Systems and devices for an updatable blood pump are disclosed herein. The blood pump can be part of a mechanical circulatory support system that can include a system controller and the blood pump. The blood pump can include a rotary motor and a control unit that can communicate with the system controller. The system controller can initiate the update process and can provide the update to the blood pump. Upon initiation of the update process, the control unit can stop the rotary motor. While the rotary motor is stopped, the blood pump can be updated. At the completion of the update, the rotary pump can be restarted.

Systems, devices, and methods are provided for the management of multiple sensor control devices and/or multiple reader devices in an in vivo analyte monitoring environment, and also for resolving conflicts when merging data collected by different reader devices.

A method and arrangement for determining a quality rating data (QRD) of a medical data acquisition system (MDAS). The method and arrangement comprise of receiving first data, which includes utilization errors occurred during performing a data acquisition procedure (DAP), by a data acquisition component of the MDAS, on a patient to acquire medical data. The method and arrangement further comprise generating second data as a function of the first data. The second data is indicative of categories of the utilization errors, wherein at least one utilization error is assigned to a corresponding category based on a predetermined parameter. The method and arrangement further comprise determining the QRD as a function of a total number of MDAS utilizations, a predetermined coefficient for the corresponding error category and a number of utilization errors in the corresponding error category.

An emergency medical device (20) (e.g., an external defibrillator/monitor) employing an emergency medical subsystem (21) for executing an emergency medical procedure (e.g., a monitoring subsystem (21) and a therapy subsystem (21)), and an emergency medical controller (23) for controlling an activation of the emergency medical subsystem (21). The subsystem (21) includes one or more operational components (22). In operation, the controller (23) conditionally actuates a device readiness indicator (24) (e.g., auditory or visual) indicative of an operational readiness of the operational component(s) (22), and conditionally actuates a failure warning indicator (25) (e.g., auditory or visual) indicative of a pending failure of the operational readiness of the operational component(s) (22). The failure warning indicator (25) may be actuated based on a predictive failure analysis of a premature degradation of the operational component(s) (22), a repeated occurrence of error conditions of the operational component(s) (22) (particularly recoverable error conditions), and a shortened reliable life of the operational component(s) (22).

In one example, an ambulatory medical device is provided. The ambulatory medical device includes a plurality of subsystems, at least one sensor configured to acquire data descriptive of a patient, a user interface and at least one processor coupled to the at least one sensor and the user interface. The at least one processor is configured to identify subsystem status information descriptive of an operational status of each subsystem of the plurality of subsystems and to provide a device health report for the ambulatory medical device via the user interface, the device health report being based on the operational status of each subsystem.

In one example, an ambulatory medical device is provided. The ambulatory medical device includes a plurality of subsystems, at least one sensor configured to acquire data descriptive of a patient, a user interface and at least one processor coupled to the at least one sensor and the user interface. The at least one processor is configured to identify subsystem status information descriptive of an operational status of each subsystem of the plurality of subsystems and to provide a device health report for the ambulatory medical device via the user interface, the device health report being based on the operational status of each subsystem.

A method to securely transfer data to aid in a medical procedure or to a data management system to be accessed in a medical care facility is provided that includes a set of data from a data storage system being downloaded via a network to a visible light communication (VLC) enabled device. The set of data from the VLC enabled device is then transferred to a VLC enabled device located in an operating room (OR) via point to point VLC or uploaded to a data management system. The transferred set of data is then used to aid in a medical procedure or be accessed by a medical care facility. Software executables are similarly transferred and run in an OR context.

Monitoring devices monitor physiological parameters of a patient undergoing surgery. The physiological parameters describe a physiological condition of the patient. A processor matches the physiological parameters to stored surgical data associated with adverse surgical events associated with surgical procedures matching the surgery. The processor determines a predicted time at which the physiological condition of the patient will meet a threshold physiological condition associated with the adverse surgical event based on a rate of change of the physiological parameters. Responsive to determining the predicted time, the processor transmits a first alert to robotic surgical controls to adjust the surgery prior to the predicted time. The processor determines that the physiological condition of the patient has met the threshold physiological condition. The processor transmits a second alert to the robotic surgical controls to terminate the surgery.

Monitoring devices monitor physiological parameters of a patient undergoing surgery. The physiological parameters describe a physiological condition of the patient. A processor matches the physiological parameters to stored surgical data associated with adverse surgical events associated with surgical procedures matching the surgery. The processor determines a predicted time at which the physiological condition of the patient will meet a threshold physiological condition associated with the adverse surgical event based on a rate of change of the physiological parameters. Responsive to determining the predicted time, the processor transmits a first alert to robotic surgical controls to adjust the surgery prior to the predicted time. The processor determines that the physiological condition of the patient has met the threshold physiological condition. The processor transmits a second alert to the robotic surgical controls to terminate the surgery.

Disclosed herein are systems and methods for identifying radiation therapy treatment data for different patients, such as field geometry. A central server collects patient data, radiation therapy treatment planning data, clinic-specific rules, and other pertinent treatment/medical data associated with a patient. The server then executes one or more machine-learning computer models to predict field geometry variables and weights associated with the patient's treatments. Using the predicted variables and weights, the server execute a clinic-specific set of logic to identify suggested field geometry, such as couch/gantry angles and/or arc attributes. The server then monitors whether end users (e.g., medical professionals) revise the suggested field geometry and trains the model accordingly.