Optimized FIR filter using genetic algorithms: A case study of ECG signals filter optimization

Date

2023

Authors

Hamici, Houssam
Kanan, Awos
Al-hammuri, Khalid

Journal Title

Journal ISSN

Volume Title

Publisher

BioMedInformatics

Abstract

The advancement in technology and the availability of specialized digital signal processing chips have made digital filter design and implementation more feasible in a variety of fields, including biomedical engineering. This paper makes two key contributions. First, it uses a genetic algorithm to optimize the coefficients of finite impulse response (FIR) filters. Second, it conducts a case study on using genetic algorithms to optimize FIR filters for electrocardiogram (ECG) biomedical signal noise removal. The goal of the proposed filter design approach is to achieve the desired signal bandwidth while minimizing the side lobe level and eliminating unwanted signals using a genetic algorithm. The results of a comprehensive analysis show that the genetic algorithm-based filter is more effective than conventional filter designs in terms of noise removal efficiency.

Description

Keywords

genetic algorithms, digital filters, metaheuristic optimization, finite impulse response (FIR), side lobe level (SLL)

Citation

Hamici, H., Kanan, A., & Al-hammuri, K. (2023). Optimized FIR filter using genetic algorithms: A case study of ECG signals filter optimization. BioMedInformatics, 3(4), 1197–1215. https://doi.org/10.3390/biomedinformatics3040071