Abstract
In this article, we propose a new algorithm using the characteristics of reconstructed phase portraits by delay-coordinate mapping utilizing lag rotundity for a real-time detection of QRS complexes in ECG signals. In reconstructing phase portrait the mapping parameters, time delay, and mapping dimension play important roles in shaping of portraits drawn in a new dimensional space. Experimentally, the optimal mapping time delay for detection of QRS complexes turned out to be 20 ms. To explore the meaning of this time delay and the proper mapping dimension, we applied a fill factor, mutual information, and autocorrelation function algorithm that were generally used to analyze the chaotic characteristics of sampled signals. From these results, we could find the fact that the performance of our proposed algorithms relied mainly on the geometrical property such as an area of the reconstructed phase portrait. For the real application, we applied our algorithm for designing a small cardiac event recorder. This system was to record patients’ ECG and R–R intervals for 1 h to investigate HRV characteristics of the patients who had vasovagal syncope symptom and for the evaluation, we implemented our algorithm in C language and applied to MIT/BIH arrhythmia database of 48 subjects. Our proposed algorithm achieved a 99.58% detection rate of QRS complexes. © 2002 Biomedical Engineering Society.
PAC2002: 8719Nn, 8719Hh, 8780-y
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REFERENCES
Babloyantz, A., and A. Destexhe. Is the normal heart a periodic oscillator? Biol. Cybern. 58:203-211, 1988.
Broomhead, D. S., and J. P. King. Extracting qualitative dynamics from experimental data. Physica D 20:217-236, 1986.
Dandapat, S., and G. C. Ray. Spike detection in biomedical signals using midprediction filter. Med. Biol. Eng. Comput. 35:354-360, 1997.
Fraser, A. M., and H. L. Swinney. Independent coordinates for strange attractors from mutual information. Phys. Rev. A 33:1134-1140, 1986.
Hahoura, M., M. Hassani, and M. Hubin. DSP implementation of wavelet transform for real time ECG wave forms detection and heart rate analysis. Comput. Methods Prog. Biomed. 52:35-44, 1997.
Hamilton, P. S., and W. J. Tompkins. Quantitative investigation of QRS detection rules using the MIT/BIH arrhythmia database. IEEE Trans. Biomed. Eng. BME-33:1157-1187, 1986.
Kadambe, S., R. Murray, and G. F. Boudreaux-Bartels. Wavelet transform-based QRS complex detector. IEEE Trans. Biomed. Eng. 46:838-848, 1999.
Kaplan, D. T., and R. J. Cohen. Is fibrillation chaos? Circ. Res. 67:886-892, 1990.
Kember, G., and A. C. Fowler. A correlation function for choosing time delays in phase reconstructions. Phys. Lett. A 179:72-80, 1993.
Khan, S., T. A. Denton, H. S. Karagueuzian, and G. A. Diamond. Effect of noise and filtering on phase plane plots and dimension for simple periodic signals. Ann. Int. Conf. IEEE EMBS 13:2232-2233, 1991.
Kreyszig, E. Advanced Engineering Mathmatics, 6th ed., New York: Wiley, 1988, p. 306.
Li, C., and C. Zheng. Detection of ECG characteristic points using wavelet transform. IEEE Trans. Biomed. Eng. 42:21-28, 1995.
Liebert, W., K. Pawelzik, and H. G. Schuster. Optimal embeddings of chaotic attractors from topological consideration. Europhys. Lett. 14:521-526, 1991.
Macfarlane, P. W., and T. D. V. Lawrie, Comprehensive Electrocardiology: Theory and Practice in Health and Disease, New York: Pergamon, 1989, Vol. 1, p. 435.
MIT/BIH Database Distribution, Massachusetts Inst. Technol., 77 Massachusetts Avenue, Room 20A-113, Cambridge, MA 02139.
Okada, M. A digital filter for the QRS complex detection. IEEE Trans. Biomed. Eng. BME-26:700-703, 1979.
Pan, J., and W. J. Tompkins. A real-time QRS detection algorithm. IEEE Trans. Biomed. Eng. BME-32:230-236, 1985.
Richter, M., T. Schreiber, and D. T. Kaplan. Fetal ECG extraction with nonlinear state-space projections. IEEE Trans. Biomed. Eng. 45:133-136, 1998.
Ruha, A., S. Sallinen, and S. Nissilä. A real-time microprocessor QRS detector system with a 1 ms timing accuracy for the measurement of ambulatory HRV. IEEE Trans. Biomed. Eng. 44:159-167, 1997.
Sahambi, J. S., S. N. Tandon, and R. K. Bhatt. Wavelet based ST-segment analysis. Med. Biol. Eng. Comput. 36:568-572, 1998.
Sauer, T. D., J. A. Yorke, and M. Casdagli. Embedology. J. Stat. Phys. 65:579, 1991.
Sauer, T. D., and J. A. Yorke. How many delay coordinated do you need? Int. J. Bifurcation and Chaos 3:737, 1993.
Sauer, T. D., and J. A. Yorke. Are the dimension of a set and its image equal under typical smooth functions? Ergodic Theory Dyn. Sys. 17:941-956, 1997.
Schuster, H. G. Deterministic Chaos. Weinheim: VCH, 1988.
Schuster, H. G., and W. Liebert. Proper choice of the time delay for the analysis of chaotic time series. Phys. Lett. A 142:107-111, 1989.
Shaw, R. S. Strange attractor, chaotic behavior and information flow. Nature (London) 36a: 1980.
Takens, F. Lecture Notes in Mathematics, Berlin: Springer, 1980, Vol. 898, p. 230.
Xue, O., Y. H. Hu, and W. J. Tompkins. Neural-networkbased adaptive matched filtering for QRS detection. IEEE Trans. Biomed. Eng. BME-39:317-329, 1992.
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Lee, JW., Kim, KS., Lee, B. et al. A Real Time QRS Detection Using Delay-Coordinate Mapping for the Microcontroller Implementation. Annals of Biomedical Engineering 30, 1140–1151 (2002). https://doi.org/10.1114/1.1523030
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DOI: https://doi.org/10.1114/1.1523030