Página 1 dos resultados de 411 itens digitais encontrados em 0.012 segundos

‣ Classification of normal swallowing and oropharyngeal dysphagia using wavelet

SPADOTTO, Andre Augusto; GATTO, Ana Rita; GUIDO, Rodrigo Capobianco; MONTAGNOLI, Arlindo Neto; COLA, Paula Cristina; PEREIRA, Jose Carlos; SCHELP, Arthur Oscar
Fonte: ELSEVIER SCIENCE INC Publicador: ELSEVIER SCIENCE INC
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
78.787803%
Oropharyngeal dysphagia is characterized by any alteration in swallowing dynamics which may lead to malnutrition and aspiration pneumonia. Early diagnosis is crucial for the prognosis of patients with dysphagia, and the best method for swallowing dynamics assessment is swallowing videofluoroscopy, an exam performed with X-rays. Because it exposes patients to radiation, videofluoroscopy should not be performed frequently nor should it be prolonged. This study presents a non-invasive method for the pre-diagnosis of dysphagia based on the analysis of the swallowing acoustics, where the discrete wavelet transform plays an important role to increase sensitivity and specificity in the identification of dysphagic patients. (C) 2008 Elsevier Inc. All rights reserved.

‣ A note on a practical relationship between filter coefficients and scaling and wavelet functions of Discrete Wavelet Transforms

GUIDO, Rodrigo Capobianco
Fonte: PERGAMON-ELSEVIER SCIENCE LTD Publicador: PERGAMON-ELSEVIER SCIENCE LTD
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
89.25579%
In this paper, the relationship between the filter coefficients and the scaling and wavelet functions of the Discrete Wavelet Transform is presented and exemplified from a practical point-of-view. The explanations complement the wavelet theory, that is well documented in the literature, being important for researchers who work with this tool for time-frequency analysis. (c) 2011 Elsevier Ltd. All rights reserved.

‣ Wavelet-based dynamic time warping

BARBON JR., Sylvio; GUIDO, Rodrigo Capobianco; VIEIRA, Lucimar Sasso; FONSECA, Everthon Silva; SANCHEZ, Fabricio Lopes; SCALASSARA, Paulo Rogerio; MACIEL, Carlos Dias; PEREIRA, Jose Carlos; CHEN, Shi-Huang
Fonte: ELSEVIER SCIENCE BV Publicador: ELSEVIER SCIENCE BV
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
78.787803%
Dynamic Time Warping (DTW), a pattern matching technique traditionally used for restricted vocabulary speech recognition, is based on a temporal alignment of the input signal with the template models. The principal drawback of DTW is its high computational cost as the lengths of the signals increase. This paper shows extended results over our previously published conference paper, which introduces an optimized version of the DTW I hat is based on the Discrete Wavelet Transform (DWT). (C) 2008 Elsevier B.V. All rights reserved.

‣ Implementação de um localizador de faltas híbrido para linhas de transmissão com três terminais baseado na transformada wavelet; Implementation of a hybrid fault location for tree-terminals transmission lines based in wavelet transform

Silva, Murilo da
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Tese de Doutorado Formato: application/pdf
Publicado em 15/02/2008 Português
Relevância na Pesquisa
89.65497%
Este trabalho apresenta o estudo e o desenvolvimento de um algoritmo híbrido para detecção, classificação e localização de faltas em sistemas com três terminais utilizando como principal ferramenta a transformada wavelet (TW) em suas versões discreta (TWD) e estacionária (TWE). O algoritmo é dito híbrido, pois alia duas metodologias para localizar a falta. A primeira baseada na análise de componentes de alta freqüência (ondas viajantes) e a segunda, baseada na extração dos componentes fundamentais para o cálculo da impedância aparente. A metodologia proposta foi concebida de maneira a trabalhar com dados sincronizados dos três terminais ou apenas dados locais para estimar a localização da falta. O localizador híbrido escolhe automaticamente qual a melhor técnica de localização ser utilizada para alcançar uma localização confiável e precisa. Deste modo, um método pode suprir as dificuldades do outro, ou, no mínimo, fornecer mais informações para que, junto ao conhecimento do operador, uma localização próxima da ótima possa ser alcançada. Com o objetivo de testar e validar a aplicabilidade do algoritmo de localização de faltas híbrido para linhas com três terminais, utilizou-se de dados de sinais faltosos obtidos através de simulações do software ATP (Altenative Transients Program)...

‣ Categorização de imagens médicas baseada em transformada wavelet e mapas auto-organizáveis.; Medical image categorization based in wavelet transform and self-organizing maps.

Silva, Leandro Augusto da
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Tese de Doutorado Formato: application/pdf
Publicado em 25/03/2009 Português
Relevância na Pesquisa
78.956523%
Nos tempos atuais, as imagens médicas são fonte de dados fundamentais na medicina moderna. As imagens armazenadas em uma base de dados de acordo com as respectivas categorias são um importante passo para aplicações como mineração de dados e recuperação de imagens por conteúdo. Estas aplicações podem apoiar médicos e estudantes na decisão de diagnóstico, permitir pesquisas e ser usadas como material didático. O trabalho propõe o uso de Mapas Auto-Organizáveis (SOM) e TransformadaWavelet combinada com momentos de Hu para a categorização de imagens médicas. Para tanto, são realizados experimentos para definição do tamanho do mapa SOM, uso do mesmo na categorização, definição da melhor família wavelet e nível de decomposição, sumarização dos coeficientes wavelets descartados por momento de Hu e experimentos comparativos com outras abordagens de categorização. Além dos experimentos de classificação comparativos em termos de taxa de acerto, é apresentada uma proposta de contribuição para uso do Mapa SOM na classificação. Nesta proposta, os resultados de classificação e o tempo de recurso computacional despendido pelo Mapa SOM mostram-se eficientes, quando comparados aos resultados e tempo apresentados pelo tradicional classificador K vizinhos mais próximos.; Nowadays...

‣ Classification of normal swallowing and oropharyngeal dysphagia using wavelet

Spadotto, Andre Augusto; Gatto, Ana Rita; Guido, Rodrigo Capobianco; Montagnoli, Arlindo Neto; Cola, Paula Cristina; Pereira, Jose Carlos; Schelp, Arthur Oscar
Fonte: Elsevier B.V. Publicador: Elsevier B.V.
Tipo: Artigo de Revista Científica Formato: 75-82
Português
Relevância na Pesquisa
78.787803%
Oropharyngeal dysphagia is characterized by any alteration in swallowing dynamics which may lead to malnutrition and aspiration pneumonia. Early diagnosis is crucial for the prognosis of patients with dysphagia, and the best method for swallowing dynamics assessment is swallowing videofluoroscopy, an exam performed with X-rays. Because it exposes patients to radiation, videofluoroscopy should not be performed frequently nor should it be prolonged. This study presents a non-invasive method for the pre-diagnosis of dysphagia based on the analysis of the swallowing acoustics, where the discrete wavelet transform plays an important role to increase sensitivity and specificity in the identification of dysphagic patients. (C) 2008 Elsevier B.V. All rights reserved.

‣ Discrete wavelet transform signal analyzer

Cox, Pedro Henrique; de Carvalho, Aparecido Augusto
Fonte: Universidade Estadual Paulista Publicador: Universidade Estadual Paulista
Tipo: Artigo de Revista Científica Formato: 1640-1647
Português
Relevância na Pesquisa
89.14527%
This paper addresses the problem of processing biological data, such as cardiac beats in the audio and ultrasonic range, and on calculating wavelet coefficients in real time, with the processor clock running at a frequency of present application-specified integrated circuits and field programmable gate array. The parallel filter architecture for discrete wavelet transform (DWT) has been improved, calculating the wavelet coefficients in real time with hardware reduced up to 60%. The new architecture, which also processes inverse DWT, is implemented with the Radix-2 or the Booth-Wallace constant multipliers. One integrated circuit signal analyzer in the ultrasonic range, including series memory register banks, is presented. © 2007 IEEE.

‣ Um método não-limiar para redução de ruído em sinais de voz no domínio wavelet

Soares, Wendel Cleber
Fonte: Universidade Estadual Paulista (UNESP) Publicador: Universidade Estadual Paulista (UNESP)
Tipo: Tese de Doutorado Formato: 205 f. : il. (algumas color.)
Português
Relevância na Pesquisa
79.27187%
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq); Pós-graduação em Engenharia Elétrica - FEIS; Neste trabalho é feito um estudo dos métodos de redução de ruído aditivo em sinais de voz baseados em wavelets e, através deste estudo, propõe-se um novo método não-limiar para redução de ruído em sinais de voz no domínio wavelet. Em geral os sinais de voz podem estar contaminados com ruídos artificiais ou reais. O problema consiste que dado um sinal limpo adiciona-se o ruído branco ou colorido, obtendo assim o sinal ruidoso, ambos no domínio do tempo. O que se propõe neste trabalho, é aplicar a transformada wavelet, obtendo assim o sinal transformado no domínio wavelet, reduzindo ou atenuando o ruído sem o uso de limiar. Os métodos mais usados no domínio wavelet são os métodos de redução por limiar, pois permitem bons resultados para sinais contaminados por ruído branco, mas não são eficientes no processamento de sinais contaminados por ruído colorido, que é o tipo de ruído mais comum em situações reais. Nesses métodos, o limiar, geralmente, é calculado nos intervalos de silêncio e aplicado em todo o sinal. Os coeficientes no domínio wavelet são comparados com este limiar e aqueles que estão abaixo deste valor são eliminados ou reduzidos...

‣ The continuous wavelet transform : a primer

Conraria, Luís Aguiar; Soares, M. J.
Fonte: Universidade do Minho. Núcleo de Investigação em Políticas Económicas (NIPE) Publicador: Universidade do Minho. Núcleo de Investigação em Políticas Económicas (NIPE)
Tipo: Trabalho em Andamento
Publicado em //2010 Português
Relevância na Pesquisa
79.39945%
Wavelet analysis is becoming more popular in the Economics discipline. Until recently, most works have made use of tools associated with the Discrete Wavelet Transform. However, after 2005, there has been a growing body of work in Economics and Finance that makes use of the Continuous Wavelet Transform tools. In this article, we give a self-contained summary on the most relevant theoretical results associated with the Continuous Wavelet Transform, the Cross-Wavelet Transform, the Wavelet Coherency and the Wavelet Phase-Difference. We describe how the transforms are usually implemented in practice and provide some examples. We also introduce the Economists to a new class of analytic wavelets, the Generalized Morse Wavelets, which have some desirable properties and provide an alternative to the Morlet Wavelet. Finally, we provide a user friendly toolbox which will allow any researcher to replicate our results and to use it in his/her own research.; Fundação para a Ciência e a Tecnologia (FCT) - Programa Operacional Ciência e Inovação 2010 (POCI 2010); Fundo Europeu de Desenvolvimento Regional (FEDER)

‣ The continuous wavelet transform : a primer

Conraria, Luís Aguiar; Soares, M. J.
Fonte: Universidade do Minho. Núcleo de Investigação em Políticas Económicas Publicador: Universidade do Minho. Núcleo de Investigação em Políticas Económicas
Tipo: Trabalho em Andamento
Publicado em /05/2011 Português
Relevância na Pesquisa
79.38733%
Economists are already familiar with the Discrete Wavelet Transform. However, a body of work using the Continuous Wavelet Transform has also been growing. We provide a self-contained summary on continuous wavelet tools, such as the Continuous Wavelet Transform, the Cross-Wavelet, the Wavelet Coherency and the Phase-Difference. Furthermore, we generalize the concept of simple coherency to Partial Wavelet Coherency and Multiple Wavelet Coherency, akin to partial and multiple correlations, allowing the researcher to move beyond bivariate analysis. Finally, we describe the Generalized Morse Wavelets, a class of analytic wavelets recently proposed. A user-friendly toolbox, with examples, is attached to this paper.; Fundação para a Ciência e a Tecnologia (FCT)

‣ Detection of small bowel tumors in capsule endoscopy frames using texture analysis based on the discrete wavelet transform

Lima, C. S.; Ramos, Jaime; Barbosa, Daniel
Fonte: IEEE-EMBS Publicador: IEEE-EMBS
Tipo: Conferência ou Objeto de Conferência
Publicado em /08/2008 Português
Relevância na Pesquisa
89.26289%
Capsule endoscopy is an important tool to diagnosis tumor lesions in the small bowel. The capsule endoscopic images possess vital information expressed by color and texture. This paper presents an approach based in the textural analysis of the different color channels, using the wavelet transform to select the bands with the most significant texture information. A new image is then synthesized from the selected wavelet bands, trough the inverse wavelet transform. The features of each image are based on second-order textural information, and they are used in a classification scheme using a multilayer perceptron neural network. The proposed methodology has been applied in real data taken from capsule endoscopic exams and reached 98.7% sensibility and 96.6% specificity. These results support the feasibility of the proposed algorithm.; Centre Algoritmi

‣ Abrupt change detection in power system fault analysis using wavelet transform

Ukil, A.; Zivanovic, R.
Fonte: IPST¿05 Publicador: IPST¿05
Tipo: Conference paper
Publicado em //2005 Português
Relevância na Pesquisa
79.17056%
This paper describes the application of the wavelets used to detect the abrupt changes in the signals recorded during disturbances in the electrical power network in South Africa. Main focus has been to estimate exactly the timeinstants of the changes in the signal model parameters during the pre-fault condition and following events like initiation of fault, circuit-breaker opening, auto-reclosure of the circuit-breakers using the wavelet transform, particularly the dyadicorthonormal wavelet transform. The key idea is to decompose the fault signals into effective detailed and smoothed version using the multiresolution signal decomposition technique based on discrete wavelet transform. Then we apply the threshold method on the decomposed signals to estimate the change time-instants, segmenting the fault signals. After segmenting the fault signal precisely into the event-specific sections, further signal processing and analysis can be performed on these segments, leading to automated fault recognition and analysis. In the scope of this paper, we focus on the first task i.e., segmentation of the fault signal into event-specific sections using the wavelet transform and threshold method. This paper presents application on recorded signals in the transmission network of South Africa.; Abhisek Ukil...

‣ Design of bi-orthogonal rational discrete wavelet transform and the associated applications.

Nguyen, Nguyen Si Tran
Fonte: Universidade de Adelaide Publicador: Universidade de Adelaide
Tipo: Tese de Doutorado
Publicado em //2014 Português
Relevância na Pesquisa
99.72829%
Time-frequency analysis has long been a very useful tool in the field of signal processing, especially in dealing with non-stationary signals. Wavelet transform is amongst many time-frequency analysis techniques whose attributes have been well exploited in many classic applications such as de-noising and compression. In recent years, representation sparsity, a measure of the representation’s ability to condense signals’ energy into few coefficients, has raised much interest from researchers in many fields such as signal processing, information theory and applied mathematics due to its wide range of use. Thus, many classes of time-frequency representations have recently been developed from the conventional ones in maximising the representation sparsity recently. Rational discrete wavelet transform (RADWT), an extended class of the conventional wavelet family, is among those representations. This thesis discusses the design of bi-orthogonal rational discrete wavelet transform which is constructed from finite impulse response (FIR) two-channel rational rate filter banks and the associated potential applications. Techniques for designing the bi-orthogonal rational filter bank are proposed, their advantages and disadvantages are discussed and compared with the existing designs in literature. Experimental examples are provided to illustrate the use of the novel bi-orthogonal RADWT in application such as signal separation. The experiments show sparser signal representations with RADWTs over conventional dyadic discrete wavelet transforms (DWTs). This is then exploited in applications such as de-noising and signal separation based on basis pursuit.; Thesis (Ph.D.) -- University of Adelaide...

‣ Directional Complex-Wavelet Processing

Fernandes, Felix; van Spaendonck, Rutger; Burrus, C. Sidney; Fernandes, Felix; van Spaendonck, Rutger; Burrus, C. Sidney
Fonte: Universidade Rice Publicador: Universidade Rice
Tipo: Conference paper
Português
Relevância na Pesquisa
79.440327%
Conference Paper; Poor directional selectivity, a major disadvantage of the separable 2D discrete wavelet transform (DWT), has previously been circumvented either by using highly redundant, nonseparable wavelet transforms or by using restrictive designs to obtain a pair of wavelet trees. In this paper, we demonstrate that superior directional selectivity may be obtained with no redundancy in any separable wavelet transform. We achieve this by projecting the wavelet coefficients to separate approximately the positive and negative frequencies. Subsequent decimation maintains non-redundancy. A novel reconstruction step guarantees perfect reconstruction within this critically-sampled framework. Although our transform generates complex-valued coefficients, it may be implemented with a fast algorithm that uses only real arithmetic. We also explain how redundancy may be judiciously introduced into our transform to benefit certain applications. To demonstrate the efficacy of our projection technique, we show that it achieves state-of-the-art performance in a seismic image-processing application.

‣ Pulmonary crackle characterization: approaches in the use of discrete wavelet transform regarding border effect, mother-wavelet selection, and subband reduction

Quandt,Verônica Isabela; Pacola,Edras Reily; Pichorim,Sérgio Francisco; Gamba,Humberto Remigio; Sovierzoski,Miguel Antônio
Fonte: Sociedade Brasileira de Engenharia Biomédica Publicador: Sociedade Brasileira de Engenharia Biomédica
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/06/2015 Português
Relevância na Pesquisa
99.45355%
Introduction Crackles are discontinuous, non-stationary respiratory sounds and can be characterized by their duration and frequency. In the literature, many techniques of filtering, feature extraction, and classification were presented. Although the discrete wavelet transform (DWT) is a well-known tool in this area, issues like signal border extension, mother-wavelet selection, and its subbands were not properly discussed. Methods In this work, 30 different mother-wavelets 8 subbands were assessed, and 9 border extension modes were evaluated. The evaluations were done based on the energy representation of the crackle considering the mother-wavelet and the border extension, allowing a reduction of not representative subbands. Results Tests revealed that the border extension mode considered during the DWT affects crackle characterization, whereas SP1 (Smooth-Padding of order 1) and ASYMW (Antisymmetric-Padding (whole-point)) modes shall not be used. After DWT, only 3 subbands (D3, D4, and D5) were needed to characterize crackles. Finally, from the group of mother-wavelets tested, Daubechies 7 and Symlet 7 were found to be the most adequate for crackle characterization. Discussion DWT can be used to characterize crackles when proper border extension mode...

‣ A fault location method using Lamb waves and discrete wavelet transform

Souza,Pablo Rodrigo de; Nobrega,Eurípedes Guilherme de Oliveira
Fonte: Associação Brasileira de Engenharia e Ciências Mecânicas - ABCM Publicador: Associação Brasileira de Engenharia e Ciências Mecânicas - ABCM
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/12/2012 Português
Relevância na Pesquisa
99.55472%
Non-destructive evaluation methods and signal process techniques are important steps in structural health monitoring systems to assess the structure integrity. This paper presents a method for fault location in aluminum beams based on time of flight of Lamb waves. The dynamic response signal captured from the structure was processed using the discrete wavelet transform. The information accuracy obtained from the processed signal depends on the correct choice of the mother wavelet. The best mother wavelet was selected using the Shannon's entropy criterion. Numerical results for a damage localized in different positions are presented using the spectral finite element method, and an experimental setup was used to assess the accuracy of the method. The results showed that the combination of the non-destructive evaluation technique based on Lamb waves with the discrete wavelet transform is effective in detecting and locating faults in aluminum beams whose results had errors less than 1%.

‣ Shift invariant wavelet processing of ultrasonic traces

Pardo, Emilia; San Emeterio, José Luis; Rodríguez, Miguel A.; Ramos, Antonio
Fonte: Sociedad Española de Acústica Publicador: Sociedad Española de Acústica
Tipo: Comunicación de congreso Formato: 95147 bytes; application/pdf
Português
Relevância na Pesquisa
79.366387%
Ponencia presentada en el XIX Congreso Internacional de Acústica (ICA2007), Madrid, 2-7 Sep 2007.-- PACS: 43.60.Hj.; Wavelet processing has become a popular and well-established technique that offers good results and great flexibility for noise reduction. The basic wavelet de-noising scheme consists of a thresholding of the Discrete Wavelet Transform (DWT) coefficients. Nevertheless, some improvements over this basic non-linear scheme can be obtained by the use of Undecimated Wavelet Transforms (UWT), also known as redundant, shift-invariant or stationary wavelet transforms, because they provide redundant and translation invariant representations. The introduction of redundancy produces less efficient signal representations but it can be useful in de-noising. Ultrasonic traces are frequently contaminated with structural or grain noise, which can not be removed by classical time averaging or band-pass filtering. An analysis of wavelet de-noising of some individual traces is presented. In addition, a significant number of synthetic ultrasonic signals are also processed for a statistical study and comparison of UWT and DWT de-noising in terms of the signal-to-noise ratio of the resulting traces.; This work has been supported by the Spanish MEC...

‣ A flexible hardware architecture for 2-D discrete wavelet transform: design and FPGA implementation

Carbone, Richard
Fonte: Rochester Instituto de Tecnologia Publicador: Rochester Instituto de Tecnologia
Tipo: Tese de Doutorado
Português
Relevância na Pesquisa
89.38437%
The Discrete Wavelet Transform (DWT) is a powerful signal processing tool that has recently gained widespread acceptance in the field of digital image processing. The multiresolution analysis provided by the DWT addresses the shortcomings of the Fourier Transform and its derivatives. The DWT has proven useful in the area of image compression where it replaces the Discrete Cosine Transform (DCT) in new JPEG2000 and MPEG4 image and video compression standards. The Cohen-Daubechies-Feauveau (CDF) 5/3 and CDF 9/7 DWTs are used for reversible lossless and irreversible lossy compression encoders in the JPEG2000 standard respectively. The design and implementation of a flexible hardware architecture for the 2-D DWT is presented in this thesis. This architecture can be configured to perform both the forward and inverse DWT for any DWTfamily, using fixed-point arithmetic and no auxiliary memory. The Lifting Scheme method is used to perform the DWT instead of the less efficient convolution-based methods. The DWT core is modeled using MATLAB and highly parameterized VHDL. The VHDL model is synthesized to a Xilinx FPGA to prove hardware functionality. The CDF 5/3 and CDF 9/7 versions of the DWT are both modeled and used as comparisons throughout this thesis. The DWT core is used in conjunction with a very simple image denoising module to demonstrate the potential of the DWT core to perform image processing techniques. The CDF 5/3 hardware produces identical results to its theoretical MATLAB model. The fixed point CDF 9/7 deviates very slightly from its floating-point MATLAB model with a ~59dB PSNR deviation for nine levels of DWT decomposition. The execution time for performing both DWTs is nearly identical at -14 clock cycles per image pixel for one level of DWT decomposition. The hardware area generated for the CDF 5/3 is -16...

‣ Change detection in time series using the maximal overlap discrete wavelet transform

Alarcon-Aquino,V.; Barria,J. A.
Fonte: Latin American applied research Publicador: Latin American applied research
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/06/2009 Português
Relevância na Pesquisa
79.669478%
The problem of change detection of time series with abrupt and smooth changes in the spectral characteristics is addressed. We first review the main characteristics of the discrete wavelet transform and the maximal overlap discrete wavelet transform. An algorithm for sequential change detection in time series is then reported based on the maximal overlap discrete wavelet transform and Bayesian analysis. The wavelet-based algorithm checks the wavelet coefficients across resolution levels and locates smooth and abrupt changes in the spectral characteristics in the given time series by using the wavelet coefficients at these levels. Simulation results demonstrate the good detection properties of the proposed algorithm when compared with previous reported algorithms, and also indicate that the quadratic spline and least-asymmetric wavelets have less amount of shift in position after wavelet decomposition and therefore an alignment of events to be detected in a multi-resolution analysis with respect to the original time series is obtained.

‣ Effectiveness of Wavelet Denoising on Electroencephalogram Signals

Mamun,Md.; Al-Kadi,Mahmoud; Marufuzzaman,Mohd.
Fonte: UNAM, Centro de Ciencias Aplicadas y Desarrollo Tecnológico Publicador: UNAM, Centro de Ciencias Aplicadas y Desarrollo Tecnológico
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/02/2013 Português
Relevância na Pesquisa
79.145273%
Analyzing Electroencephalogram (EEG) signal is a challenge due to the various artifacts used by Electromyogram, eye blink and Electrooculogram. The present de-noising techniques that are based on the frequency selective filtering suffers from a substantial loss of the EEG data. Noise removal using wavelet has the characteristic of preserving signal uniqueness even if noise is going to be minimized. To remove noise from EEG signal, this research employed discrete wavelet transform. Root mean square difference has been used to find the usefulness of the noise elimination. In this research, four different discrete wavelet functions have been used to remove noise from the Electroencephalogram signal gotten from two different types of patients (healthy and epileptic) to show the effectiveness of DWT on EEG noise removal. The result shows that the WF orthogonal meyer is the best one for noise elimination from the EEG signal of epileptic subjects and the WF Daubechies 8 (db8) is the best one for noise elimination from the EEG signal on healthy subjects.