Evaluation of the shape-varying structuring element in QRS detection for ECG compression

• Autorzy: Tadejko P. , Rakowski W.
• Języki publikacji: PL

Abstrakty

EN

Morphological operations are simple mathematical constructs, which have led to effective solution for many problems in signal and image processing. These solutions employ discrete operators (structuring element) and are applied to digitized signals. The paper presents the mathematical morphology approach to the recognition and classification of heart rhythms on the basis of electrocardiogram (EGG) waveforms. The main part in recognition is based on the morphological niters characterization of the QRS complexes. In this work, we present morphological filtering as a preliminary step for compression of ECG data using image compression algorithms. To corn-press the ECG data using for example JPEG2000, SPITH or other codec, the one-dimensional ECG sequence needs to be processed to produce a two-dimensional matrix. Detecting operator designed for creating sequence is controlled by the shape and size of the structuring element. We compare how shape and length of this element can affects sensitivity detection algorithm based on amplitude and slope. The performance of the algorithm is evaluated with standard MIT/BIll arrythmia database.

Słowa kluczowe

EN

morphological filtering; structuring element; shape-varying structuring element; multiple morphological operation; ECG; QRS detection; ECG compression

• Wydawca: Instytut Telekomunikacji i Informatyki Uniwersytetu Technologiczno-Przyrodniczego w Bydgoszczy
• Czasopismo: Image Processing & Communications
• Rocznik: 2005
• Tom: Vol. 10, no 2
• Strony: 27--38
• Opis fizyczny: Bibliogr. 14 poz., rys., wykr.

Twórcy

autor

Tadejko P.

• Faculty of Computer Science, Technical University of Bialystok, Wiejska 45A, 15-351 Bialystok, Poland

autor

Rakowski W.

• Faculty of Computer Science, Technical University of Bialystok, Wiejska 45A, 15-351 Bialystok, Poland

Bibliografia

• [1] Bilgin A., Marcellin M. W., Altbach M. L: Compression of Electrocardiogram Signals using JPEG2000, IEEE Transactions on Consumer Electronics, Vol. 49, No. 4, November 2003
• [2] Chu C. H., Delp E. J.: Impulsive noise suppression and background normalization of electrocardiogram signals using morphological operators, IEEE Transaction on Biomedical Engineering, vol. 36, no. 2 Febraury 1989
• [3] Chu-Song C., Ja-Ling W., Yi-Ping H., Theo-retical Aspects of Vertically Invariant Gray-Level Morphological Operators and Their Application on Adaptive Signal and Image Filtering, IEEE Transaction on Signal Processing, vol. 47, no. 4, April 1999.
• [4] Friesen G- M., Jannett T. C., Jadallah M. A., Yates S. L., Quint S. R., Nagle H. T.: A Comparison of the Noise Sensitivity of Nine QRS Detection Algorithms, IEEE Transaction on Biomedical Engineering, vol. 37, no. 1, January 1990
• [5] Khler B-U-, Hennig C, Orglmeister R., The Principles of Software QRS Detection, IEEE Engineering in Medicine and Biology, January/Febraury 2002
• [6] Maragos P. Morphological Signal and Image Processing, CRC Press LLC, 2000
• [7] Margos P., Schafer R. W., Morphological Filters-Part I: Their Set-Theoretic Analysis and Relations to Linear Shift-Invariant Filters, IEEE Transaction on Acoustic, Speech and Signal Processing, vol. ASSP-35, no. 8, August 1987
• [8] Maragos P., Schafer R. W., Morphological Systems for Multidimensional Signal Processing, Proceedings of the IEEE, vol. 78, no. 4, April 1990
• [9] MIT/BIH Arrhythmia Database: The MIT/BTH arrhythmia database CD-ROM, Harvard-MIT Division of Health Sciences and Technology, 1992
• [10] Serra I., Image Analysis and Mathematical Morphology, New York Academic, 1982
• [11] Sun P., Wu Q. H., Weindling A. M., Finkelstein A., Ibrahim K., An Improved Morphological Approach to Background Normalization of EGG Signals, Transaction on Biomedical Engineering, vol. 50, no. 1, January 2003
• [12] Tadejko P., Detection algorithms of characteristic points in quasi-periodic biomedical signals for compression-aimed creation of 2D images, Simulation in Research and Expansion, XII Science Workshop, PTSK, 2004
• [13] Tadejko P, Rakowski W., Matlab Simulink in modeling morphological filters for electrocardiogram signal processing, Simulation in Research and Expansion, XIII Science Workshop, PTSK, 2005
• [14] Trahanias P. E.: An approach to QRS complex detection using mathematical morphology, IEEE Transaction on Biomedical Engineering, vol. 40, no. 2, Febraury 1993