Eyewear apparatus includes dry electrophysiological electrodes and, optionally, other physiological and/or environmental sensors to measure signals such as EOG and ECG from the head of a subject. Methods of use of such apparatus to provide fitness, health, or other measured or derived, estimated, or predicted metrics are also disclosed.

Aspects of the present disclosure provide methods and apparatuses for estimating a biometric parameter using multiple sensors. As described herein, multiple sensors are strategically used to output with increased confidence a biometric parameter. Multiple sensors are strategically used to save power while determining an accurate biometric estimation. Additionally, multiple sensors are used to detect and categorize a sleep apnea event.

This document discusses, among other things, systems and methods to receive physiologic information from a patient during different first and second pacing periods having respective, different first and second atrioventricular (AV) delays, determine first and second physiologic parameters using respective received physiologic information from the first and second pacing periods, and adjust the first AV delay using the determined first and second physiologic parameters, wherein the second AV delay is longer than the first AV delay.

This document discusses, among other things, systems and methods to receive physiologic information from a patient during different first and second pacing periods having respective, different first and second atrioventricular (AV) delays, determine first and second physiologic parameters using respective received physiologic information from the first and second pacing periods, and adjust the first AV delay using the determined first and second physiologic parameters, wherein the second AV delay is longer than the first AV delay.

Aspects of the present disclosure relate to a stethoscope that includes a chestpiece having an inside surface and an outside surface. A portion of the inside surface forms a bell and a portion of the outside surface is electrically conductive. The stethoscope includes a plurality of sensors and a speaker that communicatively coupled to a first sensor. The stethoscope also includes a controller circuit that is configured to receive a plurality of sensor readings from the plurality of sensors. The controller circuit can determine a noise profile based on the plurality of sensor readings and a first volume output through the speaker, determine whether a noise profile threshold is met by the noise profile; and reduce volume output through the speaker from the first volume to a second volume based on the noise profile threshold being met.

A method for analyzing an audio respiratory signal comprises capturing the audio respiratory signal from a subject using a microphone and partitioning the audio respiratory signal into a plurality of overlapping frames. The method further comprises calculating a fourier transform for each frame and determining a magnitude spectrum using the fourier transform of the plurality of overlapping frames. Additionally, the method comprises extracting a spectrogram using the magnitude spectrum and analyzing the spectrogram to determine characteristics pertaining to wheeze sounds in the audio respiratory signal.

A program causes a computer to execute a process of acquiring motion information relating to motion of respiratory muscles or accessory respiratory muscles from a detection sensor that detects the motion information and action potential information relating to the respiratory muscles or the accessory respiratory muscles from an electromyogram sensor that acquires the action potential information, a process of detecting an abnormality in a respiratory system disease on the basis of the acquired motion information and action potential information, and a process of outputting information on the abnormality when the abnormality is detected.

An artificial intelligence-based system and method for scalable screening of individuals for respiratory infection, such as COVID-19. The system is trained to distinguish distinct latent features of cough sounds produced by a COVID-19 infected person from cough sounds produced by patients suffering from any other respiratory infection or involuntary cough sounds produced by a healthy person. Cough sound samples from individuals can be remotely collected and evaluated by the system for likelihood of the COVID-19 infection. Additionally, images of affected body parts, biomarkers, metadata, and other respiratory sound samples can also be used for screening.

A monitoring device has microphones, an ADC; a digital radio; and a processor with firmware. The firmware includes code for digitizing audio from the microphones into time-domain audio, performing FFT to provide frequency-domain audio, running a first neural network on time domain and frequency-domain audio to extract features, executing a classifier on the features to identify candidate events, and using the digital radio to upload candidate events and features. A pressure sensor awakens the processor from a low-power state. In particular embodiments, the first neural network is an embedded Gated Recurrent Unit having weights trained to extract features of use in the classifier; and candidate events include normal inhalation and exhalation breathing sounds, crackles, wheezes, coughs, snoring, gasping, choking, and speech sounds and in some embodiments heart sounds. A method of monitoring breathing during sleep includes attaching the device to, or embedding the device within, a pillow.

A user-wearable sensor device may be configured to be directly or indirectly secured to a user or to an article worn by the user. The user-wearable sensor device may include at least one sensor configured to collect sensor data associated with an orientation of the user, a display unit including at least one LED or other visual indicator, a battery configured to provide power to at least the display unit, and a control system. The control system may be configured to determine the orientation of the user based on sensor data collected by the at least one sensor, maintain the display unit in a deactivated state in the absence of a defined activation input, detect a defined activation input, activate the deactivated display unit in response to detecting the defined activation input, and control the activated display unit based on the determined orientation of the user.