Dario Farina

Comparison of algorithms for estimation of EMG variables during voluntary isometric contractions

Many algorithms have been described in the literature for estimating amplitude, frequency variables and conduction velocity of the surface EMG signal detected during voluntary contractions. They have been used in different application areas for the non invasive assessment of muscle functions. Although many studies have focused on the comparison of different methods for information extraction from surface EMG signals, they have been carried out under different conditions and a complete comparison is not available. It is the purpose of this paper to briefly review the most frequently used algorithms for EMG variable estimation, compare them using computer generated as well as real signals and outline the advantages and drawbacks of each. In particular the paper focuses on the issue of EMG amplitude estimation with and without pre-whitening of the signal, mean and median frequency estimation with periodogram and autoregressive based algorithms both in stationary and non-stationary conditions, delay estimation for the calculation of muscle fiber conduction velocity.

Rehabilitation of gait after stroke: a review towards a top-down approach

This document provides a review of the techniques and therapies used in gait rehabilitation after stroke. It also examines the possible benefits of including assistive robotic devices and brain-computer interfaces in this field, according to a top-down approach, in which rehabilitation is driven by neural plasticity.The methods reviewed comprise classical gait rehabilitation techniques (neurophysiological and motor learning approaches), functional electrical stimulation (FES), robotic devices, and brain-computer interfaces (BCI).From the analysis of these approaches, we can draw the following conclusions. Regarding classical rehabilitation techniques, there is insufficient evidence to state that a particular approach is more effective in promoting gait recovery than other. Combination of different rehabilitation strategies seems to be more effective than over-ground gait training alone. Robotic devices need further research to show their suitability for walking training and their effects on over-ground gait. The use of FES combined with different walking retraining strategies has shown to result in improvements in hemiplegic gait. Reports on non-invasive BCIs for stroke recovery are limited to the rehabilitation of upper limbs; however, some works suggest that there might be a common mechanism which influences upper and lower limb recovery simultaneously, independently of the limb chosen for the rehabilitation therapy. Functional near infrared spectroscopy (fNIRS) enables researchers to detect signals from specific regions of the cortex during performance of motor activities for the development of future BCIs. Future research would make possible to analyze the impact of rehabilitation on brain plasticity, in order to adapt treatment resources to meet the needs of each patient and to optimize the recovery process.

Influence of anatomical, physical and detection system parameters on surface EMG

Abstract. 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 non-homogeneous 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.

The linear electrode array: a useful tool with many applications

In this review we describe the basic principles of operation of linear electrode arrays for the detection of surface EMG signals, together with their most relevant current applications. A linear array of electrodes is a system which detects surface EMG signals in a number of points located along a line. A spatial filter is usually placed in each point for signal detection, so that the recording of EMG signals with linear arrays corresponds to the sampling in one spatial direction of a spatially filtered version of the potential distribution over the skin. Linear arrays provide indications on motor unit (MU) anatomical properties, such as the locations of the innervation zones and tendons, and the fiber length. Such systems allow the investigation of the properties of the volume conductor and its effect on surface detected signals. Moreover, linear arrays allow to estimate muscle fiber conduction velocity with a very low standard deviation of estimation (of the order of 0.1-0.2 m/s), thus providing reliable indications on muscle fiber membrane properties and their changes in time (for example with fatigue or during treatment). Conduction velocity can be estimated from a signal epoch (global estimate) or at the single MU level. In the latter case, MU action potentials are identified from the interference EMG signals and conduction velocity is estimated for each detected potential. In this way it is possible, in certain conditions, to investigate single MU control and conduction properties with a completely non-invasive approach. Linear arrays provide valuable information on the neuromuscular system properties and appear to be promising tools for applied studies and clinical research.

Surface electromyography for noninvasive characterization of muscle.

MERLETTI, R., A. RAINOLDI, and D. FARINA. Surface electromyography for noninvasive characterization of muscle. Exerc. Sport Sci. Rev., Vol. 29, No. 1, pp 20–25, 2001. Linear electrode arrays are used for noninvasive muscle characterization to study individual motor unit properties and the myoelectric manifestations of muscle fatigue during sustained contractions. The location of an electrode pair with respect to the innervation zone(s), the deterministic rather than stochastic nature of the signal, and the possibility of noninvasive fiber typing are discussed.

A novel approach for precise simulation of the EMG signal detected by surface electrodes

We propose a new electromyogram generation and detection model. The volume conductor is described as a nonhomogeneous (layered) and anisotropic medium constituted by muscle, fat and skin tissues. The surface potential detected in space domain is obtained from the application of a two-dimensional spatial filter to the input current density source. The effects of electrode configuration, electrode size and inclination of the fibers with respect to the detection system are included in the transfer function of the filter. Computation of the signal in space domain is performed by applying the Radon transform; this permits to draw considerations about spectral dips and clear misunderstandings in previous theoretical derivations. The effects of generation and extinction of the action potentials at the fiber end plate and at the tendons are included by modeling the source current, without any approximation of its shape, as a function of space and time and by using again the Radon transform. The approach, based on the separation of the temporal and spatial properties of the muscle fiber action potential and of the volume conductor, includes the capacitive tissue properties.

The Extraction of Neural Information from the Surface EMG for the Control of Upper-Limb Prostheses: Emerging Avenues and Challenges

Despite not recording directly from neural cells, the surface electromyogram (EMG) signal contains information on the neural drive to muscles, i.e, the spike trains of motor neurons. Using this property, myoelectric control consists of the recording of EMG signals for extracting control signals to command external devices, such as hand prostheses. In commercial control systems, the intensity of muscle activity is extracted from the EMG and used for single degrees of freedom activation (direct control). Over the past 60 years, academic research has progressed to more sophisticated approaches but, surprisingly, none of these academic achievements has been implemented in commercial systems so far. We provide an overview of both commercial and academic myoelectric control systems and we analyze their performance with respect to the characteristics of the ideal myocontroller. Classic and relatively novel academic methods are described, including techniques for simultaneous and proportional control of multiple degrees of freedom and the use of individual motor neuron spike trains for direct control. The conclusion is that the gap between industry and academia is due to the relatively small functional improvement in daily situations that academic systems offer, despite the promising laboratory results, at the expense of a substantial reduction in robustness. None of the systems so far proposed in the literature fulfills all the important criteria needed for widespread acceptance by the patients, i.e. intuitive, closed-loop, adaptive, and robust real-time (<;200 ms delay) control, minimal number of recording electrodes with low sensitivity to repositioning, minimal training, limited complexity and low consumption. Nonetheless, in recent years, important efforts have been invested in matching these criteria, with relevant steps forwards.

Interpretation of the Surface Electromyogram in Dynamic Contractions.

This review focuses on methods for extracting information from the surface EMG recorded in dynamic contractions. It examines the techniques, requirements, and limitations associated with detecting the timing of muscle activation, assessing the modulation of signal amplitude, performing EMG spectral analysis, and estimating conduction velocity. The conclusion is that interpretation of the surface EMG in dynamic tasks requires caution.

A fast and reliable technique for muscle activity detection from surface EMG signals

The estimation of on-off timing of human skeletal muscles during movement is an important issue in surface electromyography (EMG) signal processing with relevant clinical applications. In this paper, a novel approach to address this issue is proposed. The method is based on the identification of single motor unit action potentials from the surface EMG signal with the use of the continuous wavelet transform. A manifestation variable is computed as the maximum of the outputs of a bank of matched filters at different scales. A threshold is applied to the manifestation variable to detect EMG activity. A model, based on the physical structure of the muscle, is used to test the proposed technique on synthetic signals with known features. The resultant bias of the onset estimate is lower than 40 ms and the standard deviation lower than 30 ms in case of additive colored Gaussian noise with signal-to-noise ratio as low as 2 dB. Comparison with previously developed methods was performed, and representative applications to experimental signals are presented. The method is designed for a complete real-time implementation and, thus, may be applied in clinical routine activity.

Geometrical factors in surface EMG of the vastus medialis and lateralis muscles

Surface EMG signals detected in dynamic conditions are affected by a number of artefacts. Among them geometrical factors play an important role. During movement the muscle slides with respect to the skin because of the variation of its length. Such a shift can considerably modify sEMG amplitude. The purpose of this work is to assess geometrical artefacts on sEMG during isometric contractions at different muscle lengths. The average rectified value (ARV) of 15 single differential signals was obtained by means of a linear array of 16 bar electrodes from the vastus medialis and lateralis muscles. The knee angle was changed from 75 degrees to 165 degrees in steps of 30 degrees and voluntary isometric contractions at a low, medium and high force level were performed for each angle. The ARV pattern was normalized with respect to the mean activity to compare signals from different joint angles. From the data collected it was possible to separate the geometrical changes from the changes due to different intensities of activation. In three out of five subjects, we found (within the resolution of our measures) a 1 cm shift for the vastus medialis muscle while no shift was observed for the other two subjects. For the vastus lateralis muscle a 1 cm shift was found in two out of four subjects. Such a shift produces the main contribution to geometrical artefacts. To avoid such artefacts the innervation zones should be located and the EMG electrodes should not be placed near them.