In this work, we perform a comparative analysis of discrete- and continuous-time estimators of information-theoretic measures quantifying the concept of memory utilization in short-term heart rate variability (HRV). Specifically, considering heartbeat intervals in discrete time we compute the measure of information storage (IS) and decompose it into immediate memory utilization (IMU) and longer memory utilization (MU) terms; considering the timings of heartbeats in continuous time we compute the measure of MU rate (MUR). All measures are computed through model-free approaches based on nearest neighbor entropy estimators applied to the HRV series of a group of 15 healthy subjects measured at rest and during postural stress. We find, moving from rest to stress, statistically significant increases of the IS and the IMU, as well as of the MUR. Our results suggest that both discrete-time and continuous-time approaches can detect the higher predictive capacity of HRV occurring with postural stress, and that such increased memory utilization is due to fast mechanisms likely related to sympathetic activation.

Mijatovic, G., Bara, C., Pernice, R., Loncar-Turukalo, T., Nollo, G., Faes, L. (2023). Exploring the Short-Term Memory of Heart Rate Variability through Model-Free Information Measures. In Proceedings 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 1-4) [10.1109/EMBC40787.2023.10341158].

Exploring the Short-Term Memory of Heart Rate Variability through Model-Free Information Measures

Bara, Chiara;Pernice, Riccardo;Faes, Luca
2023-07-01

Abstract

In this work, we perform a comparative analysis of discrete- and continuous-time estimators of information-theoretic measures quantifying the concept of memory utilization in short-term heart rate variability (HRV). Specifically, considering heartbeat intervals in discrete time we compute the measure of information storage (IS) and decompose it into immediate memory utilization (IMU) and longer memory utilization (MU) terms; considering the timings of heartbeats in continuous time we compute the measure of MU rate (MUR). All measures are computed through model-free approaches based on nearest neighbor entropy estimators applied to the HRV series of a group of 15 healthy subjects measured at rest and during postural stress. We find, moving from rest to stress, statistically significant increases of the IS and the IMU, as well as of the MUR. Our results suggest that both discrete-time and continuous-time approaches can detect the higher predictive capacity of HRV occurring with postural stress, and that such increased memory utilization is due to fast mechanisms likely related to sympathetic activation.
lug-2023
Settore ING-INF/06 - Bioingegneria Elettronica E Informatica
979-8-3503-2447-1
Mijatovic, G., Bara, C., Pernice, R., Loncar-Turukalo, T., Nollo, G., Faes, L. (2023). Exploring the Short-Term Memory of Heart Rate Variability through Model-Free Information Measures. In Proceedings 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 1-4) [10.1109/EMBC40787.2023.10341158].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/620001
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