Abstract: Systems and methods implement a status assessment of a respiratory device with sound evaluation. In some versions, the system may include a motor operated pressure generator to generate airflow through an air circuit to a patient interface. The system may include a transducer producing a signal representing sound of the generator in the circuit. The system may include a controller, such as with a processor, for generator control. The system, such as with the controller, computes a sound representation in the frequency domain. The system applies, to the frequency domain representation, any one or more of an integer-multiple function, non-integer-multiple function, a statistical correlation function and resonant frequency function, such as of a fundamental frequency attributable to motor operation. The system may derive a noise vector with data from the function(s). The system may classify the vector to obtain a status indicator of the generator and generate indicator related output.

Abstract: Apparatus for providing air at positive pressure for respiratory therapy to a patient includes a pneumatic block including at least first and second blower sub-assemblies and a common chassis assembly configured to support each of the at least first and second blower sub-assemblies. The at least first and second blower sub-assemblies are different structurally from one another in at least one aspect. Each of the at least first and second blower sub-assemblies includes a corresponding blower configured to produce a flow of air at a therapeutic pressure. The common chassis assembly and the first blower sub-assembly form a first configuration of the pneumatic block, and the common chassis assembly and the second blower sub-assembly form a second configuration of the pneumatic block. The air flow path and the chamber arrangement of the first configuration is different than the air flow path and the chamber arrangement of the second configuration.

Abstract: A respiratory pressure therapy (RPT) device is disclosed for treatment of respiratory-related disorders. The RPT device includes a pressure generator, a pneumatic block, a chassis and a device outlet for delivering a supply of flow of gas to a patient interface. The RPT device also comprises an integrated humidifier including a water reservoir. An RPT device is also disclosed that includes a wireless data communication interface integrated with the housing and configured to connect to another device or a network.

Abstract: A compact respiratory therapy device suitable for use by a patient during sleep to provide respiratory pressure therapy such as at a pressure between 4-30 cmH2O includes a housing, an inlet, an outlet, a motor including a rotor, and an impeller configured to be rotated by the rotor to deliver a flow of air from the inlet toward the outlet. The impeller includes a set of impeller blades, each impeller blade comprising a leading edge and a trailing edge; and a first shroud and a second shroud, each shroud at least partly defining a flow passage through the impeller, the first shroud comprising a wall defining a periphery of an impeller inlet. The compact respiratory therapy device is configured to deliver the flow of air from the outlet for delivery to the patient at a pressure between 4-30 cmH2O at an overall sound power level of less than 50 dB(A) thereby reducing any disturbance to a quality of sleep for the patient. A diameter of the impeller is less than 50 mm.

Abstract: A respiratory apparatus evaluates accuracy of a pressure sensor, such as when only a single pressure sensor is provided. The accuracy of the pressure sensor may be assessed based on pressure measurement obtained from the pressure sensor and a subordinate or secondary characteristic of the respiratory device such as altitude or atmospheric pressure. A controller or processor may calculate the altitude of the respiratory device based in part on the pressure measurement. In some embodiments, the assessment of the pressure sensor may involve an evaluation of the calculated altitude. In some cases, the assessment of the pressure sensor may involve determining an estimated pressure based on a calculated altitude, and comparing the pressure measurement obtained from the pressure sensor with the estimated pressure.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for machine learning models for adjusting communication parameters. In some implementations, data for each device in a set of multiple communication devices is obtained. A machine learning model is trained based on the obtained data. The model can be trained to receive an indication of a geographic location and predict a communication setting capable of providing at least a minimum level of efficiency. After training the machine learning model, an indication of a predicted communication setting for a particular communication device is generated. A determination is then made whether to change a current communication setting for the particular communication device based on the predicted communication setting.

Abstract: Apparatus for providing air at positive pressure for respiratory therapy to a patient includes a pneumatic block including at least first and second blower sub-assemblies and a common chassis assembly configured to support each of the at least first and second blower sub-assemblies. The at least first and second blower sub-assemblies are different structurally from one another in at least one aspect. Each of the at least first and second blower sub-assemblies includes a corresponding blower configured to produce a flow of air at a therapeutic pressure. The common chassis assembly and the first blower sub-assembly form a first configuration of the pneumatic block, and the common chassis assembly and the second blower sub-assembly form a second configuration of the pneumatic block. The air flow path and the chamber arrangement of the first configuration is different than the air flow path and the chamber arrangement of the second configuration.

Abstract: A personal entertainment respiratory apparatus provides air to a user to provide a fully immersive entertainment experience. The personal entertainment system may comprise a flow generator for providing the flow of air. A personal spatial respiratory interface may be coupled to the flow generator. The personal spatial respiratory interface may comprise an outlet for the flow generator. The personal spatial respiratory interface may further be configured to direct the flow of air within an ambient breathing proximity of a user. The personal entertainment respiratory apparatus may further comprise a controller and a sensory particle dispenser. The controller and sensory particle dispenser may be configured to selectively activate release of a sensory particle from the dispenser into the directed flow of air in response to an entertainment triggering signal.

Abstract: A compact respiratory therapy device suitable for use by a patient during sleep to provide respiratory pressure therapy such as at a pressure between 4-30 cmH2O includes a housing, an inlet, an outlet, a motor including a rotor, and an impeller configured to be rotated by the rotor to deliver a flow of air from the inlet toward the outlet. The impeller includes a set of impeller blades, each impeller blade comprising a leading edge and a trailing edge; and a first shroud and a second shroud, each shroud at least partly defining a flow passage through the impeller, the first shroud comprising a wall defining a periphery of an impeller inlet. The compact respiratory therapy device is configured to deliver the flow of air from the outlet for delivery to the patient at a pressure between 4-30 cmH2O at an overall sound power level of less than 50 dB(A) thereby reducing any disturbance to a quality of sleep for the patient. A diameter of the impeller is less than 50 mm.

Abstract: A head-mountable flow generator is configured to deliver a flow of breathable gas at a continuously positive pressure with respect to ambient air pressure to a patient interface in communication with an entrance to a patient's airways including at least an entrance of the patient's nares, while the patient is sleeping, to ameliorate sleep disordered breathing. The flow generator includes a motor, an impeller assembly and housing that encases the motor and the impeller assembly. The housing is configured to be mounted on the patient's head and comprises an inlet to receive the flow of breathable gas and a pair of opposing outlets to deliver the flow of breathable gas. In addition, the impeller assembly is configured to pressurize the flow of breathable gas received from the inlet, and the housing is configured to convey the pressurized flow of breathable gas through both outlets.

Abstract: A CPAP device for delivering pressurized, humidified breathable gas for a patient includes a flow generator configured to pressurize a flow of breathable gas. The flow generator includes an air outlet and a removable water container configured to humidify the pressurized breathable gas received from the flow generator. The water container includes an air inlet and an air outlet. The CPAP device further includes a first elastomeric face seal configured to sealingly abut against a substantially flat portion of the water container surrounding the water container air inlet, the first elastomeric face seal being located at an intermediate position between the flow generator air outlet and the water container air inlet when the water container is placed into position to pneumatically communicate with the flow generator.

Abstract: A head-mountable flow generator is configured to deliver a flow of breathable gas at a continuously positive pressure with respect to ambient air pressure to a patient interface in communication with an entrance to a patient's airways including at least an entrance of the patient's nares, while the patient is sleeping, to ameliorate sleep disordered breathing. The flow generator includes a motor, an impeller assembly and housing that encases the motor and the impeller assembly. The housing is configured to be mounted on the patient's head and comprises an inlet to receive the flow of breathable gas and a pair of opposing outlets to deliver the flow of breathable gas. In addition, the impeller assembly is configured to pressurize the flow of breathable gas received from the inlet, and the housing is configured to convey the pressurized flow of breathable gas through both outlets.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining availability of network service. In some implementations, a request indicating a location and a communication service level is received. A first subset of service providers or communication technologies is determined based on outputs generated by multiple first machine learning models each trained to predict service availability for different service providers or communication technologies. A second subset is selected from the first subset based on outputs generated by multiple second machine learning models trained to predict availability of different communication service levels for different service providers or communication technologies. At least one service provider or communication technology is selected from the second subset based on output generated by a third machine learning model.

Abstract: A blower includes a housing including an inlet and an outlet, a bearing-housing structure provided to the housing and adapted to rotatably support a rotor, a motor provided to the bearing-housing structure and adapted to drive the rotor, and an impeller provided to the rotor. The bearing-housing structure includes a bearing shaft having a bearing surface that rotatably supports the rotor. The bearing shaft provides only a single bearing of the non-ball bearing type for the rotor.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training and using machine learning models to classify network traffic as IoT traffic or non-IoT traffic and managing the traffic based on the classification. In some implementations, machine learning parameters of a local machine learning model trained by the edge device is received each of at least a subset of a set of edge devices. The machine learning parameters received from an edge device are parameters of the local machine learning model trained by the edge device based on local network traffic processed by the edge device and to classify the network traffic as Internet of Things (IoT) traffic or non-IoT traffic. A global machine learning model is generated, using the machine learning parameters, to classify network traffic processed by edge devices as IoT traffic or non-IoT traffic.

Abstract: A vent arrangement is provided to a mask or associated conduit to discharge exhaled gas from the mask to atmosphere. The vent arrangement is structured to diffuse the exhaust vent flow to produce less air jetting, thereby increasing the comfort of the patient and their bed partner. For example, the vent arrangement may include one or more grill components and/or media constructed and arranged to diffuse vent flow.

Abstract: A blower for providing a supply of air at positive pressure in the range of approximately 2 cmH2O to 30 cmH20 includes a motor, at least one impeller, and a stationary component. The stationary component includes an inlet and an outlet. The motor, the impeller, the inlet and outlet are co-axial.

Abstract: A blower includes a housing including an inlet and an outlet, a bearing-housing structure provided to the housing and adapted to rotatably support a rotor, a motor provided to the bearing-housing structure and adapted to drive the rotor, and an impeller provided to the rotor. The bearing-housing structure includes a bearing shaft having a bearing surface that rotatably supports the rotor. The bearing shaft provides only a single bearing of the non-ball bearing type for the rotor.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training and using machine learning clustering models to determine conditions a satellite communication system. In some implementations, feature vectors for a time period are obtained. Each feature vector includes feature values that represent properties of a satellite communication system at a respective time during the time period. Each feature vector is provided as input to a machine learning model that assigns the feature vector to a based on the properties of the satellite communication system represented by the feature vector. Each cluster corresponds to a respective potential operating condition of the satellite communication system.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining availability of network service. In some implementations, a request indicating a location and a communication service level is received. A first subset of service providers or communication technologies is determined based on outputs generated by multiple first machine learning models each trained to predict service availability for different service providers or communication technologies. A second subset is selected from the first subset based on outputs generated by multiple second machine learning models trained to predict availability of different communication service levels for different service providers or communication technologies. At least one service provider or communication technology is selected from the second subset based on output generated by a third machine learning model.