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.

[1]  Steffen Leonhardt,et al.  Multimodal sensor fusion of cardiac signals via blind deconvolution: A source-filter approach , 2014, Computing in Cardiology 2014.

[2]  Robert L Kormos,et al.  Seventh INTERMACS annual report: 15,000 patients and counting. , 2015, The Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation.

[3]  Daniel J. Penny,et al.  Accurate Automatic Detection of End-Diastole From Left Ventricular Pressure Using Peak Curvature , 2008, IEEE Transactions on Biomedical Engineering.

[4]  Steffen Leonhardt,et al.  Determining the connection between capacitively coupled electrocardiography data and the ground truth , 2015, 2015 Computing in Cardiology Conference (CinC).

[5]  Sheng-Li Xie,et al.  A new blind deconvolution algorithm for SIMO channel based on neural network , 2005, 2005 International Conference on Machine Learning and Cybernetics.

[6]  D. Abeysinghe,et al.  A novel MEMS pressure sensor fabricated on an optical fiber , 2001, IEEE Photonics Technology Letters.

[7]  Nigel H Lovell,et al.  Developments in control systems for rotary left ventricular assist devices for heart failure patients: a review , 2013, Physiological measurement.