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 of predicting an unintentional leak in a respiratory system during a sleep session includes causing, during the sleep session, pressurized air to be delivered from a respiratory device to a user via a conduit coupled to a user interface. The method also includes receiving historical first data associated with pressurized air delivered from the respiratory device during one or more prior sleep sessions; receiving current first data associated with the pressurized air being delivered from the respiratory device during the sleep session; receiving historical second data associated with the user during one or more prior sleep sessions; and receiving, via one or more second sensors, current second data associated with the user during the current sleep session. The method determines, a likelihood that an unintentional leak in the respiratory system will occur within a predetermined amount of time.

Abstract: A method includes receiving physiological data associated with a user during a sleep session. The method also includes determining a sleep-wake signal for the user during the sleep session based at least in part on the received physiological data. The method also includes determining one or more sleep-related parameters for the user during the sleep session based at least in part on the sleep-wake signal. The method also includes determining that the user experienced insomnia during the sleep session based at least in part on at least one of the one or more sleep-related parameters. The method also includes identifying a type for the insomnia experienced by the user based at least in part on the one or more sleep-related parameters.

Abstract: Methods and apparatus provide monitoring of coughing and/or a sleep disordered breathing state of a person. One or more sensors may be configured for non-contact active and/or passive sensing. The processor(s) 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 coughing and/or sleep disordered breathing.

Abstract: System and methods are disclosed that promote a sleep stage of a user. The systems and methods determine a current sleep stage of a user during a sleep session, with the user using a respiratory therapy system during the sleep session. The systems and methods further predict an undesired sleep stage upcoming for the user during the sleep session based, at least in part, on (i) one or more user parameters, information from one or more previous sleep sessions, or a combination thereof, and (ii) the current sleep stage. The systems and methods adjust one or more control parameters of the respiratory therapy system, of one or more devices in an environment of the user, or of a combination thereof to promote a desired sleep stage of the user, thereby optimizing sleep of the user.

Abstract: A method for analyzing physical features of an individual comprises directing an acoustic signal toward a mouth of the individual, receiving a reflected acoustic signal from the interior of the mouth of the individual, generating a structural profile of at least the interior of the mouth of the individual based at least in part on the reflected acoustic signal, and causing an action to be performed in response to generating the structural profile. The acoustic signal is configured to reflect off at least a portion of the interior of the mouth of the individual. The reflected acoustic signal is indicative of structural characteristics of the mouth of the individual. The structural profile can also be based on image data associated with the exterior of the head and neck of the individual, and image data associated with the interior of the mouth of the individual.

Abstract: User alertness can be monitored and leveraged while the user is interacting with a computing device, such as a mobile device (e.g., a smartphone or tablet). By monitoring interaction data, an alertness inference of the user can be generated. The interaction data can include biometric data of the user (e.g., blink rate, eye focus, and breathing rate), inertia data of the device (e.g., swaying and orientation), and software-usage data of the device (e.g., button press speed and accuracy, app or action being used, and response times). The alertness inference can be a score measuring a degree of alertness of the user, from a deep sleep through fully alert. The alertness inference can be leveraged to automatically alert presentation of a message (e.g., notification) on the device, such as withholding presentation of the message or presenting it in different fashion (e.g., silently).

Abstract: A method includes receiving first data associated with a first sleep session of a user. The method also includes determining a first set of sleep-related parameters associated with the first sleep session of the user based at least in part on the first data. The method also includes receiving second data associated with a second sleep session of the user. The method also includes determining a second set of sleep-related parameters associated with the second sleep session of the user based at least in part on the second data. The method also includes receiving third data associated with a variable condition. The method also includes causing one or more indications associated with the variable condition and the first sleep session, the second sleep session, or both to be communicated to the user.

Abstract: A processing system includes methods to promote sleep. The system may include a monitor such as a non-contact motion sensor from which sleep information may be determined. User sleep information, such as sleep stages, hypnograms, sleep scores, mind recharge scores and body scores, may be recorded, evaluated and/or displayed for a user. The system may further monitor ambient and/or environmental conditions corresponding to sleep sessions. Sleep advice may be generated based on the sleep information, user queries and/or environmental conditions from one or more sleep sessions. Communicated sleep advice may include content to promote good sleep habits and/or detect risky sleep conditions. In some versions of the system, any one or more of a bedside unit 3000 sensor module, a smart processing device, such as a smart phone or smart device 3002, and network servers may be implemented to perform the methodologies of the system.

Abstract: A user interface of a respiratory therapy system includes a strap assembly, a frame, a connector, and a sensor. The strap assembly is positioned about a head of a user when the user wears the user interface. The frame is physically and electrically connected to the strap assembly, and defines an aperture. The connector has a first end portion and second end portion. The first end portion of the connector can be positioned within the aperture of the frame such that the connector is physically and electrically connected to the frame. The sensor is coupled to the strap assembly or the frame such that the sensor abuts a target area of the user when the user wears the user interface.

Abstract: A method includes (i) receiving data associated with a user during a sleep session; (ii) determining an alertness level of the user using a machine learning model that takes as input the received data; and (iii) generating a response to be communicated to the user based at least in part on the determined alertness level. The data associated with the user can be received from a respiratory therapy device configured to supply pressurized air to an airway of the user by way of a user interface coupled to the respiratory therapy device via a conduit, a sensor, or both the respiratory therapy device and the sensor.

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: Methods and devices provide physiological movement detection, such as gesture, breathing, cardiac and/or gross body motion, with active sound generation such as for an interactive audio device. The processor may evaluate, via a microphone coupled to the interactive audio device, a sensed audible verbal communication. 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 generated sound signal from the vicinity or user. The processor may process the reflected sound, such as by a demodulation technique, to derive a physiological movement signal. The processor may generate, in response to the sensed audible verbal communication, an output based on an evaluation of the derived physiological movement signal.

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.

Abstract: A system includes a memory storing a user profile for a user of the system and machine-readable instructions and a control system including one or more processors configured to execute the machine-readable instructions to receive physiological data associated with the user during a sleep session, determine, based at least in part on the received physiological data, a set of sleep-related parameters for the sleep session, subsequent to the sleep session, select one of the set of sleep-related parameters as a targeted parameter, the selection of the targeted parameter being based at least in part on the stored user profile, the set of sleep-related parameters, or both, and cause information to be communicated to the user via a user device, the information being indicative of the targeted parameter, a recommendation associated with improving the targeted parameter for the user in one or more subsequent sleep sessions, or both.

Abstract: A method includes receiving physiological data associated with a user during a sleep session. The method also includes determining a sleep-wake signal for the user during the sleep session based at least in part on the received physiological data. The method also includes determining one or more sleep-related parameters for the user during the sleep session based at least in part on the sleep-wake signal. The method also includes determining that the user experienced insomnia during the sleep session based at least in part on at least one of the one or more sleep-related parameters. The method also includes identifying a type for the insomnia experienced by the user based at least in part on the one or more sleep-related parameters.

Abstract: A method includes receiving first physiological data associated with a user during a first sleep session. The method also includes receiving second physiological data associated with the user subsequent to the first sleep session and prior to a second sleep session. The method also includes determining a recommended bedtime for the user for the second sleep session based at least in part on the first physiological data, the second physiological data, or both. The method also includes causing an indication of the recommended bedtime for the second sleep session to be communicated to the user via a user device before the recommended bedtime.

Abstract: A system includes a respiratory therapy device, a sensor, and a control system. The respiratory therapy device supplies pressurized air to an airway of a user during a plurality of sleep sessions. The sensor generates data including current data that is associated with a current sleep session of the plurality of sleep sessions and historical data that is associated with one or more prior sleep sessions of the plurality of sleep sessions. The control system includes one or more processors configured to execute machine-readable instructions to: analyze the historical data to determine a behavior pattern associated with the user; analyze the current data to determine a condition of the user interface in relation to the user; and generate an alarm based at least in part on the behavior pattern associated with the user and the condition of the user interface in relation to the user.

Abstract: A system includes a respiratory device, a mask, a microphone, a speaker, and a control system. The respiratory device is configured to supply pressurized air. The mask is coupled to the respiratory device and configured to engage a user during a sleep session to aid in directing the supplied pressurized air to the user. The microphone is configured to generate audio data. The speaker is configured to emit sound. The control system is configured to analyze the audio data to determine if noise associated with air leaking from the mask is occurring. Responsive to (i) the analysis resulting in a determination that noise associated with air leaking from the mask is occurring, (ii) the respiratory device determining that air is leaking from the mask, or (iii) both, the speaker is caused to emit the sound to aid in masking the noise associated with the air leaking from the mask.