TY  - 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 .

TY  - JOUR
AU  - Atanasoski, Vladimir
AU  - Petrovic, Jovana
AU  - Popović Maneski, Lana
AU  - Miletić, Marjan
AU  - Babić, Miloš
AU  - Nikolić, Aleksandra
AU  - Panescu, Dorin
AU  - Ivanović, Marija D.
PY  - 2023
UR  - https://dais.sanu.ac.rs/123456789/15362
AB  - Goal: Noise on recorded electrocardiographic (ECG) signals may affect their clinical interpretation. Electromyographic (EMG) noise spectrally coincides with the QRS complex, which makes its removal particularly challenging. The problem of evaluating the noise-removal techniques has commonly been approached by algorithm testing on the contaminated ECG signals constructed ad hoc as an additive mixture of a noise-free ECG signal and noise. Consequently, there is an absence of a unique/standard database for testing and comparing different denoising methods. We present a SimEMG database recorded by a novel acquisition method that allows for direct recording of the genuine EMG-noise-free and -contaminated ECG signals. The database is available as open source.
PB  - Institute of Electrical and Electronics Engineers (IEEE)
T2  - IEEE Open Journal of Engineering in Medicine and Biology
T1  - A database of simultaneously recorded ECG signals with and without EMG noise
SP  - 222
EP  - 4
VL  - 225
DO  - 10.1109/OJEMB.2023.3330295
UR  - https://hdl.handle.net/21.15107/rcub_dais_15362
ER  - 

@article{
author = "Atanasoski, Vladimir and Petrovic, Jovana and Popović Maneski, Lana and Miletić, Marjan and Babić, Miloš and Nikolić, Aleksandra and Panescu, Dorin and Ivanović, Marija D.",
year = "2023",
abstract = "Goal: Noise on recorded electrocardiographic (ECG) signals may affect their clinical interpretation. Electromyographic (EMG) noise spectrally coincides with the QRS complex, which makes its removal particularly challenging. The problem of evaluating the noise-removal techniques has commonly been approached by algorithm testing on the contaminated ECG signals constructed ad hoc as an additive mixture of a noise-free ECG signal and noise. Consequently, there is an absence of a unique/standard database for testing and comparing different denoising methods. We present a SimEMG database recorded by a novel acquisition method that allows for direct recording of the genuine EMG-noise-free and -contaminated ECG signals. The database is available as open source.",
publisher = "Institute of Electrical and Electronics Engineers (IEEE)",
journal = "IEEE Open Journal of Engineering in Medicine and Biology",
title = "A database of simultaneously recorded ECG signals with and without EMG noise",
pages = "222-4",
volume = "225",
doi = "10.1109/OJEMB.2023.3330295",
url = "https://hdl.handle.net/21.15107/rcub_dais_15362"
}

Atanasoski, V., Petrovic, J., Popović Maneski, L., Miletić, M., Babić, M., Nikolić, A., Panescu, D.,& Ivanović, M. D.. (2023). A database of simultaneously recorded ECG signals with and without EMG noise. in IEEE Open Journal of Engineering in Medicine and Biology
Institute of Electrical and Electronics Engineers (IEEE)., 225, 222-4.
https://doi.org/10.1109/OJEMB.2023.3330295
https://hdl.handle.net/21.15107/rcub_dais_15362

Atanasoski V, Petrovic J, Popović Maneski L, Miletić M, Babić M, Nikolić A, Panescu D, Ivanović MD. A database of simultaneously recorded ECG signals with and without EMG noise. in IEEE Open Journal of Engineering in Medicine and Biology. 2023;225:222-4.
doi:10.1109/OJEMB.2023.3330295
https://hdl.handle.net/21.15107/rcub_dais_15362 .

Atanasoski, Vladimir, Petrovic, Jovana, Popović Maneski, Lana, Miletić, Marjan, Babić, Miloš, Nikolić, Aleksandra, Panescu, Dorin, Ivanović, Marija D., "A database of simultaneously recorded ECG signals with and without EMG noise" in IEEE Open Journal of Engineering in Medicine and Biology, 225 (2023):222-4,
https://doi.org/10.1109/OJEMB.2023.3330295 .,
https://hdl.handle.net/21.15107/rcub_dais_15362 .