Optimal ECG Sampling Frequency for Multiscale Entropy-Based HRV

Authors: Manjit Singh

Abstract:

Multiscale entropy (MSE) is an extensively used index to provide a general understanding of multiple complexity of physiologic mechanism of heart rate variability (HRV) that operates on a wide range of time scales. Accurate selection of electrocardiogram (ECG) sampling frequency is an essential concern for clinically significant HRV quantification; high ECG sampling rate increase memory requirements and processing time, whereas low sampling rate degrade signal quality and results in clinically misinterpreted HRV. In this work, the impact of ECG sampling frequency on MSE based HRV have been quantified. MSE measures are found to be sensitive to ECG sampling frequency and effect of sampling frequency will be a function of time scale.

Keywords: ECG, heart rate variability, HRV, multiscale entropy, sampling frequency.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1315806

References:

[1] Eckberg, D. L. (2011). Sympathovagal balance. Circulation, 96, 3224-3232.
[2] Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology (1996). Heart rate variability - standards of measurement, physiological interpretation and clinical use. European Heart Journal, 17, 354-381.
[3] Acharya, U. R., Joseph, K. P., Kannathal, N., Lim, C. M., Suri, J. S. (2006). Heart rate variability: a review. Medical and Biological Engineering and Computing, 44, 1031-1051.
[4] Singh, B., Singh, D., (2011). Ectopic beats and editing methods for Poincaré-plot-based HRV. International Journal. Biomedical Engineering and Technology, 7(4), 353–364.
[5] Berntson, G. G., Bigger, J. T., Eckberg, D.L., Grossman P., Kaufmann, P. G., Malik, M., Nagaraja, N., Porges, S. W., Saul, J. P., Stone, P. H., Van der Molen, M. W. (1997). Heart rate variability: Origins, methods, and interpretive caveats. Psychophysiology, 34, 623-648.
[6] Singh. B., Singh, D. (2012). Effect of Threshold Value r on Multiscale Entropy based Heart Rate Variability. Cardiovascular Engineering and Technology, 2(3), 211-216.
[7] Pagani, M., Lombardi, F., Guzzetti, S., Rimoldi, O., Furlan R., Pizzinelli P., Sandrone G., Malfatto G., Dell'Orto, S., Piccaluga, E. (1986). Power spectral analysis of heart rate and arterial pressure variability as a marker of sympatho-vagal interaction in man and conscious dog. Circulation Research, 59,178-183.
[8] Singh, B., Singh, D., (2012). Modified multiscale entropy in HRV for automatic selection of threshold value r. International Journal Medical Engineering and Informatics. 4(1), 55–65.
[9] Costa, M., Goldberger, A. L., Peng, C. K. (2002) Multiscale entropy analysis of complex physiological time series. Physical Review Letters, 89(6), 068102(1)–068102(4).
[10] Costa, M., Goldberger, A. L., Peng, C. K. (2002). Multiscale entropy to distinguish physiological and synthetic RR time series. Computers in Cardiology, 29, 37–40.
[11] Costa, M., Goldberger, A. L., Pen, C. K. (2005). Multiscale entropy analysis of biological signals. Physical Review E, 71(2), 021906(1)–021906(18).
[12] Pincus, S. M. (1991). Approximation entropy as a measure of system complexity. Proceedings of the National Academy of Sciences USA, 88, 2297–2301.
[13] Pincus, S. M., Goldberger, A. L. (1994) Physiological time-series analysis: what does regularity quantify. American Journal of Physiology (Heart CircPhysiol), 35, 1643–656.
[14] Richman, J. S., Moorman, J. R. (2002). Physiological time series analysis using approximate entropy and sample entropy. American Journal of Physiology – Heart and Circulatory Physiology, 278, 2039–2049.
[15] Singh, B., Singh, D., Jaryal, A. K., Deepak, K. K. (2012). Ectopic beats in approximate entropy and sample entropy-based HRV assessment. International Journal of Systems Science, 43(5), 884-893.
[16] Hejjel, L., Rooth, E. (2004). What is the adequate sampling interval of ECG signal for heart rate variability analysis in time domain?. Physiological Measurements, 25, 1405-1411.
[17] Ziemsseen, T., Gascg, Z., Ruediger, H. (2008). Influence of ECG sampling frequency on spectral analysis of RR intervals and baroreflex sensitivity using eurobarvar data. Journal of Clinical Monitoring and Computing, 22, 159-168.
[18] Abboud, S, Barnea, O. (1995). Errors due to sampling frequency of electrocardiogram in spectral analysis of heart rate signals with low variability. Proceedings of IEEE Computers in Cardiology, 461-463.
[19] Singh, B., Singh, M., Banga V. K., (2014). Sample entropy based HRV: effect of ECG sampling frequency. Biomedical Science and Engineering, 2(3), 68-72.
[20] Singh, M., Singh, B., Banga, V. K. (2014). Effect of ECG sampling frequency on approximate entropy based HRV. International. Journal of Bio-Science and Bio-Technology, 6(4), 179-186.
[21] Zidelmal, Z., Amirou, A., Moukadem, A., Dieterlen, A. (2014). QRS detection using S-transform and Shannon energy. Computer Methods and Programs in Biomedicine, 116(1), 1–9.n.
[22] Zidelmal, Z., Amirou, A., Adnane, M., Belouchrani, A. (2014) QRS detection based on wavelet coefficients. Computer Methods and Programs in Biomedicine, 107(3), 490–496.
[23] Pan, J., Tompkins, W. J. (1985). A real-time QRS detection algorithm. IEEE Transaction on Biomedical Engineering, 32(3), 230–336.