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.

Avaliação da adaptação marginal de diferentes tipos de restaurações obtidas por CAD/CAM e métodos convencionais

The past few decades have brought many changes to the dental practice and the technology has become ready available. The result of a satisfactory rehabilitation treatment basically depends on the balance between biological and mechanical factors. The marginal adaptation of crowns and prosthetic structures is vital factor for long-term success. The development of CAD / CAM technology in the manufacture of dental prostheses revolutionized dentistry, this technology is capable of generating a virtual model from the direct digital scanning from the mouth, casts or impressions. It allows the planning and design of the structure in a computered software. The virtual projects are obtained with high precision and a significant reduction in clinical and laboratory time. Thus, the present study (Chapters 1, 2 and 3) computed microtomography was used to evaluate, different materials, different CAD/CAM systems, different ways of obtaining virtual model (with direct or indirect scanning), and in addition, also aims to evaluate the influence of cementing agent in the final adaptation of crowns and copings obtained by CAD / CAM. Furthermore, this study (Chapter 4, 5 and 6) also aims to evaluate significant differences in vertical and horizontal misfits in abutment-free frameworks on external hexagon implants (HE) using full castable UCLAs, castable UCLAs with cobalt-chromium pre-machined bases and obtained by CAD / CAM with CoCr or Zirconia by different scanning and milling systems. For this, the scanning electron microscopy and interferometry were used. It was concluded that the CAD / CAM technology is capable to produce restorations, copings and screw-retained implant-supported frameworks in different materials and systems offering satisfactory results of marginal accuracy, with significative reduction in clinical and laboratory time.