ENG  Vol.5 No.10 B , October 2013
Triangle Characters of Electrocardiogram for Distinguishing States between Exercise and Relaxation
Abstract: Will exercise-induced cardiovascular workload be monitored by Electrocardiogram (ECG) waveform morphology? The discrimination ability of ECG morphology from 30 subjects was tested for distinguishing states between exercise and relaxation in terms of side lengths, lengths of high lines, angles, perimeters and areas of triangle QRS and triangle T. As a result, 4 characters from triangle QRS had significant differences (t test, p<0.05) for over 85% of subjects in distinguishing between exercise states and relaxation states, which were: ratio of QR side length to RS side length in triangle QRS, angle S and angle Q, as well as the ratio between them. Moreover, ratio of angle S to angle Q had significant differences (t test, p<0.05) for all subjects. In conclusion, triangle characters in ECG could be used to distinguish exercise states from relaxation states.
Cite this paper: Li, Y. , Yan, H. , Song, J. , Yu, X. , Sun, Z. and Wei, H. (2013) Triangle Characters of Electrocardiogram for Distinguishing States between Exercise and Relaxation. Engineering, 5, 126-131. doi: 10.4236/eng.2013.510B026.

[1]   J. P. Higgins and J. A. Higgins, “Electrocardiographic Exercise Stress Testing: An Update beyond the ST Segment,” International Journal of Cardiology, Vol. 116, 2007, pp. 285-299.

[2]   Y. J. Li, H. Yan, W. Chen, L. Zhang and B. Zhang, “Different Characteristics of Heart Rate Variability in Mental and Physical Fatigue States,” Space Medicine & Medical Engineering, Vol. 23, No. 3, 2010, pp. 157-162.

[3]   A. Svensbergh, M. Johansson, O. Pahlm and L. H. Brudin, “ST-Recovery Loop of Exercise-induced ST Deviation in the Identification of Coronary Artery Disease: Which Parameters Should We Measure?” Journal of Electrocardiology, Vol. 37, No. 4, 2004, pp. 275-283.

[4]   Y. J. Li, H. Yan and Z. L.Wang, “Study of Electrocardio-Waveform Variability,” Science in China, Series C: Life Sciences, Vol. 39, No. 12, 2009, pp. 1181-1187.

[5]   H. Yan and Y. J. Li, “Electrocardiogram Analysis Based on the Karhunen-Loève Transform,” In: W. C. Yu, M. Zhang, L. P. Wang and Y. B. Song, Eds., 2010 3rd International Conference on BioMedical Engineering and Informatics (BMEI2010), Institute of Electrical and Electronics Engineers, Yantai, 2010, pp. 887-890.

[6]   J. Z. Song, H. Yan, Y. J. Li and K. Y. Mu, “Research on Electrocardiogram Baseline Wandering Correction Based on Wavelet Transform, QRS Barycenter Fitting, and Regional Method,” Australasian Physical & Engineering Science in Medicine, Vol. 33, No. 3, 2010, pp. 279-283.

[7]   Y. J. Li, H. Yan, F. Hong and J. Z. Song, “A New Approach of QRS Complex Detection Based on Matched Filtering and Triangle Character Analysis,” Australasian Physical & Engineering Science in Medicine, Vol. 35, No. 3, 2012, pp. 341-356.

[8]   Q. H. Zhang, A. I. Manriquez, C. Médigue, Y. Papelier and M. Sorine, “An Algorithm for Robust and Efficient Location of T-Wave Ends in Electrocardiograms,” IEEE Transactions on Biomedical Engineering, Vol. 53, No. 12, 2006, pp. 2544-2552.

[9]   J. Mateo, P. Serrano and R. Bailon, “ECG-Based Clinical Indexes during Exercise Test Including Repolarization, Depolarization and HRV,” Computers in Cardiology, Vol. 28, 2001, pp. 309-312.

[10]   J. F. He, Y. Kinouchi, H. Yamaguchi and H. Miyamoto, “Exercise-Induced Changes in R Wave Amplitude and Heart Rate in Normal Subjects,” Journal of Electrocardiology, Vol. 28, No. 2, 1995, pp. 99-106.