Resmed Inc.

Methods or systems ( 7000 ) are implemented for treatment with or monitoring use of respiratory pressure therapy device(s). The device may be for a respiratory disorder. A processor, such as a processor of a server communicating with the therapy device, may analyse data relating to respiratory therapy delivered by the device. The processor may generate data in the processor representing a prediction, such as compliance prediction(s), about progress of therapy based on the analysis. The processor may select an action to improve therapy based on data representing the prediction. The processor may take or prompt selected action to improve the therapy. In some cases, a processor may analyse usage data concerning a period of days with a therapy device and generate compliance prediction indicators based on the analysis. The indicators indicate whether compliance will be likely. The processor may recommend engagement action to improve compliance based on evaluation of the indicators.

A mobile device for identifying a potential candidate includes a screen, a sensor, and a control system. The sensor configured to generate sensor data associated with use of the mobile device. The control system is configured to: extract location data from the sensor data, the location data including physical location of the mobile device at different time intervals; determine from the location data whether mobility of the mobile device is below a threshold; extract mobile device usage data from the sensor data; determine, from the mobile device usage data, a pattern of use of the mobile device to obtain a sleeping pattern of the potential candidate; and based at least in part on the mobility of the mobile device being below a threshold and the pattern of use of the mobile device, cause the screen to display an alert.

Accordingly, systems and methods have been developed to monitor, diagnose, and predict the course of a wound to aid in determining whether a wound is properly healing. This includes systems and methods that may be performed by the patient in the home in some cases, and some that utilized sensors available on mobile devices. Thus, patients may be able to manage wounds at home without the intervention of caregivers and reduce the costs of admission to hospitals.

Techniques for machine learning-based dropout severity prediction are provided. Usage information for a patient is accessed, the usage information indicating participation, by the patient, in a respiratory therapy. A dropout event with respect to the respiratory therapy is identified based on evaluating the usage information using a consolidated usage rule. In response to identifying the dropout event, a dropout severity prediction is generated based on the usage information and a trained machine learning model. In response to determining that the dropout severity prediction satisfies one or more criteria, one or more interventions for the patient are initiated.

This description provides asthma risk notifications in advance of predicted rescue usage events in order to help effect behavior changes in a patient to prevent those events from occurring. Rescue medication events, changes in environmental conditions, and other contextually relevant information are detected by sensors associated with the patient's medicament device/s and are collected from other sources, respectively, to provide a basis to determine a patient's risk score. This data is analyzed to determine the severity of the patient's risk for an asthma event and is used to send notifications accordingly.

A system and method to collect feedback data from a patient wearing an interface such as a mask when using a respiratory pressure therapy device such as a CPAP device. The system includes a storage device including a facial image of the patient. An interface in communication with the respiratory pressure therapy device collect operational data from when the patient uses the interface. A patient interface collects subjective patient input data from the patient in relation to the patient interface. An analysis module correlates a characteristic of the interface with the facial image data, operational data and subjective patient input data.

A system and method to collect feedback data from a patient wearing an interface such as a mask when using a respiratory pressure therapy device such as a CPAP device. The system includes a storage device including a facial image of the patient. An interface in communication with the respiratory pressure therapy device collect operational data from when the patient uses the interface. A patient interface collects subjective patient input data from the patient in relation to the patient interface. An analysis module correlates a characteristic of the interface with the facial image data, operational data and subjective patient input data.

A medicament device sensor (Sensor) comprises a body, a front wall, a back wall, an audio sensor, and a plurality of pressure sensors. The body includes a bottom surface on which the various sensors are coupled. The front wall and the back wall provide mirror symmetry in at most one plane, thereby defining a single orientation in which the Sensor attaches to the medicament device. The front wall includes a securement clip that attaches to a ledge on the medicament device. To detect secure attachment of the Sensor to the medicament device, one pressure sensor detects pressure when the Sensor is secured to the medicament device. Another one or more pressure sensors detect depression of one or more dosing buttons confirming priming of the medicament device. The audio sensor detects an inhalation confirming dispensing of medicament. In effect, the Sensor determines a dispensing event has occurred.

A system and method for updating patient devices is disclosed. The patient devices may include respiratory therapy devices that operate in accordance with instruction sets, such as software or firmware. A server may maintain a database of configuration data indicating the versions of the software and firmware that is currently installed on the patient devices. The server may also transmit updated instructions from over a network, including a wireless network. Particular patient devices may be selected for updating based on the configuration data. Upon performing an update a patient device may transmit configuration data to the server.

A communication system for operation of respiratory pressure therapy devices for treating respiratory disorders of a plurality of patients includes one or more servers configured to communicate with the plurality of respiratory pressure therapy devices. The server(s) are configured to receive communications relating to respiratory therapy delivered to a patient via at least one respiratory pressure therapy device of the plurality of respiratory pressure therapy devices. The server(s) are configured to transmit one or more responsive communications for control of the at least one respiratory pressure device according to a selected action to improve the respiratory therapy. The selected action includes transmitting, from the server(s), a control command to the at least one respiratory pressure therapy device. The responsive communication(s) are generated in response to a compliance prediction that is a score indicating a probability that the patient will be compliant with a predetermined compliance rule.