Multi-Channel simulation of long term surface EMG, with the consideration of both geometric parameters and tissue nonhomogeneity from muscle to skin

Simulation models are unavoidable in experimental research when the point is to develop new processing algorithms to be applied on real signals in order to extract specific parameter values or behaviors. Such algorithms have to be optimized generally by comparing true parameter values to those deduced from the algorithm. Only a simulation model can allow the user to access and control the actual process parameter values. This constraint is especially true when dealing with biomedical signals like surface electromyogram (SEMG) is taken into account.This work is an attempt to produce an efficient SEMG simulation model as a help for assessing algorithms related to SEMG features description (such as decomposition algorithm). It takes into account the most important parameters, which could influence these characteristics. Precise propagation and distribution of potential (influences of tissue structure by electrical network parameters in fiber model and nonhomogeneous - anisotropic medium (4 layer) in volume conductor model, Respectively) are considered as such parameters. The effects of electrode configuration, electrode size, inclination of the fiber with respect to the detection system and statistical parameters changes are also included in the model. Using this model we obtain a long term SEMG, which with an additive noise can be used for evaluating decomposition algorithms.