Reduction of power line interference in electrocardiographic signals by dual Kalman filtering
Reducción de interferencia de línea de potencia en señales electrocardiográficas mediante el filtro dual de Kalman
DOI:
https://doi.org/10.15446/ing.investig.v27n3.14848Keywords:
Kalman filtering, power line reduction, dual state and parameter estimation, delta operator, electro-cardiogram (en)filtro de Kalman, reducción de línea de potencia, transformada delta, electrocardiograma (es)
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This paper presents a filter for reducing powerline interference in electrocardiographic signals (ECG), based on dual parameter and state estimation using with a Kalman filter. Two models were used to represent power-line interference and ECG signal. Both models were combined to simulate the ECG signal whose state was estimated for separating the ECG signal from the interference. The proposed algorithm was fine-tuned and compared using a set of tests relying on the QT arrhythmia database. Tuning tests were done for tracking clean ECG; these results were used for setting the algorithm’s parameters for later filtering tests. Exhaustive filtering tests were carried out on artificially corrupted database registers for given signal to noise ratios; performance curves were thus obtained, leading to comparing the proposed algorithm with other filtering methods. The proposed algorithm was compared to an recursive infinite impulse response filter (IIR) and a Kalman filter based on a simpler model. A filtering algorithm was thus obtained which is robust for changes in interference amplitude and keeps these properties for different types of ECG morphologies.
En este artículo se presenta el desarrollo de un filtro para la reducción de la interferencia de línea de potencia en señales electrocardiográficas (ECG), basado en estimación dual de parámetros y de estado, empleando la filtración Kalman, en el cual se consideran modelos independientes entre la interferencia de línea de potencia y la señal ECG. Ambos modelos son combinados para simular la señal ECG medida sobre la que se realiza la estimación de estado para separar la señal de la interferencia. El algoritmo propuesto es sintonizado y comparado en un conjunto de pruebas realizadas sobre la base de datos QT de electrocardiografía. Inicialmente se hacen pruebas de sintonización del algoritmo para el rastreo de la señal ECG limpia, cuyos resultados son utilizados después para las pruebas de filtrado. Luego se llevan a cabo pruebas exhaustivas sobre la base de datos QT en la filtración de interferencia de línea de potencia, la cual ha sido introducida artificialmente en los registros, para una relación de señal a ruido (SNR) dada, obteniendo así curvas del desempeño del algoritmo, que permiten a su vez comparar con el desempeño de otros algoritmos de filtración, a saber, un filtro notch recursivo de respuesta infinita al impulso (IIR) y un filtro de Kalman, basado en un modelo más simple para la señal ECG. Como resultado, se demuestra que el algoritmo de filtrado obtenido es robusto a los cambios de amplitud de la interferencia; además, conserva sus propiedades para los diferentes tipos de morfologías de señales ECG normales y patológicas.
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1. Roshan M. Bodile, T. V. K. Hanumantha Rao. (2021). Computational Vision and Bio-Inspired Computing. Advances in Intelligent Systems and Computing. 1318, p.175. https://doi.org/10.1007/978-981-33-6862-0_15.
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