Abstract: Methods and apparatus for estimating a measure of cardiac contractility based on a set of features determined from a set of signals associated with a mechanical circulatory support device are provided. The method includes determining, using computer processor, a set of features based, at least in part, on the set of signals, providing the set of features as input to a machine learning model trained to output a measure of cardiac contractility, and performing an action based, at least in part, on the measure of cardiac contractility output by the machine learning model.

Abstract: Methods and systems are provided that utilize smart hemodynamic support devices positioned in one area of the body, in combination with machine learning to infer and/or detect conditions in other areas of the body operably connected via blood flow.