Abstract
The aim of this study was to combine methods from different fields of scientific research, such as dynamic programming, pattern recognition and signal processing to solve a very demanding problem of ECG signal reconstruction in extremely noisy environment. A fast method of signal decomposition into frequency subbands was developed. Its application, and processing the respective subbands with the use of either principal component analysis or dynamic time warping based methods allowed us to achieve a significant progress in suppression of highly intractable electric motion artifacts. The investigations performed showed the proposed method prevalence over the well known nonlinear state-space projections developed in the field of nonlinear dynamics.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Gupta, L., Molfese, D., Tammana, R., Simos, P.: Nonlinear alignment and averaging for estimating the evoked potential. IEEE Trans. Biomed. Eng 43(4), 348–356 (1996)
Hu, X., Nenov, V.: A single-lead ecg enhancement algorithm using a regularized data-driven filter. IEEE Trans. Biomed. Eng. 53(2), 347–351 (2006)
Jollife, I.: Principal component analysis. Springer, New York (2002)
Kotas, M.: Projective filtering of time-aligned beats for fetal ecg extraction. Bull. Pol. Acad. Sci. Tech. Sci. 55(4), 331–339 (2007)
Kotas, M.: Projective filtering of time-aligned ecg beats for repolarization duration measurement. Comput. Methods Programs Biomed. 85(2), 115–123 (2007)
Kotas, M.: Robust projective filtering of time-warped ecg beats. Comput. Methods Programs Biomed. 92(2), 161–172 (2008)
Leski, J.M.: Robust weighted averaging. Trans. Biomed. Eng. 49(8), 796–804 (2002)
Momot, A.: Methods of weighted averaging of ecg signals using bayesian inference and criterion function minimization. Biomed. Signal Process. Control. 4(2), 162–169 (2009)
Rautaharju, P., Blackburn, H.: The exercise electrocardiogram: experience in analysis of noisy cardiograms with a small computer. Am. Heart J. 69(4), 515–520 (1965)
Ros, O., Rompelmann, H.: Coherent averaging technique: a tutorial review. J. Biomed. Eng. 8(1), 24–35 (1986)
Sakoe, H., Chiba, S.: Dynamic programming algorithm optimization for spoken word recognition. Trans. Acoust. Speech Signal Process. 26(1), 43–49 (1978)
Schreiber, T., Kaplan, D.: Nonlinear noise reduction for electrocardiograms. Chaos 6(1), 87–92 (1996)
Van Alste, J.A., Van Eck, W., Herrmann, O.E.: Bag-of-words representation for biomedical time series classification. Comput. Biomed. Res. 19(5), 417–427 (1986)
Wang, J., Liu, P., She, M.: Bag-of-words representation for biomedical time series classification. Biomed. Signal Process. Control. 8(6), 634–644 (2013)
Acknowledgments
This research was partially supported by statutory funds (BK-2015, BKM-2015) of the Institute of Electronics, Silesian University of Technology and GeCONiI project (T. Moroń). The work was performed using the infrastructure supported by POIG.02.03.01-24-099/13 grant: GeCONiI–Upper Silesian Center for Computational Science and Engineering.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Moroń, T., Kotas, M., Leski, J.M. (2016). Principal Component Analysis and Dynamic Time-Warping in Subbands for ECG Reconstruction. In: Gruca, A., Brachman, A., Kozielski, S., Czachórski, T. (eds) Man–Machine Interactions 4. Advances in Intelligent Systems and Computing, vol 391. Springer, Cham. https://doi.org/10.1007/978-3-319-23437-3_27
Download citation
DOI: https://doi.org/10.1007/978-3-319-23437-3_27
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-23436-6
Online ISBN: 978-3-319-23437-3
eBook Packages: EngineeringEngineering (R0)