The present disclosure relates to a computer-implemented process for generating and providing simulated user absorption information pertaining to users and based on target profiles and target situations, thereby providing user targeted and situationally targeted content recommendations. It is an object of the present disclosure to provide a technological solution to the long felt need in small scale content recommendation systems caused by the technical problem of generating situationally targeted and user profile targeted content recommendations for users of an interactive electronic system.

A system detects a user's mood and in response establishes computer settings including computer game settings, recommends social network interactions, advises other users, alters task scheduling, and in general enhances collective group mood, collective productivity, social interaction, and engagement.

Method, apparatus and computer program for providing a personalized study plan to a learner through cognitive and behavioral diagnosis of the learner. A learner who uses a data input device such as a smart pen and a stylus pen by using data obtained from the data input device. The method, apparatus and computer program relate to technology for obtaining input data based on information inputted by a user for at least one question with the data input device, creating test behavior data on the user from the obtained input data, analyzing cognition and behavior of the user based on at least one of metadata on the at least one question and the created test behavior data, and providing a personalized study plan to the user through an algorithm using machine learning based on the cognition and behavior analysis.

Systems and methods are provided for identifying a therapeutic VR activity or exercise for a subject/patient based on the subject's impairments, dynamically adjusting a VR activity for a patient, and identifying potential impairments based on a patient's performance in a VR activity. Patients may each have various physical, neurological, cognitive, and/or sensory impairments to be treated. Not all therapeutic activities may be appropriate for some patients and their impairments. A VR therapeutic activity platform may increase patient engagement and challenge patients at more appropriate times by better matching activities corresponding to a patient's impairments and dynamically adjusting each VR activity based on performance to offer a challenging and rewarding therapeutic experience.

Systems and methods are provided for identifying a therapeutic VR activity or exercise for a subject/patient based on the subject's impairments, dynamically adjusting a VR activity for a patient, and identifying potential impairments based on a patient's performance in a VR activity. Patients may each have various physical, neurological, cognitive, and/or sensory impairments to be treated. Not all therapeutic activities may be appropriate for some patients and their impairments. A VR therapeutic activity platform may increase patient engagement and challenge patients at more appropriate times by better matching activities corresponding to a patient's impairments and dynamically adjusting each VR activity based on performance to offer a challenging and rewarding therapeutic experience.

A system and method for predicting mild cognitive impairment (MCI) related diagnosis and prognosis utilizing hybrid machine learning. More specifically, the system and method produce predictions of MCI conversions to dementia and prognosis related thereof. Using available medical imaging and non-imaging data a diagnosis and prognosis model is trained using transfer learning. A platform may then receive a request from a clinician for a target patient's diagnosis or prognosis. The target patient's medical data is retrieved and used to create a model for the target patient. Then details of the target patient's model and the diagnosis and prognosis model are compared, a prediction is generated, and the prediction is returned to the clinician. As new medical data becomes available it is fed into the respective model to improve accuracy and update predictions.

A method and system pertaining to a digital virtual sponsor to facilitate behavioral health and wellness of a user is provided. The method includes receiving an input from the user requiring assistance for a behavioral health issue, analyzing the input from the user by using an emotion recognition process to generate data associated with the user, storing the data associated with the user for access at a later time, providing the user with an instruction to complete a task as part of a program to facilitate the behavioral health and wellness of the user on a basis of the data associated with the user, and receiving an indication that the user completed the task to indicate an adherence to the program by the user.

A method and system pertaining to a digital virtual sponsor to facilitate behavioral health and wellness of a user is provided. The method includes receiving an input from the user requiring assistance for a behavioral health issue, analyzing the input from the user by using an emotion recognition process to generate data associated with the user, storing the data associated with the user for access at a later time, providing the user with an instruction to complete a task as part of a program to facilitate the behavioral health and wellness of the user on a basis of the data associated with the user, and receiving an indication that the user completed the task to indicate an adherence to the program by the user.

A goal management system receives input of a qualitative first goal related to a body of a user (step S111), identifies a quantitative second goal related to the body of the user from the first goal thus received (step S112 to step S117), and presents the second goal thus identified (step S118). The first goal is converted into the quantitative goal for at least one of a plurality of feature amounts related to the body, thereby identifying the second goal including at least one goal obtained by such conversion. The first goal is converted into the quantitative goal for each feature amount corresponding to a meaning obtained by linguistic analysis. When there are a plurality of meanings obtained by linguistic analysis of the first goal, the first goal is converted into the quantitative goal for each feature amount on the basis of a range of each feature amount per meaning. This makes it possible to indicate a quantitative goal related to the body without receiving input of a goal that is a quantitative numerical value related to the body.

An automated tracking and analysis system is described. In some instances, the system may collect data describing an attribute of a participant, predict interventions related to the attribute of the participant, and generate personalized tracks relating to the interventions, each of which may include an action. In some instances, the system may assess a performance metric indicating a level of performance of the participant in the personalized tracks, compute a participant score for the personalized tracks using the performance metric; and issue a reward to the participant based on one or more of the participant score and the performance metric.