Fabiano Araujo Soares

Motor unit action potential conduction velocity estimated from surface electromyographic signals using image processing techniques

In surface electromyography (surface EMG, or S-EMG), conduction velocity (CV) refers to the velocity at which the motor unit action potentials (MUAPs) propagate along the muscle fibers, during contractions. The CV is related to the type and diameter of the muscle fibers, ion concentration, pH, and firing rate of the motor units (MUs). The CV can be used in the evaluation of contractile properties of MUs, and of muscle fatigue. The most popular methods for CV estimation are those based on maximum likelihood estimation (MLE). This work proposes an algorithm for estimating CV from S-EMG signals, using digital image processing techniques. The proposed approach is demonstrated and evaluated, using both simulated and experimentally-acquired multichannel S-EMG signals. We show that the proposed algorithm is as precise and accurate as the MLE method in typical conditions of noise and CV. The proposed method is not susceptible to errors associated with MUAP propagation direction or inadequate initialization parameters, which are common with the MLE algorithm. Image processing -based approaches may be useful in S-EMG analysis to extract different physiological parameters from multichannel S-EMG signals. Other new methods based on image processing could also be developed to help solving other tasks in EMG analysis, such as estimation of the CV for individual MUs, localization and tracking of innervation zones, and study of MU recruitment strategies.

On the behavior of surface electromyographic variables during the menstrual cycle

The goal of this work is to study the behavior of electromyographic variables during the menstrual cycle. Ten female volunteers (24.0 ± 2.8 years of age) performed fatiguing isometric contractions, and electromyographic signals were measured on the biceps brachii in four phases of the menstrual cycle. Adaptations of classical algorithms were used for the estimation of the root mean square (RMS) value, absolute rectified value (ARV), mean frequency (MNF), median frequency (MDF), and conduction velocity (CV). The CV estimator had a higher (p = 0.002) rate of decrease at the end of the follicular phase and at the end of the luteal phase. The MDF (p = 0.002) and MNF (p = 0.004) estimators had a higher rate of decrease at the beginning of the follicular phase and at the end of the luteal phase. No significant differences between phases of the menstrual cycle were detected with the ARV and RMS estimators (p > 0.05). These results suggest that the behavior of the muscles in women presents different characteristics during different phases of the menstrual cycle. In particular, women were more susceptible to fatigue at the end of the luteal phase.

Insole with pressure control and tissue neoformation induction systems for diabetic foot

This article presents the development of a prototype insole derived from natural rubber from Hevea brasiliensis, equipped with pressure control and capable of neoformation of tissue for people who have diabetic foot. The active element of this insole is the electronic circuit that monitors the plantar pressure. In addition, on the present stage of the research, a signal irradiating cell is used based on the principle of tissue regeneration using laser. This project proposes a “smart” insole prototype with a pressure monitoring system and an electronic system for tissue regeneration, which will open a new approach in an attempt to solve the problem of diabetic foot.

Gender differences in muscle fatigue of the biceps brachii and influences of female menstrual cycle in electromyography variables

Several studies report gender differences in response to fatigue. Most results suggest that females have higher muscle endurance than males. Possible explanations lie on differences in muscle mass, substrate utilization, muscle morphology and neuromuscular activation. One relevant aspect not always considered is the hormonal fluctuations during the female menstrual cycle. The present work observed eighteen healthy and untrained adults (eight males, 26.9 ± 4.0 yr and ten females, 24.0 ± 2.8 yr) performing fatiguing isometric contractions to evaluate both the influence of menstrual cycle and gender differences in fatigability. Surface electromyographic signals were recorded from the biceps brachii using a linear electrode array of eight electrodes during 90 seconds at 40% of maximal voluntary contraction. Root mean square (RMS), mean frequency (MNF) the conduction velocity (CV) values were estimated using windows of 0.5 seconds. Female subjects showed overall lower fatigability, demonstrated by the lower mean CV decrease (1.494) compared to males (1.787). However, in periods of high decreases in hormones concentrations in females (the end of both the follicular and luteal phases), higher CV decreases were observed (1.921 and 2.183). These results indicate the need of considering the effects of hormonal fluctuations in females when observing gender effects on muscle fatigue.

Análise de Filtros Espaciais em Sinais EMG de Superfície nas Condições do Máximo Volume de Contração

Nowadays the surface EMG measurement and its signal analysis have combined two important techniques in order to improve the signal resolution and better investigate single motor units: measurements configurations with smaller pick-up areas and application of the spatial filtering to electromyography. Smaller pick-up areas can be achieved through multielectrode arrays and multichannel recording, making possible the detection of correlated excitations at different sites of the muscle. Spatial filters combine the information of several electrodes to form one output signal channel. This work aims at evaluating the EMG signals measured from some subjects with a linear array of 16 electrodes and compare their resolution through the application of Bipolar, Longitudinal Double Diferentiating and Longitudinal Quadruple Diferentiating spatial filters.

A sliding window approach to detrended fluctuation analysis of heart rate variability

The analysis of heart rate variability (HRV) aids in the diagnosis of various diseases related to the malfunction of the autonomic nervous system. Traditional approaches for analysis of HRV require the signal to be reasonably stationary during the period of observation. This is not possible when analyzing long duration signals. Detrended fluctuation analysis (DFA) is robust to this issue, as it removes external interferences (“trends”) and considers only intrinsic characteristics which are present throughout the signal. DFA is typically performed by segmenting the signal into shorter windows. This has two undesirable effects: (i) if the signal length is not a multiple of the window length, then at least one window will have fewer samples than the others; and (ii) discontinuities are observed on the detrended signal at the edges of each window. Both issues may be addressed using a sliding window. We propose and evaluate this idea, comparing its results with those obtained using the traditional approach. Experiments using different kinds of random and real HRV signals are presented. Statistically significant differences were observed with the proposed approach, especially with respect to α2 values. The proposed method also presented a great reduction in α1 error for white noise, which is a good model for congestive heart failure, with respect to α1 correlations.

Electromyographic study in 5 muscles during an isometric fatiguing protocol

In this study, 12 healthy men aging 22.8 ± 2.2 years old were submitted to a protocol of isometric resistance to fatigue contemplating elbow flexion on three different angles: 45°, 90° and 135°. The objective was to study electromyographic median frequency (MDF) in the following muscles: i) Biceps Brachialis Long Head (BBL), Brachioradialis (BRD), Flexor Digitorum Superficialis (FDS), Triceps Brachialis Long Head (TBL), and Extensor Digitorum (ED). It was verified that, for all muscles, including the muscles that act in opposition to the contraction, fatigue presence was verified by the decrease of MDF value.

Surface EMG and spatial resolution analysis with estimation of electromyographic descriptors

Spatial filtering has become a common way to improve the resolution of surface electromyographic signals (SEMG) when used in connection with electrode arrays. The goal of this study is to observe the behavior of S-EMG amplitude and spectral descriptors when signals are submitted to a longitudinal quadruple differentiating spatial filter. Signals were acquired at 20% and 60% of the maximum voluntary contraction using a linear array of eight surface electrodes in order to understand the impact of the filtering technique in the S-EMG variables during fatiguing and non-fatiguing contractions. The final results show that the filtering procedure yields better selectivity, suggesting that single motor units can be better observed if spatial filters and measurement configurations with smaller pick-up areas are used. During fatiguing contractions, however, further analysis is needed.

Algoritmo de Máxima Verossimilhança para a Estimação da Velocidade de Condução Média de Sinais Eletromiográficos de Superfície

Surface electromyographic signals may be acquired using multi-channel electrodes, allowing the estimation of important characteristics, like the motor unit or single fiber conduction velocity (CV). This work presents an algorithm to minimize the mean square error of the estimation of the delay between signals from different channels spaced between one another by the inter-electrode distance (IED). Considering the CV constant during voluntary isometric contractions of low intensity, and knowing the IED, the estimation of the delay between adjacent channels allows the direct calculation of the mean CV. In this work, in order to increase accuracy, the problem is moved to the frequency domain. A numeric method is presented to accelerate the mean square error minimization time. As a result, it was observed that the use of more channels within the calculations leads to smaller variances of the CV estimative, if all the channels considered are located between the innervation zone and the tendon region.

Effects of very short pauses on electromyographic variables measured during fatiguing isometric contractions.

15 healthy men (26.6 ± 4.6 years old, weight of 70.7 ± 8.6 kg, and height of 1.750 ± 0.072 m) performed three 30-seconds isometric contractions at 60% MVC, with two 10-seconds resting intervals between them. The goal was to study the effect of the resting intervals on the variables that are most commonly used to analyze surface electromyographic (S-EMG) signals (conduction velocity [CV], root mean square [RMS], average rectified value [ARV], mean power frequency [MNF], and median power frequency [MDF]). For the first 30-second contraction, the S-EMG variables behaved exactly like described in the literature. However, after the first and second pauses, the CV variable ceased to behave like in the literature. In the first contraction, the conduction velocity had a statistically significant decreasing trend, in the second contraction, it had a statistically non-significant positive trend, and, in the third contraction, a statistically significant positive trend. These results suggest that short pauses between isometric constant-force contractions lead to changes in the recruiting strategies of the muscles involved in the contraction. The causes of these changes are not yet clear, and further work is needed in order to understand this effect.