A wearable system configured to collect thermal measurements related to respiration. The system includes a frame configured to be worn on a user's head, and at least one non-contact thermal camera (e.g., thermopile or microbolometer based sensor). The thermal camera is small and lightweight, physically coupled to the frame, located close to the user's face, does not occlude any of the user's mouth and nostrils, and is configured to take thermal measurements of: a portion of the right side of the user's upper lip, a portion of the left side of the user's upper lip, and a portion of the user's mouth. The thermal measurements are forwarded to a computer that calculates breathing related parameters, such as breathing rate, an extent to which the breathing was done through the mouth, an extent to which the breathing was done through the nostrils, and ratio between exhaling and inhaling durations.

Methods and apparatus provide monitoring of coughing and/or a sleep disordered breathing state of a person. One or more sensors may be configured for non-contact active and/or passive sensing. The processor(s) may extract respiratory effort signal(s) from one or more motion signals generated by active non-contact sensing with the sensor(s). The processor(s) may extract one or more energy band signals from an acoustic audio signal generated by passive non-contact sensing with the sensor(s). The processor(s) may assess the energy band signal(s) and/or the respiratory efforts signal(s) to generate intensity signal(s) representing sleep disorder breathing modulation. The processor(s) may classify feature(s) derived from the one or more intensity signals to generate measure(s) of coughing and/or sleep disordered breathing. The processor may evaluate sensing signal(s) to generate indication(s) of cough event(s) and/or cough type which may include generating an indication of a coronavirus disease or a coronavirus disease cough type.

A method of detecting coughs using photoplethysmography sensor data is presented. In some embodiments, accelerometry sensor data may also be used in conjunction. A system is presented for the purpose of automatic cough detection, which may also incorporate auxiliary data relevant to the occurrence of coughs. Auxiliary data, may be used to improve cough detection and/or be for contextualization and categorization of detected coughs.

System and methods are disclosed that promote a sleep stage of a user. The systems and methods determine a current sleep stage of a user during a sleep session, with the user using a respiratory therapy system during the sleep session. The systems and methods further predict an undesired sleep stage upcoming for the user during the sleep session based, at least in part, on (i) one or more user parameters, information from one or more previous sleep sessions, or a combination thereof, and (ii) the current sleep stage. The systems and methods adjust one or more control parameters of the respiratory therapy system, of one or more devices in an environment of the user, or of a combination thereof to promote a desired sleep stage of the user, thereby optimizing sleep of the user.

According to embodiments of the present invention, a gateway device operable in a system for monitoring a plurality of bio-signals is provided. The gateway device includes a receiver unit configured to receive data and reconstruct the received data to obtain a digital sound signal representative of the plurality of bio-signals; a processing unit configured to determine at least one biometric from the digital sound signal and form a digital signal representative of the plurality of bio-signals and the determined at least one biometric, and to reconstruct the digital signal into two or more data segments, wherein each data segment includes a portion of the digital signal; and a transmitter unit configured to transmit information including the two or more data segments to an external processing module for further processing. According to further embodiments, a system and a method for monitoring a plurality of bio-signals are also provided.

The present invention relates to a system (100) and method (800) capable of indirectly monitoring respiratory and cardiac variables. A decomposition technique on time-series of features extracted from the chest audio signal α(t) is proposed. The proposed monitoring system (100) may acquire the acoustic signal on the chest of a subject (140) by means of a wearable transducer (150). The proposed system may estimate a number of physiological variables such as flow estimates, respiration rate, inspiration and expiration markers and cardiac related variables. Cough and apnea detection, adventitious sound recognition, activities performed, and information about energy estimation and the status of a monitored subject can be derived as well.

The present invention relates generally and specifically to computerized devices capable of diagnosis tailoring for an individual, and capable of controlling effectors to deliver therapy or enhance performance also tailored to an individual. The invention integrates sensors which sense signals from measurable body systems together with external machines, to form adaptive digital networks over time of general health and health of specific body functions. The invention has applications in sleep and wakefulness, sleep-disordered breathing, other breathing disturbances, memory and cognition, monitoring and response to obesity or heart failure, monitoring and response to other conditions, and general enhancement of performance.

Detecting and identifying a predetermined health event can include detecting a potential occurrence of the predetermined health event for a user by processing in real-time motion signals corresponding to motion of the user. A likelihood that the potential occurrence is an actual occurrence of the predetermined health event can be determined based on template matching of the motion signals. In response to determining that the likelihood exceeds a predetermined threshold, audio signals coinciding in time with the motion of the user can be processed using one or more layers of a multilayered audio event classifier.

The present invention is directed to systems and methods for monitoring characteristics of a subject. A system according to an exemplary embodiment of the invention includes a sensor subsystem including at least one respiratory sensor disposed proximate to the subject and configured to detect a respiratory characteristic of the subject, wherein the sensor subsystem is configured to generate and transmit at least one respiratory signal representing the respiratory characteristic, and at least one physiological sensor disposed proximate to the subject and configured to detect a physiological characteristic of the subject, wherein the sensor subsystem is configured to generate and transmit at least one physiological signal representing the physiological characteristic, and a processor subsystem in communication with the sensor subsystem, the processor subsystem being configured to receive at least one of the at least one respiratory signal and the at least one physiological signal.

The present invention will provide a measuring device embedded within an elastic garment that will provide detect bodily movement by deforming a conductive material and measuring the change in electrical quantities within the conductive material as it deforms. Furthermore, the present invention will provide a measuring device configured to incorporate machine learning algorithms to estimate physiological, kinematic, dynamic, psychological, physical, biological, or other health parameters based upon the variations in electrical quantities within the conductive material as it deforms. This is accomplished through an elastic textile, a conductive element embedded within the elastic textile, and an electronic device configured to measure electrical quantities of the conductive element. These elements work in conjunction to detect and monitor movement in the human body.