Effects of Optimization Technique on Simulated Muscle Activations and Forces

Musculoskeletal modeling and movement simulation for structural hip disorder research: A scoping review of methods, validation, and applications

Musculoskeletal modeling is a powerful tool to quantify biomechanical factors typically not feasible to measure in vivo, such as hip contact forces and deep muscle activations. While technological advancements in musculoskeletal modeling have increased accessibility, selecting the appropriate modeling approach for a specific research question, particularly when investigating pathological populations, has become more challenging. The purposes of this review were to summarize current modeling and simulation methods in structural hip disorder research, as well as evaluate model validation and study reproducibility. MEDLINE and Web of Science were searched to identify literature relating to the use of musculoskeletal models to investigate structural hip disorders (i.e., involving a bony abnormality of the pelvis, femur, or both). Forty-seven articles were included for analysis, which either compared multiple modeling methods or applied a single modeling workflow to answer a research question. Findings from studies comparing methods were summarized, such as the effect of generic versus patient-specific modeling techniques on model-estimated hip contact forces or muscle forces. The review also discussed limitations in validation practices, as only 11 of the included studies conducted a validation and used qualitative approaches only. Given the lack of information related to model validation, additional details regarding the development and validation of generic models were retrieved from references and modeling software documentation. To address the wide variability and under-reporting of data collection, data processing, and modeling methods highlighted in this review, we developed a template that researchers can complete and include as a table within the methodology section of their manuscripts. The use of this table will help increase transparency and reporting of essential details related to reproducibility and methods without being limited by word count restrictions. Overall, this review provides a comprehensive synthesis of modeling approaches that can help researchers make modeling decisions and evaluate existing literature.

Influence of Walking Over Unexpected Uneven Terrain on Joint Loading for Individuals With Transtibial Amputation

Individuals with transtibial amputation (TTA) experience asymmetric lower-limb loading which can lead to joint pain and injuries. However, it is unclear how walking over unexpected uneven terrain affects their loading patterns. This study sought to use modeling and simulation to determine how peak joint contact forces and impulses change for individuals with unilateral TTA during an uneven step and subsequent recovery step and how those patterns compare to able-bodied individuals. We expected residual limb loading during the uneven step and intact limb loading during the recovery step would increase relative to flush walking. Further, individuals with TTA would experience larger loading increases compared to able-bodied individuals. Simulations of individuals with TTA showed during the uneven step, changes in joint loading occurred at all joints except the prosthetic ankle relative to flush walking. During the recovery step, intact limb joint loading increased in early stance relative to flush walking. Simulations of able-bodied individuals showed large increases in ankle joint loading for both surface conditions. Overall, increases in early stance knee joint loading were larger for those with TTA compared to able-bodied individuals during both steps. These results suggest that individuals with TTA experience altered joint loading patterns when stepping on uneven terrain. Future work should investigate whether an adapting ankle-foot prosthesis can mitigate these changes to reduce injury risk.

Use of computational modeling to examine fingertip force production in children with hemiplegic cerebral palsy

Most children with hemiplegic cerebral palsy (HCP), one of the most prevalent subtypes of cerebral palsy, struggle with grasping and manipulating objects. This impairment may arise from a diminished capacity to properly direct forces created with the finger pad due to aberrant force application. Children with HCP were asked to create maximal force with the index finger pad in the palmar (normal) direction with both the paretic and non-paretic hands. The resulting forces and finger postures were then applied to a computational musculoskeletal model of the hand to estimate the corresponding muscle activation patterns. Subjects tended to create greater shear force relative to normal force with the paretic hand (p < 0.05). The resultant force was directed 33.6°±10.8° away from the instructed palmar direction in the paretic hand, but only 8.0°±7.3° in the non-paretic hand. Additionally, participants created greater palmar force with the non-paretic hand than with the paretic hand (p < 0.05). These differences in force production are likely due to differences in muscle activation pattern, as our computational models showed differences in which muscles are active and their relative activations when recreating the measured force vectors for the two hands (p < 0.01). The models predicted reduced activation in the extrinsic and greater reductions in activation in the intrinsic finger muscles, potentially due to reduced voluntary activation or muscle atrophy. As the large shear forces could lead to objects slipping from grasp, muscle activation patterns may provide an important target for therapeutic treatment in children with HCP.

Comparison of Synergy Extrapolation and Static Optimization for Estimating Multiple Unmeasured Muscle Activations during Walking

Background

Calibrated electromyography (EMG)-driven musculoskeletal models can provide great insight into internal quantities (e.g., muscle forces) that are difficult or impossible to measure experimentally. However, the need for EMG data from all involved muscles presents a significant barrier to the widespread application of EMG-driven modeling methods. Synergy extrapolation (SynX) is a computational method that can estimate a single missing EMG signal with reasonable accuracy during the EMG-driven model calibration process, yet its performance in estimating a larger number of missing EMG signals remains unclear.

Methods

This study assessed the accuracy with which SynX can use eight measured EMG signals to estimate muscle activations and forces associated with eight missing EMG signals in the same leg during walking while simultaneously performing EMG-driven model calibration. Experimental gait data collected from two individuals post-stroke, including 16 channels of EMG data per leg, were used to calibrate an EMG-driven musculoskeletal model, providing "gold standard" muscle activations and forces for evaluation purposes. SynX was then used to predict the muscle activations and forces associated with the eight missing EMG signals while simultaneously calibrating EMG-driven model parameter values. Due to its widespread use, static optimization (SO) was also utilized to estimate the same muscle activations and forces. Estimation accuracy for SynX and SO was evaluated using root mean square errors (RMSE) to quantify amplitude errors and correlation coefficient r values to quantify shape similarity, each calculated with respect to "gold standard" muscle activations and forces.

Results

On average, SynX produced significantly more accurate amplitude and shape estimates for unmeasured muscle activations (RMSE 0.08 vs. 0.15 , r value 0.55 vs. 0.12) and forces (RMSE 101.3 N vs. 174.4   N , r value 0.53 vs. 0.07) compared to SO. SynX yielded calibrated Hill-type muscle-tendon model parameter values for all muscles and activation dynamics model parameter values for measured muscles that were similar to "gold standard" calibrated model parameter values.

Conclusions

These findings suggest that SynX could make it possible to calibrate EMG-driven musculoskeletal models for all important lower-extremity muscles with as few as eight carefully chosen EMG signals and eventually contribute to the design of personalized rehabilitation and surgical interventions for mobility impairments.

Individual Muscle Force Differences During Loaded Hexbar Jumps: A Statistical Parametric Mapping Analysis

Knowledge of individual muscle force during strength and conditioning exercises provides deeper understanding of how specific training decisions relate to desired training outcomes. The purpose of this study was to estimate individual muscle forces during hexbar jumps with 0%, 20%, 40%, and 60% of the hexbar deadlift 1-repetition maximum utilizing in vivo motion capture and computational modeling techniques of male participants. Muscle forces for the gluteus maximus, biceps femoris, rectus femoris, vastus intermedius, gastrocnemius, and soleus were estimated via static optimization. Changes in muscle forces over the concentric phase were analyzed across loading conditions using statistical parametric mapping, impulse, and peak values. Conclusions about the effects of load differ between the three analysis methods; therefore, careful selection of analysis method is essential. Peaks may be inadequate in assessing differences in muscle force during dynamic movements. If SPM, assessing point-by-point differences, is combined with impulse, where time of force application is considered, both timepoint and overall loading can be analyzed. The response of individual muscle forces to increases in external load, as assessed by impulse and SPM, includes increased total muscle output, proportionally highest at 20%1RM, and increased absolute force for the vasti and plantarflexors during the concentric phase of hexbar jumps.

Effect of Whole Body Parameters on Knee Joint Biomechanics: Implications for ACL Injury Prevention During Single-Leg Landings

BACKGROUND

Previous studies have examined the effect of whole body (WB) parameters on anterior cruciate ligament (ACL) strain and loads, as well as knee joint kinetics and kinematics. However, articular cartilage damage occurs in relation to ACL failure, and the effect of WB parameters on ACL strain and articular cartilage biomechanics during dynamic tasks is unclear.

PURPOSES

(1) To investigate the effect of WB parameters on ACL strain, as well as articular cartilage stress and contact force, during a single-leg cross drop (SLCD) and single-leg drop (SLD). (2) To identify WB parameters predictive of high ACL strain during these tasks.

STUDY DESIGN

Descriptive laboratory study.

METHODS

Three-dimensional motion analysis data from 14 physically active men and women were recorded during an SLCD and SLD. OpenSim was used to obtain their kinematics, kinetics, and muscle forces for the WB model. Using these data in kinetically driven finite element simulations of the knee joint produced outputs of ACL strains and articular cartilage stresses and contact forces. Spearman correlation coefficients were used to assess relationships between WB parameters and ACL strain and cartilage biomechanics. Moreover, receiver operating characteristic curve analyses and multivariate binary logistic regressions were used to find the WB parameters that could discriminate high from low ACL strain trials.

RESULTS

Correlations showed that more lumbar rotation away from the stance limb at peak ACL strain had the strongest overall association (ρ = 0.877) with peak ACL strain. Higher knee anterior shear force (ρ = 0.895) and lower gluteus maximus muscle force (ρ = 0.89) at peak ACL strain demonstrated the strongest associations with peak articular cartilage stress or contact force in ≥1 of the analyzed tasks. The regression model that used muscle forces to predict high ACL strain trials during the dominant limb SLD yielded the highest accuracy (93.5%), sensitivity (0.881), and specificity (0.952) among all regression models.

CONCLUSION

WB parameters that were most consistently associated with and predictive of high ACL strain and poor articular cartilage biomechanics during the SLCD and SLD tasks included greater knee abduction angle at initial contact and higher anterior shear force at peak ACL strain, as well as lower gracilis, gluteus maximus, and medial gastrocnemius muscle forces.

CLINICAL RELEVANCE

Knowledge of which landing postures create a high risk for ACL or cartilage injury may help reduce injuries in athletes by avoiding those postures and practicing the tasks with reduced high-risk motions, as well as by strengthening the muscles that protect the knee during single-leg landings.

Computation of physiological loading induced interstitial fluid motion in muscle standardized femur: Healthy vs. osteoporotic bone

BACKGROUND AND OBJECTIVES

Physiological loading-induced mechanical environments regulate bone modeling and remodeling. Thus, loading-induced normal strain is typically considered a stimulus to osteogenesis. However, several studies noticed new bone formation near the sites of minimal normal strain, e.g., the neutral axis of bending in long bones, which raises a question on how bone mass is maintained near these sites. Secondary mechanical components such as shear strain and interstitial fluid flow also stimulate bone cells and regulate bone mass. However, the osteogenic potential of these components is not well established. Accordingly, the present study estimates the distribution of physiological muscle loading-induced mechanical environments such as normal strain, shear strain, pore pressure, and interstitial fluid flow in long bones.

METHODS

A poroelastic finite element muscle standardized femur (MuscleSF) model is developed to compute the distribution of the mechanical environment as a function of bone porosities associated with osteoporotic and disuse bone loss.

RESULTS

The results indicate the presence of higher shear strain and interstitial fluid motion near the minimal strain sites, i.e., the neutral axis of bending of femoral cross-sections. This suggests that secondary stimuli may maintain the bone mass at these locations. Pore pressure and interstitial fluid motion reduce with the increased porosity associated with bone disorders, possibly resulting in diminished skeletal mechano-sensitivity to exogenous loading.

CONCLUSIONS

These outcomes present a better understanding of mechanical environment-mediated regulation of site-specific bone mass, which can be beneficial in developing prophylactic exercise to prevent bone loss in osteoporosis and muscle disuse.

Estimation of Lower Extremity Muscle Activity in Gait Using the Wearable Inertial Measurement Units and Neural Network

The inertial measurement unit (IMU) has become more prevalent in gait analysis. However, it can only measure the kinematics of the body segment it is attached to. Muscle behaviour is an important part of gait analysis and provides a more comprehensive overview of gait quality. Muscle behaviour can be estimated using musculoskeletal modelling or measured using an electromyogram (EMG). However, both methods can be tasking and resource intensive. A combination of IMU and neural networks (NN) has the potential to overcome this limitation. Therefore, this study proposes using NN and IMU data to estimate nine lower extremity muscle activities. Two NN were developed and investigated, namely feedforward neural network (FNN) and long short-term memory neural network (LSTM). The results show that, although both networks were able to predict muscle activities well, LSTM outperformed the conventional FNN. This study confirms the feasibility of estimating muscle activity using IMU data and NN. It also indicates the possibility of this method enabling the gait analysis to be performed outside the laboratory environment with a limited number of devices.

A subject-specific musculoskeletal model to predict the tibiofemoral contact forces during daily living activities

Accurate prediction of tibiofemoral contact force (TFCF) during daily living activities is significant for understanding the initiation, progression, and treatment of knee osteoarthritis (KOA). However, the diversity of target activities, prediction accuracy, and computational efficiency of the current musculoskeletal simulations need to be further improved. In this study, a subject-specific musculoskeletal model considered the tibiofemoral alignment, medial-lateral contact locations, secondary tibiofemoral and all patellofemoral motions, and knee ligaments was proposed to predict the TFCFs during the five daily activities (normal walking, sit-to-stand, stand-to-sit, stair ascent, and stair descent) in OpenSim software. The standing lower-limbs-full-length radiograph, local radiograph of knee joint, motion capture data, and force plate data of eighteen subjects were acquired as the input data of the musculoskeletal model. The results showed good agreements of TFCFs between the predictions based on our proposed musculoskeletal model and the in-vivo measurements based on instrumented knee implants during the five daily activities (RMSE: 0.16 ∼ 0.31 BW, R²: 0.88 ∼ 0.97, M: -0.11 ∼ -0.02, P: 0.03 ∼ 0.10, and C: 0.04 ∼ 0.14). Additionally, the order of the peak total and lateral TFCFs from low to high was normal walking, stair ascent and stand-to-sit, and stair descent and sit-to-stand (P < 0.05), and the peak medial TFCF was stand-to-sit, sit-to-stand, normal walking, stair ascent and stair descent (P < 0.05). The outcomes of this study are valuable for further understanding the knee biomechanics during daily living activities and providing theoretical guidance for the treatments of KOA.

Associations between changes in loading pattern, deformity, and internal stresses at the foot with hammer toe during walking; a finite element approach

Over the past decade, Finite Element (FE) modelling has been used as a method to understand the internal stresses within the diabetic foot. Foot deformities such as hammer toe have been associated with increased risk of foot ulcers in diabetic patients. Hence the aim of this study is to investigate the influence of hammer toe deformity on internal stresses during walking. A 3D finite element model of the human foot was constructed based on capturing Magnetic Resonance Imaging (MRI) of a diabetic neuropathic volunteer exhibiting hammer toe. 3D gait measurements and a multi-body musculoskeletal model for the same participant were used to define muscle forces. FE simulations were run at five different instances during the stance phase of gait. Peak plantar pressure and pressure distribution results calculated from the model showed a good agreement with the experimental measurement having less than 11% errors. Maximum von Mises internal stresses in the forefoot hard tissue were observed at the 3^rd and 5^th metatarsals and 4^th proximal phalanx. Moreover, presence of hammer toe deformity was found to shift the location of maximum internal stresses on the soft tissue to the forefoot by changing the location of centre of pressure with internal stress 1.64 times greater than plantar pressure. Hammer toe deformity also showed to reduce the involvement of the first phalanx in internal/external load-bearing during walking. The findings of this study support the association between changes in loading pattern, deformity, and internal stresses in the soft tissue that lead to foot ulceration.