Systems and methods are provided for using stored physiologic information about a subject to detect a previous treatment event. Physiologic information can be sensed from a subject using one or more sensors. Using a detection circuit, a change in the sensed physiologic information, such as a change from reference physiologic information, can be used to identify a candidate previous treatment event. An alert or other information about the candidate treatment event can be provided to a patient or clinician. In an example, a candidate treatment event can include a heart failure or diuresis treatment that is identified using information about a change in one or more of a subject's circadian pattern, a subject's thoracic impedance, or a subject's respiration status.

A system comprising: one or more sensors for detecting parameters of a respiratory cycle in a patient; and an implantable cardiac device comprising: at least one lead comprising one or more electrodes for applying cardiac contractility modulation stimulation to the heart; and circuitry for controlling and activating the leads, the circuitry programmed to set parameters of the cardiac contractility modulation stimulation according to the parameters of the respiratory cycle detected by the one or more sensors.

The present disclosure pertains to a system and method to inexsufflate a subject. The system provides effective way to ensure that a desired lung volume is recruited when using mechanical in-exsufflation therapy. The system includes a volume operation mode such that a desired target respiratory volume for achieving a therapy objective is set and the in-exsufflation therapy delivered based on the target respiratory volume. In some embodiments, gas parameters of the pressurized flow of breathable gas are determined based on a target respiratory volume. A first respiratory cycle is delivered based on the determined gas parameters and breathing parameters of subject are determined during the first respiratory cycle of in-exsufflation. A second respiratory cycle is delivered based on the determined breathing parameters of subject and the target respiratory volume.

A system includes a sensor device having a body configured to be inserted into an airway of a patient and one or more sensors mounted in or on the body. The one or more sensors are configured to collect sensor data associated with the airway of the patient. The system also includes a signal analyzer configured to analyze the sensor data. The one or more sensors could include one or more microphones. The signal analyzer could identify volume and/or pitch characteristics of the sensor data, perform pattern recognition to identify one or more patterns using the volume and/or pitch characteristics, and use the one or more patterns to identify a type, a location, and/or a degree of airway obstruction. This could be done, for instance, to determine if the patient suffers from obstructive sleep apnea or other condition that affects his or her airway.

A system includes a sensor device having a body configured to be inserted into an airway of a patient and one or more sensors mounted in or on the body. The one or more sensors are configured to collect sensor data associated with the airway of the patient. The system also includes a signal analyzer configured to analyze the sensor data. The one or more sensors could include one or more microphones. The signal analyzer could identify volume and/or pitch characteristics of the sensor data, perform pattern recognition to identify one or more patterns using the volume and/or pitch characteristics, and use the one or more patterns to identify a type, a location, and/or a degree of airway obstruction. This could be done, for instance, to determine if the patient suffers from obstructive sleep apnea or other condition that affects his or her airway.

Systems and methods for detecting worsening cardiac conditions such as worsening heart failure events are described. A system may include sensor circuits to sense physiological signals and signal processors to generate from the physiological signals first and second signal metrics. The system may include a risk stratifier circuit to produce a cardiac risk indication. The system may use at least the first signal metric to generate a primary detection indication, and use at least the second signal metric and the risk indication to generate a secondary detection indication. The risk indication may be used to modulate the second signal metric. A detector circuit may detect the worsening cardiac event using the primary and secondary detection indications.

Systems and methods for detecting worsening cardiac conditions such as worsening heart failure events are described. A system may include sensor circuits to sense physiological signals and signal processors to generate from the physiological signals first and second signal metrics. The system may include a risk stratifier circuit to produce a cardiac risk indication. The system may use at least the first signal metric to generate a primary detection indication, and use at least the second signal metric and the risk indication to generate a secondary detection indication. The risk indication may be used to modulate the second signal metric. A detector circuit may detect the worsening cardiac event using the primary and secondary detection indications.

A method of assessing a subject including: measuring a plurality of respirations of the subject; determining one or more respiration parameter from the plurality of respirations; and determining, using the one or more respiration parameter, one or more of: a state of consciousness of the subject; and a prognosis of the subject.

A method of assessing a subject including: measuring a plurality of respirations of the subject; determining one or more respiration parameter from the plurality of respirations; and determining, using the one or more respiration parameter, one or more of: a state of consciousness of the subject; and a prognosis of the subject.

A method for estimating an inhale dose when a drug is delivered to a person using an inhaler is disclosed. A predicted inhale dose (PID) of the drug is estimated based on at least one first-type parameter and at least one second-type parameter. The first-type parameter is related to a breath pattern of the person, and the second-type parameter is related to the inhaler.