scholarly journals A multiple-layer finite-element model of the surface EMG signal

2002 ◽  
Vol 49 (5) ◽  
pp. 446-454 ◽  
Author(s):  
M.M. Lowery ◽  
N.S. Stoykov ◽  
A. Taflove ◽  
T.A. Kuiken
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Element Model ◽  
Surface Emg ◽  
Emg Signal ◽  
Multiple Layer ◽  
Surface Emg Signal

scholarly journals Predicting electromyographic signals under realistic conditions using a multiscale chemo–electro–mechanical finite element model

2015 ◽  
Vol 5 (2) ◽  
pp. 20140076 ◽  
Author(s):  
Mylena Mordhorst ◽  
Thomas Heidlauf ◽  
Oliver Röhrle
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Motor Neurons ◽  
Tibialis Anterior Muscle ◽  
Element Model ◽  
Surface Emg ◽  
Muscle Fibres ◽  
Emg Signal ◽  
Motor Unit Discharge ◽  
Human Tibialis Anterior Muscle

This paper presents a novel multiscale finite element-based framework for modelling electromyographic (EMG) signals. The framework combines (i) a biophysical description of the excitation–contraction coupling at the half-sarcomere level, (ii) a model of the action potential (AP) propagation along muscle fibres, (iii) a continuum-mechanical formulation of force generation and deformation of the muscle, and (iv) a model for predicting the intramuscular and surface EMG. Owing to the biophysical description of the half-sarcomere, the model inherently accounts for physiological properties of skeletal muscle. To demonstrate this, the influence of membrane fatigue on the EMG signal during sustained contractions is investigated. During a stimulation period of 500 ms at 100 Hz, the predicted EMG amplitude decreases by 40% and the AP propagation velocity decreases by 15%. Further, the model can take into account contraction-induced deformations of the muscle. This is demonstrated by simulating fixed-length contractions of an idealized geometry and a model of the human tibialis anterior muscle (TA). The model of the TA furthermore demonstrates that the proposed finite element model is capable of simulating realistic geometries, complex fibre architectures, and can include different types of heterogeneities. In addition, the TA model accounts for a distributed innervation zone, different fibre types and appeals to motor unit discharge times that are based on a biophysical description of the α motor neurons.

A Finite Element Model of Skin Subjected to a Flash Fire

1994 ◽  
Vol 116 (3) ◽  
pp. 250-255 ◽  
Author(s):  
D. A. Torvi ◽  
J. D. Dale
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Closed Form Solution ◽  
Blood Perfusion ◽  
Element Model ◽  
Form Solution ◽  
Bioheat Transfer ◽  
Multiple Layer ◽  
Degree Burn ◽  
Flash Fire

A variable property, multiple layer finite element model was developed to predict skin temperatures and times to second and third degree burns under simulated flash fire conditions. A sensitivity study of burn predictions to variations in thermal physical properties of skin was undertaken using this model. It was found that variations in these properties over the ranges used in multiple layer skin models had minimal effects on second degree burn predictions, but large effects on third degree burn predictions. It was also found that the blood perfusion source term in Pennes’ bioheat transfer equation could be neglected in predicting second and third degree burns due to flash fires. The predictions from this model were also compared with those from the closed form solution of this equation, which has been used in the literature for making burn predictions from accidents similar to flash fires.

A Finite Element Model for Describing the Effect of Muscle Shortening on Surface EMG

2006 ◽  
Vol 53 (4) ◽  
pp. 593-600 ◽  
Author(s):  
L. Mesin ◽  
M. Joubert ◽  
T. Hanekom ◽  
R. Merletti ◽  
D. Farina
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Element Model ◽  
Surface Emg ◽  
Muscle Shortening
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