Embodiments disclosed herein relate to devices and methods for monitoring one or more physiological parameters of a subject. In an embodiment, a wearable device comprises a substrate configured to attached to a subject's skin. The substrate comprises a middle portion arranged between two end portions, wherein the middle portion is more flexible than at least one of the end portions. The wearable device also comprises a physiological sensor arranged on the middle portion. The physiological sensor is configured to sense a physiological signal of the subject when the wearable device is attached to the subject's skin. And, the wearable device comprises one or more electrical components arranged on at least one of the end portions, wherein at least one of the one or more electrical components is coupled to the physiological sensor.

To enable accurately determining, based on a sound emitted by an inspection target, a classification of the sound. A control apparatus (1) according to an embodiment includes a classification information acquiring unit (13) that acquires classification information of a sound, a sound acquiring unit (11) that acquires a sound data including information of the sound, a storage unit (20) that stores definition data (25), an extraction unit (12) that extracts a plurality of features of the sound data, and a model construction unit (15) that constructs a learned model where machine learning, based on the plurality of features of the sound data and the classification information, on a correlation between the plurality of features and the classification of the sound is performed.

Disclosed herein are systems, devices, and methods for evaluating or analyzing complex audio signals using multi-dimensional statistical signatures and machine learning algorithms. One advantage of the present disclosure is the ability for remote evaluation of respiratory tract health using speech analysis. The need for remote collection capabilities that can sensitively and reliably characterize respiratory tract function is particularly pertinent in view of the recent Covid-19 pandemic, which may adversely affect the health of individuals who could already be experiencing health problems with respiratory tract function.

Disclosed is an apparatus for recording respiratory rate of a subject. The apparatus comprises a first component to be arranged on the subject and away from nostrils of the subject, the first component comprises a battery, optionally electronics for the sensor, and electronics for transmitting respiration rate data; and a second component for being arranged in an area of the nose of the subject, the second component comprising at least one sensor for recording respiratory rate. Disclosed is also a method for recording respiratory rate of a subject with such an apparatus. The method comprises arranging the second component in an area of the nose of the subject; arranging the first component on the subject and no further than 30 centimeters from the second component; recording respiratory rate data with the second component, and sending the respiratory rate data to the first component; and sending the respiratory rate data from the first component to a monitor or a hub.

There is provided a device for measuring fatigue of a person, the device comprising a frame configured to be worn within the mouth of the person, a microphone mounted within the frame and configured to measure sound data, and a cavity located within the frame and adjacent to the microphone, wherein the cavity does not communicate with the environment surrounding the frame. There is also provided a computer-implemented method for determining a fatigue metric representing a level of physical fatigue of a person

In examples, there is a method comprising receiving an esophageal gas sample at a nitric oxide sensor, the nitric oxide sensor generating a signal indicative of the amount of nitric oxide in the esophageal gas sample, the nitric oxide sensor outputting the signal, and, based on the signal, determining the amount of nitric oxide in the esophageal gas sample.

A device for determining measurement values describing the function of the lungs or the respiratory system of a patient includes a mouthpiece including a tube for introducing respiratory air and for sucking in air, and a gas measurement space. At least one of the following gas sensors is arranged in the gas measurement space: nitrogen monoxide sensor, carbon dioxide sensor, oxygen sensor, carbon monoxide sensor, multi-gas sensor, sensor for volatile organic compounds, alkane sensor, infrared sensor, fiber optic sensor, resistance sensor, and semiconductor sensor. The gas measurement chamber is separated by a closable opening into a first gas measurement chamber and a second gas measurement chamber, the second gas measurement chamber being closed or closable. The closable opening opens a flow path from the first gas measurement chamber into the second gas measurement chamber. A gas sensor is arranged in the second gas measurement chamber.

Devices and methods for monitoring physiologic parameters are described where an airway device, in one embodiment, may comprise a mouthpiece section and an opening section defining one or more airway lumens therethrough with a first sensor in fluid communication with the one or more airway lumens and a second sensor positioned upon a hand-piece for contact against a portion of the user. The first sensor may be configured to detect an airway pressure when a user inhales or exhales through the one or more airway lumens, and the second sensor may be configured to detect a physiological signal from the user. Additionally, a controller may be in communication with the first and second sensors where the controller is programmed to correlate pressure oscillations in the airway pressure with heartbeats.

Systems, apparatus, and methods for measuring heart rate are disclosed. An example system includes a transmitter to emit electromagnetic waves; a first sensor to output signals representative of the electromagnetic waves reflected by a subject; a second sensor to generate image data, the image data including data corresponding to a chest of the subject; machine readable instructions; and processor circuitry to at least one of instantiate or execute the machine readable instructions to generate heartbeat data by cancelling harmonics associated with respiration by the subject from data corresponding to the output signals of the first sensor based on the image data, and determine a heart rate for the subject based on the heartbeat data.

In one aspect, a computer-implemented method includes receiving a signal corresponding to impedance across a patient's chest cavity; filtering the signal using one or more filters that reduce noise and center the signal around a zero baseline; adjusting an amplitude of the filtered signal based on a threshold value; separating the amplitude-adjusted signal into component signals, where each of the component signals represents a frequency-limited band; detecting a fractional phase transition of a component signal of the component signals; selecting a dominant component signal from the component signals based on amplitudes of the component signals at a time corresponding to the detected fractional phase transition; determining a frequency of the dominant component signal at the time corresponding to the detected fractional phase transition; and determining a respiratory rate of the patient based on the determined frequency.