An efficient selection, scoring, and variation ratio test algorithm for ECG R-wave peak detection

Experimental and Clinical Cardiology

Volumn 20, Issue 8, 2014, Pages 4256-4263

  Ding, Jian Jiun ^a   Huang, Chen Wei ^a   Ho, Yi Lwun ^b   Hung, Chi Sheng ^c   Lin, Yen Hung ^b   Chen, Ying Hsien ^c  

^a NATIONAL TAIWAN UNIVERSITY   (Taiwan)

^b NATIONAL TAIWAN UNIVERSITY   (Taiwan)

^c NATIONAL TAIWAN UNIVERSITY HOSPITAL   (Taiwan)

Author keywords

Electrocardiogram; Fast algorithm; R wave peak candidate selection; R wave peak detection; Variation ratio test

Indexed keywords

ALGORITHM; ARTICLE; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; CONTROLLED STUDY; DATA BASE; DIAGNOSTIC ACCURACY; DIAGNOSTIC ERROR; DIAGNOSTIC VALUE; FILTER; FOURIER TRANSFORMATION; HAAR LIKE MATCHED FILTER; HEART ARRHYTHMIA; NOISE REDUCTION; R WAVE; WAVELET ANALYSIS;

EID: 84906962405     PISSN: 12056626     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (22)

1. Wang Y, Deepu CJ, Lian Y: A computationally efficient QRS detection algorithm for wearable ECG sensors. Ann Int Conf IEEE EMBC, pp. 5641-5644, Boston, MA, USA, Sept. 2011.
2. Hamilton PS, Tompkins WJ: Quantitative investigation of QRS detection rules using the MIT/BIH arrhythmia database. IEEE Trans Biomed Eng. 1986; 33: 1157-1165.
3. thAnnual International Conference of the IEEE, vol. 4, pp. 1396-1398, Amsterdam, the Netherlands, Nov. 1996.
4. Zhang CF, Bae TW: VLSI friendly ECG QRS complex detector for body sensor networks. IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 2012; 2: 52-59.
5. Zhang F, Lian Y: QRS detection based on multiscale mathematical morphology for wearable ECG devices in body area networks. IEEE Trans Biomed Circuits Syst. 2009; 3: 220-228.
6. Suarez KV, Silva JC, Berthoumieu Y, Gomis P, Najim M: ECG beat detection using a geometrical matching approach. IEEE Trans Biomed Eng. 2007; 54: 641-650.
7. Pan J, Tompkins WJ: A real-time QRS detection algorithm. IEEE Trans Biomed Eng. 1985; 32: 230-236.
8. Kohler BU, Henning C, Orglmeister R: QRS detection using zero crossing counts. Progress in Biomedical Research. 2003; 8: 138-154.
9. Cui X: A new real-time ECG R-wave detection algorithm. IFOST, pp. 1252-1255, Harbin, China, Aug. 2011.
10. Arzeno NM, Deng ZD, Poon CS: Analysis of first-derivative based QRS detection algorithms. IEEE Trans Biomed Eng. 2008; 55: 478-484.
11. Chen SW, Chen HC, Chan HL: A real-time QRS detection method based on moving-averaging incorporating with wavelet denoising. Computer Methods and Programs in Biomedicine. 2006; 82: 187-195.
12. Zheng H, Wu J: Real-time QRS detection method. International Conference on e-health Networking, Applications and Services, pp. 169-170, Singapore, July 2008.
13. Liu X, Zheng Y, Phyu MW, Endru FN, Navaneethan V, and Zhao B: An ultra-low power ECG acquisition and monitoring ASIC system for WBAN applications. IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 2012; 2: 60-70.
14. Jr Schuck A, Wisbeck JO: QRS detector pre-processing using the complex wavelet transform. Ann. Int. Conf. IEEE EMBC, vol. 3, pp. 2590-2593, Cancun, Mexico, Sept. 2003.
15. Pan T, Zhang L, Zhou S: Detection of ECG characteristic points using biorthogonal spline wavelet. Int Conf BMEI, vol. 2, pp. 858-863, Yantai, China, Oct. 2010.
16. Moody GB, Mark RG: The impact of the MIT-BIH Arrhythmia database. IEEE Eng Med Biol Mag. 2001; 20: 45-50 [Data is available online: http://www.physionet.org/physiobank/database/mitdb/].
17. Goldberger AL, Amaral LAN, Glass L, Hausdorff JM, Ivanov PC, Mark RG, Mietus JE, Moody GB, Peng CK, Stanley HE: PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals. Circulation. 2000; 101: 215-220.
18. Afonso VX, Tompkins WJ, Nguyen TQ, Luo S: ECG beat detection using filter banks. IEEE Trans Biomed Eng. 1999; 46: 192-202.
19. Poli R, Cagnoni S, Valli G: Genetic design of optimum linear and nonlinear QRS detectors. IEEE Trans Biomed Eng. 1995; 42: 1137-1141.
20. Lewandowski J, Arochena HE, Naguib RNG, Chao K: A simple real-time QRS detection algorithm utilizing curve-length concept with combined adaptive threshold for electrocardiogram signal classification. TENCON, IEEE Region 10 Conference, pp. 1-6, Nov. 2012.
21. Jagrič T, Marhl M, Štajer D, Kocjančič ST, Jagrič T, Podbregar M, Perc M: Irregularity test for very short electrocardiogram (ECG) signals as a method for predicting a successful defibrillation in patients with ventricular fibrillation. Translational Research. 2007; 149: 145-151.
22. Kannathal N, Acharya UR, Lim CM, Sadasivan PK, Krishnan SM: Classification of cardiac patient states using artificial neural networks. Experimental & Clinical Cardiology. 2003; 8: 206-211.