UPSI Digital Repository (UDRep)
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UPSI Digital Repository (UDRep)
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| Abstract : Universiti Pendidikan Sultan Idris |
| Electrocardiogram (ECG) examination is of great importance in medical diagnosis of the cardiac disease, but wrong interpretation due to noise interference in the signal could be dangerous as this may lead to wrong diagnoses of patient’s heart condition. De-noising helps to reduce the noise level for a better interpretation of the signals. In this study, an analysis of Savitzky-Golay (S-G) filter for ECG de-noising using Daubechies wavelets has been carried out using MATLAB version 2015a. Noisy ECG signals downloaded from physionet.org under MIT-BIH arrhythmia database was de-noised using S-G filter of polynomial order 9 to data frames of length 21 displayed in both time and frequency domains while a quantitative evaluation was carried out to check the performance of the filter under signal-to-noise ratio (SNR), mean square error (MSE) and signal-to-interference ratio (SIR). Results show that de-noising using S-G filter for SNR, MSE, and SIR gives an average value of 32.78dB, 0.0001 and 1852.358dB respectively. This implies that the S-G filter helps eliminates the background noise as well as maintaining a good fit for our data, and also do not allow co-channel interference from other radio transmitters, which makes it an excellent filter for ECG signal de-noising. Hospitals management and cardiac health centers most understand the importance of these parameters in the selection of de-noising filters for good quality ECG in diagnosis and treatment of cardiac patients. |
| References |
Han, G. and Xu, Z. (2016). Electrocardiogram Signal De-noising based on a new improved wavelet thresholding. Review of Scientific Instruments, 87(8), 084303.
Ravandale, Y.V. and Jain, S.N.A. (2015). Review on Methodological Analysis of Noise Reduction in ECG. IOSR Journal of Electronics and Communication Engineering, 21-28, e-ISSN: 2278-2834, p-ISSN: 2278-8735.
Ravindra, P.N., Seema, V. and Singhal, P.K. (2013). Reduction of noise from ECG signal using FIR low pass filter with various window techniques. Current Research in Engineering, Science and Technology Journals, 1(5), 117-122
Subbiah, S., Patro, R. and Rajendran, K. (2014). Reduction of Noises in ECG Signal by Various Filters. International Journal of Engineering Research & Technology, 3(1), 656-660.
Shanmugasundaram, N., Vajubunnisa, B.R., Sushita, K. and Ganesh, E.N. (2019). Design of IIR Notch Filter with Improved Frequency Response. Journal of Applied Science and Computations, 5(12), 1213-1220.
Martis, R.J., Acharya, U.R. and Adeli, H. (2014). Current methods in electrocardiogram characterization. Computers in Biology and Medicine, 48(1), 133-149.
Velayudhan, A. and Peter, S. (2016). Noise Analysis and Different De-noising Techniques of ECG signal-a Survey. IOSR Journal of Electronics and Communication Engineering (IOSR-JECE), 40-44, e-ISSN: 2278-2834, p- ISSN: 2278-8735.
Harjeet, K. and Rajini, R. (2016). ECG Signal de-noising with Savitzky-Golay filter and discrete wavelet transform (DWT). International Journal of Engineering Trends and Technology, 36(5), 266-269. [9] Wedeld, M.D. (2018). Preliminary pre-processing of ECG-signals for use in multivariate analysis. Dissertation, University of Science and Technology Norwegian (Unpublished).
Kohler, B.U., Hennig, C. and Orglmeister, R. (2002). The principles of software QRS detection. IEEE Engineering in Medicine and Biology Magazine, 21(1), 42-57.
Sadhukhan, D. and Mitra, M. (2012). R-peak detection algorithm for ECG using double difference and RR interval processing. Procedia Technology, 4, 873-877.
Thalkar, S. and Upasani, D. (2013). Various Techniques for Removal of Power Line Interference from ECG Signal. International Journal of Science and Engineering Research, 4(12), 12-23.
Fisch, C. (1989). Evolution of the clinical electrocardiogram. Journal of the American College of Cardiology, 14(5), 1127-1138. https://doi.org/10.1016/0735-1097(89)90407-5
Jayes, R.L., Larsen, G.C., Beshansky, J.R., D’Agostino, R.B. and Selker, H.P. (1992). Physician electrocardiogram reading in the emergency department—Accuracy and effect on triage decisions. Journal of General Internal Medicine, 7(4), 387-392.
Rastogi, N. and Mehra, R. (2013). Analysis of butterworth and chebyshev filters for ECG denoising using wavelets. IOSR Journal of Electronics and Communication Engineering, 6(6), 37-44.
Savitzky, A. and Golay, M.J. (1964). Smoothing and differentiation of data by simplified least squares procedures. Analytical Chemistry, 36(8), 1627-1639.
Schafer, R.W. (2011). What is a Savitzky-Golay filter. IEEE Signal Processing Magazine, 28(4), 111-117
Sophocles, J.O. (2010). Introduction to signal processing. Pearson Education Inc, New York City USA.
Press, W.H., Teukolsky, S.A., Vetterling, W.T. and Flannery, B.P. (1992). Numerical recipes in C++. The Art of Scientific Computing, 2(1), 1002.
Daqrouq, K. and Al-Qawasmi, A.R. (2010). ECG enhancement using wavelet transforms. WSEAS Trans Biol Biomed, 7(2), 62-72.
Net Spot (2019a). What is the signal-to-noise ratio and why is it important. https://www.netspotapp.com/help/what-is-the-signal-to-noise/. Accessed 16 March 2020
Bruner, B. (2003). Mean square error: definition and examples. Study. https://study.com/academy/lesson/estimation-of-r-squared-variance-of-epsilon-definition-examples.html. Accessed 18 March 2020
Nnebe, S.U., Onoh, G.N. and Ohaneme, C.O. (2012). Empirical Analysis of Signal-to-Interference Ratio Variations in IEEE 802.11b WLAN. International Journal of Innovative Research in Science, Engineering and Technology, 1(2), 263-670.
Suksompong, P. (2020). Co-channel Interference: Cellular Systems. DocPlayer. https://docplayer.net/31071961-Ecs455-chapter-2-cellular-systems.html. Accessed 04 April 2020
Net Spot (2019b). What is the signal-to-interference ratio? https://www.netspotapp.com/help/signal-to-interference-ratio/. Accessed 16 March 2020
El-Dahshan, E.S.A. (2011). Genetic algorithm and wavelet hybrid scheme for ECG signal denoising. Telecommunication Systems, 46(3), 209–215. https://doi.org/10.1007/s11235-010-9286-2
Hitrangi Sawant, C. and Patil, H.T. (2014). ECG Signal De-noising using Discrete Wavelet Transform. International Journal of Electronics and Communication Computer Engineering, 5(4), 23-28. [28] Sadhukhan, D. and Mitra, M. (2014). ECG noise reduction using Fourier coefficient suppression. In Proceedings of the 2014 International Conference on Control, Instrumentation, Energy and Communication, 142-146. https://doi.org/10.1109/CIEC.2014.6959066.
Sharma, B. and Suji, J. (2016). Analysis of various window techniques used for denoising ECG signal. In 2016 Symposium on Colossal Data Analysis and Networking, pp. 1-5
Alyasseri, Z.A., Khader, A.T., Al-Betar, M.A. and Awadallah, M.A. (2017). Hybridizing β-hill climbing with wavelet transform for denoising ECG signals. Information Sciences, 3(22), 229-46.
Ahmad, A.S.S., Matti, M.S., ALhabib, O.A. and Shaikhow, S. (2018). Denoising of Arrhythmia ECG Signals. International Journal of Medical Research & Health Sciences, 7(3), 83-93.
Krishnamurthy, P., Swethaanjali, N. and Laxshmi, M.A.B. (2015). Comparison of various filtering techniques used for removing high frequency noise in ECG signal. International Journal of Students Research in Technology & Management, 3(1), 211-215.
Sharma, S. and Narwaria, R.P. (2014). Performance Evaluation of Various Window Techniques for Noise Cancellation from ECG Signal. International Journal of Computer Applications, 93(19), 1-5. https://doi.org/10.5120/16464-5826.
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