Biogeography Based Optimization based Fuzzy Adaptive Filter for ECG signals denoising.
DOI:
https://doi.org/10.67603/jaate.v1i02.10452Keywords:
Fuzzy logic, fuzzy filter, ECG signal, ECG denoising, BBOAbstract
A novel fuzzy adaptive filter method is presented, which applies fuzzy logic, for electrocardiogram signals denoising. Fuzzy adaptive filter is information processor where both numerical and linguistic information are used in the form of input-output pairs and fuzzy IF-THEN rules. Proposed FAF is based on a recursive procedure to achieve acceptable information extraction in the case where the statistical characteristics of input-output signal are unknown. The filter is displayed as a dual-layered feedback system for the purpose of this study. Each layer has different function: the first layer being the fuzzy autoregressive filter model, the second layer being responsible for the training of the membership functions parameters. The second layer adjusts the fuzzy adaptive filter parameters, which will allow the reaching of the required signal reconstruction by decreasing the fitness based on the biogeography-based optimisation algorithm. For evaluation purposes, various artefacts were added to the ECG signals; these included real and artificial noise. For comparison purposes, the investigation uses both model and non-model-based methods recently published. In addition, the impact of the proposed filtering method on the distortion of diagnostic features of the ECG was investigated using an ECG diagnostic distortion measure called the: Multi-Scale Entropy Based Weighted Distortion Measure
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