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Exploring the Short-Term Memory of Heart Rate Variability through Model-Free Information Measures
  • +3
  • Gorana Mijatovic,
  • Chiara Barà,
  • Riccardo Pernice,
  • Tatjana Loncar-Turukalo,
  • Giandomenico Nollo,
  • Luca Faes
Gorana Mijatovic

Corresponding Author:[email protected]

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Chiara Barà
Riccardo Pernice
Tatjana Loncar-Turukalo
Giandomenico Nollo
Luca Faes


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.
20 Dec 2023Submitted to TechRxiv
22 Dec 2023Published in TechRxiv