Parameters for vocal acoustic analysis - cured database

This paper describes the construction and organization of a database of speech parameters extracted from a speech database. This article intends to inform the community about the existence of this database for future research. The database includes parameters extracted from sounds produced by patients distributed among 19 diseases and control subjects. The set of parameters of this database consists of the jitter, shimmer, Harmonic to Noise Ratio (HNR), Noise to Harmonic Ratio (NHR), autocorrelation and Mel Frequency Cepstral Coefficients (MFCC) extracted from the sound of sustained vowels /a/, /i/ and /u/ at the high, low and normal tones, and a short German sentence. The cured database has a total number of 707 pathological subjects (distributed by the various diseases) and 194 control subjects, in a total of 901 subjects.info:eu-repo/semantics/publishedVersio

Outliers treatment to improve the recognition of voice pathologies

In some of the processes used in data analysis, such as the recognition of pathologies and pathological subjects, the presence of anomalous instances in the dataset is an unfavorable situation that can lead to misleading results. This article presents a function that implements the identification of anomalies in dataset using the boxplot and standard deviation methods. Also was used the filling technique to treat these anomalies, in which the anomalous point value were substituted by a limit value determined by the boxplot or standard deviation methods. To improve the outliers methods some normalization processes based on the z-score, logarithmic and squared root methodologies were experimented. These outliers treatment were applied to the dataset used in the recognition of vocal pathologies (dysphonia, chronic laryngitis and vocal cords paralysis vs control), performed by a MLP and LSTM neural networks. After the experiments, both the standard deviation and the boxplot methods with z-score normalization showed very useful for pre-processing the dataset for voice pathologies recognition. The accuracy was improved between 3 and 13 points in percentage.info:eu-repo/semantics/publishedVersio

Transfer learning with audioSet to voice pathologies identification in continuous speech

The classification of pathological diseases with the implementation of concepts of Deep Learning has been increasing considerably in recent times. Among the works developed there are good results for the classification in sustained speech with vowels, but few related works for the classification in continuous speech. This work uses the German Saarbrücken Voice Database with the phrase “Guten Morgen, wie geht es Ihnen?” to classify four classes: dysphonia, laryngitis, paralysis of vocal cords and healthy voices. Transfer learning concepts were used with the AudioSet database. Two models were developed based on Long-Short-Term-Memory and Convolutional Network for classification of extracted embeddings and comparison of the best results, using cross-validation. The final results allowed to obtaining 40% of f1-score for the four classes, 66% f1-score for Dysphonia x Healthy, 67% for Laryngitis x healthy and 80% for Paralysis x Healthy.info:eu-repo/semantics/publishedVersio

Ceramic piece productinon through the slip casting technique using clay from the Jacobina-Bahia area

The identity of Bahia is based on pillars that are reinforced every year. As main goal, this work approaches an ancient technique of producing ceramic pieces using the clay found in the region of Jacobina-BA by casting slip – a widely used technique and of low cost. To use the minerals collected, a characterization of the materials was carried out, using techniques as X-Ray Diffraction, X-Ray Fluorescence and Thermal Analysis. Although it is a simple process, it is necessary to monitor and study it in order to obtain the required knowledge to execute the project, always regarding the ecology and the promotion of arts and decoration, the real purpose of those techniques.A identidade da Bahia está baseada em pilares que são reforçados a cada ano. Como principal objetivo, o presente trabalho aborda uma antiga técnica para criação de peças cerâmicas utilizando argilas oriundas da região de Jacobina-BA por meio da colagem de barbotina - técnica amplamente difundida e de baixo custo. Para a utilização dos minerais dali retirados fez-se necessária uma caracterização dos materiais empregados, feita por meio de técnicas como Difração de Raio-X, Fluorescência de Raio-X e Análises Térmicas. Embora trate-se de um processo simples faz-se necessário o acompanhamento e estudo para a obtenção dos conhecimentos mínimos para a execução do projeto, tendo em vista sempre a questão ecológica e o fomento à área de artes e decoração, a que se destina as técnicas de fato.São Cristóvão, S

Epilepsy Detection Using Artificial Neural Networks

Epilepsy is a neurological disorder, where there is a cluster of brain cells that behave in a hyperexcitable manner, the individual can promote injuries, trauma or, in more severe cases, sudden death. Electroencephalogram (EEG) is the most used way to detect epileptic seizures. Therefore, more simplified methods of analysis of the EEG can help in the diagnosis and treatment of these individuals more quickly. In this study, we extracted pertinent EEG characteristics to assess the epileptic seizure period. We use Perceptron Multilayer artificial neural networks to classify the period of the crisis, obtaining a more efficient diagnosis. The multilayer neural network obtained an accuracy of 98%. Thus, the strategy of extracting characteristics and the architecture of the assigned network were sufficient for a rapid and accurate diagnosis of epilepsy

Perfil clínico das gestantes com síndromes hipertensivas atendidas no CAIS da Mulher em Anápolis-GO

As síndromes hipertensivas na gestação são classificadas em quatro categorias: pré-eclâmpsia/eclâmpsia, hipertensão arterial crônica, hipertensão arterial crônica com pré-eclâmpsia superajuntada e hipertensão gestacional. As crises hipertensivas são caracterizadas por um aumento acentuado da pressão arterial, que pode acarretar, para a gestante e o feto, complicações graves e até levar ao óbito. Este estudo tem como objetivo descrever o perfil clínico de gestantes com síndromes hipertensivas, além de identificar a ocorrência de complicações obstétricas decorrentes. Trata-se de um estudo observacional transversal analítico. Será realizado no município de Anápolis - Goiás por meio de coleta dos dados com aplicação de questionários, em uma população de 46 gestantes, entre o período de agosto a dezembro de 2023. As características sociodemográficas avaliadas serão: faixa etária; etnia; nível de escolaridade; renda familiar; estado marital; profissão. As variáveis clínico-epidemiológicas serão: medidas da pressão arterial; número de gestações; idade gestacional; comorbidades. Espera-se relatar o perfil das gestantes com síndromes hipertensivas, bem como as complicações obstétricas relacionadas. Dessa maneira, identificar a prevalência e as variáveis clínicas mais recorrentes das pacientes avaliadas no CAIS da Mulher no município de Anápolis – GO. Portanto, com o presente estudo espera-se contribuir para o arcabouço literário do tema abordado e enfatizar que é fundamental ampliar a compreensão do fenômeno estudado, a fim de prevenir os agravos decorrentes das síndromes hipertensivas na gravidez