Abstract: A method comprises receiving data associated with a diabetes treatment plan of the individual. The method further comprises receiving data associated with a respiratory therapy plan of the individual. The respiratory therapy plan is implementable by a respiratory therapy system during a sleep session. The method further comprises determining a potential interaction between the diabetes treatment plan of the individual and the respiratory therapy plan of the individual. The method further comprises, based on the interaction, updating the diabetes treatment plan of the individual.

Abstract: Systems and methods are disclosed for categorizing and/or characterizing a user interface. The systems and methods include generating acoustic data associated with an acoustic reflection of an acoustic signal, the acoustic reflection being indicative of, at least in part, one or more features of a user interface coupled to a respiratory therapy device via a conduit. The systems and methods further include analyzing the generated acoustic data. The systems and methods further include categorizing and/or characterizing the user interface based, at least in part, on the analyzed acoustic data.

Abstract: Systems and methods are disclosed for categorizing and/or characterizing a user interface. The systems and methods include generating acoustic data associated with an acoustic reflection of an acoustic signal, the acoustic reflection being indicative of, at least in part, one or more features of a user interface coupled to a respiratory therapy device via a conduit. The systems and methods further include analyzing the generated acoustic data. The systems and methods further include categorizing and/or characterizing the user interface based, at least in part, on the analyzed acoustic data.

Abstract: A method includes generating a first airflow that travels from the respiratory therapy device to a user interface by operating a motor of the respiratory therapy device. The method also includes receiving first airflow parameter data associated with the first airflow. The method also includes determining a first user interface prediction, based on the first airflow parameter data. The method also includes generating a second airflow from the respiratory therapy device to the user interface by operating the motor of the respiratory therapy device. The method also includes receiving second airflow parameter data associated with the second airflow. The method also includes determining, based on the second airflow parameter data, a second user interface prediction. The method also includes characterizing the user interface based at least in part on the first user interface prediction and the second user interface prediction.

Abstract: A method of modifying pressure settings of a respiratory therapy system comprises supplying pressurized air at a first pressure to a user during a current sleep session; determining a number and/or type of events experienced by the user during a first portion of the current sleep session; and modifying the pressure settings of the respiratory therapy system during a subsequent sleep session portion in response to the number and/or type of events satisfying a threshold. Modifying the pressure settings can include modifying the first pressure to be a modified first pressure for the subsequent sleep session portion, (ii) modifying a difference in pressure between the first pressure and a second pressure for the subsequent sleep session portion, (iii) modifying a rate of change from the first pressure to the second pressure for the subsequent sleep session portion, or (iv) any combination of (i)-(iii).

Abstract: A method of detecting rainout in a respiratory therapy system that includes a conduit fluidly coupled to a user interface comprises generating, via at least one microphone, acoustic data representative of noise associated with the respiratory therapy system. The method further comprises analyzing the acoustic data to detect a presence of liquid in the respiratory therapy system. The method further comprises causing an action to be performed, based on the detected presence of the liquid.

Abstract: A method of determining a sleep stage of an individual comprises identifying features associated with a current epoch of the sleep session, determining a plurality of sleep stage probabilities based on the features, identifying events experienced by the individual during the current epoch, and adjusting each of the plurality of sleep stage probabilities based on events experienced by the individual during the current epoch or a prior epoch, and/or a sleep stage previously determined for the prior epoch. The features include at least one feature associated with a flow of pressurized air from a respiratory therapy system used by the individual, at least one feature associated with a respiration rate of the individual, and/or at least one feature associated with a time of the sleep session. Each sleep stage probability corresponds to a respective one of a plurality of potential sleep stages during the current epoch of the sleep session.

Abstract: A method includes providing a tag applied to an intended test subject. The tag having an anti-tamper authentication feature that is altered when the tag is removed from the test subject, and which, when altered, is rendered unsuitable for authentication. The method including providing a diagnostic device applied to a test subject. The diagnostic device interacting with the anti-tamper authentication feature of the tag. The method including authenticating the tag with the diagnostic wearable device based on the diagnostic device's interaction with the anti-tamper authentication feature. Successful authentication indicating that the test subject is the intended test subject. Unsuccessful authentication occurring when the anti-tamper authentication feature is altered. The method including collecting sensor data from the test subject via the diagnostic device.

Abstract: A method includes receiving sensor data from a device worn on one or more digits of a test subject. The method including determining physiological parameter(s) from at least a first portion of the sensor data acquired during a test session. The method including associating the determined physiological parameter(s) with the testing session. The method including authenticating the device by i) determining identification data using at least a second portion of the sensor data, the identification data including identifiable characteristic(s) of the one or more digits; ii) accessing authentication data that includes one or more authentication characteristics; and iii) comparing the identification data with the authentication data to determine a match to authenticate the device. The method including generating a chain of custody determination based at least in part on the authentication of the device. The method including associating the chain of custody determination with the testing session.

Abstract: A method includes receiving, at a user device, first sensor data from sensor(s) coupled to the user device. The method including receiving identity enrollment information associated with a test subject engaging in a testing session and establishing a communication link between the user device and a wearable diagnostic device. The method also includes associating the wearable diagnostic device with the testing session by determining, using first sensor data, that the wearable diagnostic device is being worn by the test subject at a first time. The method including receiving second sensor data from the wearable diagnostic device after the first time. The method including analyzing the second sensor data to identify an interference instance indicative that the wearable diagnostic device is no longer worn by the test subject at a second time. The method including generating a chain of custody determination based at least in part on the interference instance.

Abstract: The present disclosure relates to a method for identifying a user interface. Flow data associated with air flowing in a respiratory therapy system is received. Acoustic data associated with the respiratory therapy system is received. The received flow data and the received acoustic data are analyzed. Based at least in part on the analysis, a mask type for the user interface is determined.

Abstract: Various implementations of the present disclosure are directed to systems and methods for leak detection in a respiratory therapy system using acoustic data. According to some implementations, a method includes receiving acoustic data associated with airflow caused by operation of a respiratory therapy system during a sleep session of a user. The method also includes analyzing at least a portion of the acoustic data to determine a value of a parameter associated with the at least a portion of the acoustic data. The method further includes determining an occurrence of a leak during the sleep session in response to the determined value of the parameter satisfying a condition.

Abstract: A system and method detects an occlusion in a respiratory therapy system. The system and method includes determining an acoustic signature for a conduit of a headgear user interface. The determined acoustic signature is analyzed to identify an anomaly in the acoustic signature. In response to the determined acoustic signature being identified as anomalous, a determination is made if the identified anomaly relates to an occlusion of the conduit.

Abstract: Systems and methods are disclosed for categorizing and/or characterizing a user interface. The systems and methods include generating acoustic data associated with an acoustic reflection of an acoustic signal, the acoustic reflection being indicative of, at least in part, one or more features of a user interface coupled to a respiratory therapy device via a conduit. The systems and methods further include analyzing the generated acoustic data. The systems and methods further include categorizing and/or characterizing the user interface based, at least in part, on the analyzed acoustic data.

Abstract: A method of detecting rainout in a respiratory therapy system that includes a conduit fluidly coupled to a user interface comprises generating, via at least one microphone, acoustic data representative of noise associated with the respiratory therapy system. The method further comprises analyzing the acoustic data to detect a presence of liquid in the respiratory therapy system. The method further comprises causing an action to be performed, based on the detected presence of the liquid.

Abstract: The present disclosure relates to a method for identifying a user interface. Flow data associated with air flowing in a respiratory therapy system is received. Acoustic data associated with the respiratory therapy system is received. The received flow data and the received acoustic data are analyzed. Based at least in part on the analysis, a mask type for the user interface is determined.

Abstract: A method includes generating acoustic data representative of at least one or more reflections of an acoustic signal. The one or more reflections are indicative of a length and/or a diameter of a conduit coupled to a respiratory therapy device. The method further includes analyzing the acoustic data to determine the length and/or diameter of the conduit. In some cases, analyzing the acoustic data includes determining a resonant frequency of the conduit, and determining the length of the conduit based at least in part on the resonant frequency. In some cases, analyzing the acoustic data includes comparing the acoustic data to predetermined sets of acoustic data that each correspond to a known length and/or diameter of the conduit, and selecting one of the predetermined sets of acoustic data that best matches the generated acoustic data. The selected set of acoustic data corresponds to the length and/or diameter of the conduit.

Abstract: A method includes generating, by a sensor, physiological data associated with a user during a sleep session. The method also includes processing, by an electronic device including one or more processors, the generated physiological data to distinguish between on-therapy data and off-therapy data. The on-therapy data is the generated physiological data while a respiratory therapy system is coupled to the user and supplies pressurized air to an airway of the user. The off-therapy data is the generated physiological data while the respiratory therapy system is not supplying pressurized air to the airway of the user. The method also includes determining, by the electronic device, a sleep measure based at least in part on the off-therapy data.

Abstract: A method includes receiving first physiological data associated with a user. The method also includes determining a first emotion score associated with the user based at least in part on the first physiological data. The method also includes modifying one or more settings of a respiratory therapy system responsive to determining that the first emotion score satisfies a predetermined condition.

Abstract: A plurality of flow rate values associated with pressurized air directed to an airway of a user of a respiratory therapy system is received. A plurality of pressure values associated with the pressurized air directed to the airway of the user is received. A first time associated with a first breath of the user and a second time associated with a second breath of the user are identified. The plurality of flow rate values is filtered based at least in part on the identified first time and the identified second time. The filtering produces a subset of the plurality of flow rate values. An intentional leak characteristic curve for the respiratory therapy system is determined using at least two of the subset of the plurality of flow rate values and the corresponding pressure values for said at least two of the subset of the plurality of flow rate values.