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Updated: Jan 13, 2026

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Diseño Robusto de la Estructura del Filtro Adaptativo No Lineal de Hammerstein Utilizando un Algoritmo Evolutivo:

Shubham Yadav1, Suman Kumar Saha2, Rajib Kar3

  • 1Department of Computer Science and Engineering, C. V. Raman Global University, Bhubaneswar, Odisha, India. shubham.ydv@gmail.com.

Cardiovascular engineering and technology
|January 6, 2026
PubMed
Resumen

Este estudio mejora la calidad de la señal de electrocardiograma (ECG) eliminando artefactos mediante un novedoso filtro adaptativo de Hammerstein optimizado con la metaheurística del optimizador de crecimiento. El método mejora significativamente la relación señal/ruido y reduce el error cuadrático medio para un análisis más claro de la señal cardíaca.

Palabras clave:
Cancelación adaptativa de ruidoElectrocardiogramaOptimizador de crecimientoModelo de Hammerstein

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Área de la Ciencia:

  • Procesamiento de Señales Biomédicas
  • Inteligencia Computacional
  • Ingeniería Cardiovascular

Sus antecedentes:

  • Las señales de electrocardiograma (ECG) son datos biomédicos de baja amplitud y no estacionarios susceptibles al ruido externo y a los artefactos.
  • La eliminación de artefactos es crucial para la interpretación y el diagnóstico preciso del ECG.
  • Los métodos existentes a menudo tienen dificultades con la naturaleza compleja y no lineal de las señales de ECG y el ruido superpuesto.

Objetivo del estudio:

  • Desarrollar y evaluar una técnica eficiente de eliminación de artefactos para señales de ECG.
  • Optimizar un filtro adaptativo no lineal de Hammerstein utilizando algoritmos metaheurísticos.
  • Evaluar el rendimiento del optimizador de crecimiento en la mejora de la calidad de la señal de ECG.

Principales métodos:

  • Diseño de una estructura de filtro adaptativo no lineal de Hammerstein.
  • Aplicación de algoritmos de optimización metaheurística, incluido el optimizador de crecimiento, la optimización por enjambre de partículas, el algoritmo de polinización de flores y el algoritmo de depredadores marinos.
  • Prueba de la eficacia del filtro en señales de ECG contaminadas con diversos artefactos como ruido muscular y ruido gaussiano blanco.

Principales resultados:

  • El filtro adaptativo de Hammerstein optimizado con el optimizador de crecimiento demostró un rendimiento superior.
  • Se logró una mejora significativa en la relación señal/ruido (SNR) de 12 dB.
  • Se alcanzó un error cuadrático medio (MSE) mínimo de 3.698E-08.
  • Se validaron los resultados de la simulación utilizando un kit de procesador de señales digitales.

Conclusiones:

  • El filtro adaptativo de Hammerstein propuesto basado en el optimizador de crecimiento elimina eficazmente los artefactos de las señales de ECG.
  • La técnica ofrece una mejora significativa con respecto a los métodos existentes más avanzados.
  • Este método es adecuado para aplicaciones prácticas de mejora de señales de ECG.