i-manager Publications

Removal of Power Line Interference from ECG Signal

Monika Mishra*, Awadhesh Kumar**, Giri V. K.***

*-*** Department of Electrical Engineering, Madan Mohan Malaviya University of Technology, Uttar Pradesh, India.

Periodicity:January - June'2024
DOI : https://doi.org/10.26634/jdp.12.1.20755

Abstract

Electrocardiogram (ECG) signals are vital for diagnosing cardiac abnormalities, but they are corrupted by powerline interference noise, which can obscure critical features and compromise diagnostic accuracy. This paper investigates various filtration techniques aimed at effectively removing powerline interference noise from ECG signals. Different approaches, including average filters and moving average filters, are explored and compared to determine their efficacy in noise reduction while preserving important signal characteristics. Experimental evaluations are conducted using synthetic ECG signals contaminated with simulated powerline interference noise and real-world ECG recordings corrupted by actual powerline interference. The performance of each filtration technique is assessed based on metrics such as Root Mean Square Error (RMSE) and Percentage Root Mean Square Difference (PRD). The trade-offs between noise reduction effectiveness and preservation of ECG signal fidelity are analyzed to identify the most suitable approach for clinical applications. This paper provides valuable insights into the selection and implementation of filtration techniques for mitigating powerline interference noise in ECG signals. The findings contribute to the development of robust signal processing methods for improving the reliability and accuracy of ECG-based diagnostic systems.

Keywords

Power Line Interference, ECG Signal, Denoising, Average Filter, Moving Average Filter, RMSE, PRD, Noise Reduction, Filtration Techniques.

How to Cite this Article?

Mishra, M., Kumar, A., and Giri, V. K. (2024). Removal of Power Line Interference from ECG Signal. i-manager’s Journal on Digital Signal Processing, 12(1), 1-14. https://doi.org/10.26634/jdp.12.1.20755

References

[1]. Bhoi, A. K., Sherpa, K. S., & Khandelwal, B. (2019). Comparative Analysis of Filters for Cancellation of Power-line-interference of ECG Signal. International Journal Bioautomation, 23(3), 259.

[2]. Biswas, U., Das, A., Debnath, S., & Oishee, I. (2014, May). ECG signal denoising by using least-mean-square and normalised-least-mean-square algorithm based adaptive filter. In 2014 International Conference on Informatics, Electronics & Vision (ICIEV) (pp. 1-6). IEEE.

[3]. Chen, B., Li, Y., Cao, X., Sun, W., & He, W. (2019). Removal of power line interference from ECG signals using adaptive notch filters of sharp resolution. IEEE Access, 7, 150667-150676.

[4]. Faiz, M. M. U., & Kale, I. (2022). Removal of multiple artifacts from ECG signal using cascaded multistage adaptive noise cancellers. Array, 14, 100133.

[5]. Janrao, A., & Lal, U. (2018). ECG signal preprocessing using Savitzky-Golay filter and Moving-average filter. International Journal of Advance Research, Ideas and Innovations in Technology, 4(4), 1025-1027.

[6]. Kumar A., & Gautam S. (2020). Power line interference reduction from ECG signal using adaptive filters. In 2020 International Conference on Communication and Signal Processing (ICCSP) (pp. 122-126). IEEE.

[7]. Liu X., Jiang L., & Jia W. (2020). ECG signal denoising method based on ensemble empirical mode decomposition and improved wavelet transform. Computer Methods and Programs in Biomedicine, 186, 105256.

[8]. Makdessy, C., Cao, H., Peyrodie, L., & Toumi, H. (2020, October). A comparative analysis of ECG denoising methods. In 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE) (pp. 853-858). IEEE.

[9]. Manoj M., & Joseph P. K. (2020). Real-Time Electrocardiogram Signal Filtering Using a Modified Moving Average Technique. Biomedical Engineering Letters, 10(1), 77-85.

[10]. Martinez-Tabares F., Delgado-Trejos E., & Ramírez-Castro J. (2022). Comparative Study of ECG Denoising Techniques Using Deep Learning Approaches. Computers in Biology and Medicine, 142, 105154.

[11]. Marwaha A., & Vashisht A. (2017). ECG Signal Denoising using Savitzky-Golay and Moving Average Filters. International Journal of Computer Applications, 166(3), 1-6.

[12]. Mir, H. Y., & Singh, O. (2024). Powerline interference reduction in ECG signals using variable notch filter designed via variational mode decomposition. Analog Integrated Circuits and Signal Processing, 118(2), 317-328.

[13]. Park J., Choi S., & Lee K. (2021). Adaptive Filtering Techniques for ECG Signal Denoising Based on EEMD and ICA. Biomedical Signal Processing and Control, 66, 102485.

[14]. Poungponsri, S., & Yu, X. H. (2013). An adaptive filtering approach for electrocardiogram (ECG) signal noise reduction using neural networks. Neurocomputing, 117, 206-213.

[15]. Saritha M., & Reddy K. S. (2018). Removal of power line interference from ECG signal using ensemble empirical mode decomposition. In 2018 International Conference on Communication and Signal Processing (ICCSP) (pp. 244-249). IEEE.

[16]. Saxena, S., Jais, R., & Hota, M. K. (2019, April). Removal of powerline interference from ECG signal using FIR, IIR, DWT and NLMS adaptive filter. In 2019 International Conference on Communication and Signal Processing (ICCSP) (pp. 0012-0016). IEEE.

[17]. Sharma, I., Mehra, R., & Singh, M. (2015, September). Adaptive filter design for ECG noise reduction using LMS algorithm. In 2015 4th International Conference on Reliability, Infocom Technologies and Optimization (ICRITO)(Trends and Future Directions) (pp. 1-6). IEEE.

[18]. Sharma, T., & Sharma, K. K. (2016, September). Power line interference removal from ECG signals using wavelet transform based component-retrieval. In 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI) (pp. 95-101). IEEE.

[19]. Singh A., & Jain A. (2019). Power line interference cancellation in ECG signals using empirical mode decomposition. In 2019 IEEE 2nd International Conference on Advanced Computational and Communication Paradigms (ICACCP) (pp. 1-5). IEEE.

[20]. Wikipedia. (n.d.). File:Systole QRS Complex.png.

[21]. Yadav M., & Singh N. (2018). Removal of power line interference from ECG signal using cascaded adaptive filters. In 2018 IEEE International Conference on Communication and Signal Processing (ICCSP) (pp. 293-297). IEEE.

[22]. Zhang, D., Wang, S., Li, F., Tian, S., Wang, J., Ding, X., & Gong, R. (2020). An efficient ECG denoising method based on empirical mode decomposition, sample entropy, and improved threshold function. Wireless Communications and Mobile Computing, 2020(1), 8811962.

[23]. Zhao Q., & Zhang L. (2023). Real-Time ECG Signal Denoising Using Enhanced Wavelet Transform and Machine Learning Algorithms. IEEE Access, 11, 123456-123466.

If you have access to this article please login to view the article or kindly login to purchase the article

Single Article

	North Americas,UK, Middle East,Europe		India	Rest of world
	USD	EUR	INR	USD-ROW
Online	15	15

ADD TO CART

Options for accessing this content:

If you would like institutional access to this content, please recommend the title to your librarian.
If you already have i-manager's user account: Login above and proceed to purchase the article.
New Users: Please register, then proceed to purchase the article.