## Abstract

Original language | English |
---|---|

Journal | Chaos |

Volume | 27 |

Issue number | 9 |

DOIs | |

Publication status | Published - 2017 |

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*Chaos*,

*27*(9). https://doi.org/10.1063/1.4999353

**Assessing multiscale complexity of short heart rate variability series through a model-based linear approach.** / Porta, A.; Bari, V.; Ranuzzi, G. et al.

Research output: Contribution to journal › Article › peer-review

*Chaos*, vol. 27, no. 9. https://doi.org/10.1063/1.4999353

**Assessing multiscale complexity of short heart rate variability series through a model-based linear approach**. In: Chaos. 2017 ; Vol. 27, No. 9.

}

TY - JOUR

T1 - Assessing multiscale complexity of short heart rate variability series through a model-based linear approach

AU - Porta, A.

AU - Bari, V.

AU - Ranuzzi, G.

AU - De Maria, B.

AU - Baselli, G.

N1 - Cited By :2 Export Date: 2 March 2018 Correspondence Address: Porta, A.; Department of Biomedical Sciences for Health, University of MilanItaly; email: alberto.porta@unimi.it References: Costa, M., Goldberger, A.L., Peng, C.-K., Multiscale entropy analysis of complex physiologic time series (2002) Phys. Rev. Lett, 89; Humeau-Heurtier, A., The multiscale entropy algorithm and its variants (2015) Entropy, 17, pp. 3110-3123; Valencia, J.F., Porta, A., Vallverdù, M., Clarià, F., Baranowski, R., Orlowska-Baranowska, E., Caminal, P., Refined multiscale entropy: Application to 24-h Holter recordings of heart period variability in healthy and aortic stenosis subjects (2009) IEEE Trans. Biomed. Eng, 56, pp. 2202-2213; Wu, S.-D., Wu, C.-W., Lin, S.-G., Lee, K.-Y., Peng, C.-K., Analysis of complex time series using refined composite multiscale entropy (2014) Phys. Lett. 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PY - 2017

Y1 - 2017

N2 - We propose a multiscale complexity (MSC) method assessing irregularity in assigned frequency bands and being appropriate for analyzing the short time series. It is grounded on the identification of the coefficients of an autoregressive model, on the computation of the mean position of the poles generating the components of the power spectral density in an assigned frequency band, and on the assessment of its distance from the unit circle in the complex plane. The MSC method was tested on simulations and applied to the short heart period (HP) variability series recorded during graded head-up tilt in 17 subjects (age from 21 to 54 years, median=28 years, 7 females) and during paced breathing protocols in 19 subjects (age from 27 to 35 years, median=31 years, 11 females) to assess the contribution of time scales typical of the cardiac autonomic control, namely in low frequency (LF, from 0.04 to 0.15 Hz) and high frequency (HF, from 0.15 to 0.5 Hz) bands to the complexity of the cardiac regulation. The proposed MSC technique was compared to a traditional model-free multiscale method grounded on information theory, i.e., multiscale entropy (MSE). The approach suggests that the reduction of HP variability complexity observed during graded head-up tilt is due to a regularization of the HP fluctuations in LF band via a possible intervention of sympathetic control and the decrement of HP variability complexity observed during slow breathing is the result of the regularization of the HP variations in both LF and HF bands, thus implying the action of physiological mechanisms working at time scales even different from that of respiration. MSE did not distinguish experimental conditions at time scales larger than 1. Over a short time series MSC allows a more insightful association between cardiac control complexity and physiological mechanisms modulating cardiac rhythm compared to a more traditional tool such as MSE.

AB - We propose a multiscale complexity (MSC) method assessing irregularity in assigned frequency bands and being appropriate for analyzing the short time series. It is grounded on the identification of the coefficients of an autoregressive model, on the computation of the mean position of the poles generating the components of the power spectral density in an assigned frequency band, and on the assessment of its distance from the unit circle in the complex plane. The MSC method was tested on simulations and applied to the short heart period (HP) variability series recorded during graded head-up tilt in 17 subjects (age from 21 to 54 years, median=28 years, 7 females) and during paced breathing protocols in 19 subjects (age from 27 to 35 years, median=31 years, 11 females) to assess the contribution of time scales typical of the cardiac autonomic control, namely in low frequency (LF, from 0.04 to 0.15 Hz) and high frequency (HF, from 0.15 to 0.5 Hz) bands to the complexity of the cardiac regulation. The proposed MSC technique was compared to a traditional model-free multiscale method grounded on information theory, i.e., multiscale entropy (MSE). The approach suggests that the reduction of HP variability complexity observed during graded head-up tilt is due to a regularization of the HP fluctuations in LF band via a possible intervention of sympathetic control and the decrement of HP variability complexity observed during slow breathing is the result of the regularization of the HP variations in both LF and HF bands, thus implying the action of physiological mechanisms working at time scales even different from that of respiration. MSE did not distinguish experimental conditions at time scales larger than 1. Over a short time series MSC allows a more insightful association between cardiac control complexity and physiological mechanisms modulating cardiac rhythm compared to a more traditional tool such as MSE.

U2 - 10.1063/1.4999353

DO - 10.1063/1.4999353

M3 - Article

VL - 27

JO - Chaos

JF - Chaos

SN - 1054-1500

IS - 9

ER -