Abstract: A system and method for monitoring sleep parameters, the method including during a model training phase: receiving millimeter-wave reflection radar signals from reference subjects, extracting in-phase and quadrature components, deriving displacement signals reflecting body micromovements from cardiac and pulmonary activity, segmenting displacement signals into reference segments, forming a training dataset with segments labeled with measured sleep data, and applying machine learning to generate a sleep parameters estimation model; and during a subject monitoring phase: receiving millimeter-wave reflection radar signals from a monitored subject, extracting signal components, deriving displacement signals reflecting body micromovements, segmenting into monitored segments, applying the estimation model to estimate sleep parameters, determining overall sleep duration, and determining a sleep parameters index based on estimated parameters and duration.

Abstract: A hearing aid and related systems and methods are disclosed. In one implementation, a system may comprise a microphone and a processor. The processor may be configured to receive an original audio signal representative of sounds captured by the microphone; determine that the original audio signal includes a voice of the user; process the original audio signal according to a first processing scheme to generate a first processed audio signal; transmit the first processed audio signal to a hearing interface device after a first time delay associated with the first processing scheme; determine that the original audio signal includes an additional sound; process the original audio signal according to a second processing scheme to generate a second processed audio signal; and transmit the second processed audio signal to the hearing interface device after a second time delay associated with the second processing scheme.