Incorporating ultrasound-measured musculotendon parameters to subject-specific EMG-driven model to simulate voluntary elbow flexion for persons after stroke

EMG-Constrained and Ultrasound-Informed Muscle-Tendon Parameter Estimation in Post-Stroke Hemiparesis

Secondary morphological and mechanical property changes in the muscle-tendon unit at the ankle joint are often observed in post-stroke individuals. These changes may alter the force generation capacity and affect daily activities such as locomotion. This work aimed to estimate subject-specific muscle-tendon parameters in individuals after stroke by solving the muscle redundancy problem using direct collocation optimal control methods based on experimental electromyography (EMG) signals and measured muscle fiber length. Subject-specific muscle-tendon parameters of the gastrocnemius, soleus, and tibialis anterior were estimated in seven post-stroke individuals and seven healthy controls. We found that the maximum isometric force, tendon stiffness and optimal fiber length in the post-stroke group were considerably lower than in the control group. We also computed the root mean square error between estimated and experimental values of muscle excitation and fiber length. The musculoskeletal model with estimated subject-specific muscle tendon parameters (from the muscle redundancy solver), yielded better muscle excitation and fiber length estimations than did scaled generic parameters. Our findings also showed that the muscle redundancy solver can estimate muscle-tendon parameters that produce force behavior in better accordance with the experimentally-measured value. These muscle-tendon parameters in the post-stroke individuals were physiologically meaningful and may shed light on treatment and/or rehabilitation planning.

Automatic extraction and measurement of ultrasonic muscle morphological parameters based on multi-stage fusion and segmentation

BACKGROUND

Estimating skeletal muscle force output and structure requires measurement of morphological parameters including muscle thickness, pennation angle, and fascicle length. The identification of aponeurosis and muscle fascicles from medical images is required to measure these parameters accurately.

METHODS

This paper introduces a multi-stage fusion and segmentation model (named MSF-Net), to precisely extract muscle aponeurosis and fascicles from ultrasound images. The segmentation process is divided into three stages of feature fusion modules. A prior feature fusion module (PFFM) is designed in the first stage to fuse prior features, thus enabling the network to focus on the region of interest and eliminate image noise. The second stage involves the addition of multi-scale feature fusion module (MS-FFM) for effective fusion of elemental information gathered from different scales. This process enables the precise extraction of muscle fascicles of varied sizes. Finally, the high-low-level feature fusion attention module (H-LFFAM) is created in the third stage to selectively reinforce features containing useful information.

RESULTS

Our proposed MSF-Net outperforms other methods and achieves the highest evaluation metrics. In addition, MSF-Net can obtain similar results to manual measurements by clinical experts. The mean deviation of muscle thickness and fascicle length was 0.18 mm and 1.71 mm, and the mean deviation of pennation angle was 0.31°.

CONCLUSIONS

MSF-Net can accurately extract muscle morphological parameters, which enables medical experts to evaluate muscle morphology and function, and guide rehabilitation training. Therefore, MSF-Net provides a complementary imaging tool for clinical assessment of muscle structure and function.

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.

Electrode Size and Placement for Surface EMG Bipolar Detection from the Brachioradialis Muscle: A Scoping Review

The brachioradialis muscle (BRD) is one of the main elbow flexors and is often assessed by surface electromyography (sEMG) in physiology, clinical, sports, ergonomics, and bioengineering applications. The reliability of the sEMG measurement strongly relies on the characteristics of the detection system used, because of possible crosstalk from the surrounding forearm muscles. We conducted a scoping review of the main databases to explore available guidelines of electrode placement on BRD and to map the electrode configurations used and authors’ awareness on the issues of crosstalk. One hundred and thirty-four studies were included in the review. The crosstalk was mentioned in 29 studies, although two studies only were specifically designed to assess it. One hundred and six studies (79%) did not even address the issue by generically placing the sensors above BRD, usually choosing large disposable ECG electrodes. The analysis of the literature highlights a general lack of awareness on the issues of crosstalk and the need for adequate training in the sEMG field. Three guidelines were found, whose recommendations have been compared and summarized to promote reliability in further studies. In particular, it is crucial to use miniaturized electrodes placed on a specific area over the muscle, especially when BRD activity is recorded for clinical applications.

A Conceptual Blueprint for Making Neuromusculoskeletal Models Clinically Useful

The ultimate goal of most neuromusculoskeletal modeling research is to improve the treatment of movement impairments. However, even though neuromusculoskeletal models have become more realistic anatomically, physiologically, and neurologically over the past 25 years, they have yet to make a positive impact on the design of clinical treatments for movement impairments. Such impairments are caused by common conditions such as stroke, osteoarthritis, Parkinson’s disease, spinal cord injury, cerebral palsy, limb amputation, and even cancer. The lack of clinical impact is somewhat surprising given that comparable computational technology has transformed the design of airplanes, automobiles, and other commercial products over the same time period. This paper provides the author’s personal perspective for how neuromusculoskeletal models can become clinically useful. First, the paper motivates the potential value of neuromusculoskeletal models for clinical treatment design. Next, it highlights five challenges to achieving clinical utility and provides suggestions for how to overcome them. After that, it describes clinical, technical, collaboration, and practical needs that must be addressed for neuromusculoskeletal models to fulfill their clinical potential, along with recommendations for meeting them. Finally, it discusses how more complex modeling and experimental methods could enhance neuromusculoskeletal model fidelity, personalization, and utilization. The author hopes that these ideas will provide a conceptual blueprint that will help the neuromusculoskeletal modeling research community work toward clinical utility.

Modeling muscle function using experimentally determined subject-specific muscle properties

Muscle models are commonly based on intrinsic properties pooled across a number of individuals, often from a different species, and rarely validated against directly measured muscle forces. Here we use a rich data set of rat medial gastrocnemius muscle forces recorded during in-situ and in-vivo isometric, isotonic, and cyclic contractions to test the accuracy of forces predicted using Hill-type muscle models. We identified force-length and force-velocity parameters for each individual, and used either these subject-specific intrinsic properties, or population-averaged properties within the models. The modeled forces for cyclic in-vivo and in-situ contractions matched with measured muscle-tendon forces with r² between 0.70 and 0.86, and root-mean square errors (RMSE) of 0.10 to 0.13 (values normalized to the maximum isometric force). The modeled forces were least accurate at the highest movement and cycle frequencies and did not show an improvement in r² when subject-specific intrinsic properties were used; however, there was a reduction in the RMSE with fewer predictions having higher errors. We additionally recorded and tested muscle models specific to proximal and distal regions of the muscle and compared them to measures and models from the whole muscle belly: there was no improvement in model performance when using data from specific anatomical regions. These results show that Hill-type muscle models can yield very good performance for cyclic contractions typical of locomotion, with small reductions in errors when subject-specific intrinsic properties are used.

Determining the Online Measurable Input Variables in Human Joint Moment Intelligent Prediction Based on the Hill Muscle Model

Introduction: Human joint moment is a critical parameter to rehabilitation assessment and human-robot interaction, which can be predicted using an artificial neural network (ANN) model. However, challenge remains as lack of an effective approach to determining the input variables for the ANN model in joint moment prediction, which determines the number of input sensors and the complexity of prediction. Methods: To address this research gap, this study develops a mathematical model based on the Hill muscle model to determining the online input variables of the ANN for the prediction of joint moments. In this method, the muscle activation, muscle-tendon moment velocity and length in the Hill muscle model and muscle-tendon moment arm are translated to the online measurable variables, i.e. muscle electromyography (EMG), joint angles and angular velocities of the muscle span. To test the predictive ability of these input variables, an ANN model is designed and trained to predict joint moments. The ANN model with the online measurable input variables is tested on the experimental data collected from ten healthy subjects running with the speeds of 2, 3, 4 and 5 m/s on a treadmill. The variance accounted for (VAF) between the predicted and inverse dynamics moment is used to evaluate the prediction accuracy. Results: The results suggested that the method can predict joint moments with a higher accuracy (mean VAF = 89.67±5.56 %) than those obtained by using other joint angles and angular velocities as inputs (mean VAF = 86.27±6.6%) evaluated by jack-knife cross-validation. Conclusions: The proposed method provides us with a powerful tool to predict joint moment based on online measurable variables, which establishes the theoretical basis for optimizing the input sensors and detection complexity of the prediction system. It may facilitate the research on exoskeleton robot control and real-time gait analysis in motor rehabilitation.

Functional and Morphological Changes in the Deep Lumbar Multifidus Using Electromyography and Ultrasound

Surface electromyography (sEMG) studies have indicated that chronic low back pain (cLBP) involves altered electromyographic activity and morphological structure of the lumbar multifidus (LM) beyond pain perception; however, most studies have evaluated the superficial lumbar multifidus. It is difficult to record electromyography (EMG) signals from the deep multifidus (DM) to determine the neuromuscular activation patterns, making it difficult to determine the relationship between functional and structural changes in cLBP. We developed a novel method to record intramuscular EMG signals in the DM based on the sEMG system and fine-wire electrodes. We measured EMG signals of the DM in 24 cLBP patients and 26 pain-free healthy controls to identify changes in neuromuscular activation. We also used ultrasound to measure DM muscle thickness, cross-sectional area, and contraction activity to identify potential relationships between EMG activity and structural damage. cLBP patients had decreased average EMG and root mean square, but increased median frequency and mean power frequency. Average EMG was positively correlated with contractile activity, but not statistically correlated with noncontractile anatomical abnormalities. Our results suggest that cLBP alters the neuromuscular activation patterns and morphological structure of the contractile activity of the DM, providing insights into the mechanisms underlying pain perception.

Combined Ultrasound Imaging and Biomechanical Modeling to Estimate Triceps Brachii Musculotendon Changes in Stroke Survivors

The aim of this study was to investigate the changes of musculotendon parameters of triceps brachii in persons after stroke based on subject-specific biomechanical modeling technique combined with in vivo ultrasound measurement. Five chronic stroke survivors and five normal control subjects were recruited. B-mode ultrasound was applied to measure muscle pennation angle and the optimal length of three heads of triceps' brachii at different joint angle positions in resting and isometric contraction. Measured ultrasound data were used to reduce the unknown parameters during the modeling optimization process. The results showed that pennation angles varied with joint angles, and the longhead TRI pennation from stroke group was smaller than the literature value. The maximum isometric muscle stress from persons after stroke was significantly smaller than that found in the unimpaired subjects. The prediction of joint torque fits well with the measured data from the control group, whereas the prediction error is larger in results from persons after stroke. In vivo parameters from ultrasound data could help to build a subject-specific biomechanical model of elbow extensor for both unimpaired and hemiplegic subjects, and then the results driven from the model could enhance the understanding of motor function changes for persons after stroke.

Correlation between architectural variables and torque in the erector spinae muscle during maximal isometric contraction

This study analysed whether a significant relationship exists between the torque and muscle thickness and pennation angle of the erector spinae muscle during a maximal isometric lumbar extension with the lumbar spine in neutral position. This was a cross-sectional study in which 46 healthy adults performed three repetitions for 5 s of maximal isometric lumbar extension with rests of 90 s. During the lumbar extensions, bilateral ultrasound images of the erector spinae muscle (to measure pennation angle and muscle thickness) and torque were acquired. Reliability test analysis calculating the internal consistency (Cronbach's alpha) of the measure, correlation between pennation angle, muscle thickness and torque extensions were examined. Through a linear regression the contribution of each independent variable (muscle thickness and pennation angle) to the variation of the dependent variable (torque) was calculated. The results of the reliability test were: 0.976-0.979 (pennation angle), 0.980-0.980 (muscle thickness) and 0.994 (torque). The results show that pennation angle and muscle thickness were significantly related to each other with a range between 0.295 and 0.762. In addition, multiple regression analysis showed that the two variables considered in this study explained 68% of the variance in the torque. Pennation angle and muscle thickness have a moderate impact on the variance exerted on the torque during a maximal isometric lumbar extension with the lumbar spine in neutral position.

Change of muscle architecture following body weight support treadmill training for persons after subacute stroke: evidence from ultrasonography

Although the body weight support treadmill training (BWSTT) in rehabilitation therapy has been appreciated for a long time, the biomechanical effects of this training on muscular system remain unclear. Ultrasonography has been suggested to be a feasible method to measure muscle morphological changes after neurological diseases such as stroke, which may help to enhance the understanding of the mechanism underlying the impaired motor function. This study investigated the muscle architectural changes of tibialis anterior and medial gastrocnemius in patients after subacute stroke by ultrasound. As expected, we found the effect of BWSTT on the muscular system. Specifically, the results showed larger pennation angle and muscle thickness of tibialis anterior and longer fascicle length of medial gastrocnemius after the training. The findings of this study suggest that the early rehabilitation training of BWSTT in subacute stage of stroke provides positive changes of the muscle architecture, leading to the potential improvement of the force generation of the muscle. This may not only help us understand changes of subacute stroke in muscular system but also have clinical implications in the evaluation of rehabilitation training after neurological insults.

EMGD-FE: an open source graphical user interface for estimating isometric muscle forces in the lower limb using an EMG-driven model

Background

This paper describes the “EMG Driven Force Estimator (EMGD-FE)”, a Matlab® graphical user interface (GUI) application that estimates skeletal muscle forces from electromyography (EMG) signals. Muscle forces are obtained by numerically integrating a system of ordinary differential equations (ODEs) that simulates Hill-type muscle dynamics and that utilises EMG signals as input. In the current version, the GUI can estimate the forces of lower limb muscles executing isometric contractions. Muscles from other parts of the body can be tested as well, although no default values for model parameters are provided. To achieve accurate evaluations, EMG collection is performed simultaneously with torque measurement from a dynamometer. The computer application guides the user, step-by-step, to pre-process the raw EMG signals, create inputs for the muscle model, numerically integrate the ODEs and analyse the results.

Results

An example of the application’s functions is presented using the quadriceps femoris muscle. Individual muscle force estimations for the four components as well the knee isometric torque are shown.

Conclusions

The proposed GUI can estimate individual muscle forces from EMG signals of skeletal muscles. The estimation accuracy depends on several factors, including signal collection and modelling hypothesis issues.

Prediction of maximal surface electromyographically based voluntary contractions of erector spinae muscles from sonographic measurements during isometric contractions

OBJECTIVES

Currently, there are no studies combining electromyography (EMG) and sonography to estimate the absolute and relative strength values of erector spinae (ES) muscles in healthy individuals. The purpose of this study was to establish whether the maximum voluntary contraction (MVC) of the ES during isometric contractions could be predicted from the changes in surface EMG as well as in fiber pennation and thickness as measured by sonography.

METHODS

Thirty healthy adults performed 3 isometric extensions at 45° from the vertical to calculate the MVC force. Contractions at 33% and 100% of the MVC force were then used during sonographic and EMG recordings. These measurements were used to observe the architecture and function of the muscles during contraction. Statistical analysis was performed using bivariate regression and regression equations.

RESULTS

The slope for each regression equation was statistically significant (P < .001) with R(2) values of 0.837 and 0.986 for the right and left ES, respectively. The standard error estimate between the sonographic measurements and the regression-estimated pennation angles for the right and left ES were 0.10 and 0.02, respectively.

CONCLUSIONS

Erector spinae muscle activation can be predicted from the changes in fiber pennation during isometric contractions at 33% and 100% of the MVC force. These findings could be essential for developing a regression equation that could estimate the level of muscle activation from changes in the muscle architecture.

Subject-specific knee joint geometry improves predictions of medial tibiofemoral contact forces

Estimating tibiofemoral joint contact forces is important for understanding the initiation and progression of knee osteoarthritis. However, tibiofemoral contact force predictions are influenced by many factors including muscle forces and anatomical representations of the knee joint. This study aimed to investigate the influence of subject-specific geometry and knee joint kinematics on the prediction of tibiofemoral contact forces using a calibrated EMG-driven neuromusculoskeletal model of the knee. One participant fitted with an instrumented total knee replacement walked at a self-selected speed while medial and lateral tibiofemoral contact forces, ground reaction forces, whole-body kinematics, and lower-limb muscle activity were simultaneously measured. The combination of generic and subject-specific knee joint geometry and kinematics resulted in four different OpenSim models used to estimate muscle-tendon lengths and moment arms. The subject-specific geometric model was created from CT scans and the subject-specific knee joint kinematics representing the translation of the tibia relative to the femur was obtained from fluoroscopy. The EMG-driven model was calibrated using one walking trial, but with three different cost functions that tracked the knee flexion/extension moments with and without constraint over the estimated joint contact forces. The calibrated models then predicted the medial and lateral tibiofemoral contact forces for five other different walking trials. The use of subject-specific models with minimization of the peak tibiofemoral contact forces improved the accuracy of medial contact forces by 47% and lateral contact forces by 7%, respectively compared with the use of generic musculoskeletal model.

Ultrasound-based subject-specific parameters improve fascicle behaviour estimation in Hill-type muscle model

The estimation of muscle fascicle behaviour is decisive in a Hill-type model as they are related to muscle force by the force-length-velocity relationship and the tendon force-strain relationship. This study was aimed at investigating the influence of subject-specific tendon force-strain relationship and initial fascicle geometry (IFG) on the estimation of muscle forces and fascicle behaviour during isometric contractions. Ultrasonography was used to estimate the in vivo muscle fascicle behaviour and compare the muscle fascicle length and pennation angle estimated from the Hill-type model. The calibration-prediction process of the electromyography-driven model was performed using generic or subject-specific tendon definition with or without IFG as constraint. The combination of subject-specific tendon definition and IFG led to muscle fascicle behaviour closer to ultrasound data and significant lower forces of the ankle dorsiflexor and plantarflexor muscles compared to the other conditions. Thus, subject-specific ultrasound measurements improve the accuracy of Hill-type models on muscle fascicle behaviour.

Subject-specific tendon-aponeurosis definition in Hill-type model predicts higher muscle forces in dynamic tasks

Neuromusculoskeletal models are a common method to estimate muscle forces. Developing accurate neuromusculoskeletal models is a challenging task due to the complexity of the system and large inter-subject variability. The estimation of muscles force is based on the mechanical properties of tendon-aponeurosis complex. Most neuromusculoskeletal models use a generic definition of the tendon-aponeurosis complex based on in vitro test, perhaps limiting their validity. Ultrasonography allows subject-specific estimates of the tendon-aponeurosis complex’s mechanical properties. The aim of this study was to investigate the influence of subject-specific mechanical properties of the tendon-aponeurosis complex on a neuromusculoskeletal model of the ankle joint. Seven subjects performed isometric contractions from which the tendon-aponeurosis force-strain relationship was estimated. Hopping and running tasks were performed and muscle forces were estimated using subject-specific tendon-aponeurosis and generic tendon properties. Two ultrasound probes positioned over the muscle-tendon junction and the mid-belly were combined with motion capture to estimate the in vivo tendon and aponeurosis strain of the medial head of gastrocnemius muscle. The tendon-aponeurosis force-strain relationship was scaled for the other ankle muscles based on tendon and aponeurosis length of each muscle measured by ultrasonography. The EMG-driven model was calibrated twice - using the generic tendon definition and a subject-specific tendon-aponeurosis force-strain definition. The use of subject-specific tendon-aponeurosis definition leads to a higher muscle force estimate for the soleus muscle and the plantar-flexor group, and to a better model prediction of the ankle joint moment compared to the model estimate which used a generic definition. Furthermore, the subject-specific tendon-aponeurosis definition leads to a decoupling behaviour between the muscle fibre and muscle-tendon unit in agreement with previous experiments using ultrasonography. These results indicate the use of subject-specific tendon-aponeurosis definitions in a neuromusculoskeletal model produce better agreement with measured external loads and more physiological model behaviour.

A novel objective function for predicting reasonable muscle forces in subject-specific model

Objective functions in adjusting model parameters have been widely used to minimize the variance of joint moments, but it may be insufficient to estimate reasonable muscle forces. The purpose of this study was to introduce a novel objective function based on a correlation coefficient for predicting reliable muscle forces, and compare its performance to the existing objective function. A man with right-sided hemiparesis after stroke participated in the study, and performed the maximum voluntary isometric contractions with a dynamometer at an angular velocity of 30°/s. To compare the effects of the existing and the new objective functions on prediction of muscle forces, the relative root-mean-square error and correlation coefficient were calculated for joint moments and individual muscle forces. The new objective function yielded promising results, implying that it could potentially be used to estimate reliable muscle forces. In the future, this approach will be applied to various movements to determine the reliability of muscle forces and to understand mechanisms from the reliable muscle forces.

Distribution of Forces Between Synergistics and Antagonistics Muscles Using an Optimization Criterion Depending on Muscle Contraction Behavior

In this paper, a new neuromusculoskeletal simulation strategy is proposed. It is based on a cascade control approach with an inner muscular-force control loop and an outer joint-position control loop. The originality of the work is located in the optimization criterion used to distribute forces between synergistic and antagonistic muscles. The cost function and the inequality constraints depend on an estimation of the muscle fiber length and its time derivative. The advantages of a such criterion are exposed by theoretical analysis and numerical tests. The simulation model used in the numerical tests consists in an anthropomorphic arm model composed by two joints and six muscles. Each muscle is modeled as a second-order dynamical system including activation and contraction dynamics. Contraction dynamics is represented using a classical Hill’s model.