Hamici, H.; Kanan, A.; Al-hammuri, K. Optimized FIR Filter Using Genetic Algorithms: A Case Study of ECG Signals Filter Optimization. BioMedInformatics2023, 3, 1197-1215.
Hamici, H.; Kanan, A.; Al-hammuri, K. Optimized FIR Filter Using Genetic Algorithms: A Case Study of ECG Signals Filter Optimization. BioMedInformatics 2023, 3, 1197-1215.
Hamici, H.; Kanan, A.; Al-hammuri, K. Optimized FIR Filter Using Genetic Algorithms: A Case Study of ECG Signals Filter Optimization. BioMedInformatics2023, 3, 1197-1215.
Hamici, H.; Kanan, A.; Al-hammuri, K. Optimized FIR Filter Using Genetic Algorithms: A Case Study of ECG Signals Filter Optimization. BioMedInformatics 2023, 3, 1197-1215.
Abstract
The advancement of 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 the comprehensive analysis of the impact of different genetic operators show that the genetic algorithm-based filter outperforms conventional filter designs.
Keywords
Genetic Algorithms; Digital Filters; Metaheuristic Optimization; Finite Impulse Response (FIR); Side Lobe Level (SLL).
Subject
Computer Science and Mathematics, Mathematical and Computational Biology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
