Adaptação à distância de próteses auditivas acústicas: a teleaudiologia aplicada na melhoria da condução das Políticas Públicas no Brasil

INTRODUÇÃO: O governo brasileiro atualmente credencia cerca de 140 centros especializados para adaptações de aparelhos de amplificação sonora individual via SUS. Adaptações à distância através da internet podem permitir maior eficiência na prestação deste serviço e com maiores chances de aceitação por parte do paciente do SUS. OBJETIVOS: Descrever o caso de adaptação à distância realizado entre duas cidades, com revisão da literatura. MÉTODO: Equipamentos de informática e de tecnologia da informação, programador universal, aparelhos de amplificação sonora individual. ESTUDO DE CASO: Uma fonoaudióloga lotada num centro especializado introduziu a um centro remoto (distância de 200 km) um novo aparelho de amplificação sonora individual e seu programa de adaptação. O centro remoto assistiu a adaptação de dois pacientes em sua clínica, realizando voluntariamente a adaptação do terceiro paciente. Todo o procedimento foi realizado através da internet, contando com recursos de áudio e vídeo em todos os procedimentos. RESULTADOS: Três pacientes foram adaptados à distância. Três fonoaudiólogas receberam treinamento à distância de como adaptar aparelhos auditivos. CONCLUSÃO: Foi possível adaptar AASI à distância, além de prover treinamento e habilitar um centro remoto na adaptação de um novo aparelho de amplificação sonora individual e de seu programa de adaptação. Tal procedimento pode ser útil ao governo na condução de políticas públicas da saúde auditiva.

Single photon emission mammography with convergent collimators

Tese de doutoramento, Engenharia Biomédica e Biofísica, Universidade de Lisboa, Faculdade de Ciências, 2016

Construção tridimensional de atlas dos núcleos anteriores do tálamo a partir de cortes de um bloco de encéfalo

Tese de mestrado integrado em Engenharia Biomédica e Biofísica, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2016

Development of a magnetic resonance compatible wrist device for the analysis of movement encoding in the brain

Tese de mestrado integrado em Engenharia Biomédica e Biofísica, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2016

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.

Configurações para métodos de acesso por escaneamento

The use of access technologies for communication, based on scanning methods, enables new communication opportunities for individuals with severe motor dysfunction. One of the most commom examples of this type of technology is the single switch scanning. Single switch scanning keyboards are often used as augmentative and alternative communication devices for inidividuals with severe mobility restrictions and with compromised speech and writing. They consist of a matrix of keys and simulate the operation of a physical keyboard to write messages. One of the limitations of these systems is their low performance. Low communication rates and considerable errors ocurrence are some of the few problems that users of these devices suffers during daily use. The development and evaluation of new strategies in augmentative and alternative communication are essential to improve the communication opportunities of user who make use of such technology. Thus, this work explores different strategies to increase communication rate and reduce user’s mistakes. Computational and practical analysis were performed for the evaluation of proposed strategies.

Análise da variabilidade da marcha de indivíduos com comprometimento articular unilateral do quadril por meio de sensores inerciais

Data variability analysis has been the focus of a number of studies seeking to capture differences of patterns generated by biological systems. Although several studies related to gait employ the analysis of variability in their observations, we noticed a lack of such information for subjects with unilateral coxarthrosis undergoing total hip arthroplasty (THA). To tackle this deficiency of information, we conducted a study of the gait on a treadmill with10 healthy subjects (30.7 ± 6.75 years old) from G1 and 24 subjects (65 ± 8.5 years old) with unilateral THA from G2. Thus, by means of two inertial measurement units (IMUs) positioned in the pelvis, we have developed a detection method of the step and stride for calculating these intervals and extract the signal characteristics. The variability analysis (coefficient of variation) was performed, taking into consideration the extracted features and the step and stride times. The average and the 95% confidence interval estimate for the average of the step and stride times to each group were in agreement with literature. The mean coefficient of variation for the step and stride times was calculated and compared among groups by the Kruskal-Wallis test with 95% confidence interval. Each component X, Y and Z of the two IMUs (accelerometer, magnetometer and gyroscope) corresponded to a variable. The resultants of each sensor, the linear velocity (accelerometers) and the instantaneous angular displacement (gyroscopes) completed the set of variables. The characteristics were extracted from the signals of these variables to check the variability in the G1 and G2 groups . There were significant differences (p <0.05) between G1 and G2 for the average of the step and stride times. The variability of the step and stride, as well as the variability of all other evaluated characteristics were higher for the group G2 (p <0.05). The method proposed in this study proved to be suitable for the measuring of variability of biomechanical parameters related to the extracted features. All the extracted features categorized the groups. The G2 group showed greater variability, so it is possible that the age and the pathological condition of the hip both contributed to this result.

Classificação de nódulos pulmonares em imagens tomográficas utilizando redes neurais artificiais em cascata

Lung cancer is the most common of malignant tumors, with 1.59 million new cases worldwide in 2012. Early detection is the main factor to determine the survival of patients affected by this disease. Furthermore, the correct classification is important to define the most appropriate therapeutic approach as well as suggest the prognosis and the clinical disease evolution. Among the exams used to detect lung cancer, computed tomography have been the most indicated. However, CT images are naturally complex and even experts medical are subject to fault detection or classification. In order to assist the detection of malignant tumors, computer-aided diagnosis systems have been developed to aid reduce the amount of false positives biopsies. In this work it was developed an automatic classification system of pulmonary nodules on CT images by using Artificial Neural Networks. Morphological, texture and intensity attributes were extracted from lung nodules cut tomographic images using elliptical regions of interest that they were subsequently segmented by Otsu method. These features were selected through statistical tests that compare populations (T test of Student and U test of Mann-Whitney); from which it originated a ranking. The features after selected, were inserted in Artificial Neural Networks (backpropagation) to compose two types of classification; one to classify nodules in malignant and benign (network 1); and another to classify two types of malignancies (network 2); featuring a cascade classifier. The best networks were associated and its performance was measured by the area under the ROC curve, where the network 1 and network 2 achieved performance equal to 0.901 and 0.892 respectively.

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 da dose de radiação: angiotomografia coronariana - métodos retrospectivo e prospectivo

The aim of this study was to evaluate the effective dose received by patients undergoing CCTA in both acquisition methods in the period June 1st to October 30th, 2013. Data collection was performed at the Clínica Sabedotti in Ponta Grossa/PR, with General Electric Equipment VCT XT, 64 detections lines. The effective dose was measured from the thirty cases randomly selected of Picture Archival and Communication System – PACS, reported by Dose Lenght Product (DLP) equipment for each examination and the conversion factor (EDLP) set by the European Commission for cardiac region (EDLP = 0.014). The results showed significant differences in radiation dose delivered to the patient according to the employee acquisition method, Retrospective or Prospective of ECG.

Desenvolvimento de equipamento para estimular a propriocepção utilizando ímãs permanentes

This study developed the Magnetic Proprioceptive Stimulator – MPS at the Technological Federal University of Parana - UTFPR to stimulate, record and quantify the proprioceptive activity of the shoulder joint, using permanent magnets. A pilot study was conducted to investigate the proprioceptive stimulation generated by MPS. The results of this study show that the magnetic and mechanical forces generated by permanent magnets can change the static and dynamic stability of the shoulder joint. The angular changes of the shoulder joint during the stimulation of proprioception were photographed, videotaped and analyzed by vector editing program. The joint movements caused by the action of the magnets were recorded by an optical sensor installed in the MPS and displayed in a graphical interface for analyzing the proprioceptive dynamics. The study concluded that the Magnetic Proprioceptive Stimulator is safe, effective to stimulate proprioception and features high economic viability.

Desenvolvimento de equipamento para medir os intervalos R-R

This study aimed to develop a device to measure RR intervals, which have high correlation with the values of the gold standard device of electrocardiograph (ECG), by the time domain and frequency domain indices. To this end, a study was conducted with 18 students of Jiu-Jitsu, males with 35.5 ± 8.6 years, at least a weekly frequency of 3 times and one year training. The location was at the academy Gracie Barra de Curitiba PR. They underwent an examination at rest for a period of 7 minutes and then the results were converted into heart rate variability (HRV) and analyzed by the indexes in the time domain and the frequency domain. The results were compared statistically using the Pearson test and intraclass correlation (ICC) and according to them proves to be viable the development of this equipment, which is highly correlated and excellent reproducibility for measuring the RR intervals.

Medidas de concentração de radônio proveniente de argamassas de cimento portland, gesso e fosfogesso

Portland cement being very common construction material has in its composition the natural gypsum. To decrease the costs of manufacturing, the cement industry is substituting the gypsum in its composition by small quantities of phosphogypsum, which is the residue generated by the production of fertilizers and consists essentially of calcium dihydrate and some impurities, such as fluoride, metals in general, and radionuclides. Currently, tons of phosphogypsum are stored in the open air near the fertilizer industries, causing contamination of the environment. The 226 Ra present in these materials, when undergoes radioactive decay, produces the 222Rn gas. This radioactive gas, when inhaled together with its decay products deposited in the lungs, produces the exposure to radiation and can be a potential cause of lung cancer. Thus, the objective of this study was to measure the concentration levels of 222Rn from cylindrical samples of Portland cement, gypsum and phosphogypsum mortar from the state of Paraná, as well as characterizer the material and estimate the radon concentration in an environment of hypothetical dwelling with walls covered by such materials. Experimental setup of 222Rn activity measurements was based on AlphaGUARD detector (Saphymo GmbH). The qualitative and quantitative analysis was performed by gamma spectrometry and EDXRF with Au and Ag targets tubes (AMPTEK), and Mo target (ARTAX) and mechanical testing with x- ray equipment (Gilardoni) and the mechanical press (EMIC). Obtained average values of radon activity from studied materials in the air of containers were of 854 ± 23 Bq/m3, 60,0 ± 7,2 Bq/m3 e 52,9 ± 5,4 Bq/m3 for Portland cement, gypsum and phosphogypsum mortar, respectively. These results extrapolated into the volume of hypothetical dwelling of 36 m3 with the walls covered by such materials were of 3366 ± 91 Bq/m3, 237 ± 28 Bq/m3 e 208 ± 21 Bq/m3for Portland cement, gypsum and phosphogypsum mortar, respectively. Considering the limit of 300 Bq/m3 established by the ICRP, it could be concluded that the use of Portland cement plaster in dwellings is not secure and requires some specific mitigation procedure. Using the results of gamma spectrometry there were calculated the values of radium equivalent activity concentrations (Raeq) for Portland cement, gypsum and phosphogypsum mortar, which were obtained equal to 78,2 ± 0,9 Bq/kg; 58,2 ± 0,9 Bq/kg e 68,2 ± 0,9 Bq/kg, respectively. All values of radium equivalent activity concentrations for studied samples are below the maximum level of 370 Bq/kg. The qualitative and quantitative analysis of EDXRF spectra obtained with studied mortar samples allowed to evaluate quantitate and the elements that constitute the material such as Ca, S, Fe, and others.

Modelagem eletroquímica e do distúrbio ácido-básico em atletas de karatê participantes do campeonato mundial WKO 2014

The objective of this study was to analyze the electrochemical and acid-base disorders in high performance athletes during the World Karate Championship hosted by the WKO (World Karate Organization) in 2014. In this study 19 male athletes were analyzed (age 34 ± 8), black belts and with over 5 years of experience in the sport. Capillary blood samples from the digital pulp of the finger were collected in three stages: rest, 5 minutes after and 10 minutes after fighting (kumite). The sample was analyzed using blood gas analyzer GEM Premier 3000, using the parameters pH, Na+, K+, Ca2+, lactate e HCO3−. The values related to acid-base disturbance presented statistical differences (p <0.05) in most of the collected moments. The lactate levels found were 2.77 ± 0.97mmol / L in rest, 6.57 ± 2.1 for 5 minutes after and 4.06 ± 1.55 for 10 minutes after combat. The samples collected for the electrolytic markers showed no statistical differences in their values (p <0.05). Through the data collected, we conjecture that the sport can be characterized as a high-intensity exercise and with a predominance of the glycolytic system. The analysis of acid-base disturbance is an efficient method to assist in the control of training loads.