EFECTO DE FILTRADO EN LAS SEÑALES ELECTROCARDIOGRÁFICAS POR MEDIO DE LA APLICACIÓN DE FILTROS BASADOS EN MODELOS POLINOMIALES (FILTERING EFFECT ON ECG SIGNALS THROUGH THE APPLICATION OF FILTERS BASED ON POLYNOMIAL MODEL)
Resumen
De acuerdo con la Organización Mundial de la Salud las enfermedades cardiovasculares (ECV) son la principal causa de muerte en todo el mundo. Por lo tanto, desde hace varias décadas se han diseñado e implementado estrategias para prevenir y/o controlar los factores de riesgo. Recientemente, se han propuesto dispositivos inteligentes que procesan señales de electrocardiografía (ECG) con el propósito de detectar enfermedades cardiacas. Sin embargo, la adquisición y procesamiento de las señales de ECG sigue siendo un tema relevante porque las señales son afectadas por ruido eléctrico y artefactos de movimiento. Por lo tanto, se requieren filtros precisos para eliminar el ruido en estas señales. Este trabajo propone un estudio de aplicar filtros UFIR p-Shift y Savitzky-Golay (S-G) y filtros convencionales en señales ECG con ruido. Los resultados obtenidos indican un rendimiento superior de los filtros basados en modelos polinomiales en comparación con los filtros convencionales, evidenciado por valores promedio de error cuadrático medio de 12.64 y una desviación estándar de 1.49.
Palabras Clave: Estructuras UFIR, Filtro Savitzky-Golay, Señales ECG.
Abstract
According to the World Health Organization (WHO), cardiovascular diseases (CVD) are the leading cause of global mortality. As a result, comprehensive strategies have been devised and implemented over the course of several decades to prevent and/or manage risk factors associated with these conditions. Recently, there have been proposals for smart devices that process electrocardiography (ECG) signals to detect heart diseases. However, the acquisition and processing of ECG signals continue to pose significant challenges due to the interference of electrical noise and motion artifacts. Consequently, the implementation of accurate filters becomes imperative to eliminate noise from these signals. This research puts forth a study that explores the application of UFIR p-Shift and Savitzky-Golay (S-G) filters, as well as conventional filters, on ECG signals contaminated with noise. The findings obtained demonstrate that filters based on polynomial models exhibit superior performance in terms of mean squared error when compared to conventional filters with values 12.64 and a standard deviation of 1.49.
Keywords: ECG signals, UFIR filtering, Savitzky-Golay filter.
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