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A Quasi-Stationary Approach to the Approximate Solution of an FEA 3D Subject-Specific EMG Model

A structure based finite element analysis (FEA) model can be a means to gain better insight on how surface electromyography (EMG) signals are affected by limb geometry and tissue structures. Beyond that, and to optimize the control of myoelectric prostheses, such models can be used to evaluate signal separation algorithms, or to test the performance of different electrode configurations without the need to have several measurement sessions with a human subject present. This work presents a novel approach to the approximate modeling of a three-dimensional, subject-specific, generic EMG model by using FEA. The problems stemming from the nonrigid and irregular geometry of human body parts, the nonlinear tissue properties over frequency and temperature, the various muscle-fiber innervation possibilities, and the overall complexity of the model, are solved by defining an adequate fiber source description, simulating the volume conductor FEA model as being quasi-stationary, normalizing the true forearm geometry to a cylinder and unrolling it to be able to apply Helmholtz's principle of superposition to combine simulation results for the solving of more complex muscle-fiber set-ups. Thus, the source description presented herein appears suitable for application to different subject-specific geometries, as shown additionally by the setting into the 'Musculus pectoralis' of a targeted muscle reinnervation subject. Hence in conclusion, the strategy applied yields an overall reduced complexity of the FEA model, and therefore, substantially simplifies the processing and the visualization of the simulation results.