An apparatus, comprising a processor and memory storing instructions that, when executed by the processor, cause the processor to: receive ventilator data obtained from continual mechanical ventilatory support of a patient over a period of time, analyze the ventilator data to identify a plurality of breathing cycles, classify the plurality of breathing cycles into normal breathing cycles and abnormal breathing cycles, using a machine learning algorithm, detect a change in the normal breathing cycles, compared to normal breathing cycles identified by the apparatus based on ventilator data obtained from continual mechanical ventilatory support of the patient over a previous period of time, and generate output indicative of the change in the normal breathing cycles.

Methods, devices, and systems for contactless cough detection and attribution are presented herein. Audio data may be received using a microphone. A cough may be identified as having occurred based on the received audio data. Radar data may be received indicative of reflected radio waves from a radar sensor. A state analysis process may be performed using the received radar data. The detected cough may be attributed to a particular user based at least in part on the state analysis process performed using the radar data.

A breath analyzer for detecting breathing events of a person ventilated with a respiratory gas, comprising an electronic computing and storage unit configured to receive a signal corresponding to a ventilation pressure and/or a respiratory flow and/or a tidal volume of the respiratory gas delivered to the person and, during a predetermined analysis duration, to detect a curve of the signal by a curve analyzer. A ventilator for ventilating a person with a respiratory gas, which ventilator comprises the breath analyzer and a method for detecting breathing events of a person ventilated with a respiratory gas is also described.

Various embodiments of a system and associated method for detection of COVID-19 and other respiratory diseases through classification of audio samples are disclosed herein. The system utilizes features directly extracted from the coughing audio and develops automated diagnostic tools for COVID-19. In particular, the present application discusses a novel modification of a deep neural network architecture by using log-mel spectrograms of the audio excerpts and by optimizing a combination of binary cross-entropy and focal loss parameters. One embodiment of the system achieved an average validation AUC of 82.23% and a test AUC of 78.3% at a sensitivity of 80.49%.

There is provided a respiratory monitoring device (100) comprising one or more respiratory-related sensors (110) and a first circuit board comprising a controller. The one or more respiratory-related sensors are separated from and in communication the first circuit board. There is also provided a respiratory monitoring device comprising a controller, one or more respiratory-related sensor and an input means (114). The input means is arranged to trigger the controller to suspend sensing by at least one of the one or more respiratory-related sensors for one or more predetermined time periods. There is also provided a respiratory monitoring device having a housing comprising a front surface (102) at which one or more respiratory-related sensors are arranged, and a back surface (120), wherein the front surface is arranged to indicate an intended orientation to a user of the respiratory monitoring device.

A sensor strap system according to an embodiment of the present disclosure includes: a sensor capable of detecting physical or physiological activities or conditions of a target subject; a top strap extending along a top surface of a bed, the top strap configured to secure the sensor to the top surface of the bed; and a circumferential strap extending about a circumference of the bed and coupled with the top strap.

Methods and systems for temperature screening using a mobile device. In one example, a mobile temperature screening system may comprise a mobile device including a display, a memory, a processor, a thermal imaging camera, a visible light imaging camera, and a wireless communication capability. The processor may be configured to obtain a thermal image of a person and a visible light image of the person, determine a body temperature of the person based at least in part on the thermal image, and classify the person as having a normal body temperature when the body temperature of the person is below a threshold temperature. When the body temperature of the person exceeds the threshold temperature the processor may be configured to classify the person as having an elevated body temperature, generate a visual alert, and transmit the thermal image, the visible light image and the classification to a remote device.

An automated health check device and methods, the device comprising: at least one imaging sensor configured for capturing at least one image of at least an area confined by a window of the vehicle; at least one vital signs sensor configured for measuring a health parameter of a passenger at the area confined by the window; and at least one processor configured for: acquiring and analyzing the at least one image to determine location of the window; determining based on the determined location of the window a location of the passenger; determining the at least one vital signs sensor being oriented to a predetermined point of view in relation to the location of the passenger determined; and obtaining a measurement of the health parameter of the passenger from the at least one vital signs sensor.

A method of cough detection in a headset, the method comprising: receiving a first signal from an external transducer of the headset; receiving a second signal from an in-ear transducer of the headset; and detecting a cough of a user of the headset based on the first and second signals.

The present system (10) comprises a subject interface (22), a segmenter (12), a loosener (14), sensors (18), and computer processors (28). The segmenter is configured to selectively control gas flow through the subject interface to provide high amplitude pressure oscillations (44) during exhalation such that the high amplitude pressure oscillations aid cough productivity in the subject. The loosener controls gas flow through the subject interface to provide low amplitude pressure oscillations (43, 63) during inhalation (48, 68) and exhalation (49) such that the low amplitude pressure oscillations loosen respiratory secretions. The computer processors detect trigger events based on the output signals such that the one or more trigger events include a loosening trigger event and a segmenting trigger event (66); and responsive to detecting the loosening trigger event, control the loosener to provide the low amplitude pressure oscillations, and, responsive to detecting the segmenting trigger event, control the segmenter to provide the high amplitude pressure oscillations.