A method for determining that a patient interface component comprising a vent has been replaced between therapy sessions of treatment of sleep disordered breathing, the method comprising: acquiring or receiving first vent flow rate data representing one or more estimated first vent flow rates of gas through a first vent of a patient interface in use during a first therapy session; acquiring or receiving second vent flow rate data representing one or more estimated second vent flow rates of gas through a second vent of a patient interface in use during a second therapy session after the first therapy session; and identifying, by comparison of the second vent flow rate data to the first vent flow rate data, a difference in resistance to flow through the first vent than through the second vent indicating that the second vent is not the same vent as the first vent.

Systems and techniques for monitoring, predicting and/or alerting for short-term oxygen support needs of patients are presented. A system can include a data collection component that receives multimodal patient data for a patient having a respiratory condition in association with monitoring and treating the respiratory condition in real-time, the multimodal patient data comprising at least physiological data regarding physiological parameters tracked for the patient over a period of time, and current oxygen support data regarding a current oxygen support mechanism of the patient. The system can further include an oxygen support forecasting component that processes the multimodal patient data using an oxygen support forecasting model to generate an output forecast that indicates whether a change to the current oxygen support mechanism is recommended for the patient within a defined upcoming timeframe

Devices, systems and methods are provided for controlling the operation of a breathing assistance device for a user. The controller may include an input for receiving sensor data to measure at least one airflow parameter of the user's airflow; a memory unit that stores at least one machine learning model and at least one classifier or predictor; and a processor that is configured to perform measurements and to generate a control signal for adjusting the operation of the breathing assistance device for a current monitoring time period by: obtaining measured air pressure and/or airflow data and measured FOT data during a current monitoring time period; performing feature extraction on the measured data to obtain feature values that are used by the machine learning model employed by the at least one classifier or predictor to determine a property of the user; and adjusting the control signal based on the determined property.

Systems and methods for calibrating oxygen sensors in ventilators are provided. An oxygen sensor is coupled in flow communication with a first oxygen gas source. A calibration circuit including a second oxygen gas source is coupled in flow communication with the oxygen sensor and a third oxygen gas source is coupled in flow communication with the oxygen sensor. A controller is configured to determine a calibration curve for the oxygen sensor via the calibration circuit by measuring the second oxygen gas source and the third oxygen gas source. Based on the calibration curve, an oxygen concentration value of the first oxygen gas source is measured and distributed.

Disclosed herein is a system and method for controlling oxygen supply equipments. The system is equipped with pressure sensors coupled to the oxygen supply equipments. Depending on the oxygen supply selected by a user for the patient, the pressure sensor monitors the current pressure of the preset oxygen supply during an inhalation phase corresponding to the patient. If the current pressure is less than a minima value or if a pressure drop rate is higher than or equal to a threshold rate or both, the system generates an alarm notifying the user to check the preset oxygen supply and in the meanwhile switches the preset oxygen supply from one oxygen supply equipment to another oxygen supply equipment or vice-versa.

An oxygen concentrator may have a compressor to feed a feed gas for sieve bed(s) via a first manifold, an accumulator to receive enriched air from the bed(s) via a second manifold. It may include an outer housing for the manifolds, the compressor, and the accumulator. The housing may include an access portal to a compartment therein, for removably receiving the bed(s) as a canister assembly. The first manifold may be adjacent to the compartment and have inlet coupling(s) for removably coupling respectively with inlet(s) of the canister assembly. The inlet coupling(s) may each have a first central axis. The second manifold may be adjacent to the compartment and have outlet coupling(s) for removably coupling respectively with outlet(s) of the canister assembly. The outlet coupling(s) may each having a second central axis. The first and second central axes may form any one of an obtuse, acute, or right angle.

A ventilation adjustment method and a high-frequency ventilation system, which ensure stable and accurate oxygen concentration control within an oxygen concentration setting range, are disclosed. The ventilation adjustment method includes: determining a first gas flow rate control value and a second gas flow rate control value according to a target output flow rate and an oxygen concentration setting value; determining whether the first gas flow rate control value falls into a first dead zone range and whether the second gas flow rate control value falls into a second dead zone range; if the first gas flow rate control value falls into the first dead zone range, maintaining a first gas flow rate controller turned on in an expiratory phase; and if the second gas flow rate control value falls into the second dead zone range, maintaining a second gas flow rate controller turned on in the expiratory phase.

A method for ventilating the lungs of a patient. The method includes a smart tube for intubation comprising a tip and a cuff. The method also includes one or more cameras, coupled with the smart tube, for providing relative positional intubation measurements of the patient and/or providing intubation images of the patient. Further, the method includes one or more sensors, coupled with the smart tube, for sensing the inflation of the cuff and/or sensing pressure of the cuff. The method for ventilating additionally includes a computing method, coupled with the camera, the at least one sensor and the smart tube, for computing programmed feedback based on the relative positional intubation measurements, and/or the intubation images, and/or the inflation of the cuff, and/or the pressure of the cuff.

A system is disclosed that includes a breathing apparatus, a display unit and a processing unit that is operatively connected to the display unit. The processing unit is configured to provide a graphical visualization on the display unit. The graphical visualization in turn includes a combination of a target indication for at least one ventilation related parameter of a ventilation strategy for a patient ventilated by the apparatus, and a reciprocating animation of the at least one ventilation related parameter relative the target indication. The target indication is for instance based on input of a user, such as an operator of the breathing apparatus. Alternatively, or in addition, it may be a default value stored on a memory unit being operatively connected to the processing unit. Alternatively, or in addition, the target indication is based on a measurement value of said patient's physiology or anatomy. In this manner, the system informs clinicians in a clear and easily understandable way how a current patient ventilation is related to a chosen ventilation strategy.

Ventilation system (having a ventilator and having a diagnostic device, wherein the ventilator comprises a ventilation unit for generating a respiratory gas flow for ventilation and a detection unit (for detecting a ventilation signal characteristic for the respiratory gas flow over time. The diagnostic device comprises a sensor unit for detecting a diagnostic signal over time. The synchronization unit is operationally connected to the detection unit and the sensor unit and is suitable and configured for studying a time curve of the ventilation signal and a time curve of the diagnostic signal respectively for a signal change caused by the same event and bringing the curve of the ventilation signal and the curve of the diagnostic signal into chronological correspondence so that the event occurs simultaneously in both signal curves.