Navegando por Autor "NETO, João Evangelista"

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    Métodos de extracción de características en el ECG
    (INSTITUTO DE TECNOLOGIA, 2011) NETO, João Evangelista; SUAREZ-LEON, A. A.; VÁZQUEZ-SEISDEDOS, C. R; LÓPEZ-MORA, N. A; LEITE, J. C; OLIVEIRA, R. C. L.; Rui Nelson Otoni Magno
    The article compares three ECG feature extraction methods (Discrete Cosine Transform - DCT, Principal Component Analysis - PCA, and Kernel PCA) for heartbeat classification using an MLP neural network. Results indicate that Kernel PCA achieves the highest accuracy (98.7%) but with longer execution times, while linear PCA is the fastest but less accurate (93%). The study uses data from the MIT-BIH Arrhythmia Database.
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    Two solutions for the processing of ambulatory electrocardiogram
    (INSTITUTO DE TECNOLOGIA, 2015) SEISDEDOS, Carlos R. Vázquez; NETO, João Evangelista; LEÓN, Alexander A. Suárez; OLIVEIRA, Roberto C. Limão de.; Jandecy Cabral Leite
    The paper addresses two challenges in ambulatory electrocardiogram (ECG) processing: identifying valid heartbeats for heart rate variability (HRV) analysis and robust detection of the T-wave end (Te point) under noisy conditions. Proposed methods include computational intelligence techniques (KPCA + MLP) and a trapezoidal area-based algorithm (TRA). Results show superior accuracy and noise resilience compared to conventional approaches.