Algorithmic Processing of Pressure Waveforms to FacilitateEstimation of Cardiac Elastance

Introduction: Cardiac elastances are highly invasive to measure directly, but are clinically useful due tothe amount of information embedded in them. Information about the cardiac elastance, which can be used toestimate it, can be found in the downstream pressure waveforms of aortic pressure (Pao) and the pulmonaryartery (Ppa). However these pressure waveforms are typically noisy and biased, and require processing in orderto locate the specific information required for the cardiac elastance estimation. This paper presents the methodto algorithmically process the pressure waveforms. Methods: A shear transform is developed in order to helplocate information in the pressure waveforms. This transform turns difficult to locate corners into easy to locatemaximum or minimum points as well as providing error correction. Results: The method located all points 87out of 88 waveforms for Ppa to within the sampling frequency. For Pao, out of 616 total points, 605 were foundwithin 1%, 5 within 5%, 4 within 10% and 2 within 20%. Conclusions: The presented method provides arobust, accurate and dysfunction independent way to locate points on the aortic and pulmonary artery pressurewaveforms, allowing the non-invasive estimation of the left and right cardiac elastance.