Click to open the HelpDesk interface
AECE - Front page banner

Menu:


FACTS & FIGURES

JCR Impact Factor: 0.825
JCR 5-Year IF: 0.752
SCOPUS CiteScore: 2.5
Issues per year: 4
Current issue: May 2022
Next issue: Aug 2022
Avg review time: 79 days
Avg accept to publ: 48 days
APC: 300 EUR


PUBLISHER

Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


TRAFFIC STATS

1,942,336 unique visits
768,899 downloads
Since November 1, 2009



Robots online now
Googlebot
SemanticScholar


SCOPUS CiteScore

SCOPUS CiteScore


SJR SCImago RANK

SCImago Journal & Country Rank




TEXT LINKS

Anycast DNS Hosting
MOST RECENT ISSUES

 Volume 22 (2022)
 
     »   Issue 2 / 2022
 
     »   Issue 1 / 2022
 
 
 Volume 21 (2021)
 
     »   Issue 4 / 2021
 
     »   Issue 3 / 2021
 
     »   Issue 2 / 2021
 
     »   Issue 1 / 2021
 
 
 Volume 20 (2020)
 
     »   Issue 4 / 2020
 
     »   Issue 3 / 2020
 
     »   Issue 2 / 2020
 
     »   Issue 1 / 2020
 
 
 Volume 19 (2019)
 
     »   Issue 4 / 2019
 
     »   Issue 3 / 2019
 
     »   Issue 2 / 2019
 
     »   Issue 1 / 2019
 
 
 Volume 18 (2018)
 
     »   Issue 4 / 2018
 
     »   Issue 3 / 2018
 
     »   Issue 2 / 2018
 
     »   Issue 1 / 2018
 
 
  View all issues  








LATEST NEWS

2022-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2021. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.825 (0.722 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.752.

2022-Jun-16
SCOPUS published the CiteScore for 2021, computed by using an improved methodology, counting the citations received in 2018-2021 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering in 2021 is 2.5, the same as for 2020 but better than all our previous results.

2021-Jun-30
Clarivate Analytics published the InCites Journal Citations Report for 2020. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 1.221 (1.053 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.961.

2021-Jun-06
SCOPUS published the CiteScore for 2020, computed by using an improved methodology, counting the citations received in 2017-2020 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering in 2020 is 2.5, better than all our previous results.

2021-Apr-15
Release of the v3 version of AECE Journal website. We moved to a new server and implemented the latest cryptographic protocols to assure better compatibility with the most recent browsers. Our website accepts now only TLS 1.2 and TLS 1.3 secure connections.

Read More »


    
 

  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
 
View the paper record and citations in View the paper record and citations in Google Scholar
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (1,321 KB) | Citation | Downloads: 555 | Views: 1,000

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
Quick view
Full text preview
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 368]


[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 156] [SCOPUS Times Cited 179]


[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 321] [SCOPUS Times Cited 366]


[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 5]


[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 9] [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 63] [SCOPUS Times Cited 78]


[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 17]


[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 25] [SCOPUS Times Cited 23]


[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 35] [SCOPUS Times Cited 39]


[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 14] [SCOPUS Times Cited 17]


[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 968] [SCOPUS Times Cited 1172]


[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 68] [SCOPUS Times Cited 80]


[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 214] [SCOPUS Times Cited 274]


[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 13] [SCOPUS Times Cited 18]


[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 301] [SCOPUS Times Cited 379]


[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 103] [SCOPUS Times Cited 111]


[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 48] [SCOPUS Times Cited 58]


[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 18] [SCOPUS Times Cited 28]


[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 1726] [SCOPUS Times Cited 2122]


[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 7427]


[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 5]


[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 49] [SCOPUS Times Cited 53]


[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 5] [SCOPUS Times Cited 6]


[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 50] [SCOPUS Times Cited 55]




References Weight

Web of Science® Citations for all references: 11,613 TCR
SCOPUS® Citations for all references: 5,470 TCR

Web of Science® Average Citations per reference: 400 ACR
SCOPUS® Average Citations per reference: 189 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 2022-08-02 19:57 in 159 seconds.




Note1: Web of Science® is a registered trademark of Clarivate Analytics.
Note2: SCOPUS® is a registered trademark of Elsevier B.V.
Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.

Copyright ©2001-2022
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.

Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.

Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.




Website loading speed and performance optimization powered by: