Enhancement of the Comb Filtering Selectivity Using Iterative Moving Average for Periodic Waveform and Harmonic Elimination
| Autor: | JL Jose Ferreira, Yan Wu, Ronald M. Aarts |
|---|---|
| Přispěvatelé: | Signal Processing Systems, Biomedical Diagnostics Lab |
| Rok vydání: | 2018 |
| Předmět: |
lcsh:Medical technology
Article Subject Computer science Biomedical Engineering Health Informatics 02 engineering and technology Stopband 03 medical and health sciences Computer-Assisted 0302 clinical medicine Models Moving average 0202 electrical engineering electronic engineering information engineering Humans Waveform Comb filter lcsh:R5-920 Models Statistical Attenuation 020208 electrical & electronic engineering Bandwidth (signal processing) Electroencephalography Signal Processing Computer-Assisted Filter (signal processing) Fundamental frequency Statistical Magnetic Resonance Imaging lcsh:R855-855.5 Signal Processing Surgery lcsh:Medicine (General) Artifacts Algorithm Algorithms Software 030217 neurology & neurosurgery Research Article Biotechnology |
| Zdroj: | Journal of Healthcare Engineering, 2018:7901502. Multi-Science Publishing Co. Ltd Journal of Healthcare Engineering Journal of Healthcare Engineering, Vol 2018 (2018) |
| ISSN: | 2040-2309 2040-2295 |
| DOI: | 10.1155/2018/7901502 |
| Popis: | A recurring problem regarding the use of conventional comb filter approaches for elimination of periodic waveforms is the degree of selectivity achieved by the filtering process. Some applications, such as the gradient artefact correction in EEG recordings during coregistered EEG-fMRI, require a highly selective comb filtering that provides effective attenuation in the stopbands and gain close to unity in the pass-bands. In this paper, we present a novel comb filtering implementation whereby the iterative filtering application of FIR moving average-based approaches is exploited in order to enhance the comb filtering selectivity. Our results indicate that the proposed approach can be used to effectively approximate the FIR moving average filter characteristics to those of an ideal filter. A cascaded implementation using the proposed approach shows to further increase the attenuation in the filter stopbands. Moreover, broadening of the bandwidth of the comb filtering stopbands around −3 dB according to the fundamental frequency of the stopband can be achieved by the novel method, which constitutes an important characteristic to account for broadening of the harmonic gradient artefact spectral lines. In parallel, the proposed filtering implementation can also be used to design a novel notch filtering approach with enhanced selectivity as well. |
| Databáze: | OpenAIRE |
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