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.

Horta escolar: temas geradores e os momentos pedagógicos no ensino de ciências

Science application has faced problems in the process of training and cognizant thinking subjects in their actions. Thus, this work is justified in order to reorganize the contents of this area of knowledge. Thus, the research entitled "Plantation School: generating themes and teaching moments in teaching of science" was developed with a group of 6th grade of elementary school, from the planting of vegetables in tires without usefulness, with purpose of building meanings and scientific concepts to students. This work was based on sociointeractionist perspective of Vygotsky (1996, 1998), education for thematic research Freire (1983, 1996) as well as in problem-solving situations identified by the methodology of Pedagogical Moments Delizoicov and Angoti (1992; 2002 ) which together corroborated for the construction of a proposed teaching and learning, curriculum reorganization and significance of scientific concepts. Thus, the project breaks in practice with the linearity of the contents, to develop and analyze themes mediated by pedagogical moments, in order to ascertain the contribution of this methodological resource for the teacher's work, with regard to the understanding of scientific concepts by students. Thus, lesson plans were built based on the study situation "Horta School" and Themes Generators "human interaction with the environment", "photosynthesis", "Ecology and Nutrition of living beings", culminating in the work proposal developed in the classroom. From these themes, the contents were worked through pedagogical moments, which are organized into three stages: questioning, organization / systematization of knowledge and application / contextualization of knowledge. Thus, within each Theme Generator activities were planned which resulted in the involvement of students in learning scientific concepts, such as the issue of sustainability, environmental pollution, nutrition of living beings and the decomposition of organic matter. This work led and motivated student participation in Themes generators, and allows greater interaction between teacher-student and student among his peers, through dialogism established in the classroom, which promoted a more meaningful learning for students.