The IPFM model with time-varying threshold estimated autonomic nervous system modulation with lower errors than the constant threshold model (1.1% vs 15.0%) in simulations.
Does an IPFM model with a time-varying threshold improve the estimation of ANS modulation during exercise stress testing compared to a constant threshold model?
An IPFM model incorporating a time-varying threshold improves the accuracy of estimating autonomic nervous system modulation during exercise stress testing.
Absolute Event Rate: 1.1% vs 15%
In this paper, an approach for heart rate variability analysis during exercise stress testing is proposed based on the integral pulse frequency modulation (IPFM) model, where a time-varying threshold is included to account for the nonstationary mean heart rate. The proposed technique allows the estimation of the autonomic nervous system (ANS) modulating signal using the methods derived for the IPFM model with constant threshold plus a correction, which is shown to be needed to take into account the time-varying mean heart rate. On simulations, this technique allows the estimation of the ANS modulation on the heart from the beat occurrence time series with lower errors than the IPFM model with constant threshold (1.1% ± 1.3% versus 15.0% ± 14.9%). On an exercise stress testing database, the ANS modulation estimated by the proposed technique is closer to physiology than that obtained from the IPFM model with constant threshold, which tends to overestimate the ANS modulation during the recovery and underestimate it during the initial rest.
Bailón et al. (Sat,) conducted a other in Heart rate variability during exercise stress testing. Integral pulse frequency modulation (IPFM) model with time-varying threshold vs. IPFM model with constant threshold was evaluated on Estimation error of the autonomic nervous system modulation on the heart from the beat occurrence time series (simulations). The IPFM model with time-varying threshold estimated autonomic nervous system modulation with lower errors than the constant threshold model (1.1% vs 15.0%) in simulations.