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Stefan cel Mare
University of Suceava
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Print ISSN: 1582-7445
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WorldCat: 643243560
doi: 10.4316/AECE


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  3/2020 - 5

Shannon Energy Application for Detection of ECG R-peak using Bandpass Filter and Stockwell Transform Methods

SUBOH, M. Z. See more information about SUBOH, M. Z. on SCOPUS See more information about SUBOH, M. Z. on IEEExplore See more information about SUBOH, M. Z. on Web of Science, JAAFAR, R. See more information about  JAAFAR, R. on SCOPUS See more information about  JAAFAR, R. on SCOPUS See more information about JAAFAR, R. on Web of Science, NAYAN, N. A. See more information about  NAYAN, N. A. on SCOPUS See more information about  NAYAN, N. A. on SCOPUS See more information about NAYAN, N. A. on Web of Science, HARUN, N. H. See more information about HARUN, N. H. on SCOPUS See more information about HARUN, N. H. on SCOPUS See more information about HARUN, N. H. on Web of Science
 
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Download PDF pdficon (1,321 KB) | Citation | Downloads: 909 | Views: 2,645

Author keywords
biomedical signal processing, spectral analysis, electrocardiography, detection algorithms, signal processing algorithms

References keywords
signal(8), detection(7), transform(5), comput(5), biomed(5), wavelet(4), shannon(4), hilbert(4), energy(4), electrocardiogram(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2020-08-31
Volume 20, Issue 3, Year 2020, On page(s): 41 - 48
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2020.03005
Web of Science Accession Number: 000564453800005
SCOPUS ID: 85090323119

Abstract
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Shannon energy-based algorithm has been implemented in peak detection method of various physiological signals including electrocardiogram, which is used to enhance significant peaks for accurate peak detection. Two significant methods of R-peak detection that apply Shannon energy are identified. However, direct comparison cannot be made due to the differences in database used, number of beat analysed, frequency range selected, and signal processing technique applied. This paper aimed to properly evaluate the performance of Shannon energy-based algorithms for R-peak detection on two methods of bandpass filter and Stockwell transform. Simple enveloping technique using moving average filter is proposed, and a threshold is set to localize R-peak at a selected frequency range of 7-15 Hz. Performance of both methods were then evaluated using all 48 data from MIT-BIH Arrhythmia database. Result showed that both methods are equivalently useful in reducing P and T waves interference and produced similar output of Shannon energy envelope. However, Shannon energy application on bandpass filter offered 99.71% sensitivity, 99.80% positive predictivity and 99.52% accuracy, slightly better than that of the Stockwell transform method that only produced 99.65% sensitivity, 99.68% positive predictivity and 99.33% accuracy.


References | Cited By  «-- Click to see who has cited this paper

[1] R. McCraty and F. Shaffer, "Heart rate variability: New perspectives on physiological mechanisms, assessment of self-regulatory capacity, and health risk," Glob. Adv. Heal. Med., vol. 4, no. 1, pp. 46-61, 2015,
[CrossRef] [SCOPUS Times Cited 643]


[2] P. Laguna et al., "New algorithm for QT interval analysis in 24-hour Holter ECG: performance and applications," Med. Biol. Eng. Comput., vol. 28, no. 1, pp. 67-73, 1990,
[CrossRef] [Web of Science Times Cited 163] [SCOPUS Times Cited 185]


[3] P. Laguna, R. Jane, and C. Pere, "Automatic detection of wave boundaries in multilead ECG," Computers and Biomedical Research, vol. 27. pp. 45-60, 1994.
[CrossRef] [Web of Science Times Cited 344] [SCOPUS Times Cited 398]


[4] B. Frenay, G. De Lannoy, and M. Verleysen, "Emission modelling for supervised ecg segmentation using finite differences," IFMBE Proc., vol. 22, pp. 1212-1216, 2008,
[CrossRef] [SCOPUS Times Cited 6]


[5] G. Schreier, D. Hayn, and S. Lobodzinski, "Development of a New QT Algorithm with Heterogenous ECG Databases," J. Electrocardiol., vol. 36, no. SUPPL., pp. 145-150, 2003,
[CrossRef] [Web of Science Times Cited 11] [SCOPUS Times Cited 15]


[6] J. A. Vila, Y. Gang, J. M. R. Presedo, M. Fernândez-Delgado, S. Barro, and M. Malik, "A new approach for TU complex characterization," IEEE Trans. Biomed. Eng., vol. 47, no. 6, pp. 764-772, 2000,
[CrossRef] [Web of Science Times Cited 71] [SCOPUS Times Cited 86]


[7] R. Gupta, M. Mitra, K. Mondal, and S. Bhowmick, "A derivative-based approach for QT-segment feature extraction in digitized ECG record," Proc. - 2nd Int. Conf. Emerg. Appl. Inf. Technol. EAIT 2011, pp. 63-66, 2011,
[CrossRef] [SCOPUS Times Cited 20]


[8] I. S. N. Murthy and U. C. Niranjan, "Component wave delineation of ECG by filtering in the Fourier domain," Med. Biol. Eng. Comput., vol. 30, no. 2, pp. 169-176, 1992,
[CrossRef] [Web of Science Times Cited 27] [SCOPUS Times Cited 26]


[9] H. Li and X. Wang, "Detection of electrocardiogram characteristic points using lifting wavelet transform and Hilbert transform," Trans. Inst. Meas. Control, vol. 35, no. 5, pp. 574-582, 2013,
[CrossRef] [Web of Science Times Cited 36] [SCOPUS Times Cited 43]


[10] K. Friganovic, D. Kukolja, A. Jovic, M. Cifrek, and G. Krstacic, "Optimizing the Detection of Characteristic Waves in ECG Based on Processing Methods Combinations," IEEE Access, vol. 6, 2018,
[CrossRef] [Web of Science Times Cited 20] [SCOPUS Times Cited 24]


[11] J. P. Martinez, R. Almeida, S. Olmos, A. P. Rocha, and P. Laguna, "A Wavelet-Based ECG Delineator Evaluation on Standard Databases," IEEE Trans. Biomed. Eng., vol. 51, no. 4, pp. 570-581, 2004,
[CrossRef] [Web of Science Times Cited 1105] [SCOPUS Times Cited 1366]


[12] J. P. V. Madeiro, P. C. Cortez, J. A. L. Marques, C. R. V. Seisdedos, and C. R. M. R. Sobrinho, "An innovative approach of QRS segmentation based on first-derivative, Hilbert and Wavelet Transforms," Med. Eng. Phys., vol. 34, no. 9, pp. 1236-1246, 2012,
[CrossRef] [Web of Science Times Cited 79] [SCOPUS Times Cited 98]


[13] M. S. Manikandan and K. P. Soman, "A novel method for detecting R-peaks in electrocardiogram (ECG) signal," Biomed. Signal Process. Control, vol. 7, no. 2, pp. 118-128, 2012,
[CrossRef] [Web of Science Times Cited 267] [SCOPUS Times Cited 349]


[14] R. Kumar, A. Kumar, and G. K. Singh, "Electrocardiogram signal compression based on 2D-transforms: A research overview," J. Med. Imaging Heal. Informatics, vol. 6, no. 2, pp. 285-296, 2016,
[CrossRef] [Web of Science Times Cited 14] [SCOPUS Times Cited 22]


[15] D. Benitez, P. A. Gaydecki, A. Zaidi, and A. P. Fitzpatrick, "The use of the Hilbert transform in ECG signal analysis," Comput. Biol. Med., vol. 31, no. 5, pp. 399-406, 2001,
[CrossRef] [Web of Science Times Cited 334] [SCOPUS Times Cited 424]


[16] M. R. Homaeinezhad, A. Ghaffari, H. Najjaran Toosi, M. Tahmasebi, and M. M. Daevaeiha, "A Unified Framework for Delineation of Ambulatory Holter ECG Events via Analysis of a Multiple-Order Derivative Wavelet-Based Measure," Iran. J. Electr. Electron. Eng., vol. 7, no. 1, pp. 1-18, 2011

[17] Z. Zidelmal, A. Amirou, D. Ould-Abdeslam, A. Moukadem, and A. Dieterlen, "QRS detection using S-Transform and Shannon energy," Comput. Methods Programs Biomed., vol. 116, no. 1, pp. 1-9, 2014,
[CrossRef] [Web of Science Times Cited 116] [SCOPUS Times Cited 126]


[18] H. Zhu and J. Dong, "An R-peak detection method based on peaks of Shannon energy envelope," Biomed. Signal Process. Control, vol. 8, no. 5, pp. 466-474, 2013,
[CrossRef] [Web of Science Times Cited 58] [SCOPUS Times Cited 71]


[19] H. Beyramienanlou and N. Lotfivand, "Shannon's Energy Based Algorithm in ECG Signal Processing," Comput. Math. Methods Med., vol. 2017, 2017,
[CrossRef] [Web of Science Times Cited 24] [SCOPUS Times Cited 42]


[20] O. Navin, G. Kumar, N. Kumar, K. Baderia, R. Kumar, and A. Kumar, "R-peaks detection using shannon energy for HRV analysis," Lect. Notes Electr. Eng., vol. 526, pp. 401-409, 2019,
[CrossRef] [SCOPUS Times Cited 2]


[21] G. B. Moody and R. G. Mark, "The impact of the MIT-BIH arrhythmia database," IEEE Eng. Med. Biol. Mag., vol. 20, no. 3, pp. 45-50, 2001,
[CrossRef] [Web of Science Times Cited 2556] [SCOPUS Times Cited 3318]


[22] I. Silva and G. B. Moody, "An Open-source Toolbox for Analysing and Processing PhysioNet Databases in MATLAB and Octave," J. Open Res. Softw., vol. 2, pp. 2-5, 2014,
[CrossRef]


[23] A. L. Goldberger et al., "PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Reseach Resource for COmplex Physiologic Signals," Circulation, vol. 101, no. 23, 2000,
[CrossRef] [Web of Science Times Cited 10277]


[24] N. A. Nayan and H. A. Hamid, "Evaluation of patient electrocardiogram datasets using signal quality indexing," Bull. Electr. Eng. Informatics, vol. 8, no. 2, pp. 521-528, 2019,
[CrossRef] [SCOPUS Times Cited 9]


[25] L. G. Tereshchenko and M. E. Josephson, "Frequency content and characteristics of ventricular conduction," J. Electrocardiol., vol. 48, no. 6, pp. 933-937, 2015,
[CrossRef] [Web of Science Times Cited 85] [SCOPUS Times Cited 96]


[26] A. A. Fedotov, A. S. Akulova, and S. A. Akulov, "Effective QRS-detector based on Hilbert transform and adaptive thresholding," IFMBE Proc., vol. 57, no. October, pp. 140-144, 2016,
[CrossRef] [Web of Science Times Cited 6] [SCOPUS Times Cited 8]


[27] M. Elgendi, M. Jonkman, and F. Deboer, "Frequency bands effects on QRS detection," BIOSIGNALS 2010 - Proc. 3rd Int. Conf. Bio-inpsired Syst. Signal Process. Proc., no. 2002, pp. 428-431, 2010.

[28] J. E. Poole, J. P. Singh, and U. Birgersdotter-Green, "QRS duration or QRS morphology what really matters in cardiac resynchronization therapy?," J. Am. Coll. Cardiol., vol. 67, no. 9, pp. 1104-1117, 2016,
[CrossRef] [Web of Science Times Cited 62] [SCOPUS Times Cited 75]




References Weight

Web of Science® Citations for all references: 15,655 TCR
SCOPUS® Citations for all references: 7,452 TCR

Web of Science® Average Citations per reference: 540 ACR
SCOPUS® Average Citations per reference: 257 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-12-07 10:52 in 176 seconds.




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