Estimation of the aortic pressure waveform from a peripheral artery pressure waveform via an adaptive transfer function

We developed a new technique to estimate the aortic pressure (AP) waveform from a single peripheral artery pressure (PAP) waveform. The technique 1) employs a parallel tube model of the arterial tree to establish a transfer function relating PAP to AP with unknown parameters; 2) estimates the parameters from the measured PAP waveform, along with a single non-invasive measurement of the wave transmission delay from the aorta to the peripheral artery measurement site, by exploiting the fact that aortic flow is zero during diastole; and 3) applies the transfer function to the PAP waveform to predict the unmeasured AP waveform. In this way, in contrast to the conventional generalized transfer function paradigm, the transfer function is able to adapt to the inter-subject and temporal variability of the arterial tree. We applied this adaptive transfer function technique to PAP waveforms measured from five dogs instrumented with reference AP catheters during various hemodynamic interventions. Our results showed that the technique was able to reliably estimate the AP waveform with an overall error of 4.2 mmHg. For comparison, the corresponding errors of two previously proposed generalized transfer functions trained on a subset of the same canine data were, on average, 19% larger.