Prediction and Verification of Internal Electric Current Distribution in Muscle From Surface Application
Abstract
The use of surface electrical stimulation therapy for clinical rehabilitation has created the need for an improved modeling method to predict internal current density. 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. In this study, a method was developed to model quantitatively the current density delivered to the target muscle and it can also be used to optimize electrical stimulation protocols. The finite element method (FEM) was used to model the internal electric current density in muscle resulting from surface application because the FEM provides the ability to model complex properties found in living tissue. To test the FEM programming method used in this research, electric current was passed through a cylinder of normal saline. Current density was measured and recorded. A replica of the saline cylinder was then modeled using the FEM. The results of the FEM model matched both the laboratory measurements and a previously published analytical solution for bipolar stimulation of a saline cylinder. With the verification of the programming methodology complete, two additional FEM cylindrical models were created to test the ability to model the non-linearities, anisotropisms, and inhomogeneities found in biological tissue. The next step was to move from modeling the simple cylindrical geometry to the geometry found in a hind leg of a lamb. This leg of lamb was modeled because its size and level of tissue complexity is similar to that of a human thigh. Internal muscle voltage gradient measurements were made upon a sacrificed leg of lamb during the application of bipolar stimulation. These measurements allowed for the mapping of muscle current density.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 26, 1999
- Accession Number
- ADA366398
Entities
People
- William A. Waugaman
Organizations
- Air Force Institute of Technology