DocumentCode :
406973
Title :
An anatomically based surface EMG model
Author :
Lowery, M.M. ; Stoykov, N.S. ; Kuiken, T.A.
Author_Institution :
Rehabilitation Inst. of Chicago, IL, USA
Volume :
3
fYear :
2003
fDate :
17-21 Sept. 2003
Firstpage :
2822
Abstract :
A model of the surface EMG signal based on a realistic arm anatomy is presented. A finite element volume conductor model was developed using magnetic resonance (MR) images of the upper arm of a healthy male subject. The model includes both resistive and capacitive material properties. To examine the ability of the model to predict the potential distribution around the surface of the arm, experimental and simulated data were compared during the application of a sub-threshold current source to the skin surface. The agreement between the simulated and experimental data varied with the choice of material properties used, with the closest approximation to the experimental data yielding a mean root mean square (RMS) error at the recording electrodes of 18% or 27%, depending on the site of the applied current source. To examine the influence of limb geometry on the EMG signal, action potentials from a curved muscle fiber in the realistic volume conductor model and an idealized cylindrical model were compared. The specific geometry of the limb caused substantial variations in the shapes of the surface potentials. However, more qualitative features of the surface EMG signal, such as the rate of decay of the surface action potential amplitude, were similar in both the realistic and idealized volume conductor models.
Keywords :
electromyography; finite element analysis; magnetic resonance imaging; measurement errors; physiological models; skin; action potentials; arm anatomy; curved muscle fiber; finite element model; limb geometry; magnetic resonance images; potential distribution; root mean square error; skin surface; sub-threshold current source; surface EMG model; volume conductor model; Anatomy; Conducting materials; Conductors; Electromyography; Finite element methods; Geometry; Magnetic resonance; Material properties; Predictive models; Solid modeling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2003. Proceedings of the 25th Annual International Conference of the IEEE
ISSN :
1094-687X
Print_ISBN :
0-7803-7789-3
Type :
conf
DOI :
10.1109/IEMBS.2003.1280505
Filename :
1280505
Link To Document :
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