Product
Patsnap Eureka
For R&D, Patsnap Eureka makes reading and utilizing patents & technical documents easy.
Patsnap Eureka AIR
Designed for self-driven R&D workflows. Generate viable solutions, solve complex R&D challenges, empower your innovation with AI.
Patsnap Eureka Materials
Designed for material experts only. Revolutionize your material R&D, from search, analyze, to developing new materials.
Feature
TechResearch
Generate reliable direction feasibility study reports for your R&D in just a few steps.
TechSeek
Discover and master advanced knowledge NOW. Basics, ideas, possibilities, all at once.
TechMind
As an expert in R&D Theories, TechMind can generates customized viable solutions instantly.
TechRisk
Analyze your overall solution with one click, know your potential R&D risks in advance.
TechMonitor
Get weekly tech updates, stay abreast of the latest tech innovations and key insights.
Patents
Literature
Hiro is an intelligent assistant for R&D personnel, combined with Patent DNA, to facilitate innovative research.
32 results about "Cognition.status" patented technology
Efficacy Topic
Property
Owner
Technical Advancement
Application Domain
Technology Topic
Technology Field Word
Patent Country/Region
Patent Type
Patent Status
Application Year
Inventor
Cognistat, formerly known as the Neurobehavioral Cognitive Status Examination (NCSE), is a cognitive screening test that assesses five cognitive ability areas (language, construction, memory, calculations and reasoning).
Interactive and adaptive learning, neurocognitive disorder diagnosis, and noncompliance detection systems using pupillary response and face tracking and emotion detection with associated methods
InactiveUS20200178876A1High precision estimationLess-proneHealth-index calculationAcquiring/recognising eyesSubstance abuserAdaptive learning
A system for detection of noncompliance including substance abuse, driving under influence, and untruthful testimony giving under law enforcement setting, comprising optical sensors for capturing a subject's pupillary responses, blinking eye movements, point-of-gaze, facial expression, and head pose during a compliance test session. The system can also be applied in neurocognitive disorder diagnosis. The subject's affective and cognitive states estimation based on the captured sensory data during a diagnosis test is feedback to the system to drive the course of the compliance or cognitive test, adaptively change the test materials, and influence the subject's affective and cognitive states. The estimated affective and cognitive states in turn provide a more accurate reading of the subject's condition.
Owner:LAM YUEN LEE VIOLA
Interactive and adaptive learning and neurocognitive disorder diagnosis systems using face tracking and emotion detection with associated methods
InactiveUS20200046277A1Less-proneData processing applicationsSpeech analysisAdaptive learningPsychiatry
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.
Owner:LAM YUEN LEE VIOLA
Cross-subject EEG cognitive state recognition method based on prototype clustering domain adaptation algorithm
PendingCN112580518AImprove training efficiencyAddressing Individual DifferencesCharacter and pattern recognitionNeural learning methodsCognitive computingAlgorithm
The invention discloses a cross-subject EEG cognitive state recognition method based on a prototype clustering domain adaptation algorithm. According to the method, the concept of category domains isintroduced, on one hand, on the basis of multi-source domain alignment of labels, feature distribution differences between different categories are considered, structural fine-grained alignment underthe category conditions between different source domains in a feature space is researched, and the problem of category imbalance in the multi-source domains is converted into a mode of the category domains; and prototype theoretical clustering alignment between the source domain and the target domain is carried out, i.e., clustering between similar source domains is carried out on the target domain by taking a dynamic adjustment prototype center as a constraint, and similar features and sparse heterogeneous features between the domains are realized, wherein the former realizes intra-domain class conditional structure feature alignment, and the latter realizes global fine-grained structure feature alignment. According to the invention, the method can be compatible with category balance andimbalance, effectively solves the problem of individual difference of electroencephalogram signals in the field of brain cognitive calculation, has high generalization ability, and can be well suitable for clinical diagnosis and practical application.
Owner:HANGZHOU DIANZI UNIV
Student Bloom grasp degree evaluation method and system and storage medium
PendingCN112527821AAchieve the purpose of operationRelational databasesEducational modelsDeep knowledgeTracking model
The invention discloses a student Bloom mastery degree evaluation method and system and a storage medium. The method comprises the steps: constructing and training a deep knowledge tracking model; when the student generates a new learning behavior, predicting the question solving accuracy of the student on each exercise through the trained deep knowledge tracking model; and evaluating the Bloom grasp degree of the knowledge point of the student at the current moment based on the prediction result of the question solving accuracy of the student on each exercise. The Bloom mastery degree of theknowledge points can be modeled through the learning behavior sequence of the students and the deep knowledge tracking method, the ability information and the mastery degree of the students on the knowledge point granularity can be visually represented, and the method and system can be deployed to an online education and mixed education platform. Study ability changes and cognitive state changes of students are effectively represented, and the purpose of Bloom operation is achieved.
Owner:东软教育科技集团有限公司
Cross-subject EEG cognitive state recognition method based on prototype clustering domain adaptation algorithm
InactiveCN112749635AAddressing Individual DifferencesReduce complexityCharacter and pattern recognitionCognitive computingAlgorithm
The invention discloses a cross-subject EEG cognitive state recognition method based on a prototype clustering domain adaptation algorithm. According to the method, the concept of a category domain is introduced, on one hand, on the basis of label multi-source domain alignment, feature distribution differences between different categories are considered, structure fine-grained alignment under the category condition between different source domains in a feature space is researched, and the problem of category imbalance in the multi-source domains is converted into a category domain mode; and on the other hand, prototype theoretical clustering alignment between the source domain and the target domain is carried out, namely clustering between similar source domains is carried out on the target domain by taking a dynamic adjustment prototype center as a constraint, so that similar features between the domains are similar, and heterogeneous features are sparse. The former achieves intra-domain class condition structure feature alignment, and the latter acieves global fine-grained structure feature alignment. According to the method, the conditions of category balance and imbalance can be compatible, the problem of individual difference of electroencephalogram signals in the field of brain cognition calculation is effectively solved, the generalization ability is high, and the method can be well suitable for clinical diagnosis and practical application.
Owner:HANGZHOU DIANZI UNIV
Test question recommendation method and device, electronic equipment and storage medium
The invention provides a test question recommendation method and device, electronic equipment and a storage medium, and the method comprises the steps: determining the cognitive state of a target user and each candidate test question special topic of the target user based on the historical answer record of the target user; on the basis of the cognitive state of the target user, determining similar users of the target user and model users whose cognitive states are superior to those of the target user; and on the basis of the mastering degree of the similar users for each candidate test question special topic and the mastering degree of the model user for each candidate test question special topic, determining a to-be-recommended special topic from each candidate test question special topic, and pushing the to-be-recommended special topic to the target user. The test questions are recommended by combining the mastering degrees of the similar users and the model users on the candidate test question themes, the test questions can be recommended according to the knowledge themes that the target user masters weak knowledge points, test question resources with high difficulty can be accurately selected and recommended to the target user, and personalized test question recommendation is achieved.
Owner:IFLYTEK CO LTD
Identification method of user operation intention and cognitive state in human-computer interaction
PendingCN111214227AImprove interaction efficiencyImprove reliabilitySensorsPsychotechnic devicesSvm classifierHuman–robot interaction
The present invention discloses an identification method of user operation intention and cognitive state in human-computer interaction. The method comprises the following steps: collecting eye movement characteristic data and electroencephalogram signal data of users in a human-computer interaction process; pre-processing the collected data and respectively dividing into a training set and a testset; and using the training set to train an SVM classifier and then using the optimized classifier to classify the test set to obtain corresponding operation intention and cognitive state. The identification method can identify operation requirements in the interaction process, provides a basis for adaptive adjustment of interfaces, at the same time, can judge the cognitive state of the interaction process and ensures reliability of completion of interaction tasks.
Owner:AIR FORCE UNIV PLA
Cognitive state alteration system integrating multiple feedback technologies
A cognitive alteration system includes a storage unit at least to store one or more scripts, each to control a cognitive alteration process where the process comprises first and second in session media-based treatment processes and an out of session reinforcement stimulus process between the first and second in session processes, and where the storage unit stores both a script per in session process and a script per out of session process; a script handler at least to run at least one script; at least one of a wearable and a non-wearable element to sense an attribute of a subject or to provide an output to the subject during one of the in session and out of session processes; an information analyzer at least to perform analysis of the readings of the at least one element, an integrator to integrate the analysis and a script updater to update at least one of the scripts.
Owner:PSYABLE TECH LTD
Cross-subject EEG cognitive state detection method based on efficient multi-source capsule network
PendingCN113842151AEffectively describe spaceEffectively describe the part-whole hierarchical relationshipSensorsPsychotechnic devicesPattern recognitionEeg data
The invention provides a cross-subject EEG cognitive state detection method based on an efficient multi-source capsule network. The method comprises the following steps: aligning the feature distribution of a target domain and the feature distribution of a multi-source domain, so as to effectively migrate inter-domain features; constructing EEG into a multi-channel one-dimensional structure, so as to improve the training efficiency, and improve the model performance at the same time; secondly, introducing a self-expression module to capture potential relations between samples, so as to well adapt cross-subject EEG data analysis with significant individual differences under different tasks; and finally, providing a space attention algorithm based on a dynamic sub-capsule to further learn fine-grained feature information on the spatial level of the EEG data, and effectively describing the spatial relationship between parts and the partial-overall hierarchical relationship of the EEG data. According to the method, the individual difference problem of electroencephalogram signals in the field of brain cognitive calculation is effectively avoided, the method can be suitable for cognitive state recognition based on EEG under any task, the generalization ability is high, and the method can be well suitable for clinical diagnosis and practical application.
Owner:HANGZHOU DIANZI UNIV
Eye movement analysis with co-clustering of hidden markov models (emhmm with co-clustering) and with switching hidden markov models (emshmm)
PendingUS20220361747A1Easy to predictEasy to analyzeMathematical modelsEye diagnosticsMedicineHide markov model
Owner:VERSITECH LTD
Student score prediction method and device based on fuzzy cloud cognitive diagnosis model
PendingCN113674116AReduced execution timeImprove forecast accuracyForecastingFuzzy logic based systemsPredictive methodsOnline learning
The invention discloses a student score prediction method and device based on a fuzzy cloud cognitive diagnosis model. The method comprises the following steps: establishing a student cognitive cloud model; according to a solving result of the student cognitive cloud model, obtaining a mastery degree interval number of students on knowledge points; according to the mastering degree interval number of the knowledge points, obtaining the mastering degree interval number of the students on test questions; and obtaining a prediction score of the test questions according to a target model parameter obtained by iterative training and the mastering degree interval number of the students on the test questions. According to the fuzzy cloud cognitive diagnosis model, fuzzy interval numbers obtained through student cognitive cloud conversion are used for depicting fuzziness and uncertainty of knowledge point mastering degrees of students, and more comprehensive representation of student cognitive states is achieved; besides, the fuzzy cloud cognitive diagnosis model simplifies model parameters, shortens model execution time, and effectively improves the prediction accuracy and calculation efficiency of student scores in a large-scale online learning scene under the support of the model.
Owner:HUNAN NORMAL UNIVERSITY
Multi-source-domain adaptive cross-subject EEG cognitive state evaluation method based on label alignment
ActiveCN113392733AAvoid individual differencesImprove generalization abilityCharacter and pattern recognitionNeural architecturesCognitive computingFeature extraction
The invention discloses a multi-source-domain self-adaptive cross-subject EEG cognitive state evaluation method based on label alignment. The method comprises the following steps: 1, data acquiring; 2, data preprocessing; 3, a cross-subject EEG cognitive state evaluation method based on the LA-MSDA model. According to the method, a shared common feature extractor and a non-shared sub-feature extractor are used in stages, and tested invariant features and specific features of a source domain sample and a target domain sample are further learned; in consideration of the relationship and similarity between cross-subjects, a method for aligning inter-domain distribution of local and global representation is provided to evaluate the cognitive state of the cross-subjects, and the problem that it is difficult to learn fine-grained class condition information and adapt to decision boundary samples of the cross-subjects is solved. Finally, the problem of individual difference of electroencephalogram signals in the field of brain cognitive calculation is effectively avoided, the method can be suitable for cognitive state recognition based on EEG under any task, the generalization ability is high, and the method can be well suitable for clinical diagnosis and practical application.
Owner:HANGZHOU DIANZI UNIV
Implementing cognitive state recognition within a telematics system
ActiveUS10730527B2Registering/indicating working of vehiclesCharacter and pattern recognitionPersonalizationEngineering
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.
Owner:INT BUSINESS MASCH CORP
Alert generation based on a cognitive state and a physical state
ActiveUS20210042680A1Natural language analysisSemantic analysisPhysical medicine and rehabilitationVoice communication
Owner:IBM CORP
Universal cognitive state decoder based on brain signal and method and apparatus for predicting ultra-high performance complex behavior using the same
Disclosed are a universal cognitive state decoder based on a brain signal and a method and apparatus for predicting an ultra-high performance complex behavior using the same. The method of predicting a complex behavior may include configuring a high-level cognitive state decoder based on a brain signal for classifying a human's high-level core cognitive state, configuring a universal cognitive state decoder by including a calculated value of the high-level cognitive state decoder in another cognitive state decoder as an input value, and predicting a human's complex behavior using the universal cognitive state decoder.
Owner:KOREA ADVANCED INST OF SCI & TECH
Alert generation based on a cognitive state and a physical state
ActiveUS11410110B2Natural language analysisSemantic analysisPhysical medicine and rehabilitationVoice communication
Owner:IBM CORP
Knowledge point recommendation method and device and storage medium
PendingCN114491254APreferences matchAppropriate level of studyData processing applicationsText database queryingData miningData science
Owner:HUNAN UNIV
System and method for assessing cognitive and emotional states of real-world users based on virtual-world activity
ActiveCN109688909BRobust and more accurate data execution assessmentAccurate Data Execution AssessmentMedical automated diagnosisMental therapiesVirtual worldCognition.status
Owner:JANSSEN PHARMA NV
Intelligent chronic disease screening system based on cognitive state
ActiveCN113892909AExpedited screeningImprove efficiencyDiagnostic recording/measuringSensorsDiseaseData set
The invention discloses an intelligent chronic disease screening system based on a cognitive state. The system comprises a data acquisition module which is used for acquiring a chronic disease clinical diagnosis guide data set and an expert consensus data set formed by experts in a chronic disease diagnosis and treatment process; a data processing module which is used for performing fuzzy clustering analysis on the same kind of chronic disease parameters in the expert consensus data set and the clinical diagnosis guide data set to obtain a chronic disease cognitive diagnosis parameter subset; a model generation module which is used for training a maximum entropy model based on the chronic disease cognitive diagnosis parameter subset and generating a chronic disease pre-classification model; and an intelligent screening module which is used for intelligently screening the chronic diseases according to a chronic disease cognitive diagnosis model. According to the invention, the consensus parameter subsets and the clinical diagnosis guide related data parameter subset set formed by experts in different fields in the chronic disease diagnosis and treatment process can be obtained, and fused chronic disease cognitive diagnosis is carried out.
Owner:吾征智能技术(北京)有限公司
Cognitive alert system
ActiveUS11179539B2Improve sleepingAcoustic time signalsTime indicationPhysical medicine and rehabilitationSleep patterns
Systems and methods to facilitate sleep are described. In on example, a cognitive alarm clock system for children learns sleep patterns and activities towards recommending sleep schedules and teaching independence. The system may detect the cognitive state of a child based on voice or cry pattern recognition, a time of day or night, scheduled activities, and social context, among other factors. The system may initiate actions to facilitate sleep in response to the cognitive factors. For example, the system may adjust lighting or push back a wakeup time. In another example, the system may use the cognitive analysis to teach children good sleeping habits by making recommendations to facilitate a good night's rest and encourage independence.
Owner:IBM CORP
Knowledge tracking method and system integrating long short-term memory and Bayesian network
ActiveCN110807469BIn line with learning rulesFit the learning processCharacter and pattern recognitionNeural architecturesData setTracking model
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.
Owner:HUAZHONG NORMAL UNIV
A method and system for measuring personality based on neural response
ActiveCN109567830BAccurate assessmentAvoid questions that are influenced by the subject's subjective factorsDiagnostic signal processingSensorsPersonality testArtificial intelligence
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.
Owner:TSINGHUA UNIV
Cognitive alert system
ActiveUS11179540B2Improve sleepingTime indicationAcoustic time signalsPhysical medicine and rehabilitationSleep patterns
Systems and methods to facilitate sleep are described. In on example, a cognitive alarm clock system for children learns sleep patterns and activities towards recommending sleep schedules and teaching independence. The system may detect the cognitive state of a child based on voice or cry pattern recognition, a time of day or night, scheduled activities, and social context, among other factors. The system may initiate actions to facilitate sleep in response to the cognitive factors. For example, the system may adjust lighting or push back a wakeup time. In another example, the system may use the cognitive analysis to teach children good sleeping habits by making recommendations to facilitate a good night's rest and encourage independence.
Owner:IBM CORP
Brain cognitive state recognition method based on network entropy
PendingCN114298186AStrong resolutionValid different statesCharacter and pattern recognitionHigh level techniquesPattern recognitionNetwork entropy
The invention relates to a brain cognitive state recognition method based on network entropy. The method comprises the following steps: S1, constructing a complex network based on an electroencephalogram time sequence; s2, the connectivity of the complex network is judged, and the network shortest distance of any child node in the complex network is calculated; s3, performing mathematical statistics on the calculation result of the network shortest distance of any child node; s4, calculating a network entropy parameter based on a multi-scale network space distance according to a mathematical statistics result; and S5, inputting the network entropy parameter as a feature vector into a mode classifier, and performing mode classification of the cognitive state of the brain complex network. According to the method, a new network entropy parameter is constructed, the network entropy parameter can effectively represent various network states, and on the basis of the network entropy parameter, the cognitive activity state of the human brain can be effectively recognized.
Owner:HUIZHOU UNIV
Cognitive tracking method fusing knowledge association path
PendingCN114861916AImprove performanceAccurate trackingNeural architecturesKnowledge representationArtificial intelligenceMachine learning
The invention discloses a knowledge association path-fused cognitive tracking method, which comprises the following steps of: 1, constructing a question-knowledge point association matrix, 2, constructing a knowledge point association matrix, 3, constructing a knowledge point difficulty library, 4, calculating a skill mode, 5, aggregating, embedding and representing exercises and knowledge points, 6, embedding and representing exercises, 7, obtaining related historical exercises, and 7, obtaining a knowledge association path-fused knowledge association path-fused knowledge association path-fused knowledge association path-fused knowledge association path-fused knowledge association path-fused knowledge association path-fused knowledge association path-fused knowledge association path-fused knowledge association path-fused knowledge association path-fused knowledge association path-fused knowledge association path-fused knowledge association path-fused knowledge association path. 8, acquiring knowledge point mastering conditions of the students, 9, acquiring skill mode mastering conditions of the students, and 10, predicting future answering performance of the students. The method can start from the thinking process of the students in question making, considers the process that the students associate the knowledge points to solve the questions, integrates the knowledge association paths, and fully excavates the association relationship between the knowledge points, so that the cognitive state change of the students can be accurately and quickly tracked, and the future answering performance of the students can be predicted.
Owner:HEFEI UNIV OF TECH
Cognitive function evaluation method based on Stroop color word test and near-infrared brain function imaging
PendingCN114767114AReliable test resultsThe testing process is simpleMedical imagingDiagnostics using spectroscopyPrefrontal lobeStroop color word test
The invention relates to a cognitive function evaluation method based on Stroop color word testing and near-infrared brain function imaging. The cognitive function evaluation method is technically characterized by comprising the following steps: acquiring light intensity data of brain tissues of prefrontal lobes on two sides and a Stroop color word testing result of a subject in the Stroop color word testing process through a functional near-infrared imaging system; converting the light intensity data of the subject into brain physiological information data, and calculating the intensity of a double-forehead area; according to the method, the subjects which have cognitive function decline or poor cognitive states and cannot be well matched to complete traditional neuropsychological scale evaluation are tested; and comparing the Stroop color word test results of the subject and the normal person and whether the intensity of the double-forehead region is obviously different, and analyzing the correlation between the Stroop color word test results and the intensity of the double-forehead region and the MoCA score. According to the method, the Stroop color word test and near-infrared brain function imaging technology are adopted, the cognitive function is evaluated through brain function connectivity, the test result is accurate and reliable, the test process is simple, and a subject can easily complete the test.
Owner:天津市环湖医院 +1
Cognitive alarm clock
ActiveUS20200038621A1Improve sleepingAcoustic time signalsTime indicationPhysical medicine and rehabilitationSleep patterns
Systems and methods to facilitate sleep are described. In on example, a cognitive alarm clock system for children learns sleep patterns and activities towards recommending sleep schedules and teaching independence. The system may detect the cognitive state of a child based on voice or cry pattern recognition, a time of day or night, scheduled activities, and social context, among other factors. The system may initiate actions to facilitate sleep in response to the cognitive factors. For example, the system may adjust lighting or push back a wakeup time. In another example, the system may use the cognitive analysis to teach children good sleeping habits by making recommendations to facilitate a good night's rest and encourage independence.
Owner:IBM CORP
A system and method for adaptive learning based on a word cognitive state model
ActiveCN106897950BExpansion of learning resourcesMeet learning needsMetadata audio data retrievalData processing applicationsAdaptive learningComputer terminal
Owner:BEIJING NORMAL UNIVERSITY
Cognitive analysis method and cognitive analysis device for learning object, and electronic equipment
PendingCN113129190AFix technical issues with lower accuracyResponse score prediction performance is goodData processing applicationsFuzzy logic based systemsCognitive analysisMachine learning
The invention discloses a cognitive analysis method and a cognitive analysis device for a learning object, and electronic equipment. The cognitive analysis method comprises the steps: obtaining a plurality of continuous score sets, a plurality of fuzzy score sets and a plurality of fuzzy cognitive sets when all learning objects answer various types of exercises, wherein each type of exercises corresponds to one knowledge point, each continuous score set comprises a plurality of continuous scores of one knowledge point, the fuzzy cognitive set comprises the mastering degree of the learning object on the knowledge points; determining a fuzzy membership distribution map based on each continuous score set, the plurality of fuzzy score sets and the plurality of fuzzy cognitive sets; constructing a cognitive model based on the plurality of fuzzy membership distribution maps; and analyzing the score of the target learning object when answering the exercises of the same kind of knowledge points by adopting the cognitive model. According to the method and the device, the technical problem of relatively low accuracy of student cognitive state evaluation due to the adoption of a binary score evaluation mode in a student learning model in related technologies is solved.
Owner:HEFEI UNIV OF TECH
Multi-source Domain Adaptive Cross-subject EEG Cognitive State Assessment Method Based on Label Alignment
ActiveCN113392733BAvoid individual differencesImprove generalization abilityCharacter and pattern recognitionNeural architecturesCognitive computingDecision boundary
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.
Owner:HANGZHOU DIANZI UNIV
Who we serve
- R&D Engineer
- R&D Manager
- IP Professional
Why Patsnap Eureka
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com