Disclosed is a method and device for assessing respiratory data in a monitored subject. The disclosed method comprises collecting respiratory data of the subject at different levels of exertion with a physiological monitoring system (15-19), the respiratory data at least relating to instantaneous lung volume and comprising the end expiratory lung volume (EELV) after expirations; collecting exertion level data of the subject at the different levels of exertion, the exertion level data at least relating to instantaneous oxygen demand and/or heart rate; establishing a parametric relation (14, 15) between the collected respiratory data and the collected exertion level data, the parametric relation being described by one or more parameters; and assessing the respiratory data of the subject in terms of the value of the one or more parameters. The method and device allow a reliable measuring of dynamic hyperinflation in subjects without requiring much attention on the part of the subject.

Disclosed is a method and device for assessing respiratory data in a monitored subject. The disclosed method comprises collecting respiratory data of the subject at different levels of exertion with a physiological monitoring system (15-19), the respiratory data at least relating to instantaneous lung volume and comprising the end expiratory lung volume (EELV) after expirations; collecting exertion level data of the subject at the different levels of exertion, the exertion level data at least relating to instantaneous oxygen demand and/or heart rate; establishing a parametric relation (14, 15) between the collected respiratory data and the collected exertion level data, the parametric relation being described by one or more parameters; and assessing the respiratory data of the subject in terms of the value of the one or more parameters. The method and device allow a reliable measuring of dynamic hyperinflation in subjects without requiring much attention on the part of the subject.

A breath sampler for collecting a breath sample from a patient is disclosed. The breath sampler has a non-rebreather part including a sample inlet, a one-way outlet valve downstream of the sample inlet, and an air inlet. The one-way outlet valve and the sample inlet define a first portion of an internal breath flow pathway therebetween. The air inlet is arranged to be closed by a one-way inlet valve arranged to allow air to enter the non-rebreather part. The breath sampler also has a sample delivery part in fluid communication with the non-rebreather part at an upstream end via the one-way outlet valve. The sample delivery part defines a second portion of the internal breath flow pathway, and has an air diverter, a sample outlet, a return inlet and a sample collection chamber connector. The air diverter is arranged to divide the sample delivery part into an upstream portion upstream of the air diverter and a downstream portion downstream of the air diverter and is configured to divert the breath sample into a sample collection chamber including a liquid capture interface. The sample collection chamber is coupled to the sample collection chamber connector and includes a liquid capture interface.

A breath sampler for collecting a breath sample from a patient is disclosed. The breath sampler has a non-rebreather part including a sample inlet, a one-way outlet valve downstream of the sample inlet, and an air inlet. The one-way outlet valve and the sample inlet define a first portion of an internal breath flow pathway therebetween. The air inlet is arranged to be closed by a one-way inlet valve arranged to allow air to enter the non-rebreather part. The breath sampler also has a sample delivery part in fluid communication with the non-rebreather part at an upstream end via the one-way outlet valve. The sample delivery part defines a second portion of the internal breath flow pathway, and has an air diverter, a sample outlet, a return inlet and a sample collection chamber connector. The air diverter is arranged to divide the sample delivery part into an upstream portion upstream of the air diverter and a downstream portion downstream of the air diverter and is configured to divert the breath sample into a sample collection chamber including a liquid capture interface. The sample collection chamber is coupled to the sample collection chamber connector and includes a liquid capture interface.

Implantable devices for drug delivery in response to detected biometric parameters associated with an opioid drug overdose and associated systems and methods are disclosed herein. An implantable drug delivery device configured in accordance with some embodiments of the present technology can include a housing and a reservoir configured to contain a drug for treatment of the opioid overdose. The implantable drug delivery device can also include one or more sensors each configured to detect the biometric parameters associated with the overdose. The implantable drug delivery device can further include a controller configured to receive signals related to the biometric parameter, determine whether the overdose occurred based on the signals, and, if the overdose is detected, cause the drug to be delivered to the patient.

A system and method for a user to select and implement a lifestyle intervention. The system and method allows the user to select a lifestyle intervention and define the parameters of the intervention. The system monitors physiological parameters of the user that are related to the lifestyle intervention.

Disclosed are methods and devices for analyzing aerosol particles in exhaled breath using diagnostic tools that enable rapid, low cost and autonomous point of care assays for several diseases including respiratory tract diseases. Disclosed are methods and devices for capturing exhaled breath aerosols in a packed bed column and analyzing exhaled captured breath aerosols for tuberculosis diagnosis.

A wake-to-sleep transition for a subject is detected based on responsiveness to breathing cues provided to the subject. A pressurized flow of breathable gas to the airway of subject having one or more gas parameters that are adjusted to provide breathing cues to the subject. Based on a detected conformance of the respiration of the subject to the breathing cues, a determination is made as to whether the subject is awake or asleep.

A controller or processor(s) implements detection of respiratory related conditions, such as asynchrony, associated with use of a respiratory treatment apparatus or ventilator. Based on data derived from sensor signals associated with the respiratory treatment, the detector may evaluate a feature set of detection values to determine whether or not an asynchrony occurs in a breath of the patient's respiratory cycle such as by comparing the values against a set of thresholds. Different events may also be identified based on the particular feature set and threshold(s) involved in the detection processing. Automated determination of feature sets may also be implemented to design different asynchrony event classifiers. The methodologies may be implemented by computers or by respiratory treatment apparatus. The detection of such asynchrony events can then also serve as part of control logic for automated adjustments to the control parameters of the respiratory treatment generated by the respiratory treatment apparatus.

A controller or processor(s) implements detection of respiratory related conditions, such as asynchrony, associated with use of a respiratory treatment apparatus or ventilator. Based on data derived from sensor signals associated with the respiratory treatment, the detector may evaluate a feature set of detection values to determine whether or not an asynchrony occurs in a breath of the patient's respiratory cycle such as by comparing the values against a set of thresholds. Different events may also be identified based on the particular feature set and threshold(s) involved in the detection processing. Automated determination of feature sets may also be implemented to design different asynchrony event classifiers. The methodologies may be implemented by computers or by respiratory treatment apparatus. The detection of such asynchrony events can then also serve as part of control logic for automated adjustments to the control parameters of the respiratory treatment generated by the respiratory treatment apparatus.