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A controller or processor(s) (1112) implements detection of respiratory related conditions, such as asynchrony, associated with use of a respiratory treatment apparatus (1102) or ventilator. Based on data derived from sensor signals associated with the respiratory treatment, the detector may evaluat

A controller or processor(s) (1112) implements detection of respiratory related conditions, such as asynchrony, associated with use of a respiratory treatment apparatus (1102) or ventilator. Based on data derived from sensor signals associated with the respiratory treatment, the detector may evaluate a feature set of detection values to determine whether or not an asynchrony occurs in a breath of the patient's respiratory cycle such as by comparing the values against a set of thresholds. Different events may also be identified based on the particular feature set and threshold(s) involved in the detection processing. Automated determination of feature sets may also be implemented to design different asynchrony event classifiers. The methodologies may be implemented by computers or by respiratory treatment apparatus. The detection of such asynchrony events can then also serve as part of control logic for automated adjustments to the control parameters of the respiratory treatment generated by the respiratory treatment apparatus.

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1. An apparatus for detection of asynchrony between a synchronized respiratory treatment and a respiratory cycle, the apparatus comprising: a memory containing data representing a feature set of detection values derived from signals of at least one sensor coupled with a respiratory treatment apparat

1. An apparatus for detection of asynchrony between a synchronized respiratory treatment and a respiratory cycle, the apparatus comprising: a memory containing data representing a feature set of detection values derived from signals of at least one sensor coupled with a respiratory treatment apparatus, in which the feature set of detection values includes a plurality of features as respective individual parameter detection variables derived from a pattern of flow indicated by the signals; anda controller of the respiratory treatment apparatus, wherein the controller is configured to access the data, and to control: a comparison of the individual parameter detection variables respectively of the plurality of features of the data of the feature set of detection values respectively with a set of associated thresholds for the individual parameter detection variables of the memory, the set of associated thresholds for the individual parameter detection variables being from other than the signals;a determination of an occurrence and type of an asynchrony event between the respiratory treatment apparatus and a patient respiratory cycle based on the comparison,wherein the determination of the occurrence and type of the asynchrony event identifies time of occurrence of a distinct asynchrony event of a plurality of distinct asynchrony events comprising at least two distinct events of (a) a post-triggering effort event, (b) a double triggering event, (c) a late triggering event, (d) an auto triggering event, (e) an early cycling event, and (f) a late cycling event; and a generation of an output representing the occurrence of the asynchrony event,in which the controller is configured to control the respiratory treatment apparatus based on the determination of the occurrence and type of the asynchrony event. 2. The apparatus of claim 1 further comprising a patient interface to carry a flow of breathable gas to a patient;a flow generator coupled with the patient interface to generate a flow of the breathable gas through the patient interface;a transducer to provide a signal indicative of patient flow through the patient interface;wherein the controller is configured to control the flow generator, detect a respiratory cycle with the signal of the flow sensor and generate flow generator control signals for producing the respiratory treatment. 3. The apparatus of claim 2 wherein the feature set of detection values comprises a respiratory rate based feature as one of the individual parameter detection variables. 4. The apparatus of claim 2 wherein the feature set of detection values comprises a respiratory volume based feature as one of the individual parameter detection variables. 5. The apparatus of claim 2 wherein the feature set of detection values comprises a respiratory mechanics based feature as one of the individual parameter detection variables. 6. The apparatus of claim 5 wherein the controller is configured to control determining resistance and compliance values based on measures of pressure, flow and volume. 7. The apparatus of claim 6 wherein the controller is configured to control multiple linear regression processing of the measure of pressure, flow and volume. 8. The apparatus of claim 7 wherein the controller is further configured to control an assessment of accuracy of the determined resistance and compliance values. 9. The apparatus of claim 8 wherein the assessment of accuracy comprises calculating a coefficient of determination and comparing the coefficient of determination to a threshold. 10. The apparatus of claim 7 wherein the determining of resistance and compliance values is based on the measures taken from a portion of a detected breathing cycle. 11. The apparatus of claim 10 wherein the portion is an expiratory portion. 12. The apparatus of claim 11 wherein the portion is an initial part of expiration during which a percentage of tidal volume is expired. 13. The apparatus of claim 12 wherein the percentage is in a range of about 85 to 90 percent. 14. The apparatus of claim 2 wherein the feature set of detection values comprises an expiratory flow morphology based feature as one of the individual parameter detection variables. 15. The apparatus of claim 2 wherein the asynchrony event comprises an expiratory ineffective effort event. 16. The apparatus of claim 15 wherein the feature set of detection values comprises as the individual parameter detection variables (a) a power of a piecewise bilinear approximation of a remainder of expiration after a location of a maximum expiratory flow, (b) a distance between a maximum and minimum values of a moving average expiratory flow, (c) an integral of a rectified and de-trended moving average of expiratory flow, (d) an inspiratory time constant, and (e) a fraction of said distance and a peak expiratory flow. 17. The apparatus of claim 15 wherein the feature set comprises a determined volume of gas moved during the ineffective effort event. 18. The apparatus of claim 2 wherein the asynchrony event comprises the post-triggering effort event. 19. The apparatus of claim 2 wherein the asynchrony event comprises the double triggering event. 20. The apparatus of claim 19 wherein the feature set comprises a maxima count and an elapsed time between maxima. 21. The apparatus of claim 2 wherein the asynchrony event comprises the autotriggering event. 22. The apparatus of claim 2 wherein the asynchrony event comprises the late triggering event. 23. The apparatus of claim 2 wherein the asynchrony event comprises the early cycling event. 24. The apparatus of claim 2 wherein the asynchrony event comprises the late cycling event. 25. The apparatus of claim 2 wherein the asynchrony event comprises an inspiratory ineffective effort event. 26. The apparatus of claim 2 wherein the controller is configured to automatically change a control parameter for delivery of the respiratory treatment based on the occurrence of the asynchrony event. 27. The apparatus of claim 26 wherein the control parameter comprises a trigger threshold. 28. The method of claim 26 wherein the control parameter comprises a cycling threshold. 29. The apparatus of claim 2 wherein the respiratory treatment apparatus comprises a ventilator. 30. The apparatus of claim 1 wherein the controller is further configured to control selecting the feature set such that the feature set comprises a subset of a superset of features, wherein the selecting comprises evaluating values of the superset for known asynchronous events occurring in data of a plurality of breaths established with a plurality of respiratory treatment apparatus. 31. The apparatus of claim 30 wherein the evaluating comprises calculating posterior-probabilities with values of the superset by Parzen-window estimation, wherein groups of values of the superset are selected by iteratively including and removing values. 32. A system for detection of asynchrony between a synchronized respiratory treatment and a respiratory cycle comprising: a controller configured to control a respiratory treatment apparatus and to process data derived from one or more pressure transducer signals from use of the respiratory treatment apparatus, the controller being configured to (a) compare respective individual parameter detection variables, in which a feature set of detection values calculated from the data includes a plurality of features as the respective individual parameter detection variables derived from a pattern of flow indicated by the signals, with a set of associated thresholds for the individual parameter detection variables, the set of associated thresholds for the individual parameter detection variables being from other than the signals, and (b) determine an occurrence and type of an asynchrony event between the respiratory treatment apparatus and a patient respiratory cycle based on the comparison,wherein the determination of the occurrence and type of the asynchrony event identifies time of occurrence of a distinct asynchrony event of a plurality of distinct asynchrony events comprising at least two distinct events of (a) a post-triggering effort event, (b) a double triggering event, (c) a late triggering event, (d) an auto triggering event, (e) an early cycling event, and (f) a late cycling event,in which the controller is configured to control the respiratory treatment apparatus based on the determination of the occurrence and type of the asynchrony event. 33. The system of claim 32, wherein the controller is configured to select the feature set such that the feature set comprises a subset of a superset of features, wherein the feature set is selected by evaluating values of the superset for known asynchronous events occurring in data of a plurality of breaths established with a plurality of respiratory treatment apparatus. 34. The system of claim 33 wherein the controller is further configured to calculate the detection values of the feature set with the data derived from signals of at least one sensor coupled to the respiratory treatment apparatus. 35. The system of claim 34 wherein the feature set of detection values comprises two or more of features of a group of features consisting of (a) a respiratory rate based feature; (b) a respiratory volume based feature; (b) a respiratory mechanics based feature; and (d) an expiratory flow morphology based feature. 36. The system of claim 32 wherein the at least two distinct events includes an expiratory ineffective effort event. 37. The system of claim 32 further comprising: an interface to carry a flow of breathable gas;a flow generator, coupled with the interface, that generates the breathable gas; anda flow sensor for generating the pressure transducer signals;wherein the controller is further configured to control the flow generator to provide a synchronized respiratory treatment. 38. The system of claim 37 wherein the synchronized respiratory treatment is respiratory support ventilation. 39. A non-transitory information-bearing medium having processor-readable information thereon, the processor-readable information to control a respiratory treatment apparatus and an apparatus for detection of asynchrony between a synchronized respiratory treatment and a respiratory cycle, the processor-readable information comprising control instructions to: access detection values of a feature set with data derived from signals of at least one sensor coupled with the respiratory treatment apparatus, in which the feature set of detection values includes a plurality of features as respective individual parameter detection variables derived from a pattern of flow indicated by the signals;compare the individual parameter detection variables respectively of the feature set of detection values with a set of associated thresholds for the individual parameter detection variables, the set of associated thresholds for the individual parameter detection variables being from other than the signals;determine an occurrence and type of an asynchrony event between the respiratory treatment apparatus and a patient respiratory cycle based on the comparison;wherein the determination of the occurrence and type of the asynchrony event identifies time of occurrence of a distinct asynchrony event of a plurality of distinct asynchrony events comprising at least two distinct events of (a) a post-triggering effort event, (b) a double triggering event, (c) a late triggering event, (d) an auto triggering event, (e) an early cycling event, and (f) a late cycling event,in which the apparatus for detection of asynchrony is configured to control the respiratory treatment apparatus based on the determination of the occurrence and type of the asynchrony event.