Adaptive transfer function for determining central blood pressure

A method for determining central blood pressure for a subject, comprising:

• measuring, by a sensor, a peripheral blood pressure waveform from the subject;
• defining a model that relates the measured peripheral blood pressure waveform to a central blood pressure waveform, where the model is defined in terms of parameters representing wave travel time and wave reflection coefficient;
• selecting multiple sets of candidate values for the model parameters;
• computing, for each set of candidate values, a candidate central blood pressure waveform by applying the model with a given set of candidate values to the measured peripheral blood pressure waveform;
• fitting, for each candidate central blood pressure waveform, an exponential to the diastolic decay of a given candidate central blood pressure waveform;
• and
• determining central blood pressure as being the candidate central blood pressure waveform having smallest fitting error between the exponential and the diastolic decay, where the steps of computing, fitting and determining are executed by a computer processor of a computing device.

A method for determining central blood pressure for a subject, comprising;

• measuring, by a sensor, a peripheral blood pressure waveform from the subject;
• defining a model that relates the measured peripheral blood pressure waveform to a central blood pressure waveform, where the model is defined in terms of parameters representing the wave travel time and wave reflection coefficient;
• determining the parameters representing the wave reflection coefficient based on population averages;
• determining the parameters representing wave travel time based on its inverse relationship with blood pressure;
• and
• determining central blood pressure by applying the determined model to the measured peripheral blood pressure waveform, where the step of determining is executed by a computer processor of a computing device.

A computer-implemented system for determining central blood pressure for a subject, comprising:

• a sensor configured to measure a peripheral blood pressure waveform of the subject;
• a data store that stores a model that relates the measured peripheral blood pressure waveform to a central blood pressure waveform, where the model is defined in terms of wave travel time and wave reflection coefficient;
• a model estimation module configured to receive the measured peripheral blood pressure waveform from the sensor and to receive multiple sets of candidate values for wave travel time and wave reflection coefficient,
• wherein the model estimation module computes, for each set of candidate values, a candidate central blood pressure waveform by applying the model with a given set of candidate values to the measured peripheral blood pressure waveform and fits, for each candidate central blood pressure waveform, an exponential to diastolic decay of a given candidate central blood pressure waveform, wherein the model estimation module is computer readable instructions executed by a computer processor residing on a computing device.