The present invention relates to an integrated sleep diagnosis and treatment device, and more particularly to an integrated apnea diagnosis and treatment device. The present invention additionally relates to method of sleep diagnosis and treatment.

A method of determining a duration of safe apnoea. Information is obtained relating to a respiratory indicator, and a duration of safe apnoea is determined from the obtained information. A respiratory therapy system has one or more patient interfaces. A processor is configured to determine a duration of safe apnoea based on obtained information relating to a respiratory indicator.

A patient interface for supplying a flow of breathable gas to the airways of a patient may comprise a heat and moisture exchanger (HME). The HME may be positioned in a flow path of the flow of breathable gas. The HME may absorb heat and moisture from gas exhaled by the patient and the incoming flow of breathable gas to be supplied to the patient's airways may be heated and moisturized by the heat and moisture held in the HME.

Various embodiments are described herein for a controller for controlling the operation of a breathing assistance device that provides breathing assistance to a user. The controller comprises a processor that generates a respiratory index value that is determined during a current monitoring time period to detect a respiratory failure, or predict the respiratory failure when at least one PSG signal is measured. The respiratory index value is compared to a threshold to determine if the control signal needs to be updated to reduce or eliminate respiratory failure that the user is currently experiencing or to prevent a predicted respiratory failure from occurring.

An apparatus, comprising a processor and memory storing instructions that, when executed by the processor, cause the processor to: receive ventilator data obtained from continual mechanical ventilatory support of a patient over a period of time, analyze the ventilator data to identify a plurality of breathing cycles, classify the plurality of breathing cycles into normal breathing cycles and abnormal breathing cycles, using a machine learning algorithm, detect a change in the normal breathing cycles, compared to normal breathing cycles identified by the apparatus based on ventilator data obtained from continual mechanical ventilatory support of the patient over a previous period of time, and generate output indicative of the change in the normal breathing cycles.

A process and a signal processing unit (5) approximately detect a respective characteristic heartbeat time {H_Zp[f](x), H_Zp[s](x.sub.1), . . . , H_Zp[s](x.sub.N)} per heartbeat for a sequence of heartbeats of a patient (P). A sensor array (2.1, 2.2) sends at least one sum signal [Sig.sub.Sum(1), Sig.sub.Sum(2)], which results from a superimposition of a cardiogenic signal and of a respiratory signal. A first detector (25.1) calculates a respective first detection result for each characteristic heartbeat time, and a second detector (25.2, . . . ) calculates a second detection result. The first detector (25.1) analyzes a different sum signal and/or applies a different method of analysis than the second detector (25.2, . . . ). The signal processing unit (5) calculates a respective estimation (representation) for each heartbeat time and uses this estimation as the characteristic heartbeat time. The signal processing unit (5) uses a first detection result and a second detection result to calculate the estimation.

A method and system to manage a respiratory condition of a patient. An oxygen concentrator is configured to generate and deliver oxygen enriched air to the patient according to a selected dosage. The oxygen concentrator senses and collects physiological data of the patient and collects operational data during the generation and delivery of oxygen enriched air. The oxygen concentrator adjusts the dosage of oxygen enriched air based on the sensed physiological data. The oxygen concentrator transmits operational data and the physiological data to a health data analysis engine. The health data analysis engine collects the data transmitted by the oxygen concentrator. The health analysis engine detects a triggering event based on the collected data and determines an action to resolve the detected triggering event.

A patient interface for supplying a flow of breathable gas to the airways of a patient may comprise a heat and moisture exchanger (HME). The HME may be positioned in a flow path of the flow of breathable gas. The HME may absorb heat and moisture from gas exhaled by the patient and the incoming flow of breathable gas to be supplied to the patient's airways may be heated and moisturized by the heat and moisture held in the HME.

An apparatus, method and system for delivering CO.sub.2 into an inspiratory gas stream to formulate a blended respiratory gas in a manner that continuously maintains a target CO.sub.2 concentration in a volume of the inspired respiratory gas, for example, over the course of a breath or a volumetrically definable part thereof or a series of partial or full breaths.

High flow therapy is used to treat Cheyne-Stokes respiration and other types of periodic respiration disorders by periodic application of high flow therapy, adjustment of high flow therapy flow rates and/or periodic additions of CO2 or O2 into the air flow provided to the patient.