The present disclosure relates to a method and a system for imaging a biological tissue. A monochromatic image of the biological tissue is obtained. A texture analysis of the biological tissue is performed using spatial information of the monochromatic image to identity features of the biological tissue. A texture image is generated based on the features of the biological tissue. The biological tissue of the subject is classified as normal or abnormal at least in part based on a comparison between first order statistics of the texture image and predetermined values.

System, methods and electronic devices aimed at motivating users to perform physical activity are disclosed herein. A user may be presented with a series of physical and cognitive exercises. For example, an exercise may be locked until completion of an unlocked exercise. Performance in each exercise may be tracked to display feedback to a user and track the user's improvement over time. Physical exercises may comprise challenges to move a particular distance or take a particular number of steps. Cognitive exercises comprise techniques test or train the cognitive abilities of the user in: attention, memory, processing speed, logical reasoning, numerical reasoning, spatial reasoning, verbal reasoning, language, and cognitive executive functions. Performance in one exercise may modify the difficulty or parameters of a subsequent exercise. The tracking of user improvement may comprise a progress or reward system such as the increasing of a user's “level” or awarding of “badges.”

The digital personalized medicine system uses digital data to assess or diagnose symptoms of a subject to provide personalized or more appropriate therapeutic interventions and improved diagnoses. The use of prioritized questions and answers with associated feature importance can be used to assess mental function and allow a subject to be diagnosed with fewer questions, such that diagnosis can be repeated more often and allow the dosage to be adjusted more frequently. Pharmacokinetics of the subject can be estimated based on demographic data and biomarkers or measured, in order to determine a treatment plan for the subject. Also, biomarkers can be used to determine when the patient may be at risk for experiencing undesirable side effects and the treatment plan adjusted accordingly.

An apparatus for determining a cognitive state of a user of a mobile device (2) of the apparatus (1), the apparatus (1) comprising: an output means (5) in the mobile device (2) for giving out information to the user, wherein the output means (5) comprises an optical output means (5.1) for optically giving out information to the user; a camera (3) in the mobile device (2) for recording images in a first view direction (3.1) of an environment of the mobile device (2); a path means (6) configured to determine a positional path of the mobile device (2) in the environment; a further camera (4) in the mobile device (10) for recording images in a second view direction (4.1) and/or a microphone (13) for recording an audio signal; a task means (7, 7′) for interacting via the output means (5) with the user to make the user solve a task using an augmented reality environment shown via the optical output means (5.1) and based on the environment of the mobile device (2) captured by the camera (3); a user feature means (8, 8′) for detecting and/or tracking at least one feature of the user in the images recorded by the further camera (4) while the user solves the task and/or in the audio signal recorded by the microphone (13) while the user solves the task; a cognitive state means (9, 9′) for determining the cognitive state of the user based on the positional path of the mobile device determined while the user solves the task and based on the at least one feature of the user.

A cognitive function evaluation device includes: an obtainment unit that obtains utterance data indicating a voice of an evaluatee uttering a sentence as instructed; a calculation unit that calculates, from the utterance data obtained by the obtainment unit, a feature based on the utterance data; an evaluation unit that compares the feature calculated by the calculation unit to reference data indicating a relationship between voice data indicating a voice of a person and a cognitive function of the person to evaluate the cognitive function of the evaluatee; and an output unit that outputs the sentence to be uttered by the evaluatee and outputs a result of evaluation by the evaluation unit.

In some embodiments, a display system comprising a head-mountable, augmented reality display is configured to perform a neurological analysis and to provide a perception aid based on an environmental trigger associated with the neurological condition. Performing the neurological analysis may include determining a reaction to a stimulus by receiving data from the one or more inwardly-directed sensors; and identifying a neurological condition associated with the reaction. In some embodiments, the perception aid may include a reminder, an alert, or virtual content that changes a property, e.g. a color, of a real object. The augmented reality display may be configured to display virtual content by outputting light with variable wavefront divergence, and to provide an accommodation-vergence mismatch of less than 0.5 diopters, including less than 0.25 diopters.

Methods and systems useful for detecting neurological disorders and for measuring general cognitive performance, in particular by measuring eye movements and/or pupil diameter during eye-movement tasks.

Cognitive decline detection system includes obtainment unit and determination unit. Obtainment unit obtains the amount of movement during a sleep period and the amount of movement during a non-sleep period of a user for each day, the non-sleep period being the period other than the sleep period. Determination unit determines that the cognitive function of the user is lower during a determination period than during a comparison period set before the determination period when the frequency of days when a movement amount ratio falls below a predetermined ratio among days constituting the determination period is higher than that among days constituting the comparison period, the movement amount ratio representing the ratio of the amount of movement during the non- sleep period to the amount of movement during the sleep period.

A tomographic image prediction apparatus includes an input unit, a prediction unit, an output unit, and a learning unit. The tomographic image prediction apparatus inputs a tomographic image of a brain of a subject as an input image, and predicts a tomographic image of the brain of the subject after the acquisition of the input tomographic image by a deep neural network in the prediction unit, and outputs the predicted tomographic image as an output image. The tomographic image prediction apparatus is capable of training the deep neural network using a tomographic image database.

A training data processing method and an electronic device are provided. The method includes: obtaining medical history data including at least one first disease suffered by a user; setting a plurality of disease types according to a target disease; setting a time interval; obtaining at least one second disease in the time interval from the medical history data; performing a pre-processing operation on the second disease according to the disease types to obtain processed data; and inputting the processed data to a neural network to train the neural network.