A morphology-preserving algorithm for denoising of EMG-contaminated ECG signals
Autori
Atanasoski, VladimirPetrović, Jovana
Popović Maneski, Lana
Miletić, Marjan
Babić, Miloš
Nikolić, Aleksandra
Panescu, Dorin
Ivanović, Marija D.
Članak u časopisu (Objavljena verzija)
Metapodaci
Prikaz svih podataka o dokumentuApstrakt
Goal: Clinical interpretation of an electrocardiogram (ECG) can be detrimentally affected by noise. Removal of the electromyographic (EMG) noise is particularly challenging due to its spectral overlap with the QRS complex. The existing EMG-denoising algorithms often distort signal morphology, thus obscuring diagnostically relevant information. Methods: Here, a new iterative regeneration method (IRM) for efficient EMG-noise suppression is proposed. The main hypothesis is that the temporary removal of the dominant ECG components enables extraction of the noise with the minimum alteration to the signal. The method is validated on SimEMG database of simultaneously recorded reference and noisy signals, MIT-BIH arrhythmia database and synthesized ECG signals, both with the noise from MIT Noise Stress Test Database. Results: IRM denoising and morphology-preserving performance is superior to the wavelet- and FIR-based benchmark methods. Conclusions : IRM is reliable, computationally non-intens...ive, fast and applicable to any number of ECG channels recorded by mobile or standard ECG devices.
Ključne reči:
electromyography / electrocardiography / ECG acquisition / EMG noise / heart beat / filtering / IIR filters / signal to noise ratioIzvor:
IEEE Open Journal of Engineering in Medicine and Biology, 2024, 1-10Izdavač:
- Institute of Electrical and Electronics Engineers (IEEE)
Finansiranje / projekti:
- Ministarstvo nauke, tehnološkog razvoja i inovacija Republike Srbije, institucionalno finansiranje - 200175 (Institut tehničkih nauka SANU, Beograd) (RS-MESTD-inst-2020-200175)
- Ministarstvo nauke, tehnološkog razvoja i inovacija Republike Srbije, institucionalno finansiranje - 200017 (Univerzitet u Beogradu, Institut za nuklearne nauke Vinča, Beograd-Vinča) (RS-MESTD-inst-2020-200017)
Institucija/grupa
Институт техничких наука САНУ / Institute of Technical Sciences of SASATY - JOUR AU - Atanasoski, Vladimir AU - Petrović, Jovana AU - Popović Maneski, Lana AU - Miletić, Marjan AU - Babić, Miloš AU - Nikolić, Aleksandra AU - Panescu, Dorin AU - Ivanović, Marija D. PY - 2024 UR - https://dais.sanu.ac.rs/123456789/16515 AB - Goal: Clinical interpretation of an electrocardiogram (ECG) can be detrimentally affected by noise. Removal of the electromyographic (EMG) noise is particularly challenging due to its spectral overlap with the QRS complex. The existing EMG-denoising algorithms often distort signal morphology, thus obscuring diagnostically relevant information. Methods: Here, a new iterative regeneration method (IRM) for efficient EMG-noise suppression is proposed. The main hypothesis is that the temporary removal of the dominant ECG components enables extraction of the noise with the minimum alteration to the signal. The method is validated on SimEMG database of simultaneously recorded reference and noisy signals, MIT-BIH arrhythmia database and synthesized ECG signals, both with the noise from MIT Noise Stress Test Database. Results: IRM denoising and morphology-preserving performance is superior to the wavelet- and FIR-based benchmark methods. Conclusions : IRM is reliable, computationally non-intensive, fast and applicable to any number of ECG channels recorded by mobile or standard ECG devices. PB - Institute of Electrical and Electronics Engineers (IEEE) T2 - IEEE Open Journal of Engineering in Medicine and Biology T1 - A morphology-preserving algorithm for denoising of EMG-contaminated ECG signals SP - 1 EP - 10 DO - 10.1109/OJEMB.2024.3380352 UR - https://hdl.handle.net/21.15107/rcub_dais_16515 ER -
@article{ author = "Atanasoski, Vladimir and Petrović, Jovana and Popović Maneski, Lana and Miletić, Marjan and Babić, Miloš and Nikolić, Aleksandra and Panescu, Dorin and Ivanović, Marija D.", year = "2024", abstract = "Goal: Clinical interpretation of an electrocardiogram (ECG) can be detrimentally affected by noise. Removal of the electromyographic (EMG) noise is particularly challenging due to its spectral overlap with the QRS complex. The existing EMG-denoising algorithms often distort signal morphology, thus obscuring diagnostically relevant information. Methods: Here, a new iterative regeneration method (IRM) for efficient EMG-noise suppression is proposed. The main hypothesis is that the temporary removal of the dominant ECG components enables extraction of the noise with the minimum alteration to the signal. The method is validated on SimEMG database of simultaneously recorded reference and noisy signals, MIT-BIH arrhythmia database and synthesized ECG signals, both with the noise from MIT Noise Stress Test Database. Results: IRM denoising and morphology-preserving performance is superior to the wavelet- and FIR-based benchmark methods. Conclusions : IRM is reliable, computationally non-intensive, fast and applicable to any number of ECG channels recorded by mobile or standard ECG devices.", publisher = "Institute of Electrical and Electronics Engineers (IEEE)", journal = "IEEE Open Journal of Engineering in Medicine and Biology", title = "A morphology-preserving algorithm for denoising of EMG-contaminated ECG signals", pages = "1-10", doi = "10.1109/OJEMB.2024.3380352", url = "https://hdl.handle.net/21.15107/rcub_dais_16515" }
Atanasoski, V., Petrović, J., Popović Maneski, L., Miletić, M., Babić, M., Nikolić, A., Panescu, D.,& Ivanović, M. D.. (2024). A morphology-preserving algorithm for denoising of EMG-contaminated ECG signals. in IEEE Open Journal of Engineering in Medicine and Biology Institute of Electrical and Electronics Engineers (IEEE)., 1-10. https://doi.org/10.1109/OJEMB.2024.3380352 https://hdl.handle.net/21.15107/rcub_dais_16515
Atanasoski V, Petrović J, Popović Maneski L, Miletić M, Babić M, Nikolić A, Panescu D, Ivanović MD. A morphology-preserving algorithm for denoising of EMG-contaminated ECG signals. in IEEE Open Journal of Engineering in Medicine and Biology. 2024;:1-10. doi:10.1109/OJEMB.2024.3380352 https://hdl.handle.net/21.15107/rcub_dais_16515 .
Atanasoski, Vladimir, Petrović, Jovana, Popović Maneski, Lana, Miletić, Marjan, Babić, Miloš, Nikolić, Aleksandra, Panescu, Dorin, Ivanović, Marija D., "A morphology-preserving algorithm for denoising of EMG-contaminated ECG signals" in IEEE Open Journal of Engineering in Medicine and Biology (2024):1-10, https://doi.org/10.1109/OJEMB.2024.3380352 ., https://hdl.handle.net/21.15107/rcub_dais_16515 .