A New Method in Short-Term Heart Rate Variability — Five-Class Density Histogram
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33122
A New Method in Short-Term Heart Rate Variability — Five-Class Density Histogram

Authors: Liping Li, Ke Li, Changchun Liu, Chengyu Liu, Yuanyang Li

Abstract:

A five-class density histogram with an index named cumulative density was proposed to analyze the short-term HRV. 150 subjects participated in the test, falling into three groups with equal numbers -- the healthy young group (Young), the healthy old group (Old), and the group of patients with congestive heart failure (CHF). Results of multiple comparisons showed a significant differences of the cumulative density in the three groups, with values 0.0238 for Young, 0.0406 for Old and 0.0732 for CHF (p<0.001). After 7 days and 14 days, 46 subjects from the Young and Old groups were retested twice following the same test protocol. Results showed good-to-excellent interclass correlations (ICC=0.783, 95% confidence interval 0.676-0.864). The Bland-Altman plots were used to reexamine the test-retest reliability. In conclusion, the method proposed could be a valid and reliable method to the short-term HRV assessment.

Keywords: Autonomic nervous system, congestive heart failure, heart rate variability, histogram.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1327802

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2012

References:


[1] Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology, "Heart rate variability: standards of measurement, physiological interpretation and clinical use," Circulation, vol.93, no.5, pp. 1043-1065, 1996.
[2] Y. Gang and M. Malik, "Heart Rate Variability: Measurements and Risk Stratification," in Electrical Diseases of the Heart, 1st ed. I. Gussak, C. Antzelevitch, A. Wilde, et al. Ed. London, Springer, 2008, pp. 365-378.
[3] A. Rajendra, J. Paul, N. Kannathal, et al., "Heart rate variability: a review," Med Bio Eng Comput, vol.44, no.12, pp. 1031-1051, 2006.
[4] G. Berntson, J. Bigger, D. Eckberg, et al., "Heart rate variability: origins, methods, and interpretive caveats," Psychophysiology, vol.34, no.6, pp. 623-648, 1997.
[5] R. Kleiger, P. Stein, and J. Bigger Jr, "Heart rate variability: measurement and clinical utility," Ann Noninvasive Electrocardiol, vol. 10, no. 1, pp. 88-101, 2005.
[6] C. Li, C. Zheng, and C. Tai, "Detection of ECG characteristic points using wavelet transforms", IEEE Trans Biomed Eng, vol.42, no.1, pp. 21-28, 1995ÒÇé
[7] J. Martínez, R. Almeida, S. Olmos, et al., "A wavelet-based ECG delineator: evaluation on standard databases", IEEE Trans Biomed Eng, vol.51, no.4, pp. 570-581, 2004.
[8] J. Mateo, and P. Laguna, "Analysis of heart rate variability in the presence of ectopic beats using the heart timing signal," IEEE Trans Biomed Eng, vol. 50, no. 3, pp. 334-343, 2003.
[9] K. Solem, P. Laguna, and L. Sornmo, "An efficient method for handling ectopic beats using the heart timing signal," IEEE Trans Biomed Eng, vol. 53, no. 1, pp. 13-20, 2006.
[10] J. Mcnames, T. Thong, and M. Aboy, "Impulse rejection filter for artifact removal in spectral analysis of biomedical signals," in Proc. 26th Annu. Int. Conf. IEEE-EMBS, San Francisco, CA, 2004, pp. 145-148.
[11] L. Li, J. Yang, C. Liu, B. Li, and C. Liu, "An impulse rejection filter based on moving window for artifact removal in RR interval series," J Optoelectron Laser, vol. 21, no. 9, pp. 1426-1430, 2010.
[12] J. Landis, and G. Koch, "The measurement of observer agreement for categorical data," Biometrics, vol. 33, no. 1, pp. 159-174, 1977.
[13] M. Pitzalis, F. Mastropasqua, F. Massari, et al., "Short- and long-term reproducibility of time and frequency domain heart rate variability measurements in normal subjects," Cardiovasc Res, vol. 32, no. 2, pp. 226-233, 1996.