Three groups of biocompatible implants were created, to leverage physiological impairment caused by (i) cardiovascular, (ii) renal, and (iii) neuronal diseases. Each group of implants is subdivided into three categories according to extra functionality added plus integrated additions. The first generation contains basic functionality and the second and third generations contain extra functions. Finally, further additions can be combined and integrated. Therefore, the first group comprises of the “First Generation of Cardiovascular Implants” plus the “Second Generation of Cardiovascular Implants” plus the “Third Generation of Cardiovascular Implants” plus additional integrations named “Additions”. Equally, the second group comprises of the “First”, the “Second” and the “Third” Generation of Renal Prosthetics plus Additions. The same categorisation applies to Neural Implants, which are three generations plus additions. This can be found in the description of claims presented in the Austrian Prio (provisional patent application) number A 60273/2019, from 11 Dec. 2019.

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.

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.

The EKG cord management system is a cable management system. The EKG cord management system is configured for use with the leads of an EKG machine. The EKG cord management system comprises a plurality of lead structures, a probe connector, and a housing. The EKG cord management system deploys the plurality of lead structures from the housing. The EKG cord management system retracts the plurality of lead structures into the housing. Each lead structure selected from the plurality of lead structures measures electrical activity in a human body. The probe connector electrically connects each of the plurality of lead structures to a machine known as an EKG machine.

A heart support system is provided includes a control unit and sound-generating devices, said control unit configured to detect and process alarm events and to carry out control tasks in the heart support system. The heart support system further includes a storage device configured to store one or more defined alarm signal time curves and one or more alarm priorities. Each alarm signal time curve and each alarm priority is assigned to an alarm event. A sound-generation controller is configured such that when an alarm event is detected, the controller overlays a volume time curve onto the alarm signal time curve assigned to the alarm event in the storage device, said volume time curve based on the alarm priority assigned to the respective alarm event in the storage device and the length of time since the detection of the alarm event.

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 controller for an artificial heart enables activity-specific adjustments to the operation of an artificial heart by obtaining sensor data from a plurality of sensors monitoring characteristics of a patient's body, and using the sensor data as input to one or more control parameter models for identifying control parameters to be provided to the artificial heart to adjust the operational parameters of the artificial heart. The controller is in wireless communication with the artificial heart via an application program interface (API)-based communication channel that facilitates communication between the controller and the artificial heart. Moreover, a cloud-based management computing entity may be utilized to train and/or execute one or more models to enable real-time updates to the operational characteristics of the artificial heart to enable the artificial heart to appropriately accommodate activities of the patient.

Systems, apparatuses, and methods are disclosed for optimizing management of one or more implanted artificial heart pumps. An example method includes wirelessly retrieving, via one or more portable diagnostic devices, data regarding the one or more implanted artificial heart pumps. The example method further includes analyzing, by a server device, performance characteristics of the one or more implanted artificial heart pumps based on the retrieved data. The example method further includes causing rendering of the performance characteristics. Corresponding apparatuses and computer program products are contemplated.