Abstract: The present disclosure relates to a method for determining movement of a user while using a respiratory therapy system is disclosed. Acoustic data associated with the user of the respiratory therapy system is received. The received acoustic data is analyzed. Based at least in part on the analyzed acoustic data, a movement event associated with the user is determined.

Abstract: Airflow parameters (e.g., flow rate and airflow pressure) of airflow generated by a flow generator of a respiratory therapy system can be measured during use and processed to automatically identify user interface and/or conduit identification information. This user interface and/or conduit identification information can be used to adjust settings of the respiratory therapy device, generate notifications (e.g., notifications of a detected change in user interface without concomitant, expected adjustment of settings of the respiratory therapy device), or otherwise facilitate respiratory therapy of the user or of other users. User interface and/or conduit identification information can be indicative of specific characteristics of the user interface and/or conduit (e.g., resonant frequencies, impedance, and the like), a style of the user interface (e.g., a face mask, nasal mask, or nasal pillow) and/or style of conduit, a specific manufacturer, a specific model, or other such identifiable information.

Abstract: The present disclosure relates to a method for determining a mouth leak status associated with a user of a respiratory device is disclosed. Airflow data associated with the user of the respiratory device is received. The respiratory device is configured to supply pressurized air to an airway of the user during a therapy session. The airflow data includes pressure data. The airflow data associated with the user is analyzed. Based at least in part on the analysis, the mouth leak status associated with the user is determined. The mouth leak status is indicative of whether or not air is leaking from a mouth of the user.

Abstract: Devices, systems, and methods are disclosed. The devices, systems, and methods detect one or more parameters with respect to movement of a user, cardiac activity of the user, audio associated with the user, or a combination thereof during a sleep session of the user; process the one or more parameters to determine a sleep status of the user, the sleep status being at least one of awake, asleep, or a sleep stage; and calculate an apnea-hypopnea index for the user during the sleep session based, at least in part, on the sleep status.

Abstract: Method and apparatus obtain information about a patient and/or a respiratory therapy system that is configured to deliver respiratory therapy to the patient. The respiratory therapy system may include a flow generator configured to generate a supply of pressurized air along an air circuit to a patient interface. A sound signal representing a sound in the air circuit may be processed to obtain cepstrum data. A time series of delay estimates based on acoustic signatures of the cepstrum data may be generated. Each acoustic signature may represent a reflection of sound from a patient interface along the air circuit. Variation in the time series of delay estimates may be analysed. One or more output indicators based on the variation may be generated. The one or more output indicators may concern patient and/or system status.

Abstract: Methods and apparatus provide monitoring of a sleep disordered breathing state of a person such as for screening. One or more sensors may be configured for non-contact active and/or passive sensing. The processor(s) (7304, 7006) may extract respiratory effort signal(s) from one or more motion signals generated by active non-contact sensing with the sensor(s). The processor(s) may extract one or more energy band signals from an acoustic audio signal generated by passive non-contact sensing with the sensor(s). The processor(s) may assess the energy band signal(s) and/or the respiratory efforts signal(s) to generate intensity signal(s) representing sleep disorder breathing modulation. The processor(s) may classify feature(s) derived from the one or more intensity signals to generate measure(s) of sleep disordered breathing. The processor may generate a sleep disordered breathing indicator based on the measure(s) of sleep disordered breathing.

Abstract: Methods and devices provide physiological movement detection with active sound generation. In some versions, a processor may detect breathing and/or gross body motion. The processor may control producing, via a speaker coupled to the processor, a sound signal in a user's vicinity. The processor may control sensing, via a microphone coupled to the processor, a reflected sound signal. This reflected sound signal is a reflection of the sound signal from the user. The processor may process the reflected sound, such as by a demodulation technique. The processor may detect breathing from the processed reflected sound signal. The sound signal may be produced as a series of tone pairs in a frame of slots or as a phase-continuous repeated waveform having changing frequencies (e.g., triangular or ramp sawtooth). Evaluation of detected movement information may determine sleep states or scoring, fatigue indications, subject recognition, chronic disease monitoring/prediction, and other output parameters.

Abstract: A technique for managing alarms includes acquiring a physiological parameter value and one or more alarm settings associated with the physiological parameter value. The technique also includes determining if the one or more alarm settings are associated with an adaptive alarm manager selecting an adaptive alarm condition from a plurality of adaptive alarm conditions when the one or more alarm settings are associated with the adaptive alarm manager; determining if the physiological parameter value meets the selected adaptive alarm condition; and generating an alarm in response when the physiological parameter value meets the selected adaptive alarm condition.

Abstract: A technique for managing alarms includes acquiring a physiological parameter value and one or more alarm settings associated with the physiological parameter value. The technique also includes determining if the one or more alarm settings are associated with an adaptive alarm manager selecting an adaptive alarm condition from a plurality of adaptive alarm conditions when the one or more alarm settings are associated with the adaptive alarm manager; determining if the physiological parameter value meets the selected adaptive alarm condition; and generating an alarm in response when the physiological parameter value meets the selected adaptive alarm condition.