Estimation of end-diastolic pressure via deconvolution

Left ventricular assist devices (LVADs) can significantly improve survival rate and quality of life for patients suffering from end-stage heart failure. Several promising strategies to control LVADs are being developed, some being focused on the end-diastolic pressure (EDP). For those, the problem of EDP estimation in real-time has to be solved. In this work, a deconvolution-based method to identify features in cardiac signals is presented. This method is applied to the estimation of the EDP from the left-ventricular pressure (LVP) signal and evaluated on animal trial data. In 11 trials with adult sheep, a myocardial infarction was induced and an LVAD was implanted. A total of 37.6 hours of LVP data was annotated by a medical expert. Compared to the annotations, a root mean square error of 11.6 ms / 4.1 mmHg was achieved using the proposed deconvolution method.