objective function, which was the summation of the muscle stresses squared and body weight-normalised hip contact force. The accuracy of predictions were quantified using several metrics, and muscle forces were qualitatively compared to experimental EMGs in the literature. Results: FreeBody predicted the hip contact forces during the ADLs with encouraging accuracy: The root mean squared error of predictions were 44.0 ± 8.5, 47.4 ± 6.5, and 59.8 ± 7.1% BW during slow, normal, and fast walking, 44.2 ± 16.8% and 53.3 ± 12.2% BW for stair ascent and descent, and 31.8 ± 8.2% and 17.1 ± 5.0% BW for standing up and sitting down, respectively. The error in prediction of peak hip contact forces were 14-18%, 24-28%, 17-35% for slow, normal, and fast walking, 7-25% and 15-32% in stair ascent and descent, and around 10% for standing up and sitting down. The coefficient of determination was larger than 0.90 in all activities except in standing up (0.86 ± 0.08). Conclusion: This study has implemented a novel objective function in a segment-based musculoskeletal model, FreeBody, for the prediction of hip contact forces during a large range of ADLs. The model outputs compare favourably for all ADLs and are the best in standing up and sitting down, while muscle activation patterns are consistent with experimental EMGs from literature. This new objective function addresses one of the major limitations associated with musculoskeletal models in the literature, namely the high non-physiological predicted hip joint contact forces.

A Density-Dependent Target Stimulus for Inverse Bone (Re)modeling with Homogenized Finite Element Models

Inverse bone (re)modeling (IBR) can infer physiological loading conditions from the bone microstructure. IBR scales unit loads, imposed on finite element (FE) models of a bone, such that the trabecular microstructure is homogeneously loaded and the difference to a target stimulus is minimized. Micro-FE (µFE) analyses are typically used to model the microstructure, but computationally more efficient, homogenized FE (hFE) models, where the microstructure is replaced by an equivalent continuum, could be used instead. However, also the target stimulus has to be translated from the tissue to the continuum level. In this study, a new continuum-level target stimulus relating relative bone density and strain energy density is proposed. It was applied using different types of hFE models to predict the physiological loading of 21 distal radii sections, which was subsequently compared to µFE-based IBR. The hFE models were able to correctly identify the dominant load direction and showed a high correlation of the predicted forces, but mean magnitude errors ranged from − 14.7 to 26.6% even for the best models. While µFE-based IBR can still be regarded as a gold standard, hFE-based IBR enables faster predictions, the usage of more sophisticated boundary conditions, and the usage of clinical images.

Effect of Expertise on Shoulder and Upper Limb Kinematics, Electromyography, and Estimated Muscle Forces During a Lifting Task

OBJECTIVE

To highlight the working strategies used by expert manual handlers compared with novice manual handlers, based on recordings of shoulder and upper limb kinematics, electromyography (EMG), and estimated muscle forces during a lifting task.

BACKGROUND

Novice workers involved in assembly, manual handling, and personal assistance tasks are at a higher risk of upper limb musculoskeletal disorders (MSDs). However, few studies have investigated the effect of expertise on upper limb exposure during workplace tasks.

METHOD

Sixteen experts in manual handling and sixteen novices were equipped with 10 electromyographic electrodes to record shoulder muscle activity during a manual handling task consisting of lifting a box (8 or 12 kg), instrumented with three six-axis force sensors, from hip to eye level. Three-dimensional trunk and upper limb kinematics, hand-to-box contact forces, and EMG were recorded. Then, joint contributions, activation levels, and muscle forces were calculated and compared between groups.

RESULTS

Sternoclavicular-acromioclavicular joint contributions were higher in experts at the beginning of the movement, and in novices at the end, whereas the opposite was observed for the glenohumeral joint. EMG activation levels were 37% higher for novices but predicted muscle forces were higher in experts.

CONCLUSION

This study highlights significant differences between experts and novices in shoulder kinematics, EMG, and muscle forces; hence, providing effective work guidelines to ensure the development of a safe handling strategy is important.

APPLICATION

Shoulder kinematics, EMG, and muscle forces could be used as ergonomic tools to identify inappropriate techniques that could increase the prevalence of shoulder injuries.

Can genetics guide exercise prescriptions in osteoarthritis?

Osteoarthritis (OA) is the most common form of arthritis and has a multifactorial etiology. Current management for OA focuses on minimizing pain and functional loss, typically involving pharmacological, physical, psychosocial, and mind-body interventions. However, there remain challenges in determining which patients will benefit most from which interventions. Although exercise-based interventions are recommended as first-line treatments and are known to be beneficial for managing both the disease and illness of OA, the optimal exercise “prescription” is unknown, due in part to our limited understanding of the precise mechanisms underlying its action. Here we present our perspective on the potential role of genetics in guiding exercise prescription for persons with OA. We describe key publications in the areas of exercise and OA, genetics and OA, and exercise and genetics, and point to a paucity of knowledge at the intersection of exercise, genetics, and OA. We suggest there is emerging evidence to support the use of genetics and epigenetics to explain the beneficial effects of exercise for OA. We identify missing links in the existing research relating to exercise, genetics, and OA, and highlight epigenetics as a promising mechanism through which environmental exposures such as exercise may impact OA outcomes. We anticipate future studies will improve our understanding of how genetic and epigenetic factors mediate exercise-based interventions to support implementation and ultimately improve OA patient care.

Evaluation of the Foot Center of Pressure Estimation from Pressure Insoles during Sidestep Cuts, Runs and Walks

Estimating the foot center of pressure (CoP) position by pressure insoles appears to be an interesting technical solution to perform motion analysis beyond the force platforms surface area. The aim of this study was to estimate the CoP position from Moticon® pressure insoles during sidestep cuts, runs and walks. The CoP positions assessed from force platform data and from pressure insole data were compared. One calibration trial performed on the force platforms was used to localize the insoles in the reference coordinate system. The most accurate results were obtained when the motion performed during the calibration trial was similar to the motion under study. In such a case, mean accuracy of CoP position have been evaluated to 15±4mm along anteroposterior (AP) axis and 8.5±3mm along mediolateral (ML) axis for sidestep cuts, 18±5mm along AP axis and 7.3±4mm along ML axis for runs, 15±6mm along AP axis and 6.6±3mm along ML axis for walks. The accuracy of the CoP position assesment from pressure insole data increased with the vertical force applied to the pressure insole and with the number of pressure cells involved.

Estimation of Joint Moments During Turning Maneuvers in Alpine Skiing Using a Three Dimensional Musculoskeletal Skier Model and a Forward Dynamics Optimization Framework

In alpine skiing, estimation of the joint moments acting onto the skier is essential to quantify the loading of the skier during turning maneuvers. In the present study, a novel forward dynamics optimization framework is presented to estimate the joint moments acting onto the skier incorporating a three dimensional musculoskeletal model (53 kinematic degrees of freedom, 94 muscles). Kinematic data of a professional skier performing a turning maneuver were captured and used as input data to the optimization framework. In the optimization framework, the musculoskeletal model of the skier was applied to track the experimental data of a skier and to estimate the underlying joint moments of the skier at the hip, knee and ankle joints of the outside and inside leg as well as the lumbar joint. During the turning maneuver the speed of the skier was about 14 m/s with a minimum turn radius of about 16 m. The highest joint moments were observed at the lumbar joint with a maximum of 1.88 Nm/kg for lumbar extension. At the outside leg, the highest joint moments corresponded to the hip extension moment with 1.27 Nm/kg, the knee extension moment with 1.02 Nm/kg and the ankle plantarflexion moment with 0.85 Nm/kg. Compared to the classical inverse dynamics analysis, the present framework has four major advantages. First, using a forward dynamic optimization framework the underlying kinematics of the skier as well as the corresponding ground reaction forces are dynamically consistent. Second, the present framework can cope with incomplete data (i.e., without ground reaction force data). Third, the computation of the joint moments is less sensitive to errors in the measurement data. Fourth, the computed joint moments are constrained to stay within the physiological limits defined by the musculoskeletal model.

Motion-Based Ground Reaction Forces and Moments Prediction Method for Interaction with a Moving And/Or Non-Horizontal Structure

Inverse dynamics methods are commonly used for the biomechanical analysis of human motion. External forces applied on the subject are required as an input data to solve the dynamic equilibrium of the subject. Force platforms measure ground reactions forces and moments (GRF&Ms) but they limit the ecological aspect of experimental conditions. Motion-based GRF&Ms prediction may circumvent this limitation. The current study aims at evaluating the accuracy of an optimization-based GRF&Ms prediction method modified to be applied to the interaction with a moving and/or non horizontal structure. The main improvement of the method deals with the contact detection in such a moving and/or non horizontal frame. To evaluate the accuracy of the method, 20 subjects performed squats and steps on an instrumented moving structure, measuring both motion and GRF&Ms. The comparison of the root mean square error between the predicted and measured GFR&Ms divided by the subjects mass showed a similar order of magnitude than those from the method without the studied modification (0.14 N/kg for antero-posterior forces, 0.29 N/kg for medio lateral forces, 0.61 N/kg for longitudinal forces, 0.06 Nm/kg for frontal moments, 0.13 Nm/kg for sagittal moments, and 0.03 Nm/kg for transverse moments). The results showed the suitability of the method to study human motions for tasks performed on a moving and/or non-horizontal structure.

Biomechanical Properties of Paraspinal Muscles Influence Spinal Loading—A Musculoskeletal Simulation Study

Paraspinal muscles are vital to the functioning of the spine. Changes in muscle physiological cross-sectional area significantly affect spinal loading, but the importance of other muscle biomechanical properties remains unclear. This study explored the changes in spinal loading due to variation in five muscle biomechanical properties: passive stiffness, slack sarcomere length (SSL), in situ sarcomere length, specific tension, and pennation angle. An enhanced version of a musculoskeletal simulation model of the thoracolumbar spine with 210 muscle fascicles was used for this study and its predictions were validated for several tasks and multiple postures. Ranges of physiologically realistic values were selected for all five muscle parameters and their influence on L4-L5 intradiscal pressure (IDP) was investigated in standing and 36° flexion. We observed large changes in IDP due to changes in passive stiffness, SSL, in situ sarcomere length, and specific tension, often with interesting interplays between the parameters. For example, for upright standing, a change in stiffness value from one tenth to 10 times the baseline value increased the IDP only by 91% for the baseline model but by 945% when SSL was 0.4 μm shorter. Shorter SSL values and higher stiffnesses led to the largest increases in IDP. More changes were evident in flexion, as sarcomere lengths were longer in that posture and thus the passive curve is more influential. Our results highlight the importance of the muscle force-length curve and the parameters associated with it and motivate further experimental studies on in vivo measurement of those properties.

Reinforcement learning coupled with finite element modeling for facial motion learning

BACKGROUND AND OBJECTIVE

Facial palsy patients or patients with facial transplantation have abnormal facial motion due to altered facial muscle functions and nerve damage. Computer-aided system and physics-based models have been developed to provide objective and quantitative information. However, the predictive capacity of these solutions is still limited to explore the facial motion patterns with emerging properties. The present study aims to couple the reinforcement learning and the finite element modeling for facial motion learning and prediction.

METHODS

A novel modeling workflow for learning facial motion was developed. A physically-based model of the face within the Artisynth modeling platform was used. Information exchange protocol was proposed to link reinforcement learning and rigid multi-bodies dynamics outcomes. Two reinforcement learning algorithms (deep deterministic policy gradient (DDPG) and Twin-delayed DDPG (TD3)) were used and implemented to drive the simulations of symmetry-oriented and smile movements. Numerical outcomes were compared to experimental observations (Bosphorus database) for evaluation and validation purposes.

RESULTS

As result, after more than 100 episodes of exploring the environment, the agent starts to learn from previous trials and can find the optimal policy after more than 300 episodes of training. Regarding the symmetry-oriented motion, the muscle excitations predicted by the trained agent help to increase the value of reward from R = -2.06 to R = -0.23, which counts for ∼89% improvement of the symmetry value of the face. For smile-oriented motion, two points at the edge of the mouth move up 0.35 cm, which is within the range of movements estimated from the Bosphorus database (0.4 ± 0.32 cm).

CONCLUSIONS

The present study explored the muscle excitation patterns by coupling reinforcement learning with a detailed finite element model of the face. We developed, for the first time, a novel coupling scheme to integrate the finite element simulation into the reinforcement learning process for facial motion learning. As perspectives, this present workflow will be applied for facial palsy and facial transplantation patients to guide and optimize the functional rehabilitation program.

Medial and Lateral Tibiofemoral Compressive Forces in Patients Following Unilateral Total Knee Arthroplasty During Stationary Cycling

Patients following unilateral total knee arthroplasty (TKA) display interlimb differences in knee joint kinetics during gait and more recently, stationary cycling. The purpose of this study was to use musculoskeletal modeling to estimate total, medial, and lateral tibiofemoral compressive forces for patients following TKA during stationary cycling. Fifteen patients of unilateral TKA, from the same surgeon, participated in cycling at 2 workrates (80 and 100 W). A knee model (OpenSim 3.2) was used to estimate total, medial, and lateral tibiofemoral compressive forces for replaced and nonreplaced limbs. A 2 × 2 (limb × workrate) and a 2 × 2 × 2 (compartment × limb × workrate) analysis of variance were run on the selected variables. Peak medial tibiofemoral compressive force was 23.5% lower for replaced compared to nonreplaced limbs (P = .004, G = 0.80). Peak medial tibiofemoral compressive force was 48.0% greater than peak lateral tibiofemoral compressive force in nonreplaced limbs (MD = 344.5 N, P < .001, G = 1.6) with no difference in replaced limbs (P = .274). Following TKA, patients have greater medial compartment loading on their nonreplaced compared to their replaced limbs and ipsilateral lateral compartment loading. This disproportionate loading may be cause for concern regarding exacerbating contralateral knee osteoarthritis.