Abstract
In the study, Granger causality frequency analysis based on directed coherence is utilized to detect and quantify directional interaction among heart rate, systolic blood pressure and respiratory signal during postural stress from supine to standing and from standing to supine. The directional information flow during postural stress from supine to standing is dominant on cardiorespiratory interaction, vasculo-respiratory interaction and cardiovascular interaction. Conversely, the reverse postural stress from standing to supine resulted in a contrary effect on both cardiorespiratory and cardiovascular interactions without significant change in vasculo-respiratory interaction. Based on the power change, we observed that postural stress gets affected by both cardiorespiratory and cardiovascular but not by vasculo-respiratory system. Therefore, the directed coherence power calculated for each interaction helps to identify short-term regulatory mechanism during postural stress.
Similar content being viewed by others
Abbreviations
- ABP:
-
Arterial blood pressure
- AR:
-
Autoregressive
- DC:
-
Directed coherence
- ECG:
-
Electrocardiogram
- HF:
-
High frequency
- LF:
-
Low frequency
- MVAR:
-
Multivariate autoregressive
- RESP:
-
Respiration
- PSD:
-
Power spectral density
- A :
-
Model coefficient matrix
- \(\varGamma \) :
-
Coherence
- \(\gamma \) :
-
Directed coherence power
References
Acharya, U.R., Joseph, K.P., Kannathal, N., Lim, C.M., Suri, J.S.: Heart Rate Variability, Advances in Cardiac Signal Processing, pp. 121–165. Springer, Berlin (2007)
Akaike, H.: A new look at the statistical model identification. IEEE Trans. Autom. Control 19(6), 716–723 (1974)
Akselrod, S., Gordon, D., Ubel, F.A., Shannon, D.C., Berger, A., Cohen, R.J.: Power spectrum analysis of heart rate fluctuation: a quantitative probe of beat-to-beat cardiovascular control. Science 213(4504), 220–222 (1981)
Baccala, L., Sameshima, K., Ballester, G., Do Valle, A., Timo-Iaria, C.: Studying the interaction between brain structures via directed coherence and Granger causality. Appl. Signal Process. 5(1), 40 (1998)
Baselli, G., Cerutti, S., Livraghi, M., Meneghini, C., Pagani, M., Rimoldi, O.: Causal relationship between heart rate and arterial blood pressure variability signals. Med. Biol. Eng. Comput. 26(4), 374–378 (1988)
Baselli, G., Porta, A., Rimoldi, O., Pagani, M., Cerutti, S.: Spectral decomposition in multichannel recordings based on multivariate parametric identification. IEEE Trans. Biomed. Eng. 44(11), 1092–1101 (1997)
De Boer, R., Karemaker, J., Strackee, J.: Relationships between short-term blood-pressure fluctuations and heart-rate variability in resting subjects I: a spectral analysis approach. Med. Biol. Eng. Comput. 23(4), 352–358 (1985)
Eftaxias, K., Sanei, S.: Discrimination of task-related eeg signals using diffusion adaptation and s-transform coherency. In: IEEE International Workshop on Machine Learning for Signal Processing (MLSP), pp. 1-6. (2014)
Eichler, M.: Causal inference with multiple time series: principles and problems. Philos. Trans. R. Soc. A 371(1997), 20110613 (2013)
Escudero, J., Sanei, S., Jarchi, D., Abasolo, D., Hornero, R.: Regional coherence evaluation in mild cognitive impairment and alzheimer’s disease based on adaptively extracted magnetoencephalogram rhythms. Physiol. Meas. 32(8), 1163 (2011)
Faes, L., Erla, S., Porta, A., Nollo, G.: A framework for assessing frequency domain causality in physiological time series with instantaneous effects. Philos. Trans. R. Soc. A 371(1997), 20110618 (2013)
Faes, L., Nollo, G.: Multivariate frequency domain analysis of causal interactions in physiological time series. In: Biomedical Engineering, Trends in Electronics, Communications and Software. InTech (2011)
Faes, L., Nollo, G., Porta, A.: Information domain approach to the investigation of cardio-vascular, cardio-pulmonary, and vasculo-pulmonary causal couplings. Front. Physiol. 2, 80 (2011)
Faes, L., Nollo, G., Porta, A.: Compensated transfer entropy as a tool for reliably estimating information transfer in physiological time series. Entropy 15(1), 198–219 (2013)
Faes, L., Widesott, L., Del Greco, M., Antolini, R., Nollo, G.: Causal cross-spectral analysis of heart rate and blood pressure variability for describing the impairment of the cardiovascular control in neurally mediated syncope. IEEE Trans. Biomed. Eng. 53(1), 65–73 (2006)
Granger, C.W.: Investigating causal relations by econometric models and cross-spectral methods. Econom.: J. Econom. Soc. 37(3), 424–438 (1969)
Granger, C.W.: Testing for causality: a personal view point. J. Econ. Dyn. Control 2, 329–352 (1980)
Javorka, M., Czippelova, B., Turianikova, Z., Lazarova, Z., Tonhajzerova, I., Faes, L.: Causal analysis of short-term cardiovascular variability: state-dependent contribution of feedback and feedforward mechanisms. Med. Biol. Eng. Comput. 55(2), 179–190 (2017)
Li, B.N., Dong, M.C., Vai, M.I.: On an automatic delineator for arterial blood pressure waveforms. Biomed. Signal Process. Control 5(1), 76–81 (2010)
Manikandan, M.S., Soman, K.: A novel method for detecting R-peaks in electrocardiogram (ECG) signal. Biomed. Signal Process. Control 7(2), 118–128 (2012)
Marwaha, P., Sunkaria, R.K.: Exploring total cardiac variability in healthy and pathophysiological subjects using improved refined multiscale entropy. Med. Biol. Eng. Comput. 55(2), 191–205 (2017)
Marwan, N., Zou, Y., Wessel, N., Riedl, M., Kurths, J.: Estimating coupling directions in the cardiorespiratory system using recurrence properties. Philos. Trans. R. Soc. A 371(1997), 20110624 (2013)
Mary, M.H., Singh, D., Deepak, K.: Impact of respiration on cardiovascular coupling using Granger causality analysis in healthy subjects. Biomed. Signal Process. Control 43, 196–203 (2018)
Naidu, V., Reddy, M.: Autoregressive (AR) based power spectral analysis of heart rate time series signal (HRTS signal). In: IEEE Conference on Convergent Technologies for the Asia-Pacific Region TENCON, vol. 4, pp. 1391–1394 (2003)
Nollo, G., Faes, L., Porta, A., Antolini, R., Ravelli, F.: Exploring directionality in spontaneous heart period and systolic pressure variability interactions in humans: implications in the evaluation of baroreflex gain. Am. J. Physiol.-Heart Circ. Physiol. 288(4), H1777–H1785 (2005)
Parati, G., Saul, J.P., Di Rienzo, M., Mancia, G.: Spectral analysis of blood pressure and heart rate variability in evaluating cardiovascular regulation: a critical appraisal. Hypertension 25(6), 1276–1286 (1995)
Perlmuter, L.C., Sarda, G., Casavant, V., OHara, K., Hindes, M., Knott, P.T., Mosnaim, A.D.: A review of orthostatic blood pressure regulation and its association with mood and cognition. Clin. Auton. Res. 22(2), 99–107 (2012)
Porta, A., Bassani, T., Bari, V., Tobaldini, E., Takahashi, A.C., Catai, A.M., Montano, N.: Model-based assessment of baroreflex and cardiopulmonary couplings during graded head-up tilt. Comput. Biol. Med. 42(3), 298–305 (2012)
Rangayyan, R.M., Reddy, N.P.: Biomedical signal analysis: a case-study approach. Ann. Biomed. Eng. 30(7), 983–983 (2002)
Richman, J.S., Moorman, J.R.: Physiological time-series analysis using approximate entropy and sample entropy. Am. J. Physiol.-Heart Circ. Physiol. 278(6), H2039–H2049 (2000)
Schulz, S., Adochiei, F.C., Edu, I.R., Schroeder, R., Costin, H., Bar, K.J., Voss, A.: Cardiovascular and cardiorespiratory coupling analyses: a review. Philos. Trans. R. Soc. A 371(1997), 20120191 (2013)
Singh, D., Vinod, K., Saxena, S.C., Deepak, K.K.: Effects of RR segment duration on HRV spectrum estimation. Physiol. Meas. 25(3), 721 (2004)
Steven, M.K.: Modern Spectral Estimation: Theory and Application. Signal Processing Series. American Physiological Society Bethesda, MD (1988)
Stewart, J.M.: Mechanisms of sympathetic regulation in orthostatic intolerance. J. Appl. Physiol. 113(10), 1659–1668 (2012)
Acknowledgements
The authors would like to thank Biomedical Instrumentation Laboratory, Department of Instrumentation and Control, Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, and to all volunteers who took part in the recording.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Mary, M.C.H., Singh, D. & Deepak, K.K. Detecting changes in cardiovascular interaction during postural stress using directed coherence. SIViP 13, 1521–1528 (2019). https://doi.org/10.1007/s11760-019-01495-4
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11760-019-01495-4