Estimation of Muscle Forces About the Ankle During Gait in Healthy and Neurologically Impaired Subjects

2011 ◽  
pp. 320-347
Author(s):  
Daniel N. Bassett ◽  
Joseph D. Gardinier ◽  
Kurt T. Manal ◽  
Thomas S. Buchanan
Keyword(s):  
Muscle Activation ◽  
Inverse Dynamics ◽  
Biomechanical Model ◽  
Forward Dynamics ◽  
Muscle Forces ◽  
Dynamics Model ◽  
Joint Moments ◽  
Neurologically Impaired ◽  
Model Predictions ◽  
Contraction Dynamics

This chapter describes a biomechanical model of the forces about the ankle joint applicable to both unimpaired and neurologically impaired subjects. EMGs and joint kinematics are used as inputs and muscle forces are the outputs. A hybrid modeling approach that uses both forward and inverse dynamics is employed and physiological parameters for the model are tuned for each subject using optimization procedures. The forward dynamics part of the model takes muscle activation and uses Hill-type models of muscle contraction dynamics to estimate muscle forces and the corresponding joint moments. Inverse dynamics is used to calibrate the forward dynamics model predictions of joint moments. In this chapter we will describe how to implement an EMG-driven hybrid forward and inverse dynamics model of the ankle that can be used in healthy and neurologically impaired people.

scholarly journals Estimation of Muscle Forces and Joint Moments Using a Forward-Inverse Dynamics Model

2005 ◽  
Vol 37 (11) ◽  
pp. 1911-1916 ◽  
Author(s):  
THOMAS S. BUCHANAN ◽  
DAVID G. LLOYD ◽  
KURT MANAL ◽  
THOR F. BESIER
Keyword(s):  
Inverse Dynamics ◽  
Muscle Forces ◽  
Dynamics Model ◽  
Joint Moments

scholarly journals Inverse and forward dynamics: models of multi–body systems

2003 ◽  
Vol 358 (1437) ◽  
pp. 1493-1500 ◽  
Author(s):  
E. Otten
Keyword(s):  
Inverse Dynamics ◽  
Temporal Patterns ◽  
Forward Dynamics ◽  
Muscle Forces ◽  
Complex Behaviour ◽  
Joint Torques ◽  
Advantages And Disadvantages ◽  
Reaction Forces ◽  
Internal Forces ◽  
Multi Body

Connected multi–body systems exhibit notoriously complex behaviour when driven by external and internal forces and torques. The problem of reconstructing the internal forces and/or torques from the movements and known external forces is called the ‘inverse dynamics problem’, whereas calculating motion from known internal forces and/or torques and resulting reaction forces is called the ‘forward dynamics problem’. When stepping forward to cross the street, people use muscle forces that generate angular accelerations of their body segments and, by virtue of reaction forces from the street, a forward acceleration of the centre of mass of their body. Inverse dynamics calculations applied to a set of motion data from such an event can teach us how temporal patterns of joint torques were responsible for the observed motion. In forward dynamics calculations we may attempt to create motion from such temporal patterns, which is extremely difficult, because of the complex mechanical linkage along the chains forming the multi–body system. To understand, predict and sometimes control multi–body systems, we may want to have mathematical expressions for them. The Newton–Euler, Lagrangian and Featherstone approaches have their advantages and disadvantages. The simulation of collisions and the inclusion of muscle forces or other internal forces are discussed. Also, the possibility to perform a mixed inverse and forward dynamics calculation are dealt with. The use and limitations of these approaches form the conclusion.

scholarly journals Neuromusculoskeletal Modeling: Estimation of Muscle Forces and Joint Moments and Movements from Measurements of Neural Command

2004 ◽  
Vol 20 (4) ◽  
pp. 367-395 ◽  
Author(s):  
Thomas S. Buchanan ◽  
David G. Lloyd ◽  
Kurt Manal ◽  
Thor F. Besier
Keyword(s):  
Muscle Activation ◽  
Equations Of Motion ◽  
Muscle Forces ◽  
Joint Moments ◽  
Neural Signals ◽  
Knee Kinetics ◽  
Time Varying Parameter ◽  
Activation Dynamics ◽  
Muscle Activations ◽  
Neuromusculoskeletal Modeling

This paper provides an overview of forward dynamic neuromusculoskeletal modeling. The aim of such models is to estimate or predict muscle forces, joint moments, and/or joint kinematics from neural signals. This is a four-step process. In the first step,muscle activation dynamicsgovern the transformation from the neural signal to a measure of muscle activation—a time varying parameter between 0 and 1. In the second step,muscle contraction dynamicscharacterize how muscle activations are transformed into muscle forces. The third step requires a model of themusculoskeletal geometryto transform muscle forces to joint moments. Finally, theequations of motionallow joint moments to be transformed into joint movements. Each step involves complex nonlinear relationships. The focus of this paper is on the details involved in the first two steps, since these are the most challenging to the biomechanician. The global process is then explained through applications to the study of predicting isometric elbow moments and dynamic knee kinetics.

EMG-Assisted Neuromusculoskeletal Models Can Estimate Physiological Muscle Activations and Joint Moments Across the Neck Before Impacts

2021 ◽  
Author(s):  
Pavlos Silvestros ◽  
Claudio Pizzolato ◽  
David G. Lloyd ◽  
Ezio Preatoni ◽  
Harinderjit S. Gill ◽  
...  
Keyword(s):  
Cervical Spine ◽  
Muscle Activation ◽  
Inverse Dynamics ◽  
A Priori ◽  
Neck Muscle ◽  
Joint Moments ◽  
Activation Patterns ◽  
Muscle Activation Patterns ◽  
Flexion Extension ◽  
Muscle Activations

Abstract Knowledge of neck muscle activation strategies prior to sporting impacts is crucial for investigating mechanisms of severe spinal injuries. However, measurement of muscle activations during impacts is experimentally challenging and computational estimations are not often guided by experimental measurements. We investigated neck muscle activations prior to impacts with the use of electromyography (EMG)-assisted neuromusculoskeletal models. Kinematics and EMG recordings from four major neck muscles of a rugby player were experimentally measured during rugby activities. A subject-specific musculoskeletal model was created with muscle parameters informed from MRI measurements. The model was used in the Calibrated EMG-Informed Neuromusculoskeletal Modelling toolbox and three neural solutions were compared: i) static optimisation (SO), ii) EMG-assisted (EMGa) and iii) MRI-informed EMG-assisted (EMGaMRI). EMGaMRI and EMGa significantly (p¡0.01) outperformed SO when tracking cervical spine net joint moments from inverse dynamics in flexion/extension (RMSE = 0.95, 1.14 and 2.32 Nm) but not in lateral bending (RMSE = 1.07, 2.07 and 0.84 Nm). EMG-assisted solutions generated physiological muscle activation patterns and maintained experimental co-contractions significantly (p¡0.01) outperforming SO, which was characterised by saturation and non-physiological "on-off" patterns. This study showed for the first time that physiological neck muscle activations and cervical spine net joint moments can be estimated without assumed a priori objective criteria prior to impacts. Future studies could use this technique to provide detailed initial loading conditions for theoretical simulations of neck injury during impacts.

ESTIMATING MUSCLE FORCES AND KNEE JOINT TORQUE USING SURFACE ELECTROMYOGRAPHY: A MUSCULOSKELETAL BIOMECHANICAL MODEL

2017 ◽  
Vol 17 (04) ◽  
pp. 1750069 ◽  
Author(s):  
JIANGCHENG CHEN ◽  
XIAODONG ZHANG ◽  
LINXIA GU ◽  
CARL NELSON
Keyword(s):  
Knee Joint ◽  
Surface Electromyography ◽  
Neural Control ◽  
Muscle Activation ◽  
Muscle Force ◽  
Dynamic Properties ◽  
Biomechanical Model ◽  
Joint Torque ◽  
Muscle Forces ◽  
Flexion Extension

Surface electromyography (sEMG) is a useful tool for revealing the underlying musculoskeletal dynamic properties in the human body movement. In this paper, a musculoskeletal biomechanical model which relates the sEMG and knee joint torque is proposed. First, the dynamic model relating sEMG to skeletal muscle activation considering frequency and amplitude is built. Second, a muscle contraction model based on sliding-filament theory is developed to reflect the physiological structure and micro mechanical properties of the muscle. The muscle force and displacement vectors are determined and the transformation from muscle force to knee joint moment is realized, and finally a genetic algorithm-based calibration method for the Newton–Euler dynamics and overall musculoskeletal biomechanical model is put forward. Following the model calibration, the flexion/extension (FE) knee joint torque of eight subjects under different walking speeds was predicted. Results show that the forward biomechanical model can capture the general shape and timing of the joint torque, with normalized mean residual error (NMRE) of [Formula: see text]10.01%, normalized root mean square error (NRMSE) of [Formula: see text]12.39% and cross-correlation coefficient of [Formula: see text]0.926. The musculoskeletal biomechanical model proposed and validated in this work could facilitate the study of neural control and how muscle forces generate and contribute to the knee joint torque during human movement.

Using Hill-Type Muscle Models and EMG Data in a Forward Dynamic Analysis of Joint Moment

2003 ◽  
Vol 03 (02) ◽  
pp. 169-186 ◽  
Author(s):  
Richard Heine ◽  
Kurt Manal ◽  
Thomas S. Buchanan
Keyword(s):  
Muscle Activation ◽  
Joint Moment ◽  
Model Parameters ◽  
Time Varying ◽  
Muscle Forces ◽  
Joint Moments ◽  
Delay Term ◽  
Activation Dynamics ◽  
Moment Models ◽  
Muscle Models

There has been considerable interest in estimating muscle forces and joint moments from EMG signals, but most approaches have not been very successful. This is largely because robust models of muscle activation dynamics, Hill-type muscle contraction dynamics, and musculoskeletal geometry are generally not included. Here we present a model which includes these sub-models and we determine which model parameters are most important. The models abilities to predict joint moments about the human elbow during time-varying isometric tasks were examined. Inputs to the models were EMGs from eight muscles. Joint moment was the output, which was compared with the measured moment. Models varied in complexity, having up to 59 adjustable parameters. It was found that a seven adjustable parameter model could adequately estimate time-varying joint moments without substantial sacrifice in performance. The key parameters that were fit for each subject were two global gain factors, a time delay term, a non-linear EMG-force term, two muscle activation terms, and a term for skewing the length-tension curve with muscle activation. This approach offers advantages over optimization-based methods for estimating individual muscle forces. Most importantly, it accounts for the way muscles are activated, which makes it potentially powerful to evaluate patients with pathologies.

Bioaeroservoelastic Analysis of Involuntary Rotorcraft-Pilot Interaction

2014 ◽  
Vol 9 (3) ◽  
Author(s):  
Pierangelo Masarati ◽  
Giuseppe Quaranta
Keyword(s):  
Muscle Activation ◽  
Inverse Dynamics ◽  
Transfer Functions ◽  
Biomechanical Model ◽  
Coupled System ◽  
Multibody Modeling ◽  
Activation Patterns ◽  
Pilot Model ◽  
The Stability ◽  
Muscular Activation

This work presents the integration of a detailed biomechanical model of the arm of a helicopter pilot and an equivalently detailed aeroservoelastic model of a helicopter, resulting in what has been called a ‘bioaeroservoelastic’ analysis. The purpose of this analysis is to investigate potential adverse interactions, called rotorcraft-pilot couplings, between the aeroservoelastic system and the controls involuntarily introduced by the pilot into the control system in response to rotorcraft vibrations transmitted to the pilot through the cockpit: the so-called biodynamic feedthrough. The force exerted by the pilot on the controls results from the activation of the muscles of the arms according to specific patterns. The reference muscular activation value as a function of the prescribed action on the controls is computed using an inverse kinetostatics/inverse dynamics approach. A first-order quasi-steady correction is adopted to mimic the reflexive contribution to muscle activation. Muscular activation is further augmented by activation patterns that produce elementary actions on the control inceptors. These muscular activation patterns, inferred using perturbation analysis, are applied to control the aircraft through the pilot's limbs. The resulting biomechanical pilot model is applied to the aeroservoelastic analysis of a helicopter model expressly developed within the same multibody modeling environment to investigate adverse rotorcraft pilot couplings. The model consists of the detailed aeroelastic model of the main rotor, using nonlinear beams and blade element/momentum theory aerodynamics, a component mode synthesis model of the airframe structural dynamics, and servoactuator dynamics. Results in terms of the stability analysis of the coupled system are presented in comparison with analogous results obtained using biodynamic feedthrough transfer functions identified from experimental data.

scholarly journals Review of Modelling Techniques forIn VivoMuscle Force Estimation in the Lower Extremities during Strength Training

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Florian Schellenberg ◽  
Katja Oberhofer ◽  
William R. Taylor ◽  
Silvio Lorenzetti
Keyword(s):  
Strength Training ◽  
Exercise Performance ◽  
Inverse Dynamics ◽  
Alternative Methods ◽  
Computational Techniques ◽  
Forward Dynamics ◽  
Muscle Forces ◽  
Advantages And Disadvantages ◽  
Strength Exercises

Background. Knowledge of the musculoskeletal loading conditions during strength training is essential for performance monitoring, injury prevention, rehabilitation, and training design. However, measuring muscle forces during exercise performance as a primary determinant of training efficacy and safety has remained challenging.Methods. In this paper we review existing computational techniques to determine muscle forces in the lower limbs during strength exercisesin vivoand discuss their potential for uptake into sports training and rehabilitation.Results. Muscle forces during exercise performance have almost exclusively been analysed using so-called forward dynamics simulations, inverse dynamics techniques, or alternative methods. Musculoskeletal models based on forward dynamics analyses have led to considerable new insights into muscular coordination, strength, and power during dynamic ballistic movement activities, resulting in, for example, improved techniques for optimal performance of the squat jump, while quasi-static inverse dynamics optimisation and EMG-driven modelling have helped to provide an understanding of low-speed exercises.Conclusion. The present review introduces the different computational techniques and outlines their advantages and disadvantages for the informed usage by nonexperts. With sufficient validation and widespread application, muscle force calculations during strength exercisesin vivoare expected to provide biomechanically based evidence for clinicians and therapists to evaluate and improve training guidelines.

Coupled Bioaeroservoelastic Rotorcraft-Pilot Simulation

2013 ◽  
Author(s):  
Pierangelo Masarati ◽  
Giuseppe Quaranta
Keyword(s):  
Muscle Activation ◽  
Inverse Dynamics ◽  
Transfer Functions ◽  
Biomechanical Model ◽  
Coupled System ◽  
Multibody Modeling ◽  
Activation Patterns ◽  
Pilot Model ◽  
Aeroelastic Model ◽  
Muscular Activation

This work presents the integration of a detailed biomechanical model of the arms of a helicopter pilot and an equivalently detailed aeroservoelastic model of a helicopter, resulting in what has been called a ‘bioaeroservoelastic’ analysis. The purpose is to investigate potential adverse interactions, called rotorcraft-pilot couplings, between the aeroservoelastic system and the controls involuntarily introduced by the pilot into the control system in response to rotorcraft vibrations transmitted to the pilot through the cockpit, the so-called biodynamic feedthrough. The force exerted by the pilot on the controls results from the activation of the muscles of the arms according to specific patterns. The reference muscular activation value as a function of the prescribed action on the controls is computed using an inverse kinetostatics/inverse dynamics approach. A first-order quasi-steady correction is adopted to mimic the reflexive contribution to muscle activation. Muscular activation is further augmented by activation patterns that produce elementary actions on the control inceptors. These muscular activation patterns, inferred using perturbation analysis, are applied to control the aircraft through the pilot’s limbs. The resulting biomechanical pilot model is applied to the aeroservoelastic analysis of a helicopter model expressly developed within the same multibody modeling environment to investigate adverse rotorcraft pilot couplings. The model consists of the detailed aeroelastic model of the main rotor, using nonlinear beams and blade element/momentum theory aerodynamics, a component mode synthesis model of the airframe structural dynamics, and servoactuator dynamics. Results in terms of stability analysis of the coupled system are presented in comparison with analogous results obtained using biodynamic feedthrough transfer functions identified from experimental data.

scholarly journals A Simulation of the Effects of Badminton Serve Release Height

2021 ◽  
Vol 11 (7) ◽  
pp. 2903
Author(s):  
John Rasmussen ◽  
Mark de Zee
Keyword(s):  
Experimental Data ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
World Federation ◽  
Forward Dynamics ◽  
Dynamics Model ◽  
Rib Cage ◽  
Female Player ◽  
Ballistic Trajectory ◽  
Release Height

In this work, we develop and calibrate a model to represent the trajectory of a badminton shuttlecock and use it to investigate the influence of serve height in view of a new serve rule instated by the Badminton World Federation. The new rule means that all players must launch the shuttlecock below a height of 1.15 m, as opposed to the old rule whereby the required launch height was under the rib cage of the server. The model is based on a forward dynamics model of ballistic trajectory with drag, and it is calibrated with experimental data. The experiments also served to determine the actual influence of the new rule on the shuttlecock launch position. The model is used in a Monte Carlo simulation to determine the statistical influence of the new serve rules on the player’s ability to perform good serves; i.e., serves with little opportunity for the receiver to attack. We conclude that, for the female player in question, serving below a height of 1.15 m makes it marginally more difficult to perform excellent serves. We also conclude that there might be alternative launch positions that would be less likely to produce the best serves but could be exploited as a tactical option.

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