Comparison of spatial filter selectivity in surface myoelectric signal detection: Influence of the volume conductor model (original) (raw)
Related papers
Selectivity of spatial filters for surface EMG detection from the tibialis anterior muscle
IEEE Transactions on Biomedical Engineering, 2003
Many spatial filters have been proposed for surface electromyographic (EMG) signal detection. Although theoretical and modeling predictions on spatial selectivity are available, there are no extensive experimental validations of these techniques based on single motor unit (MU) activity detection. The aim of this study was to compare spatial selectivity of one-and two-dimensional (1-D and 2-D) spatial filters for EMG signal detection. Intramuscular and surface EMG signals were recorded from the tibialis anterior muscle of ten subjects. The simultaneous use of intramuscular wire and surface recordings (with the spike triggered averaging technique) allowed investigation of the activity of single MUs at the skin surface. The surface EMG signals were recorded with a grid of point electrodes (3 3 electrodes) and a ring electrode system at 15 locations over the muscle, with the wires detecting signals from the same intramuscular location. For most subjects, it was possible to classify, from the intramuscular recordings, the activity of the same MUs for all the contractions. The surface EMG signals were averaged with the intramuscularly detected MU action potentials as triggers. In this way, eight spatial filters-longitudinal and transversal, single and double differential (LSD, TSD, LDD, TDD), Laplacian (NDD), inverse binomial filter of the second order (IB2), inverse rectangle filter (IR), and differential ring system (C1)-could be compared on the basis of their spatial selectivity. The distance from the source (transversal with respect to the muscle fiber orientation) after which the surface detected potential did not exceed 5% of the maximal peak-to-peak amplitude (detection distance) was statistically smaller for the 2-D systems and TDD than for the other filters. The MU action potential duration was significantly shorter with LDD and with the 2-D systems than with the other filters. The 2-D filters investigated (including C1) showed very similar performance and were, thus, considered equivalent from the point of view of spatial selectivity.
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.
Effect of spatial filtering on crosstalk reduction in surface EMG recordings
Medical Engineering & Physics, 2009
Increasing the selectivity of the detection system in surface electromyography (EMG) is beneficial in the collection of information of a specific portion of the investigated muscle and to reduce the contribution of undesired components, such as non-propagating components (due to generation or endof-fibre effects) or crosstalk from nearby muscles. A comparison of the ability of different spatial filters to reduce the amount of crosstalk in surface EMG measurements was conducted in this paper using simulated signals. It focused on the influence of different properties of the muscle anatomy (changing subcutaneous layer thickness, skin conductivity, fibre length) and detection system (single, double and normal double differential, with two interelectrode distances -IED) on the amount of crosstalk present in the measurements. A cylindrical multilayer (skin, subcutaneous tissue, muscle, bone) analytical model was used to simulate single fibre action potentials (SFAPs). Fibres were grouped together in motor units (MU) and motor unit action potentials (MUAP) were obtained by adding the SFAPs of the corresponding fibres. Interference surface electromyogram (EMG) signals were obtained, modelling
The effects of skinfold thickness on the selectivity of surface EMG
Electroencephalography and Clinical Neurophysiology/Evoked Potentials Section, 1994
We investigated the effects of skinfold thickness and electrode orientation on the ability to record selectively from a localized region of a muscle using arrays of surface electrodes. EMG activity elicited by electrical stimulation and by voluntary contraction of the biceps muscle was recorded from subjects with skinfold thicknesses ranging from 2 mm to 21 mm. The selectivity of the surface electrodes increased as the skinfold thickness decreased; action potentials were more rapidly attenuated and underwent less low-pass filtering. As a result, the EMG recorded during a voluntary contraction at one site became less highly correlated with that recorded at neighboring sites as skinfold thickness decreased. We were able to determine the axis of action potential propagation (muscle fiber direction) through comparison of the amplitude and delay of cross-correlation peaks from pairs of colinear electrodes oriented at angles to one another, although the thicker the skinfold the lower the resolution. It was clear that the ability to localize EMG signal sources deteriorated as the amount of subcutaneous fat between the surface recording site and the active muscle fibers increased.
Journal of Neuroscience Methods, 2005
The aim of this simulation study was to investigate the influence of local tissue in-homogeneities on the estimates of muscle fiber conduction velocity (CV) from surface EMG signals. A recently developed analytical surface EMG model was used to generate simulated surface EMG signals from a planar layered volume conductor, comprised of the muscle tissue and fat layer, with spheres (1 mm radius) in the fat layer of conductivity different from the surrounding tissue. CV was estimated with a maximum likelihood multi-channel approach, varying the number of channels and the interchannel distance used for the estimate. The action potentials detected along the muscle fiber direction changed shape due to the presence of the in-homogeneities, thus affecting CV estimates. CV estimates were influenced by the location of the in-homogeneities with respect to the fiber and detection electrodes. The maximum percent variation of CV estimates due to the presence of inhomogeneities decreased with increasing number of channels and inter-channel distance: 19.6% (2 channels), 12.1% (3 channels), 6.4% (4 channels), for 5 mm inter-channel distance, and 12.0% (2 channels), 5.2% (3 channels), 2.4% (4 channels), for 10 mm inter-channel distance (for double differential detection). The results were in agreement and explained previous experimental findings.
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 Access
The myoelectric interfaces are being used in rehabilitation technology, assistance and as an input device. This review focuses on an insightful analysis of the data acquisition system of EMG signals from these interfaces. According to applications reported in research articles of the last five years, the properties of the sensors, the number of channels, the pre-processing of the EMG signal, as well as the software and hardware used were identified. This analysis was performed for the following applications: monitoring of muscular activation for rehabilitation, muscle activation plans, and identification of possible pathologies, exoskeletons, electric of wheelchairs, prosthetics control, myoelectric bracelets, handwriting recognition and silent speech recognition. The results presented in this review become a guide of recommendations for the myoelectric signal processing according to the application of the interface. The main developments, degrees of research and open challenges are also presented in this direction.
Surface EMG: The issue of electrode location
Journal of Electromyography and Kinesiology, 2009
This paper contributes to clarifying the conditions under which electrode position for surface EMG detection is critical and leads to estimates of EMG variables that are different from those obtained 25 in other nearby locations. Whereas a number of previous works outline the need to avoid the innervation zone (or the muscle belly), many authors place electrodes in the central part or bulge of the muscle of interest where the innervation zone is likely to be. Computer simulations are presented to explain the effect of the innervation zone on amplitude, frequency and conduction velocity estimates from the signal and the need to avoid placing electrodes near it. Experimental 30 signals recorded from some superficial muscles of the limbs and trunk (abductor pollicis brevis, flexor pollicis brevis, biceps, upper trapezius, vastus medialis, vastus lateralis) were processed providing support for the findings obtained from simulations. The use of multichannel techniques is recommended to estimate the location of the innervation zone and to properly choose the optimal position of the detection point(s) allowing meaningful estimates of EMG variable during movement 35 analysis.