RCAAP Repository

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Electromyography is a technique for the study and analysis of bioelectric phenomena that occur in the cell membranes of muscle fibers. Through this technique it is possible to diagnose a number of disorders and motor problems and also to analyze the behavior of muscles in various situations. The electromyographic (EMG) signal, resulting from the summation of Motor Unit Action Potential Trains (MUAPT s) of different muscle fibers innervated by the motor neurons, is captured and measured by a device called electromyography. With the advent of technology many electronic devices, especially in health care, have become portable and embedded as oximeters and electrocardiographs. The vast majority of electromyographic device is based on a communication with a computer, either RS-232 or USB via an interface in software, in which all processes necessaries are performed, and then saves the signal for further analysis. Thus the device, hardware, has a signal conditioning system and digitizing process for sending data to the computer. This makes the device user, i.e., physical therapists, doctors, dentists and others, to become dependent on an external device to view and process the signal. Few studies have been worrying to the fact of designing an EMG device that possessed all these traits so embedded and portable. Thus there is a lack of studies that aim this creation. In this context, the main motivation of this research is to create a prototype of a portable EMG biofeedback embedded in hardware. To do this it was created a professional printed circuit board, which contains the necessary instrumentation for acquisitioning, conditioning, digitalizing, viewing, processing, saving and also sending the EMG signal. The biofeedback for displaying this signal is provided by a Liquid Crystal Display - LCD using TFT (Thin-Film Transistor) technology, colored, touch-screen and 320x240 points. Further, as aid biofeedback, there is a bar graph with 10 LEDs for each acquisition channel in order to indicate the level of muscle activity. The system is battery-powered and has four channels of electromyography assets and a reference electrode. The results are satisfactory since it is the first version of the prototype, and the signal was conditioned satisfactorily with what was designed and also digitalized to show it on the LCD.

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Researches conducted by energy distribution companies on several industry segments showed that about 30%of inductionmotors are operating undersized, i.e. with less than 70%of the rated load. Under these conditions induction motors have low efficiency. Due to the characteristics of industrial processes, traditional methods of efficiency and operation analysis can not be used. In order to meet the requirements of these applications, several methods have been proposed. Most of these methods require only the measurement of voltages, currents and in some cases rotor speed. Often these methods estimate, using different techniques, the shaft torque and calculate the output power and efficiency. The purpose of this study is to develop and implement a real-time method to monitor operating conditions and efficiency of induction motors operating at steady state. The proposed method, by means of measured three-phase voltages and currents and the equivalent circuit of the machine, estimates the shaft torque and speed. Then, based on these estimations, calculates the power output and efficiency. The machine equivalent circuit is estimated by an iterative algorithm that uses only the machine nameplate data and the stator resistance. According to present tendencies a wireless system was developed were a central computer can monitor in real time the efficiency and the operational conditions of one or more motors in a industrial plant. This document presents the theoretical development of the proposed method and the results of computer simulations under different situations. Finally it presents an experimental implementation of the method where its performance is evaluated for different motors.

The number of plants at risk of extinction has increased gradually. With the purpose of reducing the risk is necessary identify the species for planning protection methods. The biodiversity of species existing in the plant kingdom make the use of traditional models of recognition and taxonomy a process very complex and slow. The identification of a plant can be performed observing his features, such as: fruits, seeds, flowers, roots, leaves and stems. But the simplest feature used are the leaves.This paper presents a hybrid system for identifying plant based on leaf image. This system is composed by Genetic Algorithm (GA) and Artificial Neural Network (ANN). The role played by the GA is to perform a preselection of plants forming a group that the answer of an unknown leaf is more probable and the purpose of ANN, trained by backpropagation algorithm, is to classify the unknown leaf performing the search only in the group calculated by the AG. Several tests were conducted and the results obtained demonstrate that the hybrid system achieved a recognition rate of 93,2%.

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In recent years, the wireless network technologies of broadband access with integrated data, video and voice were limited in relation to distance, QoS (Quality of Service) and bandwidth, especially in areas whit lack of infrastructure and difficult access, such as rural. The IEEE 802.16 standard was created to provide broadband connectivity to wireless fixed and mobile users in a wide coverage area with high rates of data transfer, also seeking to address the barriers found in previous technologies, promising data transfer rates of up to 1 Gbps for fixed users and 100 Mbps for mobile users and QoS for those applications. This paper aims to highlight the IEEE 802.16 standard features and also to present a proposal for an wireless rural broadband network access IEEE 802.16 standard, designed to meet communication requirements of a rural community model. The planning allowed to define a rural community that will serve as a model for other communities with similar characteristics. The Site-Survey enabled the collecting of data and information needed to adequate coverage and to determine the amount of BSs needed to cover the specified area, and the mapping of demand to determine the SSs quantity. In terms of the highlighted SS s, the demand for bandwidth to meet the user applications in PBH (Peak Busy Hour) was mapped.

This dissertation proposes a cardiac cycle detection algorithm based on digital signals generated by ECG (electrocardiogram) devices. Detection is made through a threshold, seeking R wave occurrences, as represented by its second derivate. A threshold is established dynamically based on the last 10 seconds of the signal and its value is calculated taking the standard deviation of the second derivate in the period into account. The derivates are applied to the filtered ECG signal, using a moving average filter (20 samples). To test the model performance operation, a software application was developed prepared to receive files containing digitalized data, in 16-bit words with up to 12 derivates as input and running at a configurable acquisition frequency. The application can receive real-time data acquired directly from the ECG device with digital output channels. The software that has been developed provides statistical data and information of interest related to the analyzed ECG. The algorithm was tested through experimentation with hundreds of samples coming from normal patients and from people suffering from cardiopathies. The accuracy level was above 99%.

Image Digital Processing techniques, standards recognizing, and neural artificial nets are not often used in the technology market, because they are hard to work with and expensive for who uses them. When we make research on technology tools we find them fragmented as they solve few problems and come in software with no license for copywriting. Thus, we propose a Computer System for Automatic Reading of Money Banknotes, who will join programming techniques widespread in academia to develop free software that can be used both in the market and for studies in academia, a software with applications on image capture, digital image processing, pattern recognition that uses artificial neural network techniques, coupled to a voice synthesizer, which will assist people with visual needs and even people with difficulties in achieving the necessary focus such as supermarkets. The system can be adapted to any sales place, or even where people work counting high money values. It brings the reliability needed without errors that can cause losses to the company and people as well.

The IEEE 802.16 standard also known as WiMAX (Worldwide Interoperability for Microwave Access) is a promising technology responsible for providing wireless broadband access to end users, fixed, mobile and with high-rate data transmission. The main feature provided by this standard to end users is the provision of quality of service (QoS - Quality of Service) through scheduling mechanisms, connection admission control (CAC - Connection Admission Control) and policing in both the base station (BS - Base station) and the subscriber station (SS - Subscriber Station). As these mechanisms are not defined by IEEE 802.16 and directly affect the performance of WiMAX networks, a considerable number of studies focusing on these topics has been proposed in the areas of scheduling and CAC. In this context it is proposed and evaluated in this work a mechanism for traffic policing based on the token bucket technique for controlling data flow generated by the stations in the network. The traffic policing mechanism is applied to all classes of IEEE 802.16d standard. A temporary storage queue was added to the proposed mechanism in order to offer to the packages of nrtPS and BE classes, which were not admitted to the network transmission at the first opportunity, a new chance of being admitted. Results based on modeling and simulation showed that the proposed policing mechanism has satisfactory performance.

The fingerprints are lines present on fingers of each human and they are unique, in other words, there are not two people with the same distribution of lines on their fingers. For this reason, it has been used for identification of people for many purposes, such as to check the entrancy and exit of workers in a company, the identify criminals and to restrict the access of people to restrict areas of extreme security. The proposal of this work is to improve the characteristic extraction algorithm of fingerprint developed by Jain and others. The goal of this work is to accelerate the processing time in orientation field estimation, in order to get a better quality of images, resulting of binarization process and to decrease the number of spurious minutiae on the images. The time processing of orientation field estimation improved in these work uses the commutative propriety is smaller than the same estimation wich does not use this propriety in 90%. The method of ridges extration developed in this work uses the DDA algorithm, and results in better quality images. Due to this improviment got in binarization process and the ridges break removing, the detection minutiae algorithm implemented in this work find a small quantity of spurious minutae present in the fingerprint images.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

The electrocardiogram (ECG) is generally used in order to follow and detect heart diseases, putting forward that cardiovascular pathologies being one of the leading causes of death in Brazil. Increasingly morbidity and mortality related to cardiovascular events leads recently to great impact on public health. Some countries, including Brazil, have been using the capabilities of telemedicine to provide health care in particular situations for which the access to publich health services is a critical factor, including the context of cardiovascular diseases. Minas Gerais province, for example, has started since 2006 a telecardiology system, part of Teleminas Saúde project, that already covers 70% of the population. Several quirks can interfere in the conduction of the electrical impulse and, consequently, change the ECG. Thus, in the interpretation and clinical ECG analysis must take into account numerous factors such as the ethnic compositions of diverse populations, gender, age. This thesis discusses the main changes in electrocardiographic in Teleminas Saúde, quantifies the normal ECG and investigates features of the population that could influence the amplitude values of the normal electrocardiogram. The quantification of the normal ECG and ECG were obtained through major changes of project data base Teleminas health, the sample was composed of 4000 individuals and after the exclusion, according to the criteria adopted, 1113 examinations within the bounds of normal and 1609 pathological. These findings were compared to patterns arising from the clinical literature, so that relevant differences were noticed. It was also concluded that age and gender could influence the amplitudes of the normal ECG intervals and waves.

The main objective of this work is to perform a comparative study between a three phase induction motor squirrel cage traditional and asymmetrical three-phase induction motor. Were used two motors of the same power, the motor being powered by an asymmetrical voltage source phase. In the studies we investigated the behavior of various quantities such as yield, starting current, voltage sags, power factor, and the power supplied by each machine. With the results obtained from practical experiments, it was found that the asymmetric motor features a number of advantages over traditional engines, which makes it an excellent choice when the application requires the drive loads of high power and not has a three-phase supply.

Fundação de Amparo a Pesquisa do Estado de Minas Gerais

This work proposes the quantitative analysis of electroencephalographic (EEG) signals, comparing normal subjects to patients in coma state under brain death protocol, by means of a software platform developed in MATLAB. This analysis involved peak frequencies, median frequencies, average, standard deviation and modular index. This last one relates to the bilaterality, i.e. how equidistant electrodes are on the same frequency. Results outlined that patients in coma present lower average median frequency (11.89 Hz), when compared to normal subjects (30.69 Hz). Moreover, with regard the analysis of bilaterality based on modular index, patients in coma also presented lower average standard deviation of the average median frequency (4.72 Hz) than the normal individuals (13 , 67 Hz), e.g., comatose patients presented higher bilaterality. Therefore, results suggests the possibility of applying these quantifications as biomarkers of brain death.

This dissertation analyses the electrical activity recorded in experiments involving the maturation of dissociated embryonic hippocampal cultures, using Multielectrode Array (MEA) devices, starting from the moment of the culture s placement in the device until its death, a period of 0 to 88 days in vitro (DIV). Classical spike analysis is applied to differents cultures, showing the progression of spikes and bursts . Particular attention is devoted to the last step associated with cellular death, as an unexpected rise in electrical activity amplitude is observed. In addition, other techniques such as Fourier Transform, Autocorrelation, Power Spectral Density, Peak Detection, Coherence, Detrended Fluctuation Analysis (DFA), Stacionarity and Gaussian were applied. It s possible to observe, from DIV 08 to DIV 28, by classical analysis of spikes, DFA, Stacionarity and Gaussian, culture is predominantly stationary and gaussian and there is variability in the behavior of channels showing long-range correlation. Analyzing the DIV 29 to 71 we could observe that the culture stabilizes like white noise and displaying electrical activity not stationary and not gaussian. In the later stages of development (DIV\'s 72 to 88) there is a disruption of electrical activity followed by an unexpected increase in the amount of spikes and bursts and, subsequently, cell death occurs.