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.

Influência da utilização do fluido de corte com adição de grafeno na temperatura de usinagem e formação de rebarba no processo de micro fresamento

As time passed, humanity needed the development of new materials used in various activities. High strength materials such as titanium and Inconel for example, had been studied because they are widely used for implants in biomedicine, as well as their use in aerospace and automotive industries. Because of its thermal and mechanical properties, these materials are considered difficult to machine, promoting a rapid wear of cutting tools, primarily caused by the high temperatures in machining. With the development of new materials has emerged the need of developing new manufacturing processes. One of today’s innovative processes is the micro-manufacturing. Being a process with a defined cutting tool geometry, burr formation is a constant and undesirable phenomenon formed during the machininig process. Being detrimental to the manufacturing process, overspending deburring operations are constantly employed leading to increase the aggregate cost to the manufactured material. Assembly components are also impaired if there is no control of the burr, with consequences including the disposal of components due to the occurence of this phenomenon. This paper presents the study of micro-milling Inconel 718, investigating influential parameters in the formation of burrs in order to minimize the occurrence of this phenome non. Different feed rates per tooth and cutting speed are evaluated, and different cutting fluids with different methods of applying the fluid. Adding graphene to cutting fluids was considered as a variable to be investigated, which is considered an excellent solid lubricant, in addition to increasing the thermal conductivity of the cooling solution (AZIMI; MOZAF FARI, 2015). The micro-milling temperature was evaluated in the present work. It was observed a new phenomenon that causes the machined surface temperature decreases below room temperature when using the solution water + oil. This phenomenon is explained in further chapters. In order to unravel this phenomenon, a new test was proposed and, from this test, it can be concluded, comparatively, which cutting fluid has a better cooling property.Using cutting fluid with different thermal properties has shown influence when analy zing burr formation and reducing machining temperature.