Prediction of internal electric current distribution from surface application in atrophied muscle tissue.
The use of surface electrical stimulation therapy for clinical rehabilitation has created the need for an improved modeling method to predict internal current density. A method was developed to model quantitatively the current density delivered to an atrophied muscle. Some stimulation protocols do not produce measurable physiological effects, such as muscle contraction. Therefore, traditional response-based current density modeling cannot be used. Additionally, lumped circuit models do not provide the resolution needed to optimize electrode size, shape, and placement. The quantitative approach developed here can be used to optimize electrical stimulation protocols in abnormal muscle tissue. In this study, the finite element method (FEM) is used to model the low intensity electric current stimulation resulting from surface application. FEM provides the ability to model complex tissue properties found in living tissue. A leg of lamb was modeled because its size and level of tissue complexity is similar to that of a human child's thigh. Voltage gradient measurements were made upon a sacrificed leg of lamb during the application of bipolar stimulation. These measurements were made at numerous points in the stimulated leg of lamb and allowed the mapping of the current density. The leg of lamb was then sliced and photographed to be able to create the finite element model. The empirical data compared favorably to the results of the FEM model, thus verifying the method. This FEM model was then modified to study the effects of muscle atrophy on electric current densities. This modeling method will ultimately lead to improved stimulation protocols and better clinical treatment.
Waugaman
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Department of Electrical Engineering, US Air Force Academy, CO 80840, USA.
D000818:Animals; D003198:Computer Simulation; D004599:Electric Stimulation Therapy; D004566:Electrodes; D004594:Electrophysiology; D020342:Finite Element Analysis; D008954:Models, Biological; D018482:Muscle, Skeletal / Q000503:physiopathology*; D009133:Muscular Atrophy / Q000503:physiopathology / Q000534:rehabilitation*; D009716:Numerical Analysis, Computer-Assisted; D012756:Sheep