Adriano Alves Pereira

Study of age-related changes in postural control during quiet standing through linear discriminant analysis.

BackgroundThe human body adopts a number of strategies to maintain an upright position. The analysis of the human balance allows for the understanding and identification of such strategies. The displacement of the centre of pressure (COP) is a measure that has been successfully employed in studies regarding the postural control. Most of these investigations are related to the analysis of individuals suffering from neuromuscular disorders. Recent studies have shown that the elderly population is growing very fast in many countries all over the world, and therefore, researches that try to understand changes in this group are required. In this context, this study proposes the analysis of the postural control, measured by the displacement of the COP, in groups of young and elderly adults.MethodsIn total 59 subjects participated of this study. They were divided into seven groups according to their age. The displacement of the COP was collected for each subject standing on a force plate. Two experimental conditions, of 30 seconds each, were investigated: opened eyes and closed eyes. Traditional and recent digital signal processing tools were employed for feature computation from the displacement of the COP. Statistical analyses were carried out in order to identify significant differences between the features computed from the distinct groups that could allow for their discrimination.ResultsOur results showed that Linear Discrimination Analysis (LDA), which is one of the most popular feature extraction and classifier design techniques, could be successfully employed as a linear transformation, based on the linear combination of standard features for COP analysis, capable of estimating a unique feature, so-called LDA-value, from which it was possible to discriminate the investigated groups and show a high correlation between this feature and age.ConclusionThese results show that the analysis of features computed from the displacement of the COP are of great importance in studies trying to understand the ageing process. In particular, the LDA-value showed to be an adequate feature for assessment of changes in the postural control which can be related to functional changes that occur over the ageing.

Bridging the gap between robotic technology and health care

Although technology and computation power have become more and more present in our daily lives, we have yet to see the same tendency in robotics applied to health care. In this work we focused on the study of four distinct applications of robotic technology to health care, named Robotic Assisted Surgery, Robotics in Rehabilitation, Prosthetics and Companion Robotic Systems. We identified the main roadblocks that are limiting the progress of such applications by an extensive examination of recent reports. Based on the limitations of the practical use of current robotic technology for health care we proposed a general modularization approach for the conception and implementation of specific robotic devices. The main conclusions of this review are: (i) there is a clear need of the adaptation of robotic technology (closed loop) to the user, so that robotics can be widely accepted and used in the context of heath care; (ii) for all studied robotic technologies cost is still prohibitive and limits their wide use. The reduction of costs influences technology acceptability; thus innovation by using cheaper computer systems and sensors is relevant and should be taken into account in the implementation of robotic systems.

A boost converter associated with a new nondissipative snubber

This paper presents a boost converter with a nondissipative snubber which provides a soft switching converter operation. This approach allows the main switch to work in a ZVS way and the auxiliary switch to work in a ZCS way. The nondissipative snubber is composed by two capacitors (resonant capacitors), one inductor (resonant inductor), one switch (auxiliary switch) and two diodes, one in series with the main switch and the other in series with the auxiliary switch. The complete operating principle, relevant equations, simulation results and experimental results are presented.

A power factor correction preregulator AC-DC interleaved boost with soft-commutation

This work presents the operation and design of an AC-DC boost interleaved power factor correcting preregulator circuit using a nondissipative snubber and operating at 100 kHz per cell. By using interleaved converters, one can obtain an overall reduction of the boost inductor, together with reduced switching losses. The complete operating principles, theoretical analysis, relevant equations and simulation results are presented. Experimental results of a prototype rated at 500 Watts, with an input AC voltage of 150 Vrms and, an output of 250 Vdc has been obtained in laboratory.

An online no-break with power factor correction and output voltage stabilization

The aim of this paper is to introduce a dc-dc converter that can be used in an online uninterruptible power supply (UPS). The proposed converter provides uninterrupted, reliable power and voltage regulation for critical loads, as well as power factor correction in supply systems. Operating principles, theoretical analysis, and control strategy are described. Digital simulation and experimental results are included, supporting the validity of the concept.

A 1.5 kW operation with 90% efficiency of a two transistors forward converter with non-dissipative snubber

This paper presents a nondissipative snubber forward power converter. As result of this topology, the switching losses are reduced. The proposed approach allows one to obtain better operating performances than those already known for hard-switching PWM operating at higher switching frequencies and with a wide range of power. The switches are not submitted to overvoltages and the peak of current across the switches can be adjusted by the suitable choice of the resonant capacitor and inductor.

A specialized motion capture system for real-time analysis of mandibular movements using infrared cameras

BackgroundIn the last years, several methods and devices have been proposed to record the human mandibular movements, since they provide quantitative parameters that support the diagnosis and treatment of temporomandibular disorders. The techniques currently employed suffer from a number of drawbacks including high price, unnatural to use, lack of support for real-time analysis and mandibular movements recording as a pure rotation. In this paper, we propose a specialized optical motion capture system, which causes a minimum obstruction and can support 3D mandibular movement analysis in real-time.MethodsWe used three infrared cameras together with nine reflective markers that were placed at key points of the face. Some classical techniques are suggested to conduct the camera calibration and three-dimensional reconstruction and we propose some specialized algorithms to automatically recognize our set of markers and track them along a motion capture session.ResultsTo test the system, we developed a prototype software and performed a clinical experiment in a group of 22 subjects. They were instructed to execute several movements for the functional evaluation of the mandible while the system was employed to record them. The acquired parameters and the reconstructed trajectories were used to confirm the typical function of temporomandibular joint in some subjects and to highlight its abnormal behavior in others.ConclusionsThe proposed system is an alternative to the existing optical, mechanical, electromagnetic and ultrasonic-based methods, and intends to address some drawbacks of currently available solutions. Its main goal is to assist specialists in diagnostic and treatment of temporomandibular disorders, since simple visual inspection may not be sufficient for a precise assessment of temporomandibular joint and associated muscles.

Investigation of Age-Related Changes in Physiological Kinetic Tremor

Tremor is the most common movement disorder characterized by repetitive and stereotyped movements. Most investigations on tremor attempt to understand its relation to neuromuscular dysfunctions. Therefore, there is a lack of studies that aim to investigate the complex relation between the physiological tremor and aging, especially in kinetic conditions. In this context, the main motivation of this research was to quantify age-related changes in the kinetic tremor of clinically healthy individuals. For this, a number of features extracted from tremor activity, obtained from digitized drawings of Archimedes’ spirals, were analyzed. In total, 59 subjects participated in the experiments. These individuals were divided into seven groups according to their ages and two types of analysis were carried out. First, the tremor activity of young and elderly adults was investigated by means of traditional features commonly used in tremor analysis, and secondly, linear discriminant analysis (LDA) was employed for the study of the correlation between age and tremor. The results showed significant statistical differences between the kinetic tremor activity of the young and elderly groups. Furthermore, it was found that LDA allowed for the estimate of a unique feature, so-called LDA-value, which showed to be linearly correlated with age.

Use of an artificial neural network to predict the incidence of malaria in the city of Cantá, state of Roraima

INTRODUCTION Malaria is endemic in the Brazilian Amazon region, with different risks for each region. The City of Cantá, State of Roraima, presented one of the largest annual parasite indices in Brazil for the entire study period, with a value always greater than 50. The present study aimed to use an artificial neural network to predict the incidence of malaria in this city in order to assist health coordinators in planning and managing resources. METHODS Data were collected on the website of the Ministry of Health, SIVEP--Malaria between 2003 and 2009. An artificial neural network was structured with three neurons in the input layer, two intermediate layers and an output layer with one neuron. A sigmoid activation function was used. In training, the backpropagation method was used, with a learning rate of 0.05 and momentum of 0.01. The stopping criterion was to reach 20,000 cycles or a target of 0.001. The data from 2003 to 2008 were used for training and validation. The results were compared with those from a logistic regression model. RESULTS The results for all periods provided showed that the artificial neural network had a smaller mean square error and absolute error compared with the regression model for the year 2009. CONCLUSIONS The artificial neural network proved to be adequate for a malaria forecasting system in the city studied, determining smaller predictive values with absolute errors compared to the logistic regression model and the actual values.INTRODUCTION: Malaria is endemic in the Brazilian Amazon region, with different risks for each region. The City of Canta, State of Roraima, presented one of the largest annual parasite indices in Brazil for the entire study period, with a value always greater than 50. The present study aimed to use an artificial neural network to predict the incidence of malaria in this city in order to assist health coordinators in planning and managing resources. METHODS: Data were collected on the website of the Ministry of Health, SIVEP - Malaria between 2003 and 2009. An artificial neural network was structured with three neurons in the input layer, two intermediate layers and an output layer with one neuron. A sigmoid activation function was used. In training, the backpropagation method was used, with a learning rate of 0.05 and momentum of 0.01. The stopping criterion was to reach 20,000 cycles or a target of 0.001. The data from 2003 to 2008 were used for training and validation. The results were compared with those from a logistic regression model. RESULTS: The results for all periods provided showed that the artificial neural network had a smaller mean square error and absolute error compared with the regression model for the year 2009. CONCLUSIONS: The artificial neural network proved to be adequate for a malaria forecasting system in the city studied, determining smaller predictive values with absolute errors compared to the logistic regression model and the actual values.

Assessment of inter-examiner agreement and variability in the manual classification of auditory brainstem response

BackgroundThe analysis of the Auditory Brainstem Response (ABR) is of fundamental importance to the investigation of the auditory system behaviour, though its interpretation has a subjective nature because of the manual process employed in its study and the clinical experience required for its analysis. When analysing the ABR, clinicians are often interested in the identification of ABR signal components referred to as Jewett waves. In particular, the detection and study of the time when these waves occur (i.e., the wave latency) is a practical tool for the diagnosis of disorders affecting the auditory system. Significant differences in inter-examiner results may lead to completely distinct clinical interpretations of the state of the auditory system. In this context, the aim of this research was to evaluate the inter-examiner agreement and variability in the manual classification of ABR.MethodsA total of 160 ABR data samples were collected, for four different stimulus intensity (80dBHL, 60dBHL, 40dBHL and 20dBHL), from 10 normal-hearing subjects (5 men and 5 women, from 20 to 52 years). Four examiners with expertise in the manual classification of ABR components participated in the study. The Bland-Altman statistical method was employed for the assessment of inter-examiner agreement and variability. The mean, standard deviation and error for the bias, which is the difference between examiners’ annotations, were estimated for each pair of examiners. Scatter plots and histograms were employed for data visualization and analysis.ResultsIn most comparisons the differences between examiner’s annotations were below 0.1 ms, which is clinically acceptable. In four cases, it was found a large error and standard deviation (>0.1 ms) that indicate the presence of outliers and thus, discrepancies between examiners.ConclusionsOur results quantify the inter-examiner agreement and variability of the manual analysis of ABR data, and they also allows for the determination of different patterns of manual ABR analysis.