Abstract: A determination system is an operation device that determines whether a posture of a subject who uses a terminal device is a good posture or a poor posture. The determination system includes: an obtainer that obtains an image including a background part behind the subject from an imaging device provided in the terminal device; and a determiner that determines whether a posture of the subject is the good posture or the poor posture based on the background part included in the image obtained, and outputs a determination result.

Abstract: A concentration-level estimation device includes an obtainer which obtains task information indicating a type of a task executed by a user among types of tasks; a sensor which outputs motion information indicating a feature of a motion of the user who executes the task, based on a result of sensing obtained from a sensing device; a storage which stores profiles concerning habits of the user for the types of tasks; and a calculator which calculates a concentration level of the user using the motion information and a profile corresponding to the type of the task indicated in the task information among the profiles stored in the storage.

Abstract: The present subject matter refers a method to evaluate concentration of a living being based on artificial intelligent techniques. The method comprises detecting a continuous increase in concentration of a living being based on an artificial neural network (ANN), The method comprises receiving a parameter of the continuous increase in concentration, determining a first value of the concentration based on a first condition, said first condition defined by increase of the received parameter by more than a first predetermined threshold; and determining a second value of the concentration based on a second condition, said second condition defined by decline in the concentration from the first value by more than a second predetermined threshold.

Abstract: A concentration degree measurement device includes: a concentration degree obtainer that obtains a degree of concentration of a person; a drowsiness degree obtainer that obtains a degree of drowsiness of the person; a corrector that corrects the degree of concentration, based on the degree of drowsiness; an outputter that outputs a corrected degree of concentration indicating the degree of concentration corrected by the corrector; a determiner that determines a factor for the corrected degree of concentration, based on the degree of drowsiness and the corrected degree of concentration; and a controller that controls an electronic device, based on a result of the determination by the determiner, the electronic device inducing the person to wake up or concentrate.

Abstract: A system for gaze direction detection is disclosed herein. The system comprises a face detection unit configured to detect face information from a captured image of a spectator, a head pose unit configured to detect a head pose angle based on the face information; an eye measurement unit configured to detect eye information of at-least one of a left eye or a right eye of the spectator based on the detected face information; an eye-gaze detection unit configured to estimate a gaze angle of the at-least one of the left eye or the right eye of the subject based on the eye information; a conditional gaze detection unit configured to calculate a resultant gaze angle based on the estimated gaze angles of the left eye and right eye and the head pose angle; and an effective gaze detection unit configured to estimate an effective gaze angle based the resultant gaze angle and head-pose angle.

Abstract: A risk-of-falling determination apparatus includes a walk information obtainer that obtains walk information of a user, a myoelectric sensor that measures a first myoelectric potential difference on an anterior surface of a thigh of the user and a second myoelectric potential difference on a posterior surface of the thigh, a control circuit that identifies an interval of a stance phase by using the walk information, calculates a degree of co-contraction at a corresponding leg of the user on the basis of the first and second myoelectric potential differences for the stance phase, and determines whether the degree of co-contraction is greater than or equal to a first threshold, and an outputter that outputs a signal indicating that the user has a high risk of falling if the degree of co-contraction is greater than or equal to the first threshold.

Abstract: A muscular fatigue determination apparatus includes an information obtaining unit that obtains loads applied to a pedal of a bicycle, rotation speeds of a crank of the bicycle, and myoelectric potentials of a user, the myoelectric potentials and the loads being in a one-to-one relationship, the myoelectric potentials and the rotation speeds being in a one-to-one relationship, and a muscular fatigue information generation unit that generates muscular fatigue information regarding the user on the basis of whether a difference between the myoelectric potentials of the user is larger than a first threshold, each of the myoelectric potentials being associated to a load range that is one of load ranges and to a rotation speed range that is one of rotation speed ranges, each of the loads belonging to one of the load ranges and each of the rotation speed ranges belonging to one of the rotation speed ranges.

Abstract: A risk-of-falling determination apparatus includes a walk information obtainer that obtains walk information of a user, a myoelectric sensor that measures a first myoelectric potential difference on an anterior surface of a thigh of the user and a second myoelectric potential difference on a posterior surface of the thigh, a control circuit that identifies an interval of a stance phase by using the walk information, calculates a degree of co-contraction at a corresponding leg of the user on the basis of the first and second myoelectric potential differences for the stance phase, and determines whether the degree of co-contraction is greater than or equal to a first threshold, and an outputter that outputs a signal indicating that the user has a high risk of falling if the degree of co-contraction is greater than or equal to the first threshold.

Abstract: A muscle activity amount determining device includes a shape obtainer that obtains a shape of a muscle of a user when the user is doing certain exercise; a position identifying unit that identifies a position of the muscle of the user when the user is doing the exercise; a determination circuit that refers to a determination reference that indicates a corresponding relationship between the position and shape of the muscle and an activity amount of the muscle, and determines the activity amount of the muscle using the position of the muscle identified by the position identifying unit and the shape of the muscle obtained by the shape obtainer; and an outputter that outputs the activity amount, determined by the determination circuit.

Abstract: An electrical stimulation apparatus includes a sleep depth determiner that determines a sleep depth by using biological information of a user who is sleeping; an electrical muscular stimulation intensity determiner that determines an electrical muscular stimulation intensity on basis of the sleep depth; and an output that output electrical muscular stimulation by using electrodes arranged on a skin of the user at the electrical muscular stimulation intensity determined by the electrical muscular stimulation intensity determiner.

Abstract: A muscular fatigue determination apparatus includes an information obtaining unit that obtains loads applied to a pedal of a bicycle, rotation speeds of a crank of the bicycle, and myoelectric potentials of a user, the myoelectric potentials and the loads being in a one-to-one relationship, the myoelectric potentials and the rotation speeds being in a one-to-one relationship, and a muscular fatigue information generation unit that generates muscular fatigue information regarding the user on the basis of whether a difference between the myoelectric potentials of the user is larger than a first threshold, each of the myoelectric potentials being associated to a load range that is one of load ranges and to a rotation speed range that is one of rotation speed ranges, each of the loads belonging to one of the load ranges and each of the rotation speed ranges belonging to one of the rotation speed ranges.