A review of musculoskeletal modelling of human locomotion

Computational biomechanics for a standing human body: Modal analysis and simulation

We develop computational mechanical modeling and methods for the analysis and simulation of the motions of a human body. This type of work is crucial in many aspects of human life, ranging from comfort in riding, the motion of aged persons, sports performance and injuries, and many ergonomic issues. A prevailing approach for human motion studies is through lumped parameter models containing discrete masses for the parts of the human body with empirically determined spring, mass, damping coefficients. Such models have been effective to some extent; however, a much more faithful modeling method is to model the human body as it is, namely, as a continuum. We present this approach, and for comparison, we choose two digital CAD models of mannequins for a standing human body, one from the versatile software package LS-DYNA and another from open resources with some of our own adaptations. Our basic view in this paper is to regard human motion as a perturbation and vibration from an equilibrium position which is upright standing. A linear elastodynamic model is chosen for modal analysis, but a full nonlinear viscoelastoplastic extension is possible for full-body simulation. The motion and vibration of these two mannequin models is analyzed by modal analysis, where the normal vibration modes are determined. LS-DYNA is used as the supercomputing and simulation platform. Four sets of low-frequency modes are tabulated, discussed, visualized, and compared. Higher frequency modes are also selectively displayed. We have found that these modes of motion and vibration form intrinsic basic modes of biomechanical motion of the human body. This view is supported by our finding of the upright walking motion as a low-frequency mode in modal analysis. Such a "walking mode" shows the in-phase and out-of-phase movements between the legs and arms on the left and right sides of a human body, implying that this walking motion is spontaneous, likely not requiring any directives from the brain. Dynamic motions of CAD mannequins are also simulated by drop tests for comparisons and the validity of the models is discussed through Fourier frequency analysis. All computed modes of motion are collected in several sets of video animations for ease of visualization. Samples of LS-DYNA computer codes are also included for possible use by other researchers.

Calibrationless monocular vision musculoskeletal simulation during gait

With computer vision technology and prediction of ground reaction forces (GRF), a previous study performed markerless motion capture and musculoskeletal simulation with two smartphones (OpenCap). A recent approach can reconstruct 3D human motion from a single video without calibration and it may further simplify the motion capture process. However it has not been combined with musculoskeletal simulation and the validity is unclear. Therefore, the purpose of this study was to determine the validity of the musculoskeletal simulation using a monocular vision approach. An open-source dataset that contains motion capture and video data during gait from 10 healthy participants was used. Human motion reconstruction with the skinned human (SMPL) model was performed on each video. Virtual marker data was generated by extracting the position data from the SMPL skin vertices. Inverse kinematics, GRF prediction (only for monocular vision approach), inverse dynamics and static optimization were performed using a musculoskeletal model for experimental motion capture data and the generated virtual markers from videos. Mean absolute errors (MAE) between motion capture based and monocular vision based simulation outcomes were calculated. The MAE were 8.4° for joint angles, 5.0 % bodyweight for GRF, 1.1 % bodyweight*height for joint moments and 0.11 for estimated muscle activations from 16 muscles. The entire MAE was larger but some were comparable to OpenCap. Using the monocular vision approach, motion capture and musculoskeletal simulation can be done with no preparations and is beneficial for clinicians to quantify the daily gait assessment.

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

BACKGROUND AND OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Virtual reality skateboarding training for balance and functional performance in degenerative lumbar spine disease

BACKGROUND

Degenerative lumbar spine disease (DLD) is a prevalent condition in middle-aged and elderly individuals. DLD frequently results in pain, muscle weakness, and motor impairment, which affect postural stability and functional performance in daily activities. Simulated skateboarding training could enable patients with DLD to engage in exercise with less pain and focus on single-leg weight-bearing. The purpose of this study was to investigate the effects of virtual reality (VR) skateboarding training on balance and functional performance in patients with DLD.

METHODS

Fourteen patients with DLD and 21 age-matched healthy individuals completed a 6-week program of VR skateboarding training. The motion capture and force platform systems were synchronized to collect data during a single-leg stance test (SLST). Musculoskeletal simulation was utilized to calculate muscle force based on the data. Four functional performance tests were conducted to evaluate the improvement after the training. A Visual Analogue Scale (VAS) was also employed for pain assessment.

RESULTS

After the training, pain intensity significantly decreased in patients with DLD (p = 0.024). Before the training, patients with DLD took longer than healthy individuals on the five times sit-to-stand test (p = 0.024). After the training, no significant between-group differences were observed in any of the functional performance tests (p > 0.05). In balance, patients with DLD were similar to healthy individuals after the training, except that the mean frequency (p = 0.014) was higher. Patients with DLD initially had higher biceps femoris force demands (p = 0.028) but shifted to increased gluteus maximus demand after the training (p = 0.037). Gluteus medius strength significantly improved in patients with DLD (p = 0.039), while healthy individuals showed consistent muscle force (p > 0.05).

CONCLUSION

This is the first study to apply the novel VR skateboarding training to patients with DLD. VR skateboarding training enabled patients with DLD to achieve the training effects in a posture that relieves lumbar spine pressure. The results also emphasized the significant benefits to patients with DLD, such as reduced pain, enhanced balance, and improved muscle performance.

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.

Biomechanics in anthropology

Biomechanics is the set of tools that explain organismal movement and mechanical behavior and links the organism to the physicality of the world. As such, biomechanics can relate behaviors and culture to the physicality of the organism. Scale is critical to biomechanical analyses, as the constitutive equations that matter differ depending on the scale of the question. Within anthropology, biomechanics has had a wide range of applications, from understanding how we and other primates evolved to understanding the effects of technologies, such as the atlatl, and the relationship between identity, society, culture, and medical interventions, such as prosthetics. Like any other model, there is great utility in biomechanical models, but models should be used primarily for hypothesis testing and not data generation except in the rare case where models can be robustly validated. The application of biomechanics within anthropology has been extensive, and holds great potential for the future.

The reciprocity of skeletal muscle and bone: an evolving view from mechanical coupling, secretory crosstalk to stem cell exchange

Introduction: Muscle and bone constitute the two main parts of the musculoskeletal system and generate an intricately coordinated motion system. The crosstalk between muscle and bone has been under investigation, leading to revolutionary perspectives in recent years. Method and results: In this review, the evolving concept of muscle-bone interaction from mechanical coupling, secretory crosstalk to stem cell exchange was explained in sequence. The theory of mechanical coupling stems from the observation that the development and maintenance of bone mass are largely dependent on muscle-derived mechanical loads, which was later proved by Wolff's law, Utah paradigm and Mechanostat hypothesis. Then bone and muscle are gradually recognized as endocrine organs, which can secrete various cytokines to modulate the tissue homeostasis and remodeling to each other. The latest view presented muscle-bone interaction in a more direct way: the resident mesenchymal stromal cell in the skeletal muscle, i.e., fibro-adipogenic progenitors (FAPs), could migrate to the bone injury site and contribute to bone regeneration. Emerging evidence even reveals the ectopic source of FAPs from tissue outside the musculoskeletal system, highlighting its dynamic property. Conclusion: FAPs have been established as the critical cell connecting muscle and bone, which provides a new modality to study inter-tissue communication. A comprehensive and integrated perspective of muscle and bone will facilitate in-depth research in the musculoskeletal system and promote novel therapeutic avenues in treating musculoskeletal disorders.

Modeling and Analysis of Foot Function in Human Gait Using a Two-Degrees-of-Freedom Inverted Pendulum Model with an Arced Foot

Gait models are important for the design and control of lower limb exoskeletons. The inverted pendulum model has advantages in simplicity and computational efficiency, but it also has the limitations of oversimplification and lack of realism. This paper proposes a two-degrees-of-freedom (DOF) inverted pendulum walking model by considering the knee joints for describing the characteristics of human gait. A new parameter, roll factor, is defined to express foot function in the model, and the relationships between the roll factor and gait parameters are investigated. Experiments were conducted to verify the model by testing seven healthy adults at different walking speeds. The results demonstrate that the roll factor has a strong relationship with other gait kinematics parameters, so it can be used as a simple parameter for expressing gait kinematics. In addition, the roll factor can be used to identify walking styles with high accuracy, including small broken step walking at 99.57%, inefficient walking at 98.14%, and normal walking at 99.43%.

Linking neural circuits to the mechanics of animal behavior in Drosophila larval locomotion

The motions that make up animal behavior arise from the interplay between neural circuits and the mechanical parts of the body. Therefore, in order to comprehend the operational mechanisms governing behavior, it is essential to examine not only the underlying neural network but also the mechanical characteristics of the animal's body. The locomotor system of fly larvae serves as an ideal model for pursuing this integrative approach. By virtue of diverse investigation methods encompassing connectomics analysis and quantification of locomotion kinematics, research on larval locomotion has shed light on the underlying mechanisms of animal behavior. These studies have elucidated the roles of interneurons in coordinating muscle activities within and between segments, as well as the neural circuits responsible for exploration. This review aims to provide an overview of recent research on the neuromechanics of animal locomotion in fly larvae. We also briefly review interspecific diversity in fly larval locomotion and explore the latest advancements in soft robots inspired by larval locomotion. The integrative analysis of animal behavior using fly larvae could establish a practical framework for scrutinizing the behavior of other animal species.

Video-driven simulation of lower limb mechanical loading during aquatic exercises

Understanding the mechanical demands of an exercise on the musculoskeletal system is crucial to prescribe effective training or therapeutic interventions. Yet, that knowledge is currently limited in water, mostly because of the difficulty in evaluating external resistance. Here I reconcile recent advances in 3D markerless pose and mesh estimation, biomechanical simulations, and hydrodynamic modeling, to predict lower limb mechanical loading during aquatic exercises. Simulations are driven exclusively from a single video. Fluid forces were estimated within 12.5±4.1% of the peak forces determined through computational fluid dynamics analyses, at a speed three orders of magnitude greater. In silico hip and knee resultant joint forces agreed reasonably well with in vivo instrumented implant recordings (R²=0.74) downloaded from the OrthoLoad database, both in magnitude (RMSE =251±125 N) and direction (cosine similarity = 0.92±0.09). Hip flexors, glutes, adductors, and hamstrings were the main contributors to hip joint compressive forces (40.4±12.7%, 25.6±9.7%, 14.2±4.8%, 13.0±8.2%, respectively), while knee compressive forces were mostly produced by the gastrocnemius (39.1±15.9%) and vasti (29.4±13.7%). Unlike dry-land locomotion, non-hip- and non-knee-spanning muscles provided little to no offloading effect via dynamic coupling. This noninvasive method has the potential to standardize the reporting of exercise intensity, inform the design of rehabilitation protocols and improve their reproducibility.

On the estimation of hip joint loads through musculoskeletal modeling

Noninvasive estimation of joint loads is still an open challenge in biomechanics. Although musculoskeletal modeling represents a solid resource, multiple improvements are still necessary to obtain accurate predictions of joint loads and to translate such potential into practical utility. The present study, focused on the hip joint, is aimed at reviewing the state-of-the-art literature on the estimation of hip joint reaction forces through musculoskeletal modeling. Our literature inspection, based on well-defined selection criteria, returned seventeen works, which were compared in terms of methods and results. Deviations between predicted and in vivo measured hip joint loads, taken from the OrthoLoad database, were assessed through quantitative deviation indices. Despite the numerous modeling and computational improvements made over the last two decades, predicted hip joint loads still deviate from their experimental counterparts and typically overestimate them. Several critical aspects have emerged that affect muscle force estimation, hence joint loads. Among them, the physical fidelity of the musculoskeletal model, with its parameters and geometry, plays a crucial role. Also, predicted joint loads are markedly affected by the selected muscle recruitment strategy, which reflects the underlying motor control policy. Practical guidelines for researchers interested in noninvasive estimation of hip joint loads are also provided.

Challenges in Kinetic-Kinematic Driven Musculoskeletal Subject-Specific Infant Modeling

Musculoskeletal computational models provide a non-invasive approach to investigate human movement biomechanics. These models could be particularly useful for pediatric applications where in vivo and in vitro biomechanical parameters are difficult or impossible to examine using physical experiments alone. The objective was to develop a novel musculoskeletal subject-specific infant model to investigate hip joint biomechanics during cyclic leg movements. Experimental motion-capture marker data of a supine-lying 2-month-old infant were placed on a generic GAIT 2392 OpenSim model. After scaling the model using body segment anthropometric measurements and joint center locations, inverse kinematics and dynamics were used to estimate hip ranges of motion and moments. For the left hip, a maximum moment of 0.975 Nm and a minimum joint moment of 0.031 Nm were estimated at 34.6° and 65.5° of flexion, respectively. For the right hip, a maximum moment of 0.906 Nm and a minimum joint moment of 0.265 Nm were estimated at 23.4° and 66.5° of flexion, respectively. Results showed agreement with reported values from the literature. Further model refinements and validations are needed to develop and establish a normative infant dataset, which will be particularly important when investigating the movement of infants with pathologies such as developmental dysplasia of the hip. This research represents the first step in the longitudinal development of a model that will critically contribute to our understanding of infant growth and development during the first year of life.

Altered Muscle Contributions are Required to Support the Stance Limb During Voluntary Toe-Walking

Toe-walking characterizes several neuromuscular conditions and is associated with a reduction in gait stability and efficiency, as well as in life quality. The optimal choice of treatment depends on a correct understanding of the underlying pathology and on the individual biomechanics of walking. The objective of this study was to describe gait deviations occurring in a cohort of healthy adult subjects when mimicking a unilateral toe-walking pattern compared to their normal heel-to-toe gait pattern. The focus was to characterize the functional adaptations of the major lower-limb muscles which are required in order to toe walk. Musculoskeletal modeling was used to estimate the required muscle contributions to the joint sagittal moments. The support moment, defined as the sum of the sagittal extensive moments at the ankle, knee, and hip joints, was used to evaluate the overall muscular effort necessary to maintain stance limb stability and prevent the collapse of the knee. Compared to a normal heel-to-toe gait pattern, toe-walking was characterized by significantly different lower-limb kinematics and kinetics. The altered kinetic demands at each joint translated into different necessary moment contributions from most muscles. In particular, an earlier and prolonged ankle plantarflexion contribution was required from the soleus and gastrocnemius during most of the stance phase. The hip extensors had to provide a higher extensive moment during loading response, while a significantly higher knee extension contribution from the vasti was necessary during mid-stance. Compensatory muscular activations are therefore functionally required at every joint level in order to toe walk. A higher support moment during toe-walking indicates an overall higher muscular effort necessary to maintain stance limb stability and prevent the collapse of the knee. Higher muscular demands during gait may lead to fatigue, pain, and reduced quality of life. Toe-walking is indeed associated with significantly larger muscle forces exerted by the quadriceps to the patella and prolonged force transmission through the Achilles tendon during stance phase. Optimal treatment options should therefore account for muscular demands and potential overloads associated with specific compensatory mechanisms.

Sensitivity of musculoskeletal models to variation in muscle architecture parameters

Musculoskeletal models, like all theoretical models of physical processes, depend on the assumptions needed to construct the model. For musculoskeletal models, these assumptions include, among other things, the kinematic data, the kinetic data and the muscle parameters. The former (dynamic) data can be acquired relatively easily from living subjects, but the latter are usually based on limited information, frequently determined from cadaver studies performed on elderly individuals. Previously, we determined the sensitivity of forces to dynamic differences among 10 humans walking on a straight path. Here, we assess the sensitivity of the muscle and joint reaction forces developed in human walking to variable muscle parameters obtained from 10 living adults, whose data were recently reported, and compared the results with the values from a standard model that depends on cadaveric data. We found that, while the force patterns across the stance cycle were similar among muscle parameter models, differences of as much as 15% in the force magnitude were produced. Whether or not the variation between the standard model and other muscle parameters is important depends on why the forces are required.