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.

The present invention provides a device for non-invasive monitoring and/or detection of diabetes in a subject based on detection of volatile organic compounds (VOCs) in the exhaled breath of a subject. The device comprises a functionalized carbon nanotube-based array sensor which can reversibly bind VOCs, which alters the electrical conductivity of the sensor array, which can be interpreted to monitor and/or diagnose diabetes.

Provided are computer-implemented methods and systems for generating and/or utilizing data analysis algorithm(s) for predicting and/or detecting a clinical condition related to insertion of a medical instrument toward a target in a body of a patient based, inter alia, on data related to an automated medical device and/or to operation thereof.

Provided are computer-implemented methods and systems for generating and/or utilizing data analysis algorithm(s) for predicting and/or detecting a clinical condition related to insertion of a medical instrument toward a target in a body of a patient based, inter alia, on data related to an automated medical device and/or to operation thereof.

The present disclosure relates to a difficult airway evaluation method and device based on a machine learning voice technology. The method includes the following steps: acquiring voice data of a patient; carrying out feature extraction on the voice data, obtaining a pitch period of pronunciations, and acquiring a voiced sound feature and unvoiced sound features based on the pitch period of pronunciations; and constructing a difficult airway evaluation classifier based on the machine learning voice technology, analyzing the received voiced sound feature and unvoiced sound features by the trained difficult airway evaluation classifier, and carrying out scoring on the severity of a difficult airway to obtain an evaluation result of the difficult airway.

Disclosed are a drunk driving prevention system and a drunk driving prevention method using the system that includes a sensor module measuring the alcohol content in exhaled breath of a driver at the time of breath-checking of the driver and a control module configured to check an intoxication state of the driver based on the alcohol content measured by the sensor module to determine whether or not a breath-checking is complete and block an engine start when the breath-checking fails, wherein the control module includes a bypass control unit switching a vehicle into a drivable state when the breath-checking fails.

Disclosed is a system for preventing drunk driving of a vehicle, the system including: an input unit through which a transfer intention to transfer a control privilege of a vehicle from a registered driver to a passenger is input; a sobriety determination unit configured to determine a current driver's inebriation state through a breathalyzer provided in the vehicle when the transfer intention is input through the input unit; a driver verification unit configured to identify personal information of the current driver seated on a driver's seat; and a control unit configured to transfer the control privilege of the vehicle to the passenger when the passenger is measured as being able to drive by the sobriety determination unit and the passenger and the current driver are identified to be the same by the driver verification unit.

An information display method displays brain activity information calculated using a biological signal measured from a living body so as to be superimposed on a morphological image including a plurality of sectional images. The information display method includes: acquiring mask information representing an area belonging to a brain in the morphological image; and detecting one or more extremal value positions with spatial extremal values in the brain activity information based on the mask information. A sectional image corresponding to the one or more extremal value positions is acquired from the morphological image. A brain activity distribution corresponding to the sectional image is acquired. The brain activity distribution is displayed so as to be superimposed on the sectional image.

The method and system for monitoring cough comprises receiving audio signals or audio recordings, where said signals or audio recordings comprises one or more of silent segments, cough sound segments, speech segments and extraneous noise. The processing of said received sound signals or sound recordings comprise one or more of removing one or more speech components from speech segments to render the speech unintelligible and clipping said silent segments, wherein one or more speech components include vowel sounds. Further processing of said received audio signals or audio recordings further comprises compressing said audio signals or audio recordings. In the alternative, processing of audio signals or audio recordings comprises compressing a resultant signal after said removal of one or more speech components and/or clipping of silent segments from said audio signals.

Various systems, devices, components, and methods are disclosed for measuring the concentration of an analyte, such as acetone, in a breath sample. The disclosed devices include a breath sample analysis device having a mouthpiece configured to facilitate engagement with a user's mouth to receive a breath sample. The disclosed devices also include a breath sample capture cartridge containing an interactant that extracts the analyte from a breath sample passed through the cartridge. Also disclosed are devices for routing the breath sample through the cartridge during exhalation, and for analyzing a reaction in the cartridge to measure a concentration of the analyte.