Traité de Médecine pratique et de Pathologie iatrique ou médicale : cours professé a la Faculté de Médecine de Paris.

Mode of access: Internet.

Traité de myologie et d'angéiologie /

Índice.

Myo-graphie ou Description des muscles du corps humain /

Texto con caja.

Compendio anatomico : dividido en quatro partes : primera, De la naturaleza y circunstancias de los huesos, llamada comunmente la osteologia /

Contiene con portadilla propia: Compendio anatomico segunda parte, Myotomologia ó Discurso teorico-practico de la naturaleza y circunstancias de los musculos, llamado por otro nombre la Myologia.

Compendio anatomico : segunda parte : myotomologia, o Discurso theorico-practico de la naturaleza, i circunstancias de los musculos, llamado por otro nombre la myologia /

Mode of access: Internet.

De articulis ligamentis et musculis hominis incessu statuque dirigendis in theatro anatomico Lipsiensi observationes fecit denuo recognovit et iconibus illustravit Augustinus Frid. Walther ...

Mode of access: Internet.

An essay on the vital and other involuntary motions of animals /

Mode of access: Internet.

Bernardi Siegfried Albini ... Historia musculorum hominis

Mode of access: Internet.

Lucina ruyschiana, sive Musculus uteri orbicularis /

Mode of access: Internet.

El cuerpo humano : (anatomía de las formas).

Mode of access: Internet.

Comparação das atividades musculares durante a mastigação nas maloclusões de classe I e II de Angle

O objetivo deste estudo foi comparar a atividade muscular dos músculos da face e pescoço nas maloclusões Classe I e II de Angle, segundo o sexo. A amostra constou de 36 indivíduos, sendo 22 indivíduos com maloclusão classe I com média de idade de 22,4 anos e 14 indivíduos com maloclusão Classe II com média de idade de 22,8 anos. Os registros foram realizados por um eletromiógrafo de superfície, sendo analisada a atividade dos músculos masseter, temporal feixe anterior, esternocleidomastoídeo e digástrico ventre anterior dos lados direito e esquerdo durante a mastigação dos alimentos uva passa, bolacha água e sal e goma de mascar-PLOC. Após análise estatística descritiva e análise de variância os resultados mostraram que houve diferença estatisticamente significante apenas para os músculos: masseter direito durante a mastigação de uva passa quando comparadas as maloclusões de Classe I e II no sexo masculino; para o músculo digástrico direito quando comparado sexo e as maloclusões Classe I e II durante a mastigação dos três alimentos. Por fim, para o músculo digástrico esquerdo durante a mastigação de uva passa também encontramos diferença estatisticamente significante entre os sexos para as maloclusões Classe I e II. Nossos resultados sugerem que dependendo da consistência do alimento o tipo de maloclusão e sexo podem influenciar na atividade muscular durante a função da mastigação.(AU)

Avaliação da pressão inspiratória nasal sniff na população obesa

Introdução: a avaliação da pressão inspiratória nasal (SNIP) é considerada uma manobra complementar da Pressão Inspiratória Máxima estática (PImax) em várias condições clínicas, porém não há relatos na obesidade. Por outro lado, a obesidade tem um importante impacto nos músculos respiratórios especialmente com maiores gordura abdominal o que provavelmente pode ser detectado na avaliação da SNIP que mensura mais precisamente a pressão diafragmática. Objetivo: analisar em obesos a relação entre SNIP e variáveis respiratórias e marcadores de adiposidade. Material e Método: num estudo transversal um total de 92 obesos (38.3±10.2 anos) sem história de doença respiratória ou cardíaca diagnosticada. Foram avaliados na espirometria (capacidade vital forçada-CVF; volume expiratório forçado no primeiro segundo-VEF1; volume de reserva expiratório-VRE) e pressões respiratórias estática (PImax, PEmax e SNIP) e dinâmica (ventilação voluntária máxima-VVM). Sendo considerados os marcadores de adiposidade: índice de adiposidade corporal-IAC; índice de massa corporal-IMC e circunferências do quadril (CQ), cintura (CC) e pescoço (CP). Resultados: 65 obesos mórbidos (IMC=50.8±8.1Kg/m2) e 27 obesos não mórbidos (IMC=35.6±2.7Kg/m2) foram homogêneos (p>0.05) na SNIP (99.1±24.5cmH2O, 87% do predito) e PImax (107.3±26.4cmH2O, 109% do predito). Existe correlação (r=0.5) entre SNIP e PImax somente no grupo de obesos mórbidos. De acordo com as correlações houve associação entre variáveis respiratórias (CVF r=0.48; VEF1 r=0.54; e VVM r=0.54), valores antropométricos (idade r=-0.44) e SNIP somente para os obesos mórbidos. Esses achados foram certificados quando também comparados a quantidade de gordura ao redor do pescoço (CP≥43cm). O modelo de regressão linear stepwise mostrou que a VVM parece ser o melhor preditor para explicar a SNIP nos obesos mórbidos. Nestes obesos a SNIP foi levemente mais baixa (87%predito) que os valores esperados para indivíduos brasileiros saudáveis. Conclusão: em obesos mórbidos a SNIP é moderadamente relacionada a PImax. A SNIP parece ser mais relacionada a VVM que à marcadores de adiposidade.

Efeitos imediatos da plataforma vibratória no desempenho neuromuscular do quadríceps femoral, após reconstrução do LCA: ensaio controlado, randomizado e cego

Objective: to investigate the immediate effect of the vibrating platform on the neuromuscular performance of the quadriceps femoris and on the postural oscillation of subjects submitted to Anterior Cruciate Ligament (ACL) reconstruction. Materials and methods: this study is a randomized and blind clinical trial. Forty-four male volunteers (average age of 27,4 ±6,2 IMC of 26,85± 3,8 Kg/m² and post surgery timeframe of 17± 1,4 weeks) were randomized into two groups: OFF platform (n=22, protocol of exercise over the vibrating platform off) and ON platform (n=22 protocol of exercise over the vibrating platform on, 50Hz frequency and 4mm of amplitude). All volunteers were submitted to assessment the isokinetic evaluation of the quadriceps femoris (isometric and isokinetic at 60°/s) and of the electromyography activity of the muscles Vasto Lateralis (VL) and Vasto Medialis (VM), besides the postural oscillation (baropodometry) in two distinct moments: before and immediately after the intervention protocol. The data was analyzed through the SPSS 20.0 software, with a 5% significance level. To verify the homogeneity of the groups it was used an ANOVA one way, and a ANOVA mixed model to compare the intra and inter groups. Results: it was observed differences between the pre and the post, to latero lateral velocity, isometric torque peak and total work in comparison with intragroup. However, it wasn’t verified any difference in comparing the intergroup in the preevaluation and in the post-evaluation protocol over the vibrating platform. Conclusion: the use of the vibrating platform doesn’t change as an immediate manner the isokinetic performance of the quadriceps femoris, the electromyography activity of the VL and the VM, also doesn’t interfere with the postural oscillation of individuals that were submitted to the ACL reconstruction.

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.