Normalização de eletromiografia de superfície dos músculos respiratórios em sujeitos saudáveis: contração voluntária máxima máxima isométrica versus pressões respiratórias máximas

Aim : To evaluate and to standardize surface electromyography (sEMG) normalization procedures for respiratory muscles by comparing muscle activation during Maximal Voluntary Isometric Contraction (MVIC) and Maximal Respiratory Pressures (MIP, MEP and sniff test). Methods: Healthy subjects were evalua ted regarding demographics, spirometry and sEMG during the five maneuvers: sniff test, MIP , MEP and Maximal Voluntary Isometric C ontraction (MVIC) of RA, SCM and SC A . For electrode placement, skin was prepared with abrasion, followed by shaving in the foll owing regions for acquisition of el ectromyographic signals: (1) SC M: lower third of the distance between the mastoid process and t he sternoclavicular joint; (2) SC A : 5 cm to the right from the sternoclavicular joint and at this point, up to 2 cm; and (3 ) RA: the level of umbilicus, 4 cm to the right. In electromyographic variables analysis , the data normality was assessed by Shapiro - Wilk test. Comparisons among studied maneuvers were performed by Friedman Test and Dunn’s post - hoc for multiple comparisons a mong inspiratory maneuvers, and Mann Whitney test for expiratory maneuvers. Subgroups differences between genders were performed by Student's t test or Mann - Whitney test according to data normality. Results: 35 subjects participated in the study, b ut 5 we re excluded (BMI> 25 kg/ m²). Sample consisted of 30 subjects (1 5 women), mean age 27.3±7.43 years, BMI 22.2 ± 1.69 kg/m² and spirometric indices within normal limits. Specific MVIC for SCM, SCA and RA showed the highest RMS. When we grouped sample into gender we found no difference among RMS values for the studied SCM maneuvers, while for SCA, MVIC SCM / SCA was the one with the highest RMS and for RA, MVIC RA in men. Once considering women, MVIC SCM/SCA showed the highest RMS for SCM, SCA and MVIC RA showed t he highest value for RA. Conclusion: MVIC for SCM, SCA and RA muscles showed the highest RMS values. When comparing RMS between the studied groups, there was no significant difference between men and women.

Efeito do treinamento muscular inspiratório com diferentes cargas na força e função de músculos respiratórios

Background: The inspiratory muscle training (IMT) has been considered an option in reversing or preventing decrease in respiratory muscle strength, however, little is known about the adaptations of these muscles arising from the training with charge. Objectives: To investigate the effect of IMT on the diaphragmatic muscle strength and function neural and structural adjustment of diaphragm in sedentary young people, compare the effects of low intensity IMT with moderate intensity IMT on the thickness, mobility and electrical activity of diaphragm and in inspiratory muscles strength and establish a protocol for conducting a systematic review to evaluate the effects of respiratory muscle training in children and adults with neuromuscular diseases. Materials and Methods: A randomized, double-blind, parallel-group, controlled trial, sample of 28 healthy, both sexes, and sedentary young people, divided into two groups: 14 in the low load training group (G10%) and 14 in the moderate load training group (G55%). The volunteers performed for 9 weeks a home IMT protocol with POWERbreathe®. The G55% trained with 55% of maximal inspiratory pressure (MIP) and the G10% used a charge of 10% of MIP. The training was conducted in sessions of 30 repetitions, twice a day, six days per week. Every two weeks was evaluated MIP and adjusted the load. Volunteers were submitted by ultrasound, surface electromyography, spirometry and manometer before and after IMT. Data were analyzed by SPSS 20.0. Were performed Student's t-test for paired samples to compare diaphragmatic thickness, MIP and MEP before and after IMT protocol and Wilcoxon to compare the RMS (root mean square) and median frequency (MedF) values also before and after training protocol. They were then performed the Student t test for independent samples to compare mobility and diaphragm thickness, MIP and MEP between two groups and the Mann-Whitney test to compare the RMS and MedF values also between the two groups. Parallel to experimental study, we developed a protocol with support from the Cochrane Collaboration on IMT in people with neuromuscular diseases. Results: There was, in both groups, increased inspiratory muscle strength (P <0.05) and expiratory in G10% (P = 0.009) increase in RMS and thickness of relaxed muscle in G55% (P = 0.005; P = 0.026) and there was no change in the MedF (P> 0.05). The comparison between two groups showed a difference in RMS (P = 0.04) and no difference in diaphragm thickness and diaphragm mobility and respiratory muscle strength. Conclusions: It was identified increased neural activity and diagrammatic structure with consequent increase in respiratory muscle strength after the IMT with moderate load. IMT with load of 10% of MIP cannot be considered as a placebo dose, it increases the inspiratory muscle strength and IMT with moderate intensity is able to enhance the recruitment of muscle fibers of diaphragm and promote their hypertrophy. The protocol for carrying out the systematic review published in The Cochrane Library.

Seleção de características para identificação de diferentes proporções de tipos de fibras musculares por meio da eletromiografia de superfície

Skeletal muscle consists of muscle fiber types that have different physiological and biochemical characteristics. Basically, the muscle fiber can be classified into type I and type II, presenting, among other features, contraction speed and sensitivity to fatigue different for each type of muscle fiber. These fibers coexist in the skeletal muscles and their relative proportions are modulated according to the muscle functionality and the stimulus that is submitted. To identify the different proportions of fiber types in the muscle composition, many studies use biopsy as standard procedure. As the surface electromyography (EMGs) allows to extract information about the recruitment of different motor units, this study is based on the assumption that it is possible to use the EMG to identify different proportions of fiber types in a muscle. The goal of this study was to identify the characteristics of the EMG signals which are able to distinguish, more precisely, different proportions of fiber types. Also was investigated the combination of characteristics using appropriate mathematical models. To achieve the proposed objective, simulated signals were developed with different proportions of motor units recruited and with different signal-to-noise ratios. Thirteen characteristics in function of time and the frequency were extracted from emulated signals. The results for each extracted feature of the signals were submitted to the clustering algorithm k-means to separate the different proportions of motor units recruited on the emulated signals. Mathematical techniques (confusion matrix and analysis of capability) were implemented to select the characteristics able to identify different proportions of muscle fiber types. As a result, the average frequency and median frequency were selected as able to distinguish, with more precision, the proportions of different muscle fiber types. Posteriorly, the features considered most able were analyzed in an associated way through principal component analysis. Were found two principal components of the signals emulated without noise (CP1 and CP2) and two principal components of the noisy signals (CP1 and CP2 ). The first principal components (CP1 and CP1 ) were identified as being able to distinguish different proportions of muscle fiber types. The selected characteristics (median frequency, mean frequency, CP1 and CP1 ) were used to analyze real EMGs signals, comparing sedentary people with physically active people who practice strength training (weight training). The results obtained with the different groups of volunteers show that the physically active people obtained higher values of mean frequency, median frequency and principal components compared with the sedentary people. Moreover, these values decreased with increasing power level for both groups, however, the decline was more accented for the group of physically active people. Based on these results, it is assumed that the volunteers of the physically active group have higher proportions of type II fibers than sedentary people. Finally, based on these results, we can conclude that the selected characteristics were able to distinguish different proportions of muscle fiber types, both for the emulated signals as to the real signals. These characteristics can be used in several studies, for example, to evaluate the progress of people with myopathy and neuromyopathy due to the physiotherapy, and also to analyze the development of athletes to improve their muscle capacity according to their sport. In both cases, the extraction of these characteristics from the surface electromyography signals provides a feedback to the physiotherapist and the coach physical, who can analyze the increase in the proportion of a given type of fiber, as desired in each case.

Classificação de atividade eletromiográfia facial de indivíduos saudáveis e com hanseníese por meio de máquina de vetores de suporte

A number of studies in the areas of Biomedical Engineering and Health Sciences have employed machine learning tools to develop methods capable of identifying patterns in different sets of data. Despite its extinction in many countries of the developed world, Hansen’s disease is still a disease that affects a huge part of the population in countries such as India and Brazil. In this context, this research proposes to develop a method that makes it possible to understand in the future how Hansen’s disease affects facial muscles. By using surface electromyography, a system was adapted so as to capture the signals from the largest possible number of facial muscles. We have first looked upon the literature to learn about the way researchers around the globe have been working with diseases that affect the peripheral neural system and how electromyography has acted to contribute to the understanding of these diseases. From these data, a protocol was proposed to collect facial surface electromyographic (sEMG) signals so that these signals presented a high signal to noise ratio. After collecting the signals, we looked for a method that would enable the visualization of this information in a way to make it possible to guarantee that the method used presented satisfactory results. After identifying the method's efficiency, we tried to understand which information could be extracted from the electromyographic signal representing the collected data. Once studies demonstrating which information could contribute to a better understanding of this pathology were not to be found in literature, parameters of amplitude, frequency and entropy were extracted from the signal and a feature selection was made in order to look for the features that better distinguish a healthy individual from a pathological one. After, we tried to identify the classifier that best discriminates distinct individuals from different groups, and also the set of parameters of this classifier that would bring the best outcome. It was identified that the protocol proposed in this study and the adaptation with disposable electrodes available in market proved their effectiveness and capability of being used in different studies whose intention is to collect data from facial electromyography. The feature selection algorithm also showed that not all of the features extracted from the signal are significant for data classification, with some more relevant than others. The classifier Support Vector Machine (SVM) proved itself efficient when the adequate Kernel function was used with the muscle from which information was to be extracted. Each investigated muscle presented different results when the classifier used linear, radial and polynomial kernel functions. Even though we have focused on Hansen’s disease, the method applied here can be used to study facial electromyography in other pathologies.

Classificação de atividade eletromiográfia facial de indivíduos saudáveis e com hanseníase por meio de máquina de vetores de suporte

A number of studies in the areas of Biomedical Engineering and Health Sciences have employed machine learning tools to develop methods capable of identifying patterns in different sets of data. Despite its extinction in many countries of the developed world, Hansen’s disease is still a disease that affects a huge part of the population in countries such as India and Brazil. In this context, this research proposes to develop a method that makes it possible to understand in the future how Hansen’s disease affects facial muscles. By using surface electromyography, a system was adapted so as to capture the signals from the largest possible number of facial muscles. We have first looked upon the literature to learn about the way researchers around the globe have been working with diseases that affect the peripheral neural system and how electromyography has acted to contribute to the understanding of these diseases. From these data, a protocol was proposed to collect facial surface electromyographic (sEMG) signals so that these signals presented a high signal to noise ratio. After collecting the signals, we looked for a method that would enable the visualization of this information in a way to make it possible to guarantee that the method used presented satisfactory results. After identifying the method's efficiency, we tried to understand which information could be extracted from the electromyographic signal representing the collected data. Once studies demonstrating which information could contribute to a better understanding of this pathology were not to be found in literature, parameters of amplitude, frequency and entropy were extracted from the signal and a feature selection was made in order to look for the features that better distinguish a healthy individual from a pathological one. After, we tried to identify the classifier that best discriminates distinct individuals from different groups, and also the set of parameters of this classifier that would bring the best outcome. It was identified that the protocol proposed in this study and the adaptation with disposable electrodes available in market proved their effectiveness and capability of being used in different studies whose intention is to collect data from facial electromyography. The feature selection algorithm also showed that not all of the features extracted from the signal are significant for data classification, with some more relevant than others. The classifier Support Vector Machine (SVM) proved itself efficient when the adequate Kernel function was used with the muscle from which information was to be extracted. Each investigated muscle presented different results when the classifier used linear, radial and polynomial kernel functions. Even though we have focused on Hansen’s disease, the method applied here can be used to study facial electromyography in other pathologies.

Avaliação do comportamento ingestivo utilizando eletromiografia de superfície do músculo masseter

Physiologists and animal scientists try to understand the relationship between ruminants and their environment. The knowledge about feeding behavior of these animals is the key to maximize the production of meat and milk and their derivatives and ensure animal welfare. Within the area called precision farming, one of the goals is to find a model that describes animal nutrition. Existing methods for determining the consumption and ingestive patterns are often time-consuming and imprecise. Therefore, an accurate and less laborious method may be relevant for feeding behaviour recognition. Surface electromyography (sEMG) is able to provide information of muscle activity. Through sEMG of the muscles of mastication, coupled with instrumentation techniques, signal processing and data classification, it is possible to extract the variables of interest that describe chewing activity. This work presents a new method for chewing pattern evaluation, feed intake prediction and for the determination of rumination, food and daily rest time through ruminant animals masseter muscle sEMG signals. Short-term evaluation results are shown and discussed, evidencing employed methods viability.

Ambiente para aquisição e processamento de sinal eletromiográfico de superfície

In this work, a platform to the conditioning, digitizing, visualization and recording of the EMG signals was developed. After the acquisition, the analysis can be done by signal processing techniques. The platform consists of two modules witch acquire electromyography (EMG) signals by surface electrodes, limit the interest frequency band, filter the power grid interference and digitalize the signals by the analogue-to- digital converter of the modules microcontroller. Thereby, the data are sent to the computer by the USB interface by the HID specification, displayed in real-time in graphical form and stored in files. As processing resources was implemented the operations of signal absolute value, the determination of effective value (RMS), Fourier analysis, digital filter (IIR) and the adaptive filter. Platform initial tests were performed with signal of lower and upper limbs with the aim to compare the EMG signal laterality. The open platform is intended to educational activities and academic research, allowing the addition of other processing methods that the researcher want to evaluate or other required analysis.

Relationship between internal derangement of temporomandibular joint and changes in body posture

Background: The presence of body posture changes among patients with temporomandibular disorders (TMD) has been a controversial issue in the literature, in which it supporters point out the muscular origin as the main etiological factors, mainly associated with postural changes in head. Due to this controversy, it is pertinent to check whether this relationship exists on the most common etiology of TMD, the disk displacement, which translates a biomechanical internal disorder of the temporomandibular joint (TMJ). Objectives: Assess body posture changes in subjects with internal derangement of the TMJ when compared to subjects without this biomechanical dysfunction, characterize the patterns of the jaw movements and assess to the muscle activation during jaw movements. Methods: 21 subjects with TMJ disc displacement (DD) (test group) and 21 subjects without any TMD (control group) was assessed for body posture changes through evaluation of several body segments by posturography and also was evaluated the postural balance reactions through the center of mass during jaw movements using a balance platform. For the characterization of the jaw movement patterns it was done a kinematic analysis during jaw movements (active ROM and path of the jaw). For the muscle activation during jaw movements it was evaluated the masseter, sternocleidomastoid and spinae erector muscles by surface electromyography (EMG). Results Discussion: Both groups show forward head posture and extension of the cervical spine, not noticing any other significant body posture changes in subjects with DD, and if we had to see in detail, in general, subjects without TMD shows more body posture changes than subjects with DD. The pattern of jaw movements is similar in both groups, but in subjects with DD the closing movements are more instable than the opening movements, related to a less effective movement control to counteract the force of gravity and the disk displacement. The bilateral muscle activation during jaw movements is higher in subjects with DD, likely related to a less stable pattern of movement which leads in a higher muscle activation to guide the movement and ensure the best as possible articular stability. Conclusion: The disk displacement with reduction should be viewed as part of a set of signs and symptoms that require an accurate musculoskeletal and psychosocial assessment towards an earlier diagnosis for reduction and control of the functional limiting factors. In this direction, it seems that the relevant set of limiting signs and symptoms deserve a particular attention by health care practitioners involved in the assessment and treatment of TMD, in order to define effective therapeutic options.

Motor Unit Spike Trains Recontruction from sEMG Signals for Gesture Classification on a Low-Power Processing Platform

Hand gesture recognition based on surface electromyography (sEMG) signals is a promising approach for the development of intuitive human-machine interfaces (HMIs) in domains such as robotics and prosthetics. The sEMG signal arises from the muscles' electrical activity, and can thus be used to recognize hand gestures. The decoding from sEMG signals to actual control signals is non-trivial; typically, control systems map sEMG patterns into a set of gestures using machine learning, failing to incorporate any physiological insight. This master thesis aims at developing a bio-inspired hand gesture recognition system based on neuromuscular spike extraction rather than on simple pattern recognition. The system relies on a decomposition algorithm based on independent component analysis (ICA) that decomposes the sEMG signal into its constituent motor unit spike trains, which are then forwarded to a machine learning classifier. Since ICA does not guarantee a consistent motor unit ordering across different sessions, 3 approaches are proposed: 2 ordering criteria based on firing rate and negative entropy, and a re-calibration approach that allows the decomposition model to retain information about previous sessions. Using a multilayer perceptron (MLP), the latter approach results in an accuracy up to 99.4% in a 1-subject, 1-degree of freedom scenario. Afterwards, the decomposition and classification pipeline for inference is parallelized and profiled on the PULP platform, achieving a latency < 50 ms and an energy consumption < 1 mJ. Both the classification models tested (a support vector machine and a lightweight MLP) yielded an accuracy > 92% in a 1-subject, 5-classes (4 gestures and rest) scenario. These results prove that the proposed system is suitable for real-time execution on embedded platforms and also capable of matching the accuracy of state-of-the-art approaches, while also giving some physiological insight on the neuromuscular spikes underlying the sEMG.

Coactivation of the shoulder and arm muscles during closed kinetic chain exercises on an unstable surface

Introduction: The purpose of this study was to compare the electromyography index of muscle coactivation of the following muscle pairs: posterior deltoid and pectoralis major (PD/PM); triceps brachii and biceps brachii (TB/BB); and serratus anterior and upper trapezius (SA/UT) during three different closed kinetic chain exercises (wall-press, bench-press and push-up) on an unstable surface at the maximal load. Methods: A total of 20 healthy sedentary men participated in the study. Integral linear values were obtained from three sustained contractions of six seconds each for the three proposed exercises. Mean coactivation index values were compared using the mixed-effects linear model, with a five percent significance level. Results: Electromyography indexes of muscle coactivation showed significant differences for the PD/PM and TB/BB muscle pairs. No differences were found between exercises for the SA/UT muscle pair. Conclusion: Our results seem to differ from those of previous studies, which reported that the similarity in exercises performed is responsible for the comparable muscle activation levels.

Ageing and surface EMG activity patterns of masticatory muscles

P>The purpose of this study was to evaluate the influence of age on the electromyographic activity of masticatory muscles. All volunteers were Brazilian, fully dentate (except for Group I - mixed dentition), Caucasian, aged 7-80, and divided into five groups: I (7-12 years), II (13-20 years), III (21-40 years), IV (41-60 years) and V (61-80 years). Except for Group V, which comprised nine women and eight men, all groups were equally divided with respect to gender (20 M/20 F). Surface electromyographic records of masticatory muscles were obtained at rest and during maximal voluntary contraction, right and left laterality, maximal jaw protrusion and maximal clenching in the intercuspal position. Statistically significant differences (P < 0 center dot 05) were found in all clinical conditions among the different age groups. Considerably different patterns of muscle activation were found across ages, with greater electromyographic activity in children and youth, and decreasing from adults to aged people.

Relationship between Surface and Indwelling EMG Spike Shape Measures

Indwelling electromyography (EMG) has great diagnostic value but its invasive and often painful characteristics make it inappropriate for monitoring human movement. Spike shape analysis of the surface electromyographic signal responds to the call for non-invasive EMG measures for monitoring human movement and detecting neuromuscular disorders. The present study analyzed the relationship between surface and indwelling EMG interference patterns. Twenty four males and twenty four females performed three isometric dorsiflexion contractions at five force levels from 20% to maximal force. The amplitude measures increased differently between electrode types, attributed to the electrode sensitivity. The frequency measures were different between traditional and spike shape measures due to different noise rejection criteria. These measures were also different between surface and indwelling EMG due to the low-pass tissue filtering effect. The spike shape measures, thought to collectively function as a means to differentiate between motor unit characteristics, changed independent of one another.

Laryngeal electromyography: Technical features

Laryngeal Electromyography (LEMG) is an auxiliary diagnostic method used for the comprehension and diagnosis of different neurological diseases that compromise laryngeal function. The most common LEMG technique is the percutaneous insertion of needle electrodes guided by surface anatomical references. We describe techniques for inserting needle electrodes into the tireoaritenoideus (TA), cricotireoideus (CT), cricoaritenoideus lateralis (CAL) and cricoaritenoideus posterioris (CAP) muscles; these are used at UNICAMP laryngology ambulatory; we discuss difficulties found and their proposed solutions. All patients were submitted to otorhinolaryngological, phonoaudiological and laryngeal endoscopy before LEMG. The CAP approach, by digital rotation of the thyroid cartilage was found to be the most difficult, followed by the CAL approach. TA and CT approaches gave no major problems, except with some older and obese patients. A significant complication of the TA approach via thyroid cartilage was a hematoma in one patient which partially obstructed the laryngeal lumen.

Lumbo-pelvic stability and electromyography of abdominal muscles in ballet dancers

Evaluating the ability to rectify and maintain lumbar adjustment can contribute toward the understanding of the behavior of abdominal muscles and their participation in the stability of pelvic muscles in dancers during the posterior pelvic tilt and double straight leg lowering tests. Nine healthy volunteers (male and female ballet dancers; age mean: 25.9 ±7.37 years) underwent maximal isometric voluntary contraction (MIVC), isometric voluntary contraction at 50% of MIVC, posterior pelvic tilt (PPT) and double straight leg lowering (DSLL) tests. The tests were carried out in a single day, with 3 repetitions each. During the tests, electromygraphic signals of the rectus abdominis, obliquus internus and obliquus externus were recorded. The signal acquisition system was made up of bipolar surface electrodes, electrogoniometer and an electromechanic device (pressure sensor), which were connected to a signal conditioner module. Root mean square values of each muscle during the DSLL and PPT were converted into percentage of activation of 50% MIVC. Lower back pressure was submitted to the same process. ANOVA with repeated measures was performed, with the level of significance set at p < 0.05. The results revealed that all dancers were able to maintain posterior pelvic tilt and there was trend toward greater activation of the bilateral obliquus internus muscle. In an attempt to keep the pelvic region stabilized during DSLL, there was a greater contribution from the obliquus externus muscle in relation to other abdominal muscles.

A cross-sectional electromyography assessment in linear scleroderma patients

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)