32 results about "Cognition.status" patented technology

A system for delivering learning programmes comprising optical sensors for capturing a subject's facial expression, eye movements, point-of-gaze, and head pose during a learning session; a data repository comprising task data entities; a module for estimating the subject's affective and cognitive states using the captured sensory data; and a module for selecting a task data entity for presentment to the subject after each completion of a task data entity based on a probability of the subject's understanding of the associated knowledge; wherein the probability of the subject's understanding is computed using the subject's estimated affective cognitive states.

A computer-implemented method for implementing cognitive state recognition within a telematics system includes determining moving object operation behaviors of an operator of a moving object corresponding to respective select contextual combinations, generating a personalized base characteristic for each select contextual combination, recognizing a cognitive state based on a comparison of actual moving object operation behaviors associated with the select contextual combinations and corresponding ones of the personalized base characteristics, and automatically triggering one or more actions based on the cognitive state.

Provided are techniques for alert generation based on a cognitive state and a physical state. Wearables data, text communications, voice communications, and images of a caregiver providing care to a patient are obtained. The wearables data, the text communications, the voice communications, and the images are analyzed to identify a cognitive state and a physical state of the caregiver. The cognitive state and the physical state are compared to one or more care rules associated with tasks of the caregiver for the patient. In response to the comparison indicating any one of the cognitive state and the physical state prevent the caregiver from executing the tasks, an alert is generated. One or more recommendations for resolving the alert based on one or more recommendation rules are generated.

Provided are techniques for alert generation based on a cognitive state and a physical state. Wearables data, text communications, voice communications, and images of a caregiver providing care to a patient are obtained. The wearables data, the text communications, the voice communications, and the images are analyzed to identify a cognitive state and a physical state of the caregiver. The cognitive state and the physical state are compared to one or more care rules associated with tasks of the caregiver for the patient. In response to the comparison indicating any one of the cognitive state and the physical state prevent the caregiver from executing the tasks, an alert is generated. One or more recommendations for resolving the alert based on one or more recommendation rules are generated.

The invention provides a knowledge point recommendation method and related equipment, which comprehensively considers the preference of a user for knowledge points and the cognitive state of the user for the knowledge points, and further recommends the knowledge points which are more suitable for the learning level of the user and conform to the preference of the user to the user. The method comprises the following steps: determining a user embedding vector corresponding to a target user, knowledge point embedding vectors corresponding to N knowledge points and exercise question embedding vectors corresponding to M exercise questions; determining the interest preference of the target user to each knowledge point in the N knowledge points according to the user embedding vector and the knowledge point embedding vector; determining a cognitive state of the target user for each knowledge point in the N knowledge points according to the user embedding vector and the exercise question embedding vector; determining a knowledge point recommendation degree corresponding to each knowledge point in the N knowledge points according to the interest preference of each knowledge point and the cognitive state of each knowledge point; and recommending the knowledge points to the target user according to the knowledge point recommendation degree corresponding to each knowledge point in the N knowledge points.

The present invention provides a system and method for assessing the cognitive and emotional states of real-world people based on activities in a virtual world environment with which they interact. The virtual world is configured to provide an interactive experience for assessing the cognitive and / or emotional state of the person. The system needs to configure a session avatar during each virtual world session to provide current insights into the person's emotional state. The system may need to configure an avatar that reflects the state of the person. The system requires the person to configure the virtual world environment during each virtual session to provide current insights into the person's emotional state. The system allows the user to visit destinations, perform tasks and play games included in the environment to provide a cognitive and / or emotional state of the person based on the person's choices and / or performance insights.

The invention discloses a knowledge tracking method and system integrating long-short-term memory and Bayesian network, which calculates the Bayesian value of knowledge components corresponding to the current time series by establishing a cognitive data set including time series and a long-term short-term memory neural network. The parameter group of the Yassian knowledge tracking model, so that the Bayesian knowledge tracking model is used to calculate the correct probability prediction value of the learner's answer to the topic of the current time series, and by comparing the correctness of the answer to the topic of the current time series in the cognitive data set The true value of the long-short-term memory neural network model loss function corresponding to the current time series is obtained, thereby obtaining the optimized value of the weight parameter matrix and the optimized value of the bias parameter matrix; traversing all the time series of the cognitive data set, and obtaining the long-term short-term memory The optimal value of the weight parameter matrix of the neural network model and the optimal value of the deviation parameter matrix; thereby realizing the prediction of the cognitive state of the learner to be tested, and planning and / or learning path of the learner according to the prediction of the cognitive state of the learner Or the construction of knowledge graphs.

An embodiment of the present invention provides a method and system for measuring personality based on neural responses, wherein the provided method includes: playing the personality test material in the preset material library to the subject, and receiving the subject's brain Electric signal; extracting the response feature in the EEG signal to construct the response feature vector; input the response feature vector into the preset personality trait regression model, and calculate the personality trait index of the subject through the personality trait regression model; wherein, the The response feature is the average value of the personality-related EEG components of the subject within a preset time range after the subject observes the preset personality test material. The method provided by the embodiment of the present invention uses specific materials to induce the personality trait-related cognitive state of the subject, and records the EEG signals in this process, and then judges the personality traits of the subject based on the EEG signals. Electrical data can provide a more accurate and realistic assessment of personality traits.

The invention relates to a word cognitive state model-based adaptive learning system and method. The system comprises a mobile terminal, a computer terminal and a server end; the system further comprises a domain knowledge and extension resource module, a cognitive objective introduction module, a cognitive state analysis module, an adaptive learning module and a background database. The method comprises the steps of domain knowledge and extension resource structuralization, cognitive objective introduction and learning activity design, word learning and breakthrough making, learner cognitive state analysis and adaptive content recommendation. The word cognitive state model-based adaptive learning system and method of the invention are applicable to students who can learn English, can analyze the interactive data of the learners, evaluate the cognitive states of the learners, provide accurate recommendations which are suitable for the cognitive states and capacities of the learners in word learning, and minimize the cognitive burden brought by vocabularies which have been already mastered by the learners or vocabularies which are excessively difficult so as to reduce learning burden and improve learning efficiency.

The invention discloses a multi-source domain adaptive cross-subject EEG cognitive state evaluation method based on label alignment. The present invention comprises steps: 1: data acquisition; 2: data preprocessing; 3: EEG cognitive state assessment method across subjects based on LA-MSDA model. The present invention uses the shared public feature extractor and non-shared sub-feature extractor in stages to further learn the subject invariant features and specific features of the source domain samples and target domain samples; secondly, considering the relationship and similarity between subjects , and propose methods to align the inter-domain distributions of local and global representations to assess cognitive states across subjects, addressing the difficulty of learning fine-grained class conditional information and adapting to decision boundary samples across subjects. Finally, the present invention effectively avoids the problem of individual differences in EEG signals in the field of brain cognitive computing, is applicable to EEG-based cognitive state recognition under any task, has strong generalization ability, and is well applicable to clinical diagnosis and practical application.