A method of treating a human subject which is effected by inhalation of gaseous nitric oxide, the method comprising a first treatment period comprising administering gNO by inhalation over a period of about at least 5 days, wherein the first treatment period is followed by a second treatment period comprising administering gNO by inhalation over a period of at least 3 months. The method can be utilized for treating a human subject suffering from, or prone to suffer from, a disease or disorder that is manifested in the respiratory tract, or from a disease or disorder that can be treated via the respiratory tract.

Monitors for evaluating airway procedures, particularly in a pre-hospital environment, are described herein. In an example method, an airway parameter of an individual receiving assisted ventilation is detected by an airway sensor. A monitor determines a metric based on the airway sensor. Further, the monitor performs an action based on the metric.

Monitors for evaluating airway procedures, particularly in a pre-hospital environment, are described herein. In an example method, an airway parameter of an individual receiving assisted ventilation is detected by an airway sensor. A monitor determines a metric based on the airway sensor. Further, the monitor performs an action based on the metric.

Adaptive modification and presentment of user interface elements in a computerized therapeutic treatment regimen. Embodiments of the present disclosure provide for non-linear computational analysis of cData and nData derived from user interactions with a mobile electronic device executing an instance of a computerized therapeutic treatment regimen. The cData and nData may be computed according to one or more artificial neural network or deep learning technique to derive patterns between computerized stimuli or interactions and sensor data. Patterns derived from analysis of the cData and nData may be used to define an effort metric associated with user input patterns in response to the computerized stimuli or interactions being indicative of a measure of user engagement or effort. A computational model or rules engine may be applied to adapt, modify, configure or present one or more graphical user interface elements in a subsequent instance of the computerized therapeutic treatment regimen.

Adaptive modification and presentment of user interface elements in a computerized therapeutic treatment regimen. Embodiments of the present disclosure provide for non-linear computational analysis of cData and nData derived from user interactions with a mobile electronic device executing an instance of a computerized therapeutic treatment regimen. The cData and nData may be computed according to one or more artificial neural network or deep learning technique to derive patterns between computerized stimuli or interactions and sensor data. Patterns derived from analysis of the cData and nData may be used to define an effort metric associated with user input patterns in response to the computerized stimuli or interactions being indicative of a measure of user engagement or effort. A computational model or rules engine may be applied to adapt, modify, configure or present one or more graphical user interface elements in a subsequent instance of the computerized therapeutic treatment regimen.

One variation of a method for delivering a digital medicine experience to a user includes: loading the digital medicine experience at a sensory immersion vessel; calculating a target value of a bioindicator of the physiological state of the user, the target value of the bioindicator corresponding to a target physiological state of the user; at an initial time, rendering sensory representations of a set of elements in a multi-sensory virtual environment within the sensory immersion vessel at an initial progression rate; at a time during the digital medicine experience, succeeding the initial time, measuring a value of the bioindicator; calculating a progression rate through the digital medicine experience based on a difference between the value of the bioindicator and the target value of the bioindicator; and at a second time succeeding the time, rendering sensory representations of the set of elements in the multi-sensory virtual environment at the progression rate.

One variation of a method for delivering a digital medicine experience to a user includes: loading the digital medicine experience at a sensory immersion vessel; calculating a target value of a bioindicator of the physiological state of the user, the target value of the bioindicator corresponding to a target physiological state of the user; at an initial time, rendering sensory representations of a set of elements in a multi-sensory virtual environment within the sensory immersion vessel at an initial progression rate; at a time during the digital medicine experience, succeeding the initial time, measuring a value of the bioindicator; calculating a progression rate through the digital medicine experience based on a difference between the value of the bioindicator and the target value of the bioindicator; and at a second time succeeding the time, rendering sensory representations of the set of elements in the multi-sensory virtual environment at the progression rate.

Devices, systems, and methods for detecting a sealing condition between a patient interface and a patient, and adjusting the patient interface to maintain the patient interface in sealing contact with the patient. The patient interface may include a sealing structure to form a seal on the patient, and a positioning structure to secure the sealing structure to the patient. The patient interface may include a sensor coupled to the sealing structure. A processor determines the sealing condition between the sealing structure and the patient based on a signal from the sensor, and adjusts at least one of the sealing structure and the positioning structure to maintain the sealing structure in sealing contact with the patient. A prediction system predicts a leak between the sealing structure and the patient based on the sensor signal. A learning system learns how to fit the sealing structure to the patient to form a seal.

The embodiments of the present application provide an information processing method and apparatus, wherein the method is applied to a first client side, including: receiving therapy data from a therapy device, wherein the therapy data carries therapeutic effect data, a device identification corresponding to the therapy device, and a therapy parameter; sending the therapy data; and receiving parameter update information corresponding to the therapy data, wherein the parameter update information carries a latest therapy parameter acquired by updating the therapy parameter according to the therapeutic effect data, and the device identification corresponding to the therapy device. The embodiments of the present application can collect the therapy data of a user in time and conveniently, and improves the collecting efficiency of the therapy data.

An ear-worn electronic device includes a right ear device comprising a first processor and a left ear device comprising a second processor communicatively coupled to the first processor. A physiologic sensor module comprises one or more physiologic sensors configured to sense at least one physiologic parameter from a wearer. A motion sensor module comprises one or more sensors configured to sense movement of the wearer. The first and second processors are coupled to the physiologic and motion sensor modules. The first and second processors are configured to produce a three-dimensional virtual sound environment comprising relaxing sounds, generate verbal instructions within the three-dimensional virtual sound environment that guide the wearer through a predetermined mental exercise that promotes wearer relaxation, and generate verbal commentary that assesses wearer compliance with the predetermined mental exercise in response to one or both of the sensed movement and the at least one physiologic parameter.