Métodos de extracción de características en el ECG: análisis comparativo
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Tipo do ITEM
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Artigo Ciêntifico
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Título do Artigo
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Métodos de extracción de características en el ECG: análisis comparativo
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Descrição
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ECG Feature Extraction plays a significant role in diagnosing most of the cardiac diseases. In this paper, a comparison between three ECG feature extraction methods is presented. The methods are: Linear Principal Components Analysis (PCA), Discrete Cosine Transformation (DCT) and Kernel Principal Components Analysis (KPCA). A Multilayer Perceptron is used as classifier and beats for training and validation of the classifier are extracted from twelve MIT – BIH Arrhythmia Database registers. The performance of the three classifiers is discussed and a simple execution time evaluation is performed.
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Abstract
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ECG Feature Extraction plays a significant role in diagnosing most of the cardiac diseases. In this paper, a comparison between three ECG feature extraction methods is presented. The methods are: Linear Principal Components Analysis (PCA), Discrete Cosine Transformation (DCT) and Kernel Principal Components Analysis (KPCA). A Multilayer Perceptron is used as classifier and beats for training and validation of the classifier are extracted from twelve MIT – BIH Arrhythmia Database registers. The performance of the three classifiers is discussed and a simple execution time evaluation is performed.
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Língua do arquivo
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inglês
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Data da Publicação
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Ano Desconhecido
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Autores
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JE Neto A A Suarez-Leon C R Vazquez-Seisdedos N A Lopez-Mora J C Leite y R. C. L. Oliveira
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Local
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UFPA - 2011
