A dementia information output system according to an aspect of the present invention includes: an acquisition unit configured to acquire an amount of body motion of a user; a determining unit configured to determine a likelihood that the user is developing a mild dementia or the like on the basis of a variability degree that is a degree by which an amount of body motion varies over a plurality of days in each of a plurality of time periods; and an outputting unit configured to output dementia information indicating the likelihood determined by the determining unit.

The medical information display apparatus includes a first data acquisition unit that acquires a table showing relevance between at least one item included in clinical diagnostic information on dementia and a brain area, a second data acquisition unit that acquires clinical diagnostic information on dementia of a subject, an image acquisition unit that receives an input of a three-dimensional brain image, a brain area division unit that divides the three-dimensional brain image of the subject, an image analysis unit that calculates an analysis value for each brain area, an operation unit that selects one item among items included in the clinical diagnostic information of the subject, a display unit, and a display controller that specifies a brain area corresponding to the one item selected by the operation unit and displays brain area specifying information for specifying the specified brain area and an analysis value of the brain area.

Systems and methods are disclosed for measuring pupillary light reflex and detecting diseases based on eyes features and trends in pupillary and other eye related features. In one example, disclosed is a system for evaluating pupillary features includes a device, a camera, a distance detector, a memory, and a control system. Image data corresponding to an eye of a user is received from the camera. Distance data associated with the eye of the user is received from the distance detector. The distance data is processed to determine a distance of the at least one eye of the user from the distance detector. The image data and the distance are processed to determine at least one pupillary feature. Based on the at least one pupillary feature, a health status associated with the user is determined.

A computer system supplies a health service using body information measured by a measurement instrument. The computer system includes a computer that includes an analysis unit analyzing memory of a user. The analysis unit analyzes an error pattern based on a history of a matching-determination process for body information transmitted by the measurement instrument and body information input by the user, calculates a first evaluation value for evaluating a cognitive function based on an analysis result of the error pattern, analyzes an action pattern related to an input action of body information of the user, calculates a second evaluation value for evaluating the cognitive function based on an analysis result of the action pattern, and evaluates the cognitive function of the user based on the first evaluation value and the second evaluation value.

An ear level auditory system comprising at least one ear level audio device (110, 210) adapted to provide a treatment based on inducing neural oscillations in a user.

An information processing device includes: an acquirer configured to acquire images obtained by imaging cells differentiated from pluripotent stem cells derived from a subject; and a predictor configured to input the images acquired by the acquirer to a model trained on data in which information indicating at least a neurodegenerative disease is associated with the image obtained by imaging the cells of the neurodegenerative disease differentiated from the pluripotent stem cells, and predict an onset of the neurodegenerative disease of the subject or effects of drugs on the neurodegenerative disease, based on output results of the model to which the images were input.

Systems and methods for generating a numerical model of the human head are provided. A numerical model may be created by generating a data array in a magnetic resonance modeling system, each cell of the array corresponding to a location in the head. The cells may be grouped into one or more regions, each group corresponding to a segment of the head. The cells of the array may be populated with values corresponding to tissue properties relevant to MR imaging. Tissue property values may be selected for each region based on one or more probability distributions. For each region and each tissue property, a value may be selected based on a corresponding probability distribution. Selected tissue property values may be input into cells in the array corresponding to the region with which the probability distribution is associated. The numerical model may be used as an input to an MRI simulator.

The present invention relates to an AI (Artificial Intelligence) based method for providing brain information comprising: a step 1 in which a brain signal obtaining portion of a brain signal measuring portion irradiates near-infrared ray to user's brain and detects light penetrating a cerebral cortex of the brain; a step 2 in which a brain signal processing portion of the brain signal measuring portion determines a level of oxygenation of hemoglobin in blood flow of the user's brain on the basis of the detected light; a step 3 in which a brain signal analyzing portion of the brain signal measuring portion extracts at least one brain activation area from a plurality of activated areas of the user's brain on the basis of the determined level of oxygenation of hemoglobin; and a step 4 in which a diagnosing portion determines a state of the user's brain on the basis of the at least one brain activation area extracted successively for a predetermined period of time, wherein a signal collecting operation of the brain signal obtaining portion in the step 1 is performed in a state that the user is moving.

A system for classifying an activity and connectivity of a brain into at least one neuropsychiatric disorder from magnetic resonance imaging (MRI) images. The system includes an imaging device, a network, and a brain activity analyzing server. The system (i) generate a three-dimensional (3D) structural MRI image and a 4D functional MRI images of the brain, (ii) extracts one or more features associated with one or more regions of the brain using a parcellation scheme, (iii) analyses, using a machine learning model, an intensity of at least one voxel in the one or more regions, and (iv) classifies the activity and the connectivity of the brain into at least one neuro-psychiatric disorder based on a percentage of variation of intensity of the at least one voxel in the one or more regions of the brain over the one or more features from a predefined threshold value.

Provided are systems, methods, and kits for multifunctional smell assessment. The kits may comprise a first surface adhered by a first releasable adhesive comprising an odorous volatile compound; and the system for registering if the odorous volatile compound is detected by a user. The system or method may comprise queries for obtaining a first input on whether the user detects and identifies the odorous volatile compound, and an intensity by which the odor is perceived.