Estimating blood pressure of a subject using an ecg driven cardiovascular model

A system comprising:

• a memory storing instructions in an in-silico cardiovascular hemodynamic model;
• one or more communication interfaces;
• and
• one or more hardware processors coupled to the memory (102) via the one or more communication interfaces, wherein the one or more hardware processors are configured by the instructions to:
• estimate, in each cardiac cycle of an electrocardiogram (ECG) signal, cardiac parameters based on morphology of the ECG signal associated with a subject, wherein the cardiac parameters include a continuous heart rate (HR) and a set of compliance parameters, and wherein estimating the set of compliance parameters is based on:
• (i) a set of PQRST amplitudes;
• and
• (ii) time-instances, ([(αpj, tpj), (αqj, tqj), (αrj, trj), (αsj, tsj), (αtj, ttj)];
• j∈m)
• for a jth cardiac cycle (∀j∈m) of the ECG signal;
• generate, a set of compliance functions using the estimated cardiac parameters;
• sequentially activate, a plurality of cardiac chambers, in a synchronized manner, using the generated set of compliance functions;
• and
• estimate blood pressure of the subject, by the in-silico cardiovascular hemodynamic model via the one or more hardware processors, wherein the in-silico cardiovascular hemodynamic model is driven by the ECG signal associated with the subject.

One or more non-transitory machine-readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors cause:

• estimating, by an in-silico cardiovascular hemodynamic model via one or more hardware processors, in each cardiac cycle of an electrocardiogram (ECG) signal, cardiac parameters based on morphology of the ECG signal associated with a subject, wherein the cardiac parameters include a continuous heart rate (HR) and a set of compliance parameters, and wherein estimating the set of compliance parameters is based on:
• (i) a set of PQRST amplitudes;
• and
• (ii) time-instances, ([(αpj, tpj), (αqj, tqj), (αrj, trj), (αsj, tsj), (αtj, ttj)];
• j∈m)
• for a jth cardiac cycle (∀j∈m) of the ECG signal;
• generating, by the in-silico cardiovascular hemodynamic model via the one or more hardware processors, a set of compliance functions using the estimated cardiac parameters;
• sequentially activating, by the in-silico cardiovascular hemodynamic model via the one or more hardware processors, a plurality of cardiac chambers, in a synchronized manner, using the generated set of compliance functions;
• and
• estimating blood pressure of the subject, by the in-silico cardiovascular hemodynamic model via the one or more hardware processors, wherein the in-silico cardiovascular hemodynamic model is driven by the ECG signal associated with the subject.