Feasibility of Highly Constrained Muscle Force Predictions for the Knee During Gait

2011 ◽  
Author(s):  
Jonathan P. Walter ◽  
Darryl D. D’Lima ◽  
Thor F. Besier ◽  
Benjamin J. Fregly
Keyword(s):  
Cerebral Palsy ◽  
Muscle Force ◽  
Human Muscle ◽  
Accurate Assessment ◽  
Muscle Forces

Accurate assessment of human muscle forces during walking could significantly aid in the analysis and treatment of common neuromusculoskeletal disorders such as osteoarthritis [1], stroke, and cerebral palsy. However, the inability to measure muscle forces in vivo along with the inability to calculate muscle forces directly has greatly hindered achievement of this goal. Due to its complexity, the knee is a particularly difficult joint for assessing in vivo muscle forces.

ESTIMATION OF MUSCLE FORCE DERIVED FROM IN VIVO MR ELASTOGRAPHY TESTS: A PRELIMINARY STUDY

2013 ◽  
Vol 16 (03) ◽  
pp. 1350015 ◽  
Author(s):  
Sabine F. Bensamoun ◽  
Tien Tuan Dao ◽  
Fabrice Charleux ◽  
Marie-Christine Ho Ba Tho
Keyword(s):  
Magnetic Resonance ◽  
Muscle Force ◽  
Swing Phase ◽  
Human Motion ◽  
Magnetic Resonance Elastography ◽  
Muscle Disease ◽  
Muscle Forces ◽  
Rheological Models ◽  
Tensile Forces

The objective is to estimate the vastus medialis (VM) muscle force from multifrequency magnetic resonance elastography (MMRE) tests and two different rheological models (Voigt and springpot). Healthy participants (N = 13) underwent multifrequency (70, 90 and 110 Hz) magnetic resonance elastography MMRE tests. Thus, in vivo experimental elastic (μ) properties of the VM in passive and active (20% MVC) conditions were characterized. Moreover, the muscle viscosity (η) was determined with Voigt and springpot rheological models, in both muscle states. Subsequently, the VM muscle forces were calculated with a generic musculoskeletal model (OpenSIM) where the active and passive shear moduli (μ) were implemented. The viscosity measured with the two rheological models increased when the muscle is contracted. During the stance and the swing phases, the VM tensile forces decrease and the VM force was lower with the springpot model. It can be noted that during the swing phase, the muscle forces estimated from springpot model showed a higher standard deviation compared to the Voigt model. This last result may indicate a strong sensitivity of the muscle force to the change of active and passive contractile components in the swing phase of gait. This study provides for the first time an estimation of the muscle tensile forces for lower limb, during human motion, from in vivo experimental muscle mechanical properties. The assessment of individualized muscle forces during motion is valuable for finite element models, increasing the patient specific parameters. This novel muscle database will be of use for the clinician to better elucidate the muscle pathophysiology and to better monitor the effects of the muscle disease.

An Analytical Examination of Muscle Force Estimations Using Optimization Techniques

1993 ◽  
Vol 207 (3) ◽  
pp. 139-148 ◽  
Author(s):  
J H Challis ◽  
D G Kerwin
Keyword(s):  
Objective Function ◽  
Muscle Force ◽  
Human Movement ◽  
Optimization Techniques ◽  
Muscle Model ◽  
Muscle Forces ◽  
Objective Functions ◽  
Physiological Properties ◽  
Maximal Activation

Muscle forces are often estimated during human movement using optimization procedures. The optimization procedures involve the minimization of an objective function relating to the muscle forces. In this study 15 different objective functions were evaluated by examining the analytical solutions to the objective functions and by comparing their force predictions with the forces estimated using a validated muscle model. The muscle forces estimated by the objective functions were shown to give poor correspondence with the muscle model predicted muscle forces. The objective function estimates were criticized for not taking sufficient account of the physiological properties of the muscles. As a consequence of the analysis of the objective functions an alternative, simpler function was presented with which to estimate muscle forces in vivo. This function required that to satisfy a given joint moment, the force exerted by each of the muscles divided by the maximum force possible by the muscle was constant for all muscles. For this function the maximum muscle force was determined using a muscle model assuming maximal activation.

Direct Validation of Model-Predicted Muscle Forces in the Cat Hindlimb During Locomotion

2020 ◽  
Vol 142 (5) ◽  
Author(s):  
Derya Karabulut ◽  
Suzan Cansel Dogru ◽  
Yi-Chung Lin ◽  
Marcus G. Pandy ◽  
Walter Herzog ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Muscle Force ◽  
Medial Gastrocnemius ◽  
Electromyographic Activity ◽  
Muscle Forces ◽  
Static Optimization ◽  
Individual Muscle ◽  
Length Changes ◽  
Musculoskeletal Systems

Abstract Various methods are available for simulating the movement patterns of musculoskeletal systems and determining individual muscle forces, but the results obtained from these methods have not been rigorously validated against experiment. The aim of this study was to compare model predictions of muscle force derived for a cat hindlimb during locomotion against direct measurements of muscle force obtained in vivo. The cat hindlimb was represented as a 5-segment, 13-degrees-of-freedom (DOF), articulated linkage actuated by 25 Hill-type muscle-tendon units (MTUs). Individual muscle forces were determined by combining gait data with two widely used computational methods—static optimization and computed muscle control (CMC)—available in opensim, an open-source musculoskeletal modeling and simulation environment. The forces developed by the soleus, medial gastrocnemius (MG), and tibialis anterior muscles during free locomotion were measured using buckle transducers attached to the tendons. Muscle electromyographic activity and MTU length changes were also measured and compared against the corresponding data predicted by the model. Model-predicted muscle forces, activation levels, and MTU length changes were consistent with the corresponding quantities obtained from experiment. The calculated values of muscle force obtained from static optimization agreed more closely with experiment than those derived from CMC.

Length-force characteristics of in vivo human muscle reflected by supersonic shear imaging

2014 ◽  
Vol 117 (2) ◽  
pp. 153-162 ◽  
Author(s):  
Kazushige Sasaki ◽  
Sho Toyama ◽  
Naokata Ishii
Keyword(s):  
Shear Modulus ◽  
Tibialis Anterior ◽  
Muscle Force ◽  
Tibialis Anterior Muscle ◽  
Human Muscle ◽  
Joint Angles ◽  
Fascicle Length ◽  
Voluntary Contractions ◽  
Force Relationship

Recently, an ultrasound-based elastography technique has been used to measure stiffness (shear modulus) of an active human muscle along the axis of contraction. Using this technique, we explored 1) whether muscle shear modulus, like muscle force, is length dependent; and 2) whether the length dependence of muscle shear modulus is consistent between electrically elicited and voluntary contractions. From nine healthy participants, ankle joint torque and shear modulus of the tibialis anterior muscle were measured at five different ankle joint angles during tetanic contractions and during maximal voluntary contractions. Fascicle length, pennation angle, and tendon moment arm length of the tetanized tibialis anterior calculated from ultrasound images were used to reveal the length-dependent changes in muscle force and shear modulus. Over the range of joint angles examined, both force and shear modulus of the tetanized muscle increased with increasing fascicle length. Regression analysis of normalized data revealed a significant linear relationship between force and shear modulus ( R2 = 0.52, n = 45, P < 0.001). Although the length dependence of shear modulus was consistent, irrespective of contraction mode, the slope of length-shear modulus relationship was steeper during maximal voluntary contractions than during tetanic contractions. These results provide novel evidence that length-force relationship, one of the most fundamental characteristics of muscle, can be inferred from in vivo imaging of shear modulus in the tibialis anterior muscle. Furthermore, the estimation of length-force relationship may be applicable to voluntary contractions in which neural and mechanical interactions of multiple muscles are involved.

SENSITIVITY OF MODEL-PREDICTED MUSCLE FORCES OF PATIENTS WITH CEREBRAL PALSY TO VARIATIONS IN MUSCLE-TENDON PARAMETERS

2021 ◽  
Vol 21 (01) ◽  
pp. 2150008
Author(s):  
YUNUS ZIYA ARSLAN ◽  
DERYA KARABULUT
Keyword(s):  
Cerebral Palsy ◽  
Modeling And Simulation ◽  
Muscle Fiber ◽  
Fiber Length ◽  
Muscle Force ◽  
Musculoskeletal Modeling ◽  
Healthy Children ◽  
Muscle Forces ◽  
Healthy Individuals ◽  
Slack Length

Computational musculoskeletal modeling and simulation platforms are efficient tools to gain insight into the muscular coordination of patients with motor disabilities such as cerebral palsy (CP). Muscle force predictions from simulation programs are influenced by the architectural and contractile properties of muscle-tendon units. In this study, we aimed to evaluate the sensitivity of major lower limb muscle forces in patients with CP to changes in muscle-tendon parameters. Open-access datasets of children with CP ([Formula: see text]) and healthy children ([Formula: see text]) were considered. Monte Carlo analysis was executed to specify how sensitive the muscle forces to perturbations between [Formula: see text]% and [Formula: see text]% of the nominal value of the maximum isometric muscle force, optimal muscle fiber length, muscle pennation angle, tendon slack length, and maximum contraction velocity of muscle. The sensitivity analysis revealed that muscle forces of CP patients and healthy individuals were most sensitive to perturbations in the tendon slack length ([Formula: see text]), while forces of CP patients were more sensitive to tendon slack length when compared to the healthy group ([Formula: see text]). Muscle forces of patients and healthy individuals were insensitive to the other four parameters ([Formula: see text]), except for the gracilis and sartorius muscles in which the proportion of optimal muscle fiber length to tendon slack length is higher than 1; forces of these two muscles were also sensitive to the optimal muscle fiber length. The results of this study are expected to contribute to our understanding of which parameters should be personalized when conducting musculoskeletal modeling and simulation of patients with CP.

Knee Muscle Force Estimating Model Using Machine Learning Approach

2020 ◽  
Author(s):  
Anurag Sohane ◽  
Ravinder Agarwal
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Muscle Force ◽  
Vastus Lateralis ◽  
Input Parameter ◽  
Research Work ◽  
Cost Effective ◽  
Coefficient Of Determination ◽  
Muscle Forces ◽  
Knee Muscle

Abstract Various simulation type tools and conventional algorithms are being used to determine knee muscle forces of human during dynamic movement. These all may be good for clinical uses, but have some drawbacks, such as higher computational times, muscle redundancy and less cost-effective solution. Recently, there has been an interest to develop supervised learning-based prediction model for the computationally demanding process. The present research work is used to develop a cost-effective and efficient machine learning (ML) based models to predict knee muscle force for clinical interventions for the given input parameter like height, mass and angle. A dataset of 500 human musculoskeletal, have been trained and tested using four different ML models to predict knee muscle force. This dataset has obtained from anybody modeling software using AnyPyTools, where human musculoskeletal has been utilized to perform squatting movement during inverse dynamic analysis. The result based on the datasets predicts that the random forest ML model outperforms than the other selected models: neural network, generalized linear model, decision tree in terms of mean square error (MSE), coefficient of determination (R2), and Correlation (r). The MSE of predicted vs actual muscle forces obtained from the random forest model for Biceps Femoris, Rectus Femoris, Vastus Medialis, Vastus Lateralis are 19.92, 9.06, 5.97, 5.46, Correlation are 0.94, 0.92, 0.92, 0.94 and R2 are 0.88, 0.84, 0.84 and 0.89 for the test dataset, respectively.

AN ALGORITHM TO CALCULATE THE COMPONENTS OF ALL MUSCLE FORCES DURING EACH PHASES OF THE GAIT CYCLE, FOR THE PELVIC-FEMUR COMPLEX

2005 ◽  
Vol 05 (04) ◽  
pp. 539-548 ◽  
Author(s):  
SANTANU MAJUMDER ◽  
AMIT ROYCHOWDHURY ◽  
SUBRATA PAL
Keyword(s):  
Finite Element ◽  
Hip Joint ◽  
Computational Models ◽  
Gait Cycle ◽  
Muscle Force ◽  
Fe Analysis ◽  
Muscle Forces ◽  
Force Magnitude ◽  
Flexion Extension ◽  
Force Components

With the help of finite element (FE) computational models of femur, pelvis or hip joint to perform quasi-static stress analysis during the entire gait cycle, muscle force components (X, Y, Z) acting on the hip joint and pelvis are to be known. Most of the investigators have presented only the net muscle force magnitude during gait. However, for the FE software, either muscle force components (X, Y, Z) or three angles for the muscle line of action are required as input. No published algorithm (with flowchart) is readily available to calculate the required muscle force components for FE analysis. As the femur rotates about the hip center during gait, the lines of action for 27 muscle forces are also variable. To find out the variable lines of action and muscle force components (X, Y, Z) with directions, an algorithm was developed and presented here with detailed flowchart. We considered the varying angles of adduction/abduction, flexion/extension during gait. This computer program, obtainable from the first author, is able to calculate the muscle force components (X, Y, Z) as output, if the net magnitude of muscle force, hip joint orientations during gait and muscle origin and insertion coordinates are provided as input.

Regulation of glycogenolysis in human muscle at rest and during exercise

1982 ◽  
Vol 53 (3) ◽  
pp. 708-715 ◽  
Author(s):  
D. Chasiotis ◽  
K. Sahlin ◽  
E. Hultman
Keyword(s):  
Glycogen Phosphorylase ◽  
Total Activity ◽  
Human Muscle ◽  
Phosphorylase Activity ◽  
Michaelis Constant ◽  
Bicycle Exercise ◽  
Muscle Phosphorylase ◽  
Glycogen Utilization ◽  
Main Factors

The regulation of glycogenolysis in human muscle during isometric and dynamic exercise has been investigated. Total glycogen phosphorylase and synthase activities were unchanged during exercise. The fraction of phosphorylase in the alpha form at rest was estimated to be 20%, but the data indicate that the in vivo activity was low and critically dependent on the concentration of inorganic phosphate (Pi) in the muscle. Phosphorylase alpha increased initially 2.4-fold during isometric contraction and 1.6-fold during maximal bicycle exercise but reverted to or below the resting value at fatigue/exhaustion. At rest synthase I was 1713;48% of the total activity but decreased during exercise to about half of this value. The reciprocal changes in phosphorylase and synthase correlate with the enhanced rate of glycogenolysis during exercise. Michaelis constant (Km) for Pi was 27 mmol . l-1 for phosphorylase alpha and 7 mmol . l-1 for alpha + b. From consideration of the changes in Pi during exercise (to 20–30 mmol . l–1) it was concluded that Pi is one of the main factors determining phosphorylase activity and provides a link between phosphocreatine breakdown and glycogen utilization in muscle.

scholarly journals MM-MRE: a new technique to quantify individual muscle forces during isometric tasks of the wrist using MR elastography

2019 ◽  
Author(s):  
Andrea Zonnino ◽  
Daniel R. Smith ◽  
Peyton L. Delgorio ◽  
Curtis L. Johnson ◽  
Fabrizio Sergi
Keyword(s):  
Shear Wave ◽  
Muscle Force ◽  
Muscle Mechanics ◽  
Neuromuscular Control ◽  
Joint Torque ◽  
New Technique ◽  
Muscle Forces ◽  
Individual Muscle ◽  
Complete Set ◽  
A New Technique

AbstractNon-invasive in-vivo measurement of individual muscle force is limited by the infeasibility of placing force sensing elements in series with the musculo-tendon structures. At the same time, estimating muscle forces using EMG measurements is prone to inaccuracies, as EMG is not always measurable for the complete set of muscles acting around the joints of interest. While new methods based on shear wave elastography have been recently proposed to directly characterize muscle mechanics, they can only be used to measure muscle forces in a limited set of superficial muscles. As such, they are not suitable to study the neuromuscular control of movements that require coordinated action of multiple muscles.In this work, we present multi-muscle magnetic resonance elastography (MM-MRE), a new technique capable of quantifying individual muscle force from the complete set of muscles in the forearm, thus enabling the study of the neuromuscular control of wrist movements. MM-MRE integrates measurements of joint torque provided by an MRI-compatible instrumented handle with muscle-specific measurements of shear wave speed obtained via MRE to quantify individual muscle force using model-based estimator.A single-subject pilot experiment demonstrates the possibility of obtaining measurements from individual muscles and establishes that MM-MRE has sufficient sensitivity to detect changes in muscle mechanics following the application of isometric joint torque with self-selected intensity.

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