Método para reconhecimento de vogais e extração de parâmetros acústicos para analises forenses

Forensic speaker comparison exams have complex characteristics, demanding a long time for manual analysis. A method for automatic recognition of vowels, providing feature extraction for acoustic analysis is proposed, aiming to contribute as a support tool in these exams. The proposal is based in formant measurements by LPC (Linear Predictive Coding), selectively by fundamental frequency detection, zero crossing rate, bandwidth and continuity, with the clustering being done by the k-means method. Experiments using samples from three different databases have shown promising results, in which the regions corresponding to five of the Brasilian Portuguese vowels were successfully located, providing visualization of a speaker’s vocal tract behavior, as well as the detection of segments corresponding to target vowels.

Hidrocarbonetos policíclicos aromáticos em sedimentos de fundo do estuário do rio Potengi, região da grande Natal (RN): implicações ambientais

Estuaries are environments prone to the input of chemical pollutants of various kinds and origins, including polycyclic aromatic hydrocarbons (PAHs). Anthropogenic PAHs may have two possible sources: pyrolytic (with four or more aromatic rings and low degree of alkylation) and petrogenic (with two and three aromatic rings and high degree of alkylation). This study aimed to evaluate the levels, distribution and possible sources of polycyclic aromatic hydrocarbons in the estuary of the Potengi river, Natal, Brazil. Samples of bottom sediments were collected in the final 12 km of the estuary until its mouth to the sea, where the urbanization of the Great Natal is more concentrated. Sampling was performed on 12 cross sections, with three stations each, totaling 36 samples, identified as T1 to T36. The non alkylated and alkylated PAHs were analyzed by gas chromatography coupled to mass spectrometry (GC / MS). PAHs were detected in all 36 stations with total concentration on each varying 174-109407 ng g-1. These values are comparable to those of several estuarine regions worldwide with high anthropogenic influence, suggesting the record of diffuse contamination installed in the estuary. PAHs profiles were similar for most stations. In 32 of the 36 stations, low molecular weight PAHs (with 2 and 3 ring: naphthalene, phenanthrene and their alkylated homologues) prevailed, which ranged from 54% to 100% of the total PAH, indicating that leaks, spills and combustion fuels are the dominant source of PAH pollution in the estuary. The level of contamination by PAHs in most stations suggests that there is potential risk of occasional adverse biological effects, but in some stations adverse impacts on the biota may occur frequently. The diagnostic ratios could differentiate sources of PAHs in sediments of the estuary, which were divided into three groups: petrogenic, pyrolytic and mixing of sources. The urban concentration of the Great Natal and the various industrial activities associated with it can be blamed as potential sources of PAHs in bottom sediments of the estuary studied. The data presented highlight the need to control the causes of existing pollution in the estuary

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.

Hidrocarbonetos policíclicos aromáticos em sedimentos de fundo do estuário do rio Potengi, região da grande Natal (RN): implicações ambientais

Estuaries are environments prone to the input of chemical pollutants of various kinds and origins, including polycyclic aromatic hydrocarbons (PAHs). Anthropogenic PAHs may have two possible sources: pyrolytic (with four or more aromatic rings and low degree of alkylation) and petrogenic (with two and three aromatic rings and high degree of alkylation). This study aimed to evaluate the levels, distribution and possible sources of polycyclic aromatic hydrocarbons in the estuary of the Potengi river, Natal, Brazil. Samples of bottom sediments were collected in the final 12 km of the estuary until its mouth to the sea, where the urbanization of the Great Natal is more concentrated. Sampling was performed on 12 cross sections, with three stations each, totaling 36 samples, identified as T1 to T36. The non alkylated and alkylated PAHs were analyzed by gas chromatography coupled to mass spectrometry (GC / MS). PAHs were detected in all 36 stations with total concentration on each varying 174-109407 ng g-1. These values are comparable to those of several estuarine regions worldwide with high anthropogenic influence, suggesting the record of diffuse contamination installed in the estuary. PAHs profiles were similar for most stations. In 32 of the 36 stations, low molecular weight PAHs (with 2 and 3 ring: naphthalene, phenanthrene and their alkylated homologues) prevailed, which ranged from 54% to 100% of the total PAH, indicating that leaks, spills and combustion fuels are the dominant source of PAH pollution in the estuary. The level of contamination by PAHs in most stations suggests that there is potential risk of occasional adverse biological effects, but in some stations adverse impacts on the biota may occur frequently. The diagnostic ratios could differentiate sources of PAHs in sediments of the estuary, which were divided into three groups: petrogenic, pyrolytic and mixing of sources. The urban concentration of the Great Natal and the various industrial activities associated with it can be blamed as potential sources of PAHs in bottom sediments of the estuary studied. The data presented highlight the need to control the causes of existing pollution in the estuary

Ambiente para aquisição e processamento de sinal eletromiográfico de superfície

In this work, a platform to the conditioning, digitizing, visualization and recording of the EMG signals was developed. After the acquisition, the analysis can be done by signal processing techniques. The platform consists of two modules witch acquire electromyography (EMG) signals by surface electrodes, limit the interest frequency band, filter the power grid interference and digitalize the signals by the analogue-to- digital converter of the modules microcontroller. Thereby, the data are sent to the computer by the USB interface by the HID specification, displayed in real-time in graphical form and stored in files. As processing resources was implemented the operations of signal absolute value, the determination of effective value (RMS), Fourier analysis, digital filter (IIR) and the adaptive filter. Platform initial tests were performed with signal of lower and upper limbs with the aim to compare the EMG signal laterality. The open platform is intended to educational activities and academic research, allowing the addition of other processing methods that the researcher want to evaluate or other required analysis.

Uma fundamentação para sinais e sistemas intervalares

In this work we use Interval Mathematics to establish interval counterparts for the main tools used in digital signal processing. More specifically, the approach developed here is oriented to signals, systems, sampling, quantization, coding and Fourier transforms. A detailed study for some interval arithmetics which handle with complex numbers is provided; they are: complex interval arithmetic (or rectangular), circular complex arithmetic, and interval arithmetic for polar sectors. This lead us to investigate some properties that are relevant for the development of a theory of interval digital signal processing. It is shown that the sets IR and R(C) endowed with any correct arithmetic is not an algebraic field, meaning that those sets do not behave like real and complex numbers. An alternative to the notion of interval complex width is also provided and the Kulisch- Miranker order is used in order to write complex numbers in the interval form enabling operations on endpoints. The use of interval signals and systems is possible thanks to the representation of complex values into floating point systems. That is, if a number x 2 R is not representable in a floating point system F then it is mapped to an interval [x;x], such that x is the largest number in F which is smaller than x and x is the smallest one in F which is greater than x. This interval representation is the starting point for definitions like interval signals and systems which take real or complex values. It provides the extension for notions like: causality, stability, time invariance, homogeneity, additivity and linearity to interval systems. The process of quantization is extended to its interval counterpart. Thereafter the interval versions for: quantization levels, quantization error and encoded signal are provided. It is shown that the interval levels of quantization represent complex quantization levels and the classical quantization error ranges over the interval quantization error. An estimation for the interval quantization error and an interval version for Z-transform (and hence Fourier transform) is provided. Finally, the results of an Matlab implementation is given

Correlação entre o sinal mecanomiográfico e a escala modificada de Ashworth durante avaliação clínica da espasticidade

Spasticity is a common disorder in people who have upper motor neuron injury. The involvement may occur at different levels. The Modified Ashworth Scale (MAS) is the most used method to measure involvement levels. But it corresponds to a subjective evaluation. Mechanomyography (MMG) is an objective technique that quantifies the muscle vibration during the contraction and stretching events. So, it may assess the level of spasticity accurately. This study aimed to investigate the correlation between spasticity levels determined by MAS with MMG signal in spastic and not spastic muscles. In the experimental protocol, we evaluated 34 members of 22 volunteers, of both genders, with a mean age of 39.91 ± 13.77 years. We evaluated the levels of spasticity by MAS in flexor and extensor muscle groups of the knee and/or elbow, where one muscle group was the agonist and one antagonist. Simultaneously the assessment by the MAS, caught up the MMG signals. We used a custom MMG equipment to register and record the signals, configured in LabView platform. Using the MatLab computer program, it was processed the MMG signals in the time domain (median energy) and spectral domain (median frequency) for the three motion axes: X (transversal), Y (longitudinal) and Z (perpendicular). For bandwidth delimitation, we used a 3rd order Butterworth filter, acting in the range of 5-50 Hz. Statistical tests as Spearman's correlation coefficient, Kruskal-Wallis test and linear correlation test were applied. As results in the time domain, the Kruskal-Wallis test showed differences in median energy (MMGME) between MAS groups. The linear correlation test showed high linear correlation between MAS and MMGME for the agonist muscle as well as for the antagonist group. The largest linear correlation occurred between the MAS and MMG ME for the Z axis of the agonist muscle group (R2 = 0.9557) and the lowest correlation occurred in the X axis, for the antagonist muscle group (R2 = 0.8862). The Spearman correlation test also confirmed high correlation for all axes in the time domain analysis. In the spectral domain, the analysis showed an increase in the median frequency (MMGMF) in MAS’ greater levels. The highest correlation coefficient between MAS and MMGMF signal occurred in the Z axis for the agonist muscle group (R2 = 0.4883), and the lowest value occurred on the Y axis for the antagonist group (R2 = 0.1657). By means of the Spearman correlation test, the highest correlation occurred between the Y axis of the agonist group (0.6951; p <0.001) and the lowest value on the X axis of the antagonist group (0.3592; p <0.001). We conclude that there was a significantly high correlation between the MMGME and MAS in both muscle groups. Also between MMG and MAS occurred a significant correlation, however moderate for the agonist group, and low for the antagonist group. So, the MMGME proved to be more an appropriate descriptor to correlate with the degree of spasticity defined by the MAS.

Estrutura genética populacional de Lutjanus analis cioba e Lutjanus jocu dentão (Lutjanidae) ao longo do litoral brasileiro

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Transcriptoma diferencial entre células-tronco mesenquimais humanas jovens e senescentes

Human mesenchymal stem cells (MSC) are powerful sources for cell therapy in regenerative medicine. The long time cultivation can result in replicative senescence or can be related to the emergence of chromosomal alterations responsible for the acquisition of tumorigenesis features in vitro. In this study, for the first time, the expression profile of MSC with a paracentric chromosomal inversion (MSC/inv) was compared to normal karyotype (MSC/n) in early and late passages. Furthermore, we compared the transcriptome of each MSC in early passages with late passages. MSC used in this study were obtained from the umbilical vein of three donors, two MSC/n and one MSC/inv. After their cryopreservation, they have been expanded in vitro until reached senescence. Total RNA was extracted using the RNeasy mini kit (Qiagen) and marked with the GeneChip ® 3 IVT Express Kit (Affymetrix Inc.). Subsequently, the fragmented aRNA was hybridized on the microarranjo Affymetrix Human Genome U133 Plus 2.0 arrays (Affymetrix Inc.). The statistical analysis of differential gene expression was performed between groups MSC by the Partek Genomic Suite software, version 6.4 (Partek Inc.). Was considered statistically significant differences in expression to p-value Bonferroni correction ˂.01. Only signals with fold change ˃ 3.0 were included in the list of differentially expressed. Differences in gene expression data obtained from microarrays were confirmed by Real Time RT-PCR. For the interpretation of biological expression data were used: IPA (Ingenuity Systems) for analysis enrichment functions, the STRING 9.0 for construction of network interactions; Cytoscape 2.8 to the network visualization and analysis bottlenecks with the aid of the GraphPad Prism 5.0 software. BiNGO Cytoscape pluggin was used to access overrepresentation of Gene Ontology categories in Biological Networks. The comparison between senescent and young at each group of MSC has shown that there is a difference in the expression parttern, being higher in the senescent MSC/inv group. The results also showed difference in expression profiles between the MSC/inv versus MSC/n, being greater when they are senescent. New networks were identified for genes related to the response of two of MSC over cultivation time. Were also identified genes that can coordinate functional categories over represented at networks, such as CXCL12, SFRP1, xvi EGF, SPP1, MMP1 e THBS1. The biological interpretation of these data suggests that the population of MSC/inv has different constitutional characteristics, related to their potential for differentiation, proliferation and response to stimuli, responsible for a distinct process of replicative senescence in MSC/inv compared to MSC/n. The genes identified in this study are candidates for biomarkers of cellular senescence in MSC, but their functional relevance in this process should be evaluated in additional in vitro and/or in vivo assays

Processamento embarcado aplicado a um sistema de deteccão de vazamentos

Embedded systems are widely spread nowadays. An example is the Digital Signal Processor (DSP), which is a high processing power device. This work s contribution consist of exposing DSP implementation of the system logic for detecting leaks in real time. Among the various methods of leak detection available today this work uses a technique based on the pipe pressure analysis and usesWavelet Transform and Neural Networks. In this context, the DSP, in addition to do the pressure signal digital processing, also communicates to a Global Positioning System (GPS), which helps in situating the leak, and to a SCADA, sharing information. To ensure robustness and reliability in communication between DSP and SCADA the Modbus protocol is used. As it is a real time application, special attention is given to the response time of each of the tasks performed by the DSP. Tests and leak simulations were performed using the structure of Laboratory of Evaluation of Measurement in Oil (LAMP), at Federal University of Rio Grande do Norte (UFRN)

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.

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 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.

Implante neural controlado em malha fechada

One of the challenges to biomedical engineers proposed by researchers in neuroscience is brain machine interaction. The nervous system communicates by interpreting electrochemical signals, and implantable circuits make decisions in order to interact with the biological environment. It is well known that Parkinson’s disease is related to a deficit of dopamine (DA). Different methods has been employed to control dopamine concentration like magnetic or electrical stimulators or drugs. In this work was automatically controlled the neurotransmitter concentration since this is not currently employed. To do that, four systems were designed and developed: deep brain stimulation (DBS), transmagnetic stimulation (TMS), Infusion Pump Control (IPC) for drug delivery, and fast scan cyclic voltammetry (FSCV) (sensing circuits which detect varying concentrations of neurotransmitters like dopamine caused by these stimulations). Some softwares also were developed for data display and analysis in synchronously with current events in the experiments. This allowed the use of infusion pumps and their flexibility is such that DBS or TMS can be used in single mode and other stimulation techniques and combinations like lights, sounds, etc. The developed system allows to control automatically the concentration of DA. The resolution of the system is around 0.4 µmol/L with time correction of concentration adjustable between 1 and 90 seconds. The system allows controlling DA concentrations between 1 and 10 µmol/L, with an error about +/- 0.8 µmol/L. Although designed to control DA concentration, the system can be used to control, the concentration of other substances. It is proposed to continue the closed loop development with FSCV and DBS (or TMS, or infusion) using parkinsonian animals models.