Comparison of Digital Filter Orders in Single Lead Electrocardiographic Design for Reducing Interference Motion Artifact
Abstract
Developed a new method to overcome motion artifacts in Electrocardiogram (ECG) signals, which often interfere with accurate clinical analysis. Motion artifacts, such as body movements, can cause significant distortions in the ECG signal, resulting in incorrect interpretation and affecting medical diagnosis. The main objective of this research is to design and implement an infinite impulse response (IIR) filter with a predetermined sequence, namely orders 2, 4, 6, and 8 to reduce motion artifacts in the ECG signal. We aim to improve ECG signal quality by preserving important ECG signal information and reducing noise caused by motion artifacts. This research contributes to developing more precise and reliable ECG signal processing techniques. The proposed method provides an effective approach to handling motion artifacts, enabling more accurate and reliable ECG interpretation by medical professionals. We used an ECG simulator that provides body movement simulation as a basis for experiments. The detected ECG signal is processed with a predetermined order IIR filter. We compare the filtered signal to the original signal to measure the effectiveness of reducing motion artifacts. Experimental results show that the applied IIR filter efficiently reduces motion artifacts in the ECG signal. The SNR assessment showed a significant improvement, proving the success of this method in maintaining ECG signal quality. The result is that in the 2nd order, the SNR value is 22.25 dB, in the 4th order the SNR value is 22.75 dB, in the 6th order the SNR value is 22.99 dB, in the 6th order the SNR value is 22.99 dB. 8 obtained an SNR value of 23dB. This study successfully demonstrated that using IIR filters in a specified order effectively reduces motion artifacts in the ECG signal, increases SNR, and maintains the integrity of clinical information in the ECG signal. The implications of this research extend to medical technology development and clinical applications, providing a strong foundation for continued research in more efficient and reliable ECG signal processing.
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References
A. M. Al-busaidi and L. Khriji, “Digitally Filtered ECG Signal Using Low-Cost Microcontroller,” Int. Conf. Control. Decis. Inf. Technol., pp. 258–263, 2013.
L. W. & Wilkins, “ECG Interpretation Made Incredibly Easy! (5th edition).pdf.” pp. 1–174, 2011.
H. Burri, H. Sunthorn, and D. Shah, “Simulation of anteroseptal myocardial infarction by electrocardiographic filters,” vol. 39, pp. 253–258, 2006, doi: 10.1016/j.jelectrocard.2005.11.001.
R. Panda and U. C. Pati, “Removal of artifacts from electrocardiogram using digital filter,” 2012 IEEE Students’ Conf. Electr. Electron. Comput. Sci. Innov. Humanit. SCEECS 2012, 2012, doi: 10.1109/SCEECS.2012.6184767.
H. K. Jayant, K. P. S. Rana, V. Kumar, S. S. Nair, and P. Mishra, “Efficient IIR Notch Filter Design using Minimax Optimization for 50Hz Noise Suppression in ECG,” pp. 290–295, 2015.
M. Mujahid, U. Faiz, and I. Kale, “Removal of multiple artifacts from ECG signal using cascaded multistage adaptive noise cancellers,” Array, vol. 14, no. October 2021, p. 100133, 2022, doi: 10.1016/j.array.2022.100133.
R. Dozio and M. J. Burke, “Optimised Design of the Front-End Analogue High-Pass Filter for a Diagnostic Quality ECG Monitoring System,” pp. 1770–1773, 2009.
E. A. Suprayitno and A. Arifin, “Sistem Instrumentasi Sinyal Electrocardiography Untukanalisa Dinamika Jantung,” Semin. Nas. Fis. Terap. III , Dep. Fis. FST, Univ. Airlangga Surabaya,15, 2012.
E. Mejía-mejía and P. A. Kyriacou, “Biomedical Signal Processing and Control Effects of noise and filtering strategies on the extraction of pulse rate variability from photoplethysmograms,” Biomed. Signal Process. Control, vol. 80, no. October 2022, 2023.
A. Subasi, T. Tuncer, S. Dogan, D. Tanko, and U. Sakoglu, “Biomedical Signal Processing and Control EEG-based emotion recognition using tunable Q wavelet transform and rotation forest ensemble classifier,” Biomed. Signal Process. Control, vol. 68, no. April, p. 102648, 2021, doi: 10.1016/j.bspc.2021.102648.
T. Tuncer, S. Dogan, and A. Subasi, “EEG-based driving fatigue detection using multilevel feature extraction and iterative hybrid feature selection,” Biomed. Signal Process. Control, vol. 68, no. March, p. 102591, 2021, doi: 10.1016/j.bspc.2021.102591.
A. M. Maghfiroh et al., “State-of-the-Art Method Denoising Electrocardiogram Signal: A Review,” Lect. Notes Electr. Eng., vol. 898, no. 56, pp. 301–310, 2022, doi: 10.1007/978-981-19-1804-9_24.
S. Yudha Setiawan, “Design of Single Lead Electrocardiography using Filter Order 3 to Reduce Noise Using Spektrum Analysis Based on Fast Fourier Transform,” Int. J. Adv. Heal. Sci. Technol., vol. 3, no. 3, pp. 133–139, 2023, doi: 10.35882/ijahst.v3i3.227.
J. Moeyersons et al., “Artefact detection and quality assessment of ambulatory ECG signals,” Comput. Methods Programs Biomed., vol. 182, 2019, doi: 10.1016/j.cmpb.2019.105050.
S. Jain and S. Paul, “Design of filters using current amplifiers for removal of noises from ECG signal,” Procedia Comput. Sci., vol. 218, pp. 1888–1904, 2022, doi: 10.1016/j.procs.2023.01.166.
X. An, Y. Liu, Y. Zhao, S. Lu, G. K. Stylios, and Q. Liu, “Adaptive Motion Artifact Reduction in Wearable ECG Measurements Using Impedance Pneumography Signal,” Sensors, vol. 22, no. 15, 2022, doi: 10.3390/s22155493.
J. Ding, Y. Tang, R. Chang, Y. Li, L. Zhang, and F. Yan, “Reduction in the Motion Artifacts in Noncontact ECG Measurements Using a Novel Designed Electrode Structure,” Sensors, vol. 23, no. 2, 2023, doi: 10.3390/s23020956.
Y. Liu and M. G. Pecht, “Reduction of motion artifacts in electrocardiogram monitoring using an optical sensor,” Biomed. Instrum. Technol., vol. 45, no. 2, pp. 155–163, 2011, doi: 10.2345/0899-8205-45.2.155.
A. Rahmatillah and Ataulkarim, “IIR digital filter design for powerline noise cancellation of ECG signal using arduino platform,” J. Phys. Conf. Ser., vol. 853, no. 1, 2017, doi: 10.1088/1742-6596/853/1/012009.
A. M. Maghfiroh, L. Soetjiatie, B. G. Irianto, T. Triwiyanto, A. Rizal, and N. Hidayanti, “Improved Heart Rate Measurement Accuracy by Reducing Artifact Noise from Finger Sensors Using Digital Filters,” Indones. J. Electron. Electromed. Eng. Med. Informatics, vol. 4, no. 2, pp. 68–77, 2022, doi: 10.35882/ijeeemi.v4i2.4.
J. Duvernoy, Guidance on the Computation of Calibration Uncertainties, no. 119. 2015.
R. King et al., “Nonrecursive Filters,” Digit. Filter. One Two Dimens., pp. 31–64, 1989, doi: 10.1007/978-1-4899-0918-3_2.
L. Tan, Digital Signal Processing Fundamentals and Applications, no. c. Georgia: DeVry University Decatur, 2008.
M. Welvaert and Y. Rosseel, “On the definition of signal-to-noise ratio and contrast-to-noise ratio for fMRI data,” PLoS One, vol. 8, no. 11, 2013, doi: 10.1371/journal.pone.0077089.
E. W. Transform and M. Systems, “Empirical Wavelet Transform and Wavelet,” 2019.
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