A Flow Sensor-Based Suction-Index Control Strategy for Rotary Left Ventricular Assist Devices

Abstract

Rotary left ventricular assist devices (LVAD) have emerged as a long-term treatment option for patients with advanced heart failure. LVADs need to maintain sufficient physiological perfusion while avoiding left ventricular myocardial damage due to suction at the LVAD inlet. To achieve these objectives, a control algorithm that utilizes a calculated suction index from measured pump flow (SIMPF) is proposed. This algorithm maintained a reference, user-defined SIMPF value, and was evaluated using an in silico model of the human circulatory system coupled to an axial or mixed flow LVAD with 5–10% uniformly distributed measurement noise added to flow sensors. Efficacy of the SIMPF algorithm was compared to a constant pump speed control strategy currently used clinically, and control algorithms proposed in the literature including differential pump speed control, left ventricular end-diastolic pressure control, mean aortic pressure control, and differential pressure control during (1) rest and exercise states; (2) rapid, eight-fold augmentation of pulmonary vascular resistance for (1); and (3) rapid change in physiologic states between rest and exercise. Maintaining SIMPF simultaneously provided sufficient physiological perfusion and avoided ventricular suction. Performance of the SIMPF algorithm was superior to the compared control strategies for both types of LVAD, demonstrating pump independence of the SIMPF algorithm.

Mathematical Analysis of a Low Cost Mechanical Ventilator Respiratory Dynamics Enhanced by a Sensor Transducer (ST) Based in Nanostructures of Anodic Aluminium Oxide (AAO)

“…Consequently, an algorithm was also designed to obtain the airflow, volume and pressure from the pressure difference, which were obtained by the transduction process of the transducer joined to the designed sensor. Moreover, the ST system was analyzed in dynamical and transient behavior for ranges of work that depended on geometrical parameters and physical values of airflow, pressure, and volume of mechanical ventilators for artificial human breathing, This is a novel proposed sensor design such as other new proposals [22][23][24] because of the multiple variable correlation also variables considered like disturbances (temperature and vibration) and considering the effect of nanostructures in this objective.…”

Special Issue “Computer Aided Diagnosis Sensors”

“…Ramesh et al [ 11 ] proposed the design and implementation of an explainable deep learning 1D-CNN model for use in smart healthcare systems with general-purpose devices such as smart wearables and smartphones. Liang et al [ 12 ] developed a new flow sensor-based suction index from a measured pump flow (SIMPF) control strategy for rotary left ventricular assist devices (LVADs) to provide adequate cardiac output and prevent left ventricle (LV) suction.…”