Aspects relate to methods and systems for detection of atelectasis in flight. An exemplary system includes at least an exhalation sensor configured to detect at least an exhalation parameter of a flight crew member, at least an inhalation sensor configured to detect at least an inhalation parameter of the flight crew member, at least an environmental sensor configured to detect at least an environmental parameter of a cabin within which the flight crew member is housed, and a computing device configured to determine a likelihood of atelectasis for the flight crew member as a function of the at least an exhalation parameter, the at least an inhalation parameter, and the at least an environmental parameter and generate a dosing schedule as a function of the likelihood of atelectasis.

A system for monitoring core body movement comprises a sensor device for collecting a data set representing a plurality of core body movements over time from a monitoring device; a processor for determining a plurality of risk scores from the data set; and an output device for indicating the risk scores.

Embodiments herein include testing articles to assess hydration of a test subject. The testing articles can include a carrier portion having a porous medium through which a fluid of the test subject moves. The carrier portion can include a first end and a second end opposite the first end. The testing articles can include a first chemical composition disposed in the porous medium that reacts with chloride ions to produce a first color change. The testing articles can include a wick that is in direct contact with the first end of the carrier portion to allow the transfer of the fluid from the wick to the carrier portion. The testing articles can include a fill indicator element in direct contact with the second end of the carrier portion to allow the transfer of the fluid from the carrier portion to the fill indicator element. Other embodiments are also included herein.

[Object] It is an object to provide a determination device capable of determining the health risk of a laborer due to the labor load from the measured biological information only by measuring the biological information including the heart rate of the laborer. [Solution to the problems] In order to solve the above problems, the determination device 1 according to the present invention includes a biological information acquisition unit 3 that acquires biological information including a heart rate of a laborer Wi, a model formula storage unit 4 that stores a model formula for discriminating a health risk due to a labor load based on the biological information, and a determination unit 5 that determines the health risk of the laborer Wi based on the biological information of the laborer Wi and the model formula stored in the model formula storage unit 4.

The disclosed technology provides a system and a computer implemented method for crisis state detection and intervention of a person or group of persons, the method comprising: providing a computer system designed to detect and intervene non-normal, elevated crisis operating states; using one or more sensors that ascertains a crisis state via physical, behavioral, or cognitive indicators; deducing, with computational hardware, the operational state of a user or users from one or more sensors; and administering an immediate, dual intervention of a sensory form to de-escalate the crisis operating state of a person or group of persons.

The falling risk determination device includes the acquisition unit, the calculation unit, the measurement unit, and the determination unit. The acquisition unit acquires time-series data related to gravity center oscillation of the worker from a sensor unit provided at a leg portion of a high-place work tool on which the worker rides. The calculation unit calculates an evaluation value related to the gravity center oscillation from the time-series data. The measurement unit carries out a Stroop test on the worker in parallel with processing of acquiring time-series data, and measures the fatigue level of the worker using the result of the Stroop test. The determination unit determines that the falling risk is high in a case where the evaluation value is larger than an average value of past evaluation values corresponding to the fatigue level.

A computer-implemented method includes: receiving, by a computing device, data which is associated with a user; generating, by the computing device, a personalized recommendation for the data by at least one artificial intelligence (AI) application; training, by the computing device, a machine learning (ML) model using the data from the at least one AI application; and generating, by the computing device, a trained fitness model for predicting safety issues based on the trained ML model using the data from the at least one AI application.

The present patent of invention belongs to the research sector in applied mass spectrometry, and refers, more specifically, to an equipment and method that have the purpose of evaluating and measuring the balance of an individual and determining the index of fatigue and sleepiness, and to send and store the information through the WEB, internet app or on the computer itself. The equipment consists of a box (1) equipped with an electronic display (2), on/off button (3), input (4) for USB connection, attached to a base plate (5) and elastic straps (6), and it is operated via an app, with Bluetooth communication.

In one embodiment, a method comprising: (a) receiving a set of physiological data associated with at least one health condition of an animal subject; (b) receiving a set of environmental data associated with one or more environment conditions to which the subject is or has been exposed; (c) determining a set of operating parameters for at least one environmental device based at least partially on at least a portion of the set of physiological data and at least a portion of the set of environmental data; and (d) transmitting the set of operating parameters to the at least one environmental device to at least partially control at least one controlled environmental condition to which the subject is exposed to thereby at partially control the at least one health condition.

A method for analyzing the biomechanical activity of a human subject and the exposure to a biomechanical risk factor in a context of physical activity, which comprises collecting signals from sensors of one or more muscles of the subject, collecting signals representing the movement of the subject, and processing these signals to extract signals representative of the vibratory behavior of the muscle or muscles of the subject. This method also comprises detecting a drift of the vibratory signals in relation to a frame of reference of the vibratory behavior of the muscle or muscles in the context of physical activity, and predicting a physiological break time necessary for the subject's muscles to recover their reference vibratory behavior.