A sleepiness estimating device including an auxiliary information acquirer that acquires auxiliary information including at least one of five-sense information perceived by a person or emotion information indicating an emotion of the person; and a sleepiness estimator that estimates a sleepiness of the person based on the auxiliary information.

A method for uterine activity monitoring may include: acquiring a plurality of signals from a plurality of sensors during uterine activity; processing the plurality of signals to extract a plurality of uterine electrical activity characteristics; analyzing the plurality of uterine electrical activity characteristics; and classifying the uterine activity as one of: a preterm labor contraction, a labor contraction, a Braxton-Hicks contraction, and a state of no contraction. A method of assessing over time a pre-term birth risk of a pregnant female may include: calculating a baseline pre-term birth risk score based on a user input; acquiring, over time, a signal from a sensor; analyzing the signal to extract a parameter of interest, such that the parameter of interest comprises a physiological parameter; and calculating an instant pre-term birth risk score based, at least in part, on the parameter of interest and the user input.

Methods and systems are provided for detecting a mental health condition. Structured and unstructured information is analyzed using natural language processing to extract information including clinical data values and medical concepts pertaining to a user. Reference medical information is evaluated using natural language processing to correlate medical data with mental health conditions. A classification for a mental health condition of the user is determined using a machine learning model and based on the extracted information and correlations, wherein the extracted information includes blood analysis for the user. The user is assigned to a segment of users based on the extracted information. A treatment for the mental health condition of the user is indicated based on the classification and the assigned segment of users.

The invention relates to methods and systems for determining the intention of a subject to perform a voluntary action based on the analysis of the subject's respiratory phases and neuroelectrical signals.

Systems and associated methods are provided for monitoring a user while operating a computing device and providing active feedback to said user regarding health and safety best practices associated with operating said computing device. The methods comprise obtaining user biometric data; converting said biometric data into actionable instances of health and safety user device operation use cases; and interacting with the user based on said actionable instances in order to improve or remedy any deviations from recommended health and safety user device operation practices.

A first value for each of a plurality of parameters is received, each of the first values being associated with a user and a first day. A second value for each of the plurality of parameters is received, each of the second values being associated with the user and a second day that is subsequent to the first day. For each of the plurality of parameters, a trend indication is determined, the trend indication being based on the first values, the second values, and a first time period. A base weight value for each of the plurality of parameters is determined, the base weight value being based on the first time period and the determined trend indication associated with the one of the plurality of parameters. A mood score is determined, based on the base weight value for each of the plurality of parameters.

A patient care method through artificial intelligence-based monitoring in accordance with one example of the present disclosure comprises steps of: obtaining image information relating a user by a first collecting portion, obtaining speech information relating to the user by a second collecting portion and obtaining biometrics information relating to the user by a third collecting portion (Step 1); representing at least a part of a plurality of information obtained from the first collecting portion, the second collecting portion and the third collecting portion, through a display portion of a user table (Step 2); determining health condition of the user, based on a part of the plurality of information obtained from the first collecting portion, the second collecting portion and the third collecting portion by a server (Step 3); controlling the display portion of the user table to represent a first information automatically generated based on the determined heath condition by the server (Step 4), wherein the first information is converted in real time based on user's feedback on the first information and represents a change in the determined health condition on the display portion.

A system includes: a light source that emits pulsed light that illuminates a user's head portion; a photodetector that detects at least part of pulsed light returning from the head portion and that outputs one or more signals corresponding to an intensity of the at least part; electrical circuitry; and a memory that stores an emotion model indicating a relationship between the one or more signals and emotions. Based on a change in the one or more signals, the electrical circuitry selects an emotion by referring to the model. The one or more signals include a first signal corresponding to an intensity of first part of the reflection pulsed light and a second signal corresponding to an intensity of second part of the reflection pulsed light. The first part includes part before a falling period is started; and the second part includes at least part in the falling period.

The invention relates to an interactive system (1) with a user (U) occupying a motor vehicle (100) comprising an interface (3) and an operating system for executing an application. According to the invention, the interactive system (1) comprises a measuring device (5) comprising at least one sensor that is configured to acquire at least one physiological parameter of the user (U), and an embedded processing unit (7). The processing unit (7) comprises an interpretation module that is configured to receive the physiological parameter and to define, on the basis of the physiological parameter, a datum representative of the physiological or emotional state of the user (U), and an analysis module that is configured to compare data representative of the physiological or emotional state of the user (U) before and during the execution of an application for managing a remediation exercise, and to adjust at least one parameter of the remediation exercise according to the results of the comparison. The invention also relates to an interaction method implemented at least partly by such an interactive system.

Improved assessment of brain injuries, and improved brain injury management, is achieved using a combination of impact-related data derived from instrumented mouthguard devices, human function performance testing, and biomarkers derived from biological fluid (such as saliva and/or blood). The human function performance testing may include brain function performance testing, and/or other forms of human function performance testing. This involves combining a data-driven understanding of a head impact event (based on data collected via an instrumented mouthguard device) with a data-driven understanding of human function performance following that head impact event. The biomarkers may include salivary mRNA and/or ncRNA, and/or blood proteins (for example via a FDA-approved Brain Trauma Indicator test).