A method and system for monitoring a user's intoxication including receiving a set of signals, derived from a set of samples collected from the user at a set of time points; providing a sobriety task to the user proximal to a time point of the set of time points; generating a performance dataset characterizing performance of the sobriety task by the user; receiving a supplementary dataset characterizing a demographic profile of the user and/or a physiological state of the user; determining a set of values of an intoxication metric, derived from the set of signals; generating a predicted temporal profile of the intoxication metric for the user based upon the set of values, the set of time points, and the supplementary dataset; generating an analysis of the user's sobriety based upon the performance dataset and the predicted temporal profile; and providing a notification to the user based upon the analysis.

A heartbeat measurement device includes a transmitter configured to transmit a transmission signal from a transmission antenna to a person to be measured, a receiver configured to receive a signal reflected from the person to be measured as a reception signal using a reception antenna, and an orthogonal detection circuit configured to generate an I signal that is an in-phase component of the transmission signal and the reception signal and a Q signal that is a quadrature component of the transmission signal and the reception signal. The heartbeat measurement device further includes a Fourier transform unit configured to calculate a spectrum in positive and negative frequency domains on the basis of the I signal and the Q signal and a signal processing unit configured to compare positive and negative frequency components in the spectrum to extract a heartbeat component.

A method for preventing and detecting a fall of a user and implementing a system including sensors and alarm, a pair of eyeglasses with hinged stems including rims for supporting glasses, worn by the user. The sensors are set in the hinged stems and the rims of the eyeglasses. The sensors include a triaxial accelerometer, an IR transmitter and an IR receiver of infra-red light both directed to the cornea of the user, and a barometric sensor. The triaxial accelerometer signal is acquired and processed to derive a walking pace parameter, a sit to stand parameter, a head posture parameter and an acceleration magnitude over the three axes. A composite index is computed based on the walking pace, the sit to stand and the head posture parameters. The alarm is generated if the first composite index exceeds a threshold.

Provided is a biological information measuring device with wearability for satisfying the measurement precision needed in a home medical support system. Also provided is a biological information measuring device with wearability for enhancing the QOL of a user. The present invention provides a biological information measuring device provided with a sensor and an adhesive member having an opening which surrounds the sensor. A measuring surface of the sensor is exposed. The sensor may be disposed so as to be separated from the adhesive member. The sensor includes a reflection-type pulse oximeter, and the thickness of the adhesive member from the surface of the biological information measuring device body on which the adhesive member is disposed may be greater than the thickness from the surface of the biological information measuring device body to an end part of the reflection-type pulse oximeter.

A distracted driver detection device for use in a vehicle includes a processor, a video camera, and an accelerometer. The processor is configured to compute an eye open ratio (EOR) and a mouth open ratio (MOR). The processor is configured to provide an audio alert signal to an audio alert component and provide a visual alert signal to a visual alert component when the EOR is less than an EOR threshold for a prescribed EOR assessment time, when the MOR is greater than the MOR threshold for a prescribed MOR assessment time, or when the estimate of the acceleration is greater than an acceleration threshold. The EOR and MOR are calculated from facial landmarks that are generated by a Histogram of Oriented Gradients (HOG) algorithm implemented by the processor.

Transportation systems have artificial intelligence including neural networks for recognition and classification of objects and behavior including natural language processing and computer vision systems. The transportation systems involve sets of complex chemical processes, mechanical systems, and interactions with behaviors of operators. System-level interactions and behaviors are classified, predicted and optimized using neural networks and other artificial intelligence systems through selective deployment, as well as hybrids and combinations of the artificial intelligence systems, neural networks, expert systems, cognitive systems, genetic algorithms and deep learning.

Facial skin analysis methods and systems for improving facial skin conditions using vehicle cameras of vehicles having onboard communication modules. Each vehicle is equipped to analyze the facial skin images over time periods and compare the images to determine skin conditions. Based on the facial skin conditions, a treatment recommendation can be transmitted to a seat occupant. Each vehicle is operatively connected to a facial skin analysis application in a data center. The facial skin analysis application includes a registration module which registers each vehicle. Additionally, a vehicle user may register with the facial skin analysis application to have his/her facial skin analyzed when travelling in any of the plurality of vehicles. The facial skin analysis application is operatively connected to a skin data AI analytics module and data lake and searches a plurality of databases for information related to the facial skin conditions to improve the treatment recommendation.

A physical data acquirer included in an operator device acquires at least one of health data indicating a health condition of an operator or posture data indicating a posture of the operator. A distance determiner included in an information processing apparatus determines whether a distance between the operator and a machine is below a predetermined threshold. A corrector corrects an avoidability definition value defined as a value indicating a possibility of the operator avoiding a hazard caused by the machine in accordance with at least one of the health condition of the operator indicated by the health data acquired from the operator device or the posture of the operator indicated by the posture data acquired from the operator device. A risk value calculator calculates a risk value by substituting the corrected avoidability definition value and a riskiness definition value into a calculation function for the risk value.

Various implementations include systems and approaches for determining user oxygen saturation level, and in certain cases, performing an action based on that determination. Particular aspects include a monitoring system having at least one pressure sensor for detecting air pressure in an environment proximate the at least one pressure sensor, and a processor coupled with the at least one pressure sensor, where the processor is programmed to receive air pressure data from the pressure sensor about the environment, determine an oxygen saturation level for a user in the environment based on the air pressure data, and in response to determining the oxygen saturation level of the user has met one or more predetermined conditions, perform an action.

-- A method including acquisition of useful data during an experiment phase, the useful data being physiological data obtained by means of sensor(s) and each corresponding to an input data of the monitoring application, acquisition of declarative data of the individual, in real-time during the experimental phase and/or in differed time before and/or after the experimental phase, merging of useful data and declarative data in order to calculate a true level of fatigue, labeling the useful data with the calculated true level of fatigue, and storing the labeled useful data in the learning database.