Abstract

This paper presents a simplified and effective method for determining heart rate from Electrocardiogram (ECG) signals using MATLAB. It focuses on advanced signal denoising techniques like Empirical Mode Decomposition (EMD), Notch filters, and wavelet transforms. The methodology improves signal quality by removing Power Line Interference (PLI) and Baseline Wander (BW), allowing accurate detection of R-peaks and heart rate. The algorithm’s performance is validated using datasets from the MIT/BIH database, and results are benchmarked against the Pan-Tompkins algorithm. The effectiveness of classification is also evaluated using discrete wavelet transform (DWT) based feature extraction.

References

• C. Levkov and G. Mihov, “Removal of power line interference from the ECG: a review of the subtraction procedure,” Biomedical Engineering Online, vol. 4, no. 50, 2005.
• G. B. Moody, “PhysioNet: A web-based resource for the study of physiologic signals,” IEEE Eng. Med. Biol. Mag., vol. 20, pp. 70, 2001.
• C. S. Weaver et al., “Digital Filtering with applications to electrocardiogram processing,” IEEE Trans. Audio, vol. AU-16, pp. 350, 1968.
• T. P. Taylor and P. W. Macfarlane, “Digital filtering of the ECG – a comparison of lowpass digital filters on a small computer,” Med. & Biol. Engg., vol. 12, pp. 493, 1974.
• P. A. Lynn, “Frequency sampling filters with integer multipliers,” in *Introduction to Digital Filtering*, Wiley, London, 1975.
• P. A. Lynn, “Recursive digital filters for biological signals,” Med. & Biol. Engg., vol. 9, pp. 37, 1971.
• P. S. Hamilton and W. J. Tompkins, “Quantitative investigation of QRS detection rules using the MIT/BIH arrhythmia database,” IEEE Trans. Biomed. Eng., vol. BME-33, pp. 1157, 1986.
• J. Pan and W. J. Tompkins, “A real-time QRS detection algorithm,” IEEE Trans. Biomed. Eng., vol. BME-32, pp. 230, 1985.
• N. V. Thakor, J. G. Webster, and W. J. Tompkins, “Estimation of QRS complex power spectra for design of a QRS filter,” IEEE Trans. Biomed. Eng., vol. BME-31, pp. 702, 1984.
• J. A. Alste and T. S. Schilder, “Removal of baseline wander and power line interference from the ECG by an efficient FIR filter with a reduced number of taps,” IEEE Trans. Biomed. Eng., vol. BME-32, pp. 1052, 1985.
• S. Hargittai, “Efficient and fast ECG baseline wander reduction without distortion of important clinical information,” IEEE Conf. Computers in Cardiology, pp. 841, 2008.
• L. Sornmo, “Time-varying digital filtering of ECG baseline-wander,” Med. Biol. Eng. Comput., vol. 31, pp. 503, 1993.
• J. G. Proakis and D. G. Manolakis, *Digital Signal Processing: Principles, Algorithms and Applications*, 3rd ed., Prentice Hall, 1996.
• M. S. Chavan, R. A. Agarwala, and M. D. Uplane, “Interference reduction in ECG using digital FIR filters based on rectangular window,” WSEAS Trans. Signal Process., vol. 4, pp. 340, 2008.
• M. G. Shayesteh and M. Kashtiban, “FIR filter design using a new window function,” 16th IEEE Int. Conf. Digital Signal Processing, pp. 1, 2009.
• M. S. Chavan, R. A. Agarwala, and M. D. Uplane, “Rectangular window for interference reduction in ECG,” 7th WSEAS Trans. Signal Process., vol. 110, pp. 27, 2008.
• M. S. Chavan, R. A. Agarwala, and M. D. Uplane, “FIR equiripple filter for reduction of power line interference in ECG signal,” 7th Int. Conf. Signal Processing, Robotics and Automation, pp. 147, 2008.
• V. S. Chouhan and S. S. Mehta, “Total removal of baseline drift from ECG signals,” Int. Conf. Computing: Theory and Applications, pp. 512, 2007.
• B. Salsekar and A. K. Wadhwani, “Filtering of ECG signal using Butterworth filter and its feature extraction,” Int. J. Eng. Sci. Technol., vol. 4, pp. 1292, 2012.
• T. T. Choy and P. M. Leung, “Real-time microprocessor-based 50 Hz notch filter for ECG,” J. Biomed. Eng., vol. 10, pp. 285, 1988.
• S. C. Pei and C. C. Tseng, “Elimination of AC interference in electrocardiogram using IIR notch filter with transient suppression,” IEEE Trans. Biomed. Eng., vol. 42, pp. 1128, 1995.
• A. Sander, A. Voss, and G. Griessbach, “An optimized filter system for eliminating 50 Hz interference from high resolution ECG,” Biomed. Tech. Berlin, vol. 40, pp. 82, 1995.