Methods and systems are disclosed for creating and using a neural network model to estimate a cardiac parameter of a patient, and using the estimated parameter in providing blood pump support to improve patient cardiac performance and heart health. Particular adaptations include adjusting blood pump parameters and determining whether and how to increase or decrease support, or wean the patient from the blood pump altogether. The model is created based on neural network processing of data from a first patient set and includes measured hemodynamic and pump parameters compared to a cardiac parameter measured in situ, for example the left ventricular volume measured by millar (in animals) or inca (in human) catheter. After development of a model based on the first set of patients, the model is applied to a patient in a second set to estimate the cardiac parameter without use of an additional catheter or direct measurement.

Systems and methods for controlling an implantable pump are provided. For example, the exemplary controller for controlling the implantable pump may only rely on the actuator's current measurement. The controller is robust to pressure and flow changes inside the pump head, and allows fast change of pump's operation point. For example, the controller includes, a two stage, nonlinear position observer module based on a reduced order model of the electromagnetic actuator. The controller includes an algorithm that estimates the position of the moving component of the implantable pump based on the actuator's current measurement and adjusts operation of the pump accordingly. Alternatively, the controller may rely on position measurements and/or velocity estimations.

A ventricular assist system and a blood pump controller including a blood pump usable in a state where a first slide surface and a second slide surface are brought into contact with each other, and a cool sealing liquid is supplied to a gap formed between the first slide surface and the second slide surface; a first sub controller having a first cool sealing liquid reservoir, a cool sealing liquid pump, a first pipe joint upstream side, and a fourth pipe joint downstream side; and a second sub controller having a blood pump drive circuit, a battery, a first pipe joint downstream side, a second pipe joint upstream side, a third pipe joint downstream side, and a fourth pipe joint upstream side. The first sub controller and the second sub controller are detachably connected by a first pipe joint and a fourth pipe joint.

Systems and methods for controlling an implantable pump are provided. For example, the exemplary controller for controlling the implantable pump may only rely on the actuator's current measurement. The controller is robust to pressure and flow changes inside the pump head, and allows fast change of pump's operation point. For example, the controller includes, a two stage, nonlinear position observer module based on a reduced order model of the electromagnetic actuator. The controller includes an algorithm that estimates the position of the moving component of the implantable pump based on the actuator's current measurement and adjusts operation of the pump accordingly. Alternatively, the controller may rely on position measurements and/or velocity estimations.

A rotary blood pump includes a casing defining a pumping chamber. The pumping chamber has a blood inlet and a tangential blood outlet. One or more motor stators are provided outside of the pumping chamber. A rotatable impeller is within the pumping chamber and is adapted to cause blood entering the pumping chamber to move to the blood outlet. The impeller has one or more magnetic regions. The impeller is radially constrained in rotation by magnetic coupling to one or more motor stators and is axially constrained in rotation by one or more hydrodynamic thrust bearing surfaces on the impeller.

Methods and systems are disclosed for creating and using a neural network model to estimate a cardiac parameter of a patient, and using the estimated parameter in providing blood pump support to improve patient cardiac performance and heart health. Particular adaptations include adjusting blood pump parameters and determining whether and how to increase or decrease support, or wean the patient from the blood pump altogether. The model is created based on neural network processing of data from a first patient set and includes measured hemodynamic and pump parameters compared to a cardiac parameter measured in situ, for example the left ventricular volume measured by millar (in animals) or inca (in human) catheter. After development of a model based on the first set of patients, the model is applied to a patient in a second set to estimate the cardiac parameter without use of an additional catheter or direct measurement.

A medical device for assisting a function of the heart is provided. The heart is placed in the thorax, the thoracic diaphragm is dividing the thorax from the abdomen and the pericardium is surrounding the heart and is attached to the thoracic diaphragm at a pericardial contacting section of the thoracic diaphragm. The medical device comprises a diaphragm passing part adapted to pass from the abdomen, through the thoracic diaphragm at the pericardial contacting section, into the pericardium, wherein said diaphragm passing part is adapted to allow the thoracic diaphragm to move during respiration, when implanted.

A method for providing a treatment recommendation to a physician for treating a patient is disclosed. The method comprises determining, from a processor in communication with a patient data repository, a first treatment recommendation based on a combination of selected patient demographics from the patient data repository applicable to the patient, and operational parameters of a plurality of ventricular assist devices (VADs) suitable for treating the patient, the first treatment recommendation having a first survival rate and comprising the use of a first VAD. The method then obtains a first signal from using the first VAD on the patient. The method then determines a second treatment recommendation based on the first signal and the first treatment recommendation, the second treatment recommendation having a second survival rate. The method then provides the second treatment recommendation to the physician if the second survival rate is higher than the first survival rate.

A method for providing a treatment recommendation to a physician for treating a patient is disclosed. The method comprises determining, from a processor in communication with a patient data repository, a first treatment recommendation based on a combination of selected patient demographics from the patient data repository applicable to the patient, and operational parameters of a plurality of ventricular assist devices (VADs) suitable for treating the patient, the first treatment recommendation having a first survival rate and comprising the use of a first VAD. The method then obtains a first signal from using the first VAD on the patient. The method then determines a second treatment recommendation based on the first signal and the first treatment recommendation, the second treatment recommendation having a second survival rate. The method then provides the second treatment recommendation to the physician if the second survival rate is higher than the first survival rate.

A method for providing a treatment recommendation to a physician for treating a patient is disclosed. The method comprises determining, from a processor in communication with a patient data repository, a first treatment recommendation based on a combination of selected patient demographics from the patient data repository applicable to the patient, and operational parameters of a plurality of ventricular assist devices (VADs) suitable for treating the patient, the first treatment recommendation having a first survival rate and comprising the use of a first VAD. The method then obtains a first signal from using the first VAD on the patient. The method then determines a second treatment recommendation based on the first signal and the first treatment recommendation, the second treatment recommendation having a second survival rate. The method then provides the second treatment recommendation to the physician if the second survival rate is higher than the first survival rate.