Toward a more physiologically constrained instantaneous heart rate

Danilo Scepanovic, Harvard/Massachusetts Institute of Technology

Heart rate (HR) is one of the most commonly monitored physiological signals for patients in emergency rooms and intensive care wards. Average HR is physiologically significant on its own; however, quantities derived from the time-varying HR signal have proven more useful in certain clinical situations (ex. heart rate variability (HRV)).

Unfortunately, the HR time series is poorly defined due to the randomly sampled nature of the signal, and current algorithms for estimating instantaneous HR are either non-physiological (contain stepwise discontinuities and ignore the cardiac refractory period) or inaccurate (spectrally smeared).

In our previous work, we developed a parametric model of instantaneous HR. We showed that instantaneous HR may be modeled using the statistical framework we developed, and that model parameters can be extracted from available data.

This poster presents the next phase of the work, where we lay the foundation for adding more physiological detail to the instantaneous HR model. Whereas instantaneous HR was previously an abstract concept, we aim to define it in terms of physical processes: for example, concentrations of second messengers or membrane ion channel conductance. We describe the physiology of the cells responsible for heart beat generation, how their activity is modeled, and we evaluate a parallel implementation for solving the system of equations to simulate the model.

Abstract Author(s): Danilo Scepanovic, Richard J. Cohen