An abnormal physical condition determination system includes: an extraction unit that extracts a plurality of feature quantities indicating a condition of a target person from an image of the target person; an accumulation unit that accumulates the plurality of feature quantities as time series data; a calculation unit that calculates a relationship between each feature quantity from the plurality of feature quantities accumulated in the accumulation unit; and a determination unit that determines an abnormal physical condition of the target person on the basis of the relationship. According to such an abnormal physical condition determination system, it is possible to appropriately determine the abnormal physical condition of the target person.

In various examples, systems and methods are disclosed that accurately identify driver and passenger in-cabin activities that may indicate a biomechanical distraction that prevents a driver from being fully engaged in driving a vehicle. In particular, image data representative of an image of an occupant of a vehicle may be applied to one or more deep neural networks (DNNs). Using the DNNs, data indicative of key point locations corresponding to the occupant may be computed, a shape and/or a volume corresponding to the occupant may be reconstructed, a position and size of the occupant may be estimated, hand gesture activities may be classified, and/or body postures or poses may be classified. These determinations may be used to determine operations or settings for the vehicle to increase not only the safety of the occupants, but also of surrounding motorists, bicyclists, and pedestrians.

A method for signaling a measured and/or a predetermined vital parameter and/or vital parameter pattern for a vehicle occupant in a vehicle involves arranging a functional element set up to have a visual and/or audible and/or haptic effect on at least one vehicle occupant, and a measured and/or a predetermined vital parameter and/or vital parameter pattern is signaled non-verbally by the functional element.

A system and method for classifying a type of interaction between a human user and a mobile communication device within a defined volume, based on multiple sensors. The method may include: determining a position of the mobile communication device relative to a frame of reference of the defined volume, based on: angle of arrival, time of flight, or received intensity of radio frequency (RF) signals transmitted by the mobile communication device and received by a phone location unit located within the defined volume configured to wirelessly communicate with the mobile communication device; obtaining at least one sensor measurement related to the mobile communication device from various non-RF sensors; repeating the obtaining, to yield a time series of sensor readings; and using a computer processor to classify the type of interaction into one of many predefined types of interactions, based on the position and the time series of sensor readings.

An embodiment method of controlling a moving object includes checking profile information of a user who rides in the moving object or status information of the user, checking a degree of risk based on the profile information or the status information of the user, setting an operation mode of the moving object based on the degree of risk, and controlling movement of the moving object based on the operation mode.

In accordance with one embodiment of the present disclosure, a method includes generating a plurality of icons, wherein each icon has a target frequency unique from each other, receiving brain activity data based on an epoch, generating a reference signal based on the epoch, calculating correlation coefficients between the brain activity data and the reference signal, wherein the correlation coefficients are calculated in a window that is within ±0.5 Hz of the target frequencies, including endpoints, determining a confidence score based on the correlation coefficients and the epoch, and determining a selected icon among the plurality of icons based on the correlation coefficients in response to the confidence score surpassing a threshold confidence score.

An interactive system (1) for interacting with a user is disclosed. The interactive system (1) includes at least one interface (3), a measuring device (5), and a processing unit (7) comprising an interpretation module for receiving a physiological parameter obtained by the measuring device (5) and for defining, based on the physiological parameter, a datum representative of the physiological state of the user (U). The processing unit (7) comprises a data communication module for communicating data with a server (11) storing a library of applications, a data processing module for selecting an application on the basis of the datum representative of the physiological state, an information module for notifying the user (U) of the selected application, and detecting a validation action from the user (U) validating the notified application, and a download module for downloading the validated application.

Embodiments of the present disclosure sets forth a computer-implemented method comprising receiving, from at least one sensor, sensor data associated with an environment, computing, based on the sensor data, a cognitive load associated with a user within the environment, computing, based on the sensor data, an affective load associated with an emotional state of the user, determining, based on both the cognitive load at the affective load, an affective-cognitive load, determining, based on the affective-cognitive load, a user readiness state associated with the user, and causing one or more actions to occur based on the user readiness state.

A method evaluates a degree of fatigue of a vehicle occupant in a vehicle. A number of first fatigue indicators is provided which are determined according to computation rules from a plurality of first sensor values and each represent a degree of fatigue of the vehicle occupant. The first sensor values represent measured values of the vehicle and/or measured values relating to a current journey. A first metadata record is associated with each of the number of first fatigue indicators, wherein the first metadata records represent information about the characteristics of the sensors. The first sensor values are processed in the respective first fatigue indicators. A number of second fatigue indicators is provided which are determined according to computation rules from one or more second sensor values and each represent a degree of fatigue of the vehicle occupant. The second sensor values represent physiological and/or physical parameters of the vehicle occupants. A second metadata record is associated with each of the number of second fatigue indicators. The second metadata records represent information about the characteristics of the sensors. The second sensor values are processed in the respective second fatigue indicators. An overall fatigue indicator is determined which represents the degree of fatigue of the vehicle occupant by weighting the number of first fatigue indicators and the number of second fatigue indicators. The fatigue indicators are weighted according to the information about the characteristics of the sensors contained in the first metadata record and the second metadata record.

A vehicle may have actuators, including a drive device with a drive motor that can act on a drive wheel, a brake device with a brake that can act on a drive wheel, and/or a steering device with a steering sensor by way of which the steering angle of a wheel is adjustable, a vehicle movement controller, and a setpoint value input means, a setpoint value processing means for detecting setpoint value settings of the setpoint value input means, to calculate a yaw acceleration setpoint value and translational acceleration setpoint values from the setpoint value settings. The setpoint value processing means may be configured to transfer the calculated yaw acceleration setpoint value and translational acceleration setpoint values to the vehicle movement controller, which is configured to actuate one or more of the actuators such that the yaw acceleration setpoint value and the translational acceleration setpoint values are reached.