A method of estimating a parameter indicative of respiratory flow of a patient being administered flow therapy, comprising: optionally administering a gas at a flow rate to the patient using a flow therapy apparatus with a patient interface, determin—-ing a terminal pressure in, at or proximate the outlet of the patient interface or in, at or proximate the nares of the patient, determin -ing nasal RTF, determining a nasal flow parameter being or indicative of nasal flow based on the pressure and a nasal RTF, and optionally outputting the nasal flow parameter or parameter derived therefrom.

A ventilation system includes an electrochemical filter for depleting alkyl phenols, especially 2,6-diisopropyl phenol, in breathing gas. A method uses the filter for removing alkyl phenols, especially 2,6-diisopropyl phenol, from breathing gas.

An operating unit (2) sets ventilation parameters of a control unit (11) of a ventilator (1) that includes a gas dispensing device (10) for ventilation gases. The operating unit includes a display unit and an ventilation parameters input element (23, 24). Two or more of the parameters are linked via a relation condition stored in a relation storage module (40). A relation monitor (3) includes a deviation detector (31) detecting a transgression of the relation condition during parameter setting, and outputs warning information via a warning unit (32). This avoids a need for an operator to note the sometimes complicated connections and dependencies expressed in the relations during the parameter setting. The warning may be sent before the new setting value is sent from the operating unit to the control unit. Operating safety is increased and a risk of setting errors is minimized.

Aspects of the present disclosure provide methods, apparatuses, and systems for closed-loop sleep protection and/or sleep regulation. According to an aspect, sleep disturbing noises are predicted and a biosignal parameter is measured to dynamically mask predicted disturbing environmental noises in the sleeping environment with active attenuation. Environmental noises in a sleeping environment of a subject are detected, input, or predicted based on historical data of the sleeping environment collected over a period of time. The biosignal parameter is used to determine sleep physiology of a subject. Based on the environmental noises in the sleeping environment and the determined sleep physiology, the noises are predicted to be disturbing or non-disturbing noises. For predicted disturbing noises, one or more actions are taken to regulate sleep and avoid sleep disruption by using sound masking prior to or concurrently with the occurrence of the predicted disturbing noises.

A method and a system for determining the amount of oxygen required by a user with respiratory problems are disclosed. First data about several users with respiratory problems is stored in a database. The method a) collects second data from a monitored user while (s)he is performing a test at a first location; b) computes a user’s behavioral model executing a first algorithm on the first and second data; c) collects, every period of time t1, third data of the user while (s)he is performing an activity at a second location; d) adjusts, every period of time t2, the computed user’s behavioral model using the first algorithm, providing a customized user’s behavioral model as a result; and e) computes an estimator of the quantity of oxygen to be delivered to the user by executing a second algorithm on the customized user’s behavioral model.

In certain example embodiments, an air delivery system includes a controllable flow generator operable to generate a supply of pressurized breathable gas to be provided to a patient for treatment and a pulse oximeter. In certain example embodiments, the pulse oximeter is configured to determine, for example, a measure of patient effort during a treatment period and provide a patient effort signal for input to control operation of the flow generator. Oximeter plethysmogram data may be used, for example, to determine estimated breath phase; sleep structure information; autonomic improvement in response to therapy; information relating to relative breathing effort, breathing frequency, and/or breathing phase; vasoconstrictive response, etc. Such data may be useful in diagnostic systems.

A controller or processor(s) implements detection of respiratory related conditions that may serve as control logic to synchronize pressure treatment delivery with a patient's respiratory cycle. Based on data derived from sensor signals associated with the respiratory treatment, a monitoring device, detector or respiratory treatment apparatus may evaluate flow measures from a flow sensor and distinguish flow attributable to the respiratory treatment apparatus and flow attributable to patient respiratory muscles. The determination may serve as a basis of synchronization criteria that controls pressure levels from a pressure treatment apparatus, such as by evaluating the determined patient generated flow or a relationship between total flow and apparatus flow. In some embodiments, data for the cycling conditions is determined in preliminary treatment cycles during which synchronized pressure changes are controlled according to other cycling criteria. The new cycling conditions are then automatically initiated for control of synchronization in subsequent cycles.

Methods and apparatus provide automated circuit disconnection monitoring such as for a respiratory apparatus or system. Disconnection of a patient circuit, including a patient interface and air delivery circuit, may be detected and a message or alarm activated. In some versions, detecting occurrences of circuit disconnection event(s), such as by a processor, may be based on an instantaneous disconnection parameter as a function of a disconnection setting. The disconnection setting may be determined based on patient circuit type. The instantaneous disconnection parameter may be determined from detected pressure and flow rate, and may be, for example, a conductance value or an impedance value. Disconnection events may be qualified by one or more detected respiratory indicators. In some cases, instantaneous impedance or conductance may be used to assess re-connection of a patient circuit, detection of flow starvation, determine breath shape for triggering and cycling and to detect patient or circuit obstructions.

The disclosed system and method generates a trained prediction model based on a plurality of sets of sampled ventilation parameter values received from patient ventilations, and a plurality of weaning indicators representative of patient outcomes for each sampled patient ventilation. Ventilation parameter values are sampled during a current patient ventilation and input into the trained prediction model. The model selects, from the group of ventilation parameters, a ventilation parameter and associated parameter value or range of parameter values having the highest probability of positively influencing the current patient ventilation based on a threshold value of the ventilator parameter. The system may then use the returned parameter value(s) to cause an operational mode of a ventilator associated with the current patient ventilation to be adjusted.

A system for carbon dioxide (CO2) removal from a circulatory system of a patient includes a medical device providing extracorporeal lung assist (ECLA) treatment to the patient through extracorporeal removal of CO2 from the patient's blood; at least one control unit controlling the operation of the medical device so as to control a degree of CO2 removal obtained by the ECLA treatment; and a bioelectric sensor detecting a bioelectric signal indicative of the patient's efforts to breathe. The at least one control unit is configured to control the operation of the medical device based on the detected bioelectric signal.