Bootstrapping the empirical bounds on the variability of Sample Entropy in 24-hour ECG recordings for 1 hour segments

• Autorzy: Zurek S. , Grabowski W. , Kosmider M. , Jurga S. , Guzik P. , Piskorski J.

Identyfikatory

DOI

10.17512/jamcm.2018.2.09

• Języki publikacji: EN

Abstrakty

EN

We investigate the variability of one of the most often used complexity measures in the analysis of the time series of RR intervals, i.e. Sample Entropy. The analysis is carried out for a dense matrix of possible r thresholds in 79 24h recordings, for segments consisting of 5000 consecutive beats, randomly selected from the whole recording. It is repeated for the same recordings in random order. This study is made possible by the novel NCM algorithm which is many orders of magnitude faster than the alternative approaches. We find that the bootstrapped standard errors for Sample entropy are large for RR intervals in physiological order compared to the standard errors for shuffled data which correspond to the maximum available entropy. This result indicates that Sample Entropy varies widely over the circadian period. This paper is purely methodological and no physiological interpretations are attempted.

Słowa kluczowe

EN

sample entropy; complexity; bootstrap; heart rhythm variability

PL

zmienność rytmu serca; entropia próbkowa; elektrokardiogram; szacowanie błędu

• Wydawca: Wydawnictwo Politechniki Częstochowskiej
• Czasopismo: Journal of Applied Mathematics and Computational Mechanics
• Rocznik: 2018
• Tom: Vol. 17, nr 2
• Strony: 105--113
• Opis fizyczny: Bibliogr. 13 poz., rys., tab.

Twórcy

autor

Zurek S.

• Institute of Physics, University of Zielona Gora Zielona Gora, Poland

autor

Grabowski W.

• Institute of Physics, University of Zielona Gora Zielona Gora, Poland

autor

Kosmider M.

• Faculty of Medicine and Health Sciences, University of Zielona Gora Zielona Gora, Poland

autor

Jurga S.

• Faculty of Medicine and Health Sciences, University of Zielona Gora Zielona Gora, Poland

autor

Guzik P.

• Department of Cardiology - Intensive Therapy, Poznan University of Medical Sciences Poznan, Poland

autor

Piskorski J.

• Institute of Physics, University of Zielona Gora Zielona Gora, Poland

Bibliografia

• [1] Pincus, S.M., & Goldberger, A.L. (1994). Physiological time-series analysis: What does regularity quantify? Am J Physiol (Heart Circ Physiol), 266, H1643-1656.
• [2] Lu, S., Chen, X., Kanters, J., Solomon, I., & Chon, K. (2008). Automatic selection of the threshold value r for approximate entropy. IEEE Trans Biomed Eng, 55, 1966-1972.
• [3] Stam, C.J. (2005). Nonlinear dynamical analysis of eeg and meg: Review of an emerging field. Clin Neurophysiol, 116, 2266-2301.
• [4] Grassberger, P., & Procaccia, I. (1983). Measuring the strangeness of strange attractors. Physica D, 9, 189-208.
• [5] Pincus, S. M. (1991). Approximate entropy as a measure of system complexity. PNAS, 88, 2297-2301.
• [6] Pincus, S.M., Cummins, T.R., & Haddad, G.G. (1993). Heart rate control in normal and aborted-SIDS infants. Am J Physiol Regulatory Integrative Comp Physiol, 264, 638-646.
• [7] Richman, J.S., & Moorman, J.R. (2000). Physiological time-series analysis using approximate entropy and sample entropy. Am J Physiol (Heart Circ Physiol), 278, H2039-2049.
• [8] Nardelli, M., Valenza, G., Cristea, I.A., Gentili, C., Cotet, C., David, D., Lanata, A., & Sciling, E.P. (2015). Characterizing psychological dimensions in non-pathological subjects through autonomic nervous system dynamics. Front. Comput. Neurosci., 9, 37.
• [9] Lake, D.E., Richman, J. S., Griffin, M.P., & Moorman, J.R. (2002). Sample entropy analysis of neonatal heart rate variability. Am J Physiol Regul Integr Comp Physiol, 283, R789-R797.
• [10] Hu, X., Ebenli, S., Jia, Z., & Egardt, B. (2014). Enhanced sample entropy-based health management of li-ion battery for electrified vehicles. Energy, 64, 953-960.
• [11] Zurek, S., Guzik, P., Pawlak, S., Kosmider, M., & Piskorski, J. (2012). On the relation between correlation dimension, approximate entropy and sample entropy parameters, and a fast algorithm for their calculation. Physica A, 391, 6601-6610.
• [12] Hardle, W., & Simar, L. (2003). Applied Multivariate Statistical Analysis. Berlin: Springer Verlag.
• [13] Zurek, S. (2018, May 14). NCM-algorithm n.d. Retrieved from https://github.com/sebzur/NCMalgorithm.

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).