31 results about "Cognitive test" patented technology

The invention relates to the technical field of medical rehabilitation, and discloses a vestibular function and cognitive function rehabilitation training system and method based on virtual reality, and the rehabilitation training system comprises a hardware platform, a software platform and a server. The hardware platform comprises VR interaction equipment, a head motion tracking sensor and calculation and display equipment; the software platform is integrated with a user management module, a visual stimulation module, a vestibular rehabilitation training module, a cognitive evaluation and training module, a dynamic visual acuity evaluation module and a data management and analysis module. By combining black and white chess grid visual stimulation, standardized vestibular rehabilitation tasks, spatial cognitive testing and DVA objective monitoring, synchronous evaluation and personalized collaborative intervention of vestibular functions and cognitive functions of dizzy patients are realized. According to the method, the problems of boring traditional rehabilitation means, subjective evaluation and lack of quantitative feedback are solved, and the scientificity, interestingness and curative effect testability of rehabilitation training are remarkably improved.

The invention discloses a multi-modal feature fusion prediction method and system for early screening of Alzheimer's disease, and belongs to the technical field of brain disease prediction. The method comprises the following steps: acquiring multi-dimensional data containing cognitive test scores, brain image scanning results and biomarker concentration levels from a patient record database, and performing standardization processing to obtain a multi-dimensional data set in a unified format; key feature vectors are extracted through a dimensionality reduction analysis method to capture the covariant relation between cognitive test scores and brain image changes; when the reduction range of the cognitive test score exceeds a preset threshold value and the brain image displays an atrophy sign, a classification model is constructed through an integrated learning method to preliminarily classify abnormal signals; and fusing the biomarker concentration level to obtain an abnormal signal vector. According to the method, the accuracy and efficiency of early screening of brain diseases such as Alzheimer's disease are remarkably improved through accurate evaluation of key parts of the human brain, such as hippocampus.

The invention discloses a cognitive evaluation system and method based on a single-class implicit association test. The cognitive evaluation system comprises a feature screening module, a cognitive test module and a cognitive evaluation module. The feature screening module is used for screening out key abnormal words and key psychological difference groups. And the cognitive test module carries out cognitive test by enabling the subject to recognize the category labels of the stimulation words, and inputs a test result into the cognitive evaluation module to obtain cognitive evaluation of the subject. The cognition test module comprises an internal implicit impression test module, a self-graphic test module and an internal implicit impression recognition test module; the implicit implicit impression test module takes the key psychological difference group and the key abnormal word as stimulation words to carry out cognitive test; the self graph type test module takes the key psychological difference group and the identity word describing the self as stimulation words to carry out cognitive test; and the internal stealth part recognition test module takes identity words and key abnormal words as stimulus words to carry out cognitive test.

The present application relates to the field of mental fatigue model, and aims to solve the problems of long cycle and complex detection method in establishing mental fatigue model, and provides a method for constructing zebrafish mental fatigue model and application thereof.The method for constructing zebrafish mental fatigue model is as follows: 2-5 dpf zebrafish is given 100% white light and dark alternating stroboscopic cycle stimulation for 0-24 h; then cognitive response behavior analysis is carried out on the zebrafish.The present application constructs a zebrafish model of mental (brain) fatigue induced by white light stroboscopic stimulation, and explores a mental (brain) fatigue model induced by physical stimulation to simulate the environment and life and learning pressure in life.The present application also provides application of the zebrafish mental fatigue model constructed by the method, which is used for evaluating the anti-mental fatigue efficacy of drugs, health foods, foods or medical devices; and is used for mental (brain) fatigue cognitive test, memory test, learning test, reaction ability test and motor ability test of zebrafish.

The present application relates to the technical field of cognitive impairment rehabilitation, in particular to a brain cognitive recovery training scheme analysis system and method for cognitive impairment, comprising five units of basic information acquisition, cognitive test execution, test report generation, norm updating and training scheme analysis, wherein the norm database is modeled in multiple dimensions according to age, educational background and medical history, a regional correction factor is introduced, data freshness is verified by means of blockchain storage, an adaptive sequence is generated for cognitive test, multi-modal data such as correct answer rate, touch screen trajectory and eye movement data are collected, time domain signal separation and denoising are performed, the training scheme analysis unit locates cognitive defects, matches the training module, monitors the brain electrical theta wave and P300 latency through biological feedback, dynamically adjusts the training intensity and frequency, promotes neural circuit reorganization and improves rehabilitation accuracy.

A computer-implemented system and method for delivering scalable precision education through cognitive testing and personalised curriculum generation. The system comprises a memory 114 storing large l

The invention discloses a directional cognitive ability assessment method and device based on virtual reality. The system comprises a universal treadmill, a motion measurement module, a virtual reality helmet, an olfactory electroencephalogram module, a directional cognitive ability assessment module and a monitoring module. The universal treadmill, the motion measurement module, the virtual reality helmet and the monitoring module are connected with the directional cognitive ability evaluation module; the monitoring module is used for collecting and processing physiological signals of a user to obtain a collected information set; and the directional cognitive competence evaluation module is used for evaluating the motion track information of the legs of the user, feedback information of the directional cognitive test information and the like to obtain directional cognitive competence evaluation result information of the user. The universal treadmill is introduced, various psychological and physiological indexes of the user are collected while the user completes the virtual directional cross-country activity, measurement information capable of reflecting the real directional cognitive ability of the user is obtained, and it is guaranteed that the evaluation result is objective and accurate.

The application discloses a multi-modal low-rank adaptive cognitive function estimation method based on physiological-molecular phenotype, belongs to the technical field of cognitive function estimation, and first collects physiological-molecular phenotype, dynamic physiological signals and cognitive test time information of a subject in a plateau hypoxic environment, and constructs a 28-dimensional multi-modal input feature vector after preprocessing; then, a hybrid expert base model is pre-trained based on a source cognitive task with the largest data volume; finally, the base model parameters are frozen for a new target task, a LoRA low-rank adaptive technology is introduced, only a small number of parameters are trained to complete cross-task adaptation, and the cognitive task reaction time and accuracy are output to realize estimation. The application realizes unified estimation of eight types of core cognitive functions, has high migration efficiency, excellent estimation precision and stability, and can be accurately applied to real-time monitoring of cognitive functions of workers in a plateau hypoxic environment.

The invention discloses a cognition-emotion evaluation method and system based on a supernormal child core feature theoretical model. The method comprises the following steps: presenting test tasks to multiple users at a computer end; collecting correct rate data of the work memory ability, the logical reasoning ability, the spatial cognitive ability and the speech ability by utilizing a cognitive test task; collecting non-cognitive test data by using a standardized scale; combining empirical weights, machine learning feature importance and large-scale norm data to establish a fractal dimension and comprehensive total score calculation rule; training a supernormal child identification model by taking Webster child intelligence test and Rayleigh reasoning test results as effect criteria; behavior data of new users are collected, and evaluation system construction and the supernormal child identification model are optimized and iterated. According to the method, various forms of cognitive test, non-cognitive test, static test and dynamic test are combined, and machine learning is utilized to analyze accuracy and non-cognitive scale scores, so that cognitive and emotional characteristics associated with supernormal child identification are accurately mapped.

The invention provides a time series data exception identification and verification method and system oriented to cognitive testing, and relates to the technical field of data processing, and the method comprises the steps: collecting a time series data sample set; extracting time domain features and domain difference features from the original data based on the time sequence data sample set; performing multi-level anomaly recognition according to the time domain features and the domain difference features; and inputting the obtained anomaly detection result of each level into a meta classifier to carry out anomaly comprehensive analysis and confidence judgment at each time point, outputting an anomaly identification verification result, and carrying out verification result identification through the anomaly confidence. The technical problem that in the prior art, due to the fact that standardized cognitive testing depends on macroscopic summary indexes, subtle cognitive anomalies are masked, and then the confidence coefficient of a time series data anomaly recognition result is affected is solved, anomaly analysis is conducted through the multi-level anomaly features and input into the meta classifier, and the time series data anomaly recognition accuracy is improved. And the accuracy and the credibility of time series data exception identification are improved.

The invention relates to the technical field of artificial intelligence and psychological diagnosis, and particularly discloses a psychological health auxiliary diagnosis and intervention system and method based on multi-source data fusion, which ensure authority based on SCID-V and DSM-5 standards; diagnosis terms are automatically converted into a questioning mode suitable for the identity of an evaluated person, and the compliance and authenticity are improved; in combination with a subjective scale, an objective cognitive test and physiological index parameters, the diagnosis scientificity and accuracy are improved; outputting a disease possibility and an interpretable basis based on a machine learning / deep learning model; a graphical diagnosis report is generated and is convenient to understand; longitudinal effect evaluation after multiple evaluation and training is supported, and the method is suitable for scientific research and clinical tracking; localized deployment and privacy protection are supported, and medical data compliance is met.

A means for distinguishing subjects with subtle cognitive impairment in the context of a neuropsychological assessment which comprises a battery of cognitive tests. A first set of tests is administered which have a time-constraint or other cognitive demand parameter imposed. A second set of tests is administered for which the time constraint or other cognitive demand parameter is not imposed. Based on comparing or relating the scores between the two sets of tests, subtle cognitive impairment can be detected, based on a criterion that subjects with subtle cognitive impairment present with a greater disparity in these two sets of scores than do normal subjects.

The invention, which belongs to the technical field of medical artificial intelligence, discloses a multi-modal Transform-based early auxiliary diagnosis system for Alzheimer's disease, comprising a data acquisition module, a preprocessing module, a medical priori knowledge guiding module, a hierarchical feature extraction module, a hierarchical diagnosis module, a lightweight reasoning module and a diagnosis output module. According to the system, multi-modal data such as MRI images, cognitive tests and voice features are deeply fused through a hierarchical Transform architecture, a medical priori knowledge guidance model is introduced to pay attention to tiny changes of key brain areas such as hippocampus, ventricle and temporal lobe, and a lightweight reasoning module is adopted to support efficient operation of a basic medical terminal. A visual thermodynamic diagram is generated through the interpretability analysis module to enhance the interpretability of diagnosis, the accuracy of early detection of Alzheimer's disease is improved to 92%, the reasoning speed is improved by 3-5 times, and a key time window is provided for early intervention and treatment.

A method for delivering electrical stimulation to alter a cognitive state of a user, the method comprising: monitoring a brain signal from the user via one or more intracranial electrodes implanted in the brain of the user while the user is presented with a stimulus; comparing the brain signal to a testing phase biomarker, wherein the testing phase biomarker is derived from a cognitive test performed on a contributor during a testing phase; delivering electrical stimulation to a brain of the user based on the comparing step to steer the brain of the user towards a high performance cognitive state.

The invention provides a cognitive evaluation method, system and device, a medium and a program product wherein the cognitive evaluation method comprises: obtaining test data of a test object, the test data comprising multi-source data generated by the test object in a cognitive test process; obtaining a fatigue index and a cognitive index of the test object based on the test data; and performing cognitive evaluation on the test object based on the fatigue index and the cognitive index. According to the method and the device, the test data of the test object is acquired, the test data comprises the multi-source data generated by the test object in the test process, and the fatigue index and the cognitive index of the test object can be further acquired based on the multi-source test data, so that the fatigue degree and the cognitive condition of the test object are acquired in real time; the test object is subjected to cognitive evaluation through the fatigue index and the cognitive index, dynamic adjustment of cognitive evaluation can be achieved, cognitive evaluation is more targeted, and real cognitive states of different individuals are accurately reflected.

The invention relates to the technical field of cognitive impairment rehabilitation, in particular to a human brain cognitive recovery training scheme analysis system and method for cognitive impairment, and the system comprises a basic information acquisition unit, a cognitive test execution unit, a test report generation unit, a norm updating unit and a training scheme analysis unit, a norm database performs multi-dimensional layered modeling according to age, education background and medical history, introduces a regionalized correction factor, stores an evidence through a block chain and verifies data freshness, generates an adaptive sequence through cognitive testing, collects answer accuracy, a touch screen track and eye movement data in a multi-modal manner, performs time domain signal separation and denoising, and trains a scheme analysis unit to position cognitive defects. The training module is matched, the incubation period of electroencephalogram theta waves and P300 is monitored through biological feedback, the training intensity and frequency are dynamically adjusted, neural circuit recombination is promoted, and rehabilitation accuracy is improved.

This invention discloses a multimodal cognitive screening method and apparatus based on brain-computer interface and facial expression recognition. The apparatus includes: a brain-computer interface module, an image acquisition module, a signal feature extraction module, and a cognitive assessment module. The brain-computer interface module is used to acquire the electroencephalogram (EEG) signal sequence of a user during a cognitive test. The image acquisition module is used to acquire a set of facial expression images of the user during the cognitive test. The signal feature extraction module is used to perform feature recognition and extraction processing on the acquired EEG signal sequence and facial expression image set to obtain an EEG feature sequence and an expression category sequence. The cognitive assessment module is used to perform fusion assessment processing on the EEG feature sequence, expression category sequence, facial expression image set, and EEG signal sequence to obtain a cognitive impairment assessment result.

The invention relates to a portable, autonomous device for evaluating sensory and cognitive problems, characterised in that it comprises: - a processor configured to acquire and analyse real-time data; - an ECG module for capturing the user's heart rate variability (HRV) in response to sensory and cognitive stimuli; - an inertial measurement unit (IMU) comprising an accelerometer and a gyroscope, configured to detect and record the movements and posture of the user; - a capacitive touch screen for interaction with the user for carrying out standardised cognitive tests; - an integrated memory for storing the captured data and the programs; - a wireless connectivity module for transmitting the data to an external device; and in that the device is configured to perform, in real time, at least one evaluation of the impact of the disruptive sensory stimuli, including motion sickness and virtual-reality sickness, in uncontrolled environments.

An apparatus and a method for providing a user-customized program for improving cognitive ability are provided. The method comprises the steps of: providing a first questionnaire for a cognitive test to a terminal of a user; upon receiving a first response to the first questionnaire from the user terminal, calculating dementia risk of the user on the basis of the first response; providing a first training program for a preset first period to the user terminal on the basis of the dementia risk; providing, to the user terminal at the end time point of the first period, a second questionnaire for a lifestyle assessment based on the first response; upon receiving a second response to the second questionnaire from the user terminal, calculating a first lifestyle score of the user on the basis of the second response; and providing a second training program for a preset second period to the user terminal on the basis of the first lifestyle score.

A method for adjustment of a cognitive testing routine in dependence upon detection of a motor impairment of the patient during performance of the cognitive testing routine. In particular, a workflow for administering a neuropsychological assessment which comprises one or more cognitive tests is adjusted in dependence upon detection of a motor impairment.

The invention discloses a real-time cognitive test evaluation method and system based on a connection test and electronic equipment. The method comprises the following steps: calculating a first cognitive test sub-evaluation value and a second cognitive test sub-evaluation value of each cognitive test corresponding to a testee; calculating a cognitive test total evaluation value of each cognitive test; determining a plurality of cognitive test types, and determining a cognitive test type model corresponding to each cognitive test type; the historical type data is divided into a type training set and a type test set, the type training set is adopted to train a cognitive test type model corresponding to each cognitive test type, the type test set is adopted to evaluate each trained cognitive test type model, and a model evaluation accurate value of each cognitive test type model is obtained; and calculating a type comprehensive evaluation value of each cognitive test type based on all cognitive tests, the cognitive test total evaluation value, the model evaluation accurate value and multiple cognitive test types. The accuracy of the evaluation result can be improved.

The invention relates to the technical field of subject cognition testing, and discloses a subject selection response testing method and device and a storage medium, the testing is divided into at least two stages, multi-dimensional biological information of a subject in the testing process is obtained, the multi-dimensional biological information can reflect the comprehensive performance of the subject in the testing process, and the comprehensive performance of the subject in the testing process can be reflected by the multi-dimensional biological information. And the performance grade of the subject can be determined through the multi-dimensional biological information, so that a reliable basis is provided for generation of a customized test scheme in the next step. And finally, a target display strategy, a plurality of target selection objects and a plurality of target interference objects of the next stage are generated in a customized manner by integrating historical test results and subject performance levels corresponding to the historical test results. The test of the next stage is generated based on historical test and comprehensive performance, so that the pertinence is higher, the obtained test result is more reliable, and finally the reliability of the subject selection reaction test is improved.

The application relates to a nuclear power plant operator pre-service evaluation method and device, computer equipment, a readable storage medium and a program product. The method comprises the following steps: establishing a questionnaire test library and a cognitive test library, obtaining multi-dimensional questionnaires and multi-dimensional test questions from the questionnaire test library and the cognitive test library according to a pre-service test plan, generating pre-service evaluation test questions based on the multi-dimensional questionnaires and the multi-dimensional test questions, obtaining evaluation test results fed back by an operator for the pre-service evaluation test questions through a client, obtaining questionnaire scores of each dimension questionnaire according to questionnaire test results, obtaining cognitive scores of each dimension test question according to cognitive test results, obtaining a current test score according to the questionnaire scores and the cognitive scores, and evaluating a pre-service state of the operator based on the current test score and a personal norm score corresponding to the operator. The method can improve evaluation efficiency.

The invention provides an artificial intelligence model cognitive evaluation question generation method and system based on a DIKWP five-layer cognitive model (data, information, knowledge, wisdom and intention). By constructing a cognitive layer and AI capability dimension mapping table and a DIKWP * DIKWP semantic interaction matrix, a multi-language multi-mode engine is utilized to automatically generate test questions covering cognition of each layer, and question stems, options and reasoning prompts are output in a template form. The system adopts a dynamic sampling algorithm to regulate and control difficulty distribution, subjects are attached with labels such as cognitive categories, ability dimensions, difficulty, standard answers and the like, and evaluation and training reuse is supported. And a built-in verification mechanism ensures consistent logic, clear expression and reliable evaluation. Experiments prove that the method can quickly construct a high-quality sample library, realizes full-link quantitative evaluation of a large model from perception to intention, and improves the standardization and diagnostic value of white-box evaluation.

The application discloses a kind of based on brain-computer interface and multimodal cognitive screening method and device of skin electricity ring, the device includes: brain-computer interface module, skin electricity ring, signal feature extraction module, cognitive assessment module;The brain-computer interface module is used to collect the electroencephalogram sequence of user when carrying out cognitive test;The skin electricity ring is used to collect the electrodermal signal sequence of user when carrying out cognitive test;The signal feature extraction module is used to carry out feature extraction processing to the electroencephalogram sequence and electrodermal signal sequence collected, and obtains electroencephalogram feature sequence and skin electricity feature sequence;The cognitive assessment module is used to carry out cognitive impairment assessment processing to the electroencephalogram feature sequence, skin electricity feature sequence, electrodermal signal sequence and electroencephalogram sequence, and obtains cognitive impairment assessment result.

The invention belongs to the technical field of psychological health informatization, and discloses a psychological health inquiry and auxiliary diagnosis double-end architecture system which realizes intelligent acquisition, data fusion analysis, auxiliary diagnosis and intervention management of psychological health problems through cooperative operation of a user end and a physician end. The double-end architecture of the system is used for giving consideration to the self-service inquiry experience of the user and the professional diagnosis requirement of the doctor; through multi-source data fusion of natural language, scale and cognitive test, the diagnosis accuracy is improved; structured medical records are automatically generated, intervention suggestions are intelligently output, and the burden of doctors is relieved; the system can realize continuous tracking, provides follow-up visit and effect evaluation functions, and supports long-term mental health management; the system provided by the invention meets the medical data privacy protection requirement and supports local deployment of hospitals.

The disclosure is concerned with a method of identifying, evaluating and / or optimizing a functional health product benefit connoted by a flavour composition, said method comprising the step of employing an implicit cognitive test to measure a human subject's sub-conscious association between the flavour composition and the functional health product benefit.

This application discloses a method, apparatus, device, medium, and product for cognitive function assessment, relating to the fields of computer and speech processing technology. The method includes: acquiring target speech data; extracting features from the target speech data according to feature categories within a preferred subset of speech features corresponding to the target cognitive test task, obtaining a target speech feature set; inputting the target speech feature set into a cognitive function assessment model corresponding to the target cognitive test task, obtaining the cognitive function assessment result of the target test subject; wherein, by constructing a multimodal cognitive database, extracting wide-area speech features from each form of speech data in the database, and based on the wide-area speech features and corresponding cognitive function assessment results, selecting a preferred subset of speech features based on the correlation strength with cognitive function, and determining the cognitive function assessment model, machine learning and statistical methods are used. This application achieves accurate and efficient cognitive function assessment.

The application discloses a method for differentiating Late-Life Depression (LLD) and amnestic Mild Cognitive Impairment (aMCI) based on plasma metabolomics combined with neural cognitive evaluation. The application detects metabolite spectrum in the plasma of the subject by hydrogen proton magnetic resonance spectrum metabolomics technology, screens out Scyllo-inositol as a key differential marker, and combines with neural cognitive test scores (especially memory scale scores) to construct a joint diagnosis model. The method can effectively distinguish LLD, aMCI and healthy control groups, and has high diagnostic accuracy and specificity. In addition, the method further introduces two-way double-sample Mendelian Randomization (MR) analysis to verify the causal relationship between Scyllo-inositol and the risk of dementia from the genetic point of view, and to strengthen the reliability of Scyllo-inositol as a biomarker. The application provides a diagnosis method with both metabolomics and genetic evidence support for early identification, accurate typing and intervention of high-risk groups of senile dementia, and has important clinical application value.

The invention relates to the technical field of medical data processing, in particular to a tracking and collecting system for postoperative cognitive health information of old patients in the perioperative period. The system comprises a data acquisition module, a cognitive analysis module and a data correction module which are respectively used for acquiring multi-source health data of an elderly patient; dividing the whole course of a single cognitive test into a plurality of time periods, and determining an attention decline index of the elderly patient based on the reaction time and the error rate of each time period; analyzing an attention decline index and cognitive health data and weakness degree data of the elderly patient, and determining an inhibition condition value of information acquisition accuracy of each time period; and inputting the inhibition condition value as the data weight of the cognitive health data into the trained neural network model, and outputting the corrected cognitive health data. According to the method, the evaluation accuracy of the postoperative cognitive function change of the perioperative old patient is effectively improved.