A novel approach for precise simulation of the EMG signal detected by surface electrodes (original) (raw)
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IEEE Transactions on Biomedical Engineering, 2006
This study analytically describes surface electromyogram (sEMG) signals generated by a model of a triangular muscle, i.e., a muscle with fibres arranged in a fan shape. Examples of triangular muscles in the human body are the deltoid, the pectoralis major, the trapezius, the adductor pollicis. A model of triangular muscle is proposed. It is a sector of a cylindrical volume conductor (with the fibres directed along the radial coordinate) bounded at the muscle/fat interface. The muscle conductivity tensor reflects the fan anisotropy. Edge effects have been neglected. A solution of the non space invariant problem for a triangular muscle is provided in the Fourier domain. An approximate analytical solution for a two plane layer volume conductor model is obtained by introducing a homogeneous layer (modelling the fat) over the triangular muscle. The results are implemented in a complete sEMG generation model (including the finite length of the fibres), simulating single fibre action potentials. The model is not space invariant due to the changes of the volume conductor along the direction of action potential propagation. Thus the detected potentials at the skin surface change shape as they propagate. This determines problems in the extraction and interpretation of parameters. As a representative example of application of the simulation model, the influence of the inhomogeneity of the volume conductor in CV estimation is addressed (for two channels; maximum likelihood and reference point methods). Different fibre depths, electrode placements and small misalignments of the detection system with respect to the fibre have been simulated. The error in CV estimation is large when the depth of the fibre increases, when the detection system is not aligned with the fibre and close to the innervation point and to the tendons.
Medical & Biological Engineering & Computing, 2004
Surface electromyographic (EMG) signal modelling is important for signal interpretation, testing of processing algorithms, detection system design and didactic purposes. Various surface EMG signal models have been proposed in the literature. This study focuses on the proposal of a method for modelling surface EMG signals, using either analytical or numerical descriptions of the volume conductor for space-conductor by numerical approaches, accurately describing the volume conductor geometry and the conductivity, as mainly done in the past, but also the conductivity tensor of the muscle tissue. For volume conductors that are space-invariant in the direction of source propagation, the surface potentials generated by any source can be computed by one-dimensional convolutions, once the volume conductor transfer function has been derived (analytically or numerically). Conversely, more complex volume conductors require a complete numerical approach. In a numerical approach, the conductivity tensor of the muscle tissue should be matched with the fibre orientation. In some cases (e.g. multi-pinnate muscles), accurate description of the conductivity tensor can be very complex. A method for relating the conductivity tensor of the muscle tissue, to be used in a numerical approach, to the curve describing the muscle fibres is presented and applied to investigate representatively a bi-pinnate muscle with rectilinear and curvilinear fibres. The study thus proposes an approach for surface EMG signal simulation in space invariant systems, as well as new models of the volume conductor using numerical methods.
IEEE Transactions on Biomedical Engineering, 2004
Surface EMG signal modeling has important applications in the interpretation of experimental EMG data. Most models of surface EMG generation considered volume conductors homogeneous in the direction of propagation of the action potentials. However, this may not be the case in practice due to local tissue in-homogeneities or to the fact that there may be groups of muscle fibers with different orientations. This study addresses the issue of analytically describing surface EMG signals generated by bi-pinnate muscles, i.e., muscles which have two groups of fibers with two orientations. The approach will also be adapted to the case of a muscle with fibers inclined in the depth direction. Such muscle anatomies are in-homogeneous in the direction of propagation of the action potentials with the consequence that the system can not be described as space invariant in the direction of source propagation. In these conditions, the potentials detected at the skin surface do not travel without shape changes. This determines numerical issues in the implementation of the model which are addressed in this work. The study provides the solution of the non-homogenous, anisotropic problem, proposes an implementation of the results in complete surface EMG generation models (including finite length fibers), and shows representative results of the application of the models proposed.
Volume Conduction in an Anatomically Based Surface EMG Model
IEEE Transactions on Biomedical Engineering, 2004
A finite-element model to simulate surface electromyography (EMG) in a realistic human upper arm is presented. The model is used to explore the effect of limb geometry on surface-detected muscle fiber action potentials. The model was based on magnetic resonance images of the subject's upper arm and includes both resistive and capacitive material properties. To validate the model geometry, experimental and simulated potentials were compared at different electrode sites during the application of a subthreshold sinusoidal current source to the skin surface. Of the material properties examined, the closest approximation to the experimental data yielded a mean root-mean-square (rms) error of the normalized surface potential of 18% or 27%, depending on the site of the applied source. Surface-detected action potentials simulated using the realistic volume conductor model and an idealized cylindrical model based on the same limb geometry were then compared. Variation in the simulated limb geometry had a considerable effect on action potential shape. However, the rate of decay of the action potential amplitude with increasing distance from the fiber was similar in both models. Inclusion of capacitive material properties resulted in temporal low-pass filtering of the surface action potentials. This effect was most pronounced in the end-effect components of action potentials detected at locations far from the active fiber. It is concluded that accurate modeling of the limb geometry, asymmetry, tissue capacitance and fiber curvature is important when the specific action potential shapes are of interest. However, if the objective is to examine more qualitative features of the surface EMG signal, then an idealized volume conductor model with appropriate tissue thicknesses provides a close approximation.
Influence of anatomical, physical, and detection-system parameters on surface EMG
2002
Many previous studies were focused on the influence of anatomical, physical, and detection-system parameters on recorded surface EMG signals. Most of them were conducted by simulations. Previous EMG models have been limited by simplifications which did not allow simulation of several aspects of the EMG generation and detection systems. We recently proposed a model for fast and accurate simulation of the surface EMG. It characterizes the volume conductor as a nonhomogeneous and anisotropic medium, and allows simulation of EMG signals generated by finite-length fibers without approximation of the current-density source. The influence of thickness of the subcutaneous tissue layers, fiber inclination, fiber depth, electrode size and shape, spatial filter transfer function, interelectrode distance, length of the fibers on surface, single-fiber action-potential amplitude, frequency content, and estimated conduction velocity are investigated in this paper. Implications of the results on electrode positioning procedures, spatial filter design, and EMG signal interpretation are discussed.
A surface EMG generation model with multilayer cylindrical description of the volume conductor
IEEE Transactions on Biomedical Engineering, 2004
We propose a model for surface EMG signal generation with cylindrical description of the volume conductor. The model is more general and complete with respect to previous approaches. The volume conductor is described as a multi-layered cylinder in which the source can be located either along the longitudinal or the angular direction, in any of the layers. The source is represented as a spatio-temporal function which describes the generation, propagation, and extinction of the intracellular action potential at the end-plate, along the fiber, and at the tendons, respectively. The layers are anisotropic. The volume conductor effect is described as a two dimensional spatial filtering. Electrodes of any shape or dimension are simulated, forming structures which are described as spatial filters. The analytical derivation which leads to the signal in the temporal domain is performed in the spatial and temporal frequency domains. Numerical issues related to the frequency-based approach are discussed. The descriptions of the volume conductor and of the source are applied to the cases of signal generation from a limb and a sphincter muscle. Representative simulations of both cases are provided. The resultant model is based on analytical derivations and constitutes a step forward in surface EMG signal modeling, including features not described in any other analytical approach.
IEEE Transactions on Biomedical Engineering, 2008
This study analytically describes surface electromyogram (sEMG) signals generated by a model of a triangular muscle, i.e., a muscle with fibres arranged in a fan shape. Examples of triangular muscles in the human body are the deltoid, the pectoralis major, the trapezius, the adductor pollicis. A model of triangular muscle is proposed. It is a sector of a cylindrical volume conductor (with the fibres directed along the radial coordinate) bounded at the muscle/fat interface. The muscle conductivity tensor reflects the fan anisotropy. Edge effects have been neglected. A solution of the non space invariant problem for a triangular muscle is provided in the Fourier domain. An approximate analytical solution for a two plane layer volume conductor model is obtained by introducing a homogeneous layer (modelling the fat) over the triangular muscle. The results are implemented in a complete sEMG generation model (including the finite length of the fibres), simulating single fibre action potentials. The model is not space invariant due to the changes of the volume conductor along the direction of action potential propagation. Thus the detected potentials at the skin surface change shape as they propagate. This determines problems in the extraction and interpretation of parameters. As a representative example of application of the simulation model, the influence of the inhomogeneity of the volume conductor in CV estimation is addressed (for two channels; maximum likelihood and reference point methods). Different fibre depths, electrode placements and small misalignments of the detection system with respect to the fibre have been simulated. The error in CV estimation is large when the depth of the fibre increases, when the detection system is not aligned with the fibre and close to the innervation point and to the tendons.
IEEE Transactions on Biomedical Engineering, 2003
We describe a new method for the estimation of muscle fiber conduction velocity (CV) from surface electromyography (EMG) signals. The method is based on the detection of two surface EMG signals with different spatial filters and on the compensation of the spatial filtering operations by two temporal filters (with CV as unknown parameter) applied to the signals. The transfer functions of the two spatial filters may have different magnitudes and phases, thus the detected signals have not necessarily the same shape. The two signals are first spatially and then temporally filtered and are ideally equal when the CV value selected as a parameter in the temporal filters corresponds to the velocity of propagation of the detected action potentials. This approach is the generalization of the classic spectral matching technique. A theoretical derivation of the method is provided together with its fast implementation by an iterative method based on the Newton's method. Moreover, the lowest CV estimate among those obtained by a number of filter pairs is selected to reduce the CV bias due to nonpropagating signal components. Simulation results indicate that the method described is less sensitive than the classic spectral matching approach to the presence of nonpropagating signals and that the two methods have similar standard deviation of estimation in the presence of additive, white, Gaussian noise. Finally, experimental signals have been collected from the biceps brachii muscle of ten healthy male subjects with an adhesive linear array of eight electrodes. The CV estimates depended on the electrode location with positive bias for the estimates from electrodes close to the innervation or tendon regions, as expected. The proposed method led to significantly lower bias than the spectral matching method in the experimental conditions, confirming the simulation results.