Estimation and Modeling of QT-Interval Adaptation to Heart Rate Changes

Abstract

. Performance of this methodology is evaluated using synthetic data. In parallel, a new model of QT-interval dynamics behavior related to heart rate changes is presented. Since two kinds of QT response have been pointed out, the main idea is to split the modeling process into two steps: 1) the modeling of the fast adaptation, which is inspired by the electrical behavior at the cellular level relative to the electrical restitution curve, and, 2) the modeling of the slow adaptation, inspired by experimental works at the cellular level. Both approaches are based on a low-complexity autoregressive process whose parameters are estimated using an unbiased estimator. This new modeling of QT adaptation, combined with the presented QT estimation process, is applied to several ECG recordings with various heart rate variability dynamics. Its potential is then illustrated on ECG recorded during rest, atrial fibrillation episodes, and exercise. Meaningful results in agreement with physiological knowledge at the cellular level are obtained.

Scaling and correlation properties of RR and QT intervals at the cellular level

“…In a normal heart, QT variability is often described in the context of heart rate variability, because the variability in RR intervals is the major physiological source of variability in QT intervals 8 . There is a clear response of QT to the acceleration and deceleration of the heart rate 37 . Moreover, recent studies have shown that there is a non-trivial dynamic relationship in terms of transfer entropy between RR and QT intervals 38 .…”

Beat-to-Beat Variability of Ventricular Action Potential Duration Oscillates at Low Frequency During Sympathetic Provocation in Humans

“…Extrapolation from our findings on BBV of APD with cycle length maintained constant to studies of QT variability is not straightforward. In physiological conditions QT variability is substantially influenced by heart rate variability due to the rapid and slow components of the cycle length dependence of APD (Franz et al, 1988 ; Zaza et al, 1991 ; Cabasson et al, 2012 ). QT variability when cycle length is held constant is considered to be due to both variation in APD and variation in activation pattern and hence conduction time (Baumert et al, 2016 ).…”

Categorization and theoretical comparison of quantitative methods for assessing QT/RR hysteresis

“…Two‐parameter models differentiate immediate QT response and long‐term memory (Halamek et al., ; Jacquemet et al., ). This is conceptually similar to the Cabasson model (Cabasson et al., ) which approximates the fast component of QT response to correspond to the immediate response of APD described by S1‐S2 restitution curves, and adds an element of memory to explain slower QT changes. Indeed, the S1‐S2 and dynamic restitution protocols are thought to respectively describe the fast and steady‐state response of APD to rate change (Kalb et al., ).…”