R-Peak Identification in ECG Signals using Pattern-Adapted Wavelet Technique

References

• N. M. Arzeo, D. Z. De, and C. S. Poon, “Analysis of first-derivative based QRS detection algorithms,” IEEE Trans. Biomed. Eng., Vol. 55, pp. 478–84, 2008. doi:10.1109/TBME.2007.912658.
   PubMed Web of Science ®Google Scholar
• 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, 118–28, 2012.
   Web of Science ®Google Scholar
• R. J. Martis, U. Rajendra Acharya, and H. Adeli, “Current methods in electrocardiogram characterization,” Comput. Biol. Med., Vol. 48, pp. 133–49, 2014.
   PubMed Web of Science ®Google Scholar
• P. E. McSharry, G. D. Clifford, L. Tarassenko, and L. A. Smith, “A dynamical model for generating synthetic electrocardiogram signals,” IEEE Trans. Biomed. Eng., Vol. 50, pp. 289–94, 2003.
   PubMed Web of Science ®Google Scholar
• T. Sharma, and K. K. Sharma, “QRS complex detection in ECG signals using locally adaptive weighted total variation denoising,” Comput. Biol. Med., Vol. 87, pp. 187–99, Aug 2017.
   PubMed Web of Science ®Google Scholar
• S. S. Joshi, and P. Srivastava. “ECG beat detection using wavelet denoising”, S J Pise. Springer, 2011.
   Google Scholar
• A. Kaur, A. Agarwal, R. Agarwal, and S. Kumar, “A novel approach to ECG R-peak detection,” Arab. J. Sci. Eng., Vol. 44, 2018. doi:10.1007/s13369-018-3557-8.
   Web of Science ®Google Scholar
• C. Nayak, S. K. Saha, R. Kar, and D. Mandal, “Automated QRS complex detection using MFO-based DFOD,” IET Signal Proc., Vol. 12, no. 9, 2018. ISSN 1751-9675.
   Web of Science ®Google Scholar
• H. Kaur, and R. Rajni, “Electrocardiogram signal analysis for R-peak detection and denoising with hybrid linearization and principal component analysis,” Turkish J. Electri. Eng. Comput. Sci., Vol. 25, pp. 2163–75, 2017.
   Web of Science ®Google Scholar
• J.-S. Park, S.-W. Lee, and U. Park, “R-peak detection method using wavelet transform and modified Shannon energy envelope,” Hindawi J. Healthcare Eng., Vol. 2017, no. 46, pp. 1–14, 2017, Article ID 4901017.
   Google Scholar
• B. Biswal, “ECG signal analysis using modified S-transform,” Healthc. Technol. Lett., Vol. 4, no. 2, pp. 68–72, 2017.
   PubMed Web of Science ®Google Scholar
• Q. Qin, J. Li, Y. Yue, and C. Liu, “An adaptive and time-efficient ECG R-peak detection algorithm,” Hindawi J. Healthcare Eng., Vol. 2017, pp. 14, 2017. Article ID 5980541.
   Web of Science ®Google Scholar
• M. Rakshit, and S. Das, “An efficient wavelet-based automated R-peaks detection method using Hilbert transform,” Biocybernetics Biomed. Eng., Vol. 37, no. 3, 2017. BBE 190 1–12.
   Web of Science ®Google Scholar
• M. Meraha, T. A. Abdelmalika, and B. H. Larbic, “R-peaks detection based on stationary wavelet transform,” Comput. Methods Programs Biomed., Vol. 121, no. 3, pp. 149–60, 2015, COMM-3936.
   PubMed Web of Science ®Google Scholar
• 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.
   PubMed Web of Science ®Google Scholar
• R. Haddadi, E. Abdel mounim, M. E. Hanine, and A. Belaguid, “Discrete wavelet transform based algorithm for recognition of QRS complexes,” World Computer Sci. Inf. Technol. J. (WCSIT), Vol. 4, no. 9, pp. 127–32, 2014.
   Google Scholar
• A. Ghaffari, H. Golbayani, and M. Ghasemi, “A new mathematical based QRS detector using continuous wavelet transform,” Comput. Electr. Eng., Vol. 34, pp. 81–91, 2008.
   Web of Science ®Google Scholar
• J. P. Martínez, 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, pp. 570–81, 2004.
   PubMed Web of Science ®Google Scholar
• M. Ayat, M. B. Sham sollahi, B. Mozaffari, and S. Kharabian. “ECG denoising using modulus maxima of wavelet transform”, in Conference Proceedings IEEE Engineering Medicine and Biology Society, 2009, pp. 416–9.
   Google Scholar
• N. Boichat, N. Khaled, F. Rincon, and D. Atienza. “Wavelet-based ECG delineation on a wearable embedded sensor platform”, in Proc. 6th IEEE Int. Work. Body-Sen. Net., 2009, pp. 256–61.
   Google Scholar
• A. Ghaffari, M. R. Homaeinezhad, M. Khazraee, and M. Daevaeiha, “Segmentation of Holter ECG waves via analysis of a discrete wavelet derived multiple skewness-kurtosis based metric,” Ann. Biomed. Eng, Vol. 38, no. 4, pp. 1497–510, 2010.
   PubMed Web of Science ®Google Scholar
• H. Q. Li, and X. F. Wang, “Detection of electrocardiogram characteristic points using lifting wavelet transform and Hilbert transform,” Trans. Inst. Meas. Control, Vol. 35, no. 5, pp. 574–82, 2013.
   Web of Science ®Google Scholar
• Y. Misiti, M. Misiti, G. Oppenheim, and J. M. Poggi. “Wavelets and their applications”, 2003.
   Google Scholar
• S. Pal, and M. Mitra, “Detection of ECG characteristic points using multiresolution wavelet analysis based selective coefficient method,” Elsevier Meas., Vol. 43, no. 2, pp. 255–61, February2010.
   Google Scholar
• J. Pan, and W. J. Tompkins, “A real time QRS detection algorithm,” IEEE Trans. Biomed. Eng., Vol. 32, no. 3, pp. 230–6, March 1985.
   PubMed Web of Science ®Google Scholar
• T. R. Gopalakrishnan Nair, A. P. Geetha, and M. Asharani, “Continuous digital ECG analysis over accurate R-peak detection using adapted wavelet technique,” J. pf Med. Eng. Technol., Vol. 37, no. 7, pp. 429–35, 2013.
   PubMedGoogle Scholar
• D. Zhang. “Wavelet approach for ECG baseline wander correction and noise reduction”, in 27th Ann. Int. Conf. Eng.Med. Biol. Soc. IEEE-EMBS, 2005, pp. 1212–5.
   Google Scholar
• B. N. Madhukar, S. R. Megha, and T. R. Sithara, “Analysis of noise removal in ECG signal using Symlet transform,” Int. J. Latest Technol. Eng. Manag. Appl Sci. (IJLTEMAS), 1st Spec Issue Eng Technol., Vol. 6, no. VS, pp. 17–22, May 2017.
   Google Scholar
• Z. Zidelmal, A. Amirou, M. Adnane, and A. Belouchrani, “QRS detection based on wavelet coefficients,” Comput. Methods Programs Biomed., Vol. 107, pp. 490–6, 2012.
   PubMed Web of Science ®Google Scholar