1,721,016 research outputs found
Identificação de eventos epileptiformes em sinais de EEG com escalogramas como entrada de redes neurais artificiais
Get PDFDissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia Elétrica, Florianópolis, 2015.Esta pesquisa apresenta uma metodologia na identificação de paroxis-mos epileptiformes em sinais de EEG baseada no escalograma Wavelet, que é um mapeio do sinal no tempo e na escala usando uma função Wavelet. Foram avaliadas 65 funções Wavelet das famílias: Daubechies, Biorthogonal, Symlets, Reverse Biorthogonal e Coiflets. Após confor-mar o conjunto de padrões mediante o escalograma foi usada uma rede neural Multi-Layer Perceptron (MLP) para identificar os eventos epileptiformes (espículas e ondas agudas). Foram usados dois bancos de sinais: EEG-Bank-A e EEG-Bank-B, de características totalmente diferentes para testar a metodologia proposta. Propuseram-se duas formas de treinar a rede neural: usando o escalograma diádico completo ou usando as escalas diádicas mais relacionadas à atividade epileptiforme, que demonstraram ser: 25, 26, 27 e 28. O propósito é diminuir a alta redundância de informação do escalograma Wavelet contínuo, diminuindo também o alto custo computacional. Foram treinadas e validadas 260 redes neurais usando o mesmo vetor de pesos inicial. Os testes foram realizados de forma cruzada (entre os bancos), gerando os indicadores de desempenho: sensibilidade, especificidade, valor preditivo positivo, valor preditivo negativo, prevalência, eficiência (EFI) e área abaixo da curva ROC (AUC, Area Under the Curve). As funções Wavelet analisadas foram avaliadas baseadas no produto da área abaixo da curva ROC e da eficiência (AUC x EFI). Para o EEG-Bank-A, foram escolhidas as funções bior3.7, bior3.9 e rbio1.5, obtendo os indicadores de desempenho: sensibilidade de 78,21%, especificidade de 94,52%, valor preditivo positivo de 89,97%, valor preditivo negativo de 87,33%, prevalência de 38,62%, eficiência de 88,22% e AUC de 0,9617. Para o EEG-Bank-B foram escolhidas rbio1.5, rbio1.3 e coif1, obtendo os indicadores de desempenho: sensibilidade de 89,03%, especificidade de 89,33%, valor preditivo positivo de 85,40%, valor preditivo negativo de 92,07%, prevalência de 41,21%, eficiência de 89,20% e AUC de 0,9461. A função rbio1.5 forneceu altos indicadores de desempenho para os dois bancos utilizados. Em geral, todas as funções Wavelet são uteis na identificação de paroxismos epileptiformes, porém as funções daub10 até daub15 atingiram um produto (AUC x EFI) menor de 75%, que foi considerado um valor baixo. O tempo de processamento do sistema proposto foi de 2,5 segundos.Abstract : This research presents a methodology for the identification of epileptiform paroxysms in EEG signals based on Wavelet scalogram that maps the signal in time and scale using a Wavelet function. It was used 65 Wavelet functions of families: Daubechies, Biorthogonal, Symlets, Reverse Biorthogonal and Coiflets. After feature extraction via scalograms it was designed a Multi-Layer Perceptron (MLP) artificial neural network to identify the epileptiform events (spikes and sharp waves). Two banks of signals were used: EEG-Bank-A and EEG-Bank-B which are totally different and they will help to test the proposed methodology. It was proposed two ways for the training stage: using the full dyadic scalogram or the dyadic scales more strongly related to epileptiform activity, the dyadic scales: 25, 26, 27 and 28. The purpose is to decrease high redundancy of information of the CWT also reducing the high computational cost. It was trained 260 neural networks using the same vector of initial weights. The tests were performed using a cross-data technique (between the banks), generating the following indicators of performance: sensitivity, specificity, positive and negative predictive values, prevalence, maximum efficiency and area under the ROC curve (AUC). The Wavelet functions were evaluated based on the AUC x EFI product. For EEG-Bank-A the functions bior3.7, bior3.9 and rbio1.5 were chosen obtaining the indicators of performance: sensitivity of 78.21%, specificity of 94.53%, positive predictive value of 89.97%, negative predictive value of 87.33%, prevalence of 38.62%, maximum efficiency of system of 88.22% and AUC of 0.9617. For EEG-Bank-B were chosen rbio1.5, rbio1.3 and coif1 obtaining the indicators: sensitivity of 89.03%, specificity of 89.33%, positive predictive value of 85.40%, negative predictive value of 92.07%, prevalence of 41.21%, maximum efficiency of 89.20% and AUC of 0.9461. The rbio1.5 function provides high indicators of performance for both banks. In general, all Wavelet functions are useful for the identification of epileptiform paroxysms, even though the function daub10 to daub15 reached AUC x EFI indicators smaller than 75% that was considered a low value. Finally, the processing time of the proposed system was 2.5 seconds
First evidence on a general disease (“d”) factor underlying psychopathology and physical illness in adolescents
No full textThe coexistence of mental and physical health illnesses could be accounted for by an underlying general disease factor (termed d-factor), reflecting theoretical underpinnings based on possible genetic and pathophysiological overlapping mechanisms. This study evaluated whether the d-factor underlies mental and physical health illnesses in adolescents. A series of confirmatory factor analyses were conducted using data from 1120 adolescents. The proposed common underlying factor, we believe is the d-factor, was consistently present across different modeling approaches, including unidimensional, correlated-factor, and bifactor models. The best model fit was achieved with the bifactor model represented by mental, neurological, and psychical conditions tested. The first compelling evidence was provided supporting the existence of the transdiagnostic d-factor in youth, opening the door to innovative research of comorbid mental and physical health conditions.</p
Epilepsy
Get PDFWith the vision of including authors from different parts of the world, different educational backgrounds, and offering open-access to their published work, InTech proudly presents the latest edited book in epilepsy research, Epilepsy: Histological, electroencephalographic, and psychological aspects. Here are twelve interesting and inspiring chapters dealing with basic molecular and cellular mechanisms underlying epileptic seizures, electroencephalographic findings, and neuropsychological, psychological, and psychiatric aspects of epileptic seizures, but non-epileptic as well
Epilepsy
No full textWith the vision of including authors from different parts of the world, different educational backgrounds, and offering open-access to their published work, InTech proudly presents the latest edited book in epilepsy research, Epilepsy: Histological, electroencephalographic, and psychological aspects. Here are twelve interesting and inspiring chapters dealing with basic molecular and cellular mechanisms underlying epileptic seizures, electroencephalographic findings, and neuropsychological, psychological, and psychiatric aspects of epileptic seizures, but non-epileptic as well
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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