A sterile packaging assembly for transporting interventional devices to a robotic surgery site includes a sterile barrier having a hub support portion and configured to enclose a sterile volume; and at least a first interventional device within the sterile volume. The first interventional device includes a hub and an elongate flexible body. The hub includes at least one magnet and at least one roller configured to roll on the hub support portion of the sterile barrier.

Temperature sensors are configured to sense a temperature for the sleeper and transmit temperature readings. A controller is configured to receive temperature readings; and send to a heating subsystem instructions to initiate a warming process that raises a distal temperature of the sleeper more than a proximal temperature of the sleeper. The heating subsystem that may include a heating element that, when engaged, can raise the distal temperature of the sleeper more than the proximal temperature of the sleeper.

A shroud for a mask system includes a retaining portion structured to retain a frame, a pair of upper headgear connectors each including an elongated arm and a slot at the free end of the arm adapted to receive a headgear strap, and a pair of lower headgear connectors each adapted to attach to a headgear strap. The retaining portion, the upper headgear connectors, and the lower headgear connectors are integrally formed as a one piece structure.

A sensing system for sensing a potential complication at a venous catheter site. The system includes a sensor module for attachment at the site of the catheter. The sensor module includes a pressure sensor configured to generate pressure data representing measured pressure at the site of the catheter; a temperature sensor configured to generate temperature data representing measured temperature at the site of the catheter; and two pairs of bio impedance electrodes that generate bioelectrical signals representing bioelectrical activity at the site of venous catheter and a transmitter for transmitting the pressure, temperature data and bio impedance data. The system also includes a computing device configured to receive the response signal that includes the generated pressure, temperature and bio impedance data; and transmit the pressure temperature and bio impedance data to a user device for comparing the generated pressure temperature bio impedance data to threshold values indicative of intravenous complications.

A system includes a memory storing a user profile for a user of the system and machine-readable instructions and a control system including one or more processors configured to execute the machine-readable instructions to receive physiological data associated with the user during a sleep session, determine, based at least in part on the received physiological data, a set of sleep-related parameters for the sleep session, subsequent to the sleep session, select one of the set of sleep-related parameters as a targeted parameter, the selection of the targeted parameter being based at least in part on the stored user profile, the set of sleep-related parameters, or both, and cause information to be communicated to the user via a user device, the information being indicative of the targeted parameter, a recommendation associated with improving the targeted parameter for the user in one or more subsequent sleep sessions, or both.

A robotically driven interventional device includes an elongate, flexible body, having a proximal end and a distal end; a hub on the proximal end; at least one rotatable roller on a first surface of the hub; and at least one magnet on the first surface of the hub.

Aspects of the present disclosure describe systems and methods for predicting an intra-aortic pressure of a patient receiving hemodynamic support from a transvalvular micro-axial heart pump. In some implementations, an intra-aortic pressure time series is derived from measurements of a pressure sensor of the transvalvular micro-axial heart pump and a motor speed time series is derived from a measured back electromotive force of a motor of the transvalvular micro-axial heart pump. Furthermore, in some implementations, machine learning algorithms, such as deep learning, are applied to the intra-aortic pressure and motor speed time series to accurately predict an intra-aortic pressure of the patient. In some implementations, the prediction is short-term (e.g., approximately 5 minutes in advance).

A therapeutic vaporizer inhalation bag attachment system with an integrated valve is disclosed. The attachment system includes a body having a lumen extending between the two openings of the body, a bag coupling, and a valve positioned within the lumen. A method of using the inhalation bag attachment system is also disclosed.

A method of displaying an operational parameter of a surgical system is disclosed. The method includes receiving, by a cloud computing system of the surgical system, first usage data, from a first subset of surgical hubs of the surgical system; receiving, by the cloud computing system, second usage data, from a second subset of surgical hubs of the surgical system; analyzing, by the cloud computing system, the first and the second usage data to correlate the first and the second usage data with surgical outcome data; determining, by the cloud computing system, based on the correlation, a recommended medical resource usage configuration; and displaying, on respective displays on the first and the second subset of surgical hubs, indications of the recommended medical resource usage configuration.

Algorithms for detecting endotracheal intubation and/or misplacement of endotracheal tubes in child patients during anesthesia for use with anesthesia machines, mechanical ventilators, and/or respiratory function monitors. An algorithm uses end-tidal carbon dioxide (EtCO.sub.2), and tidal volume (TV) or peak inspiratory pressure (PIP) to detect exact intubation time. Another algorithm uses respiratory parameters to identify and/or confirm the type of airway device used during mechanical ventilation, and to detect if and when an issue has arisen with use of a specific airway device to provide real-time decision support to attending medical care professionals.