50 results about "Neurocognitive" patented technology

The invention discloses a concentration-fatigue cooperative regulation and control method and system based on electroencephalogram bimodal feedback, and the method comprises the steps: collecting first electroencephalogram data of a student in a resting state before training, and calculating a mean value of the ratio of a theta wave to an alpha wave as a fatigue resting state reference value; after training is started, second electroencephalogram data of the trainee are collected, a concentration index is calculated according to the ratio of the beta wave to the sum of the beta wave, the theta wave and the alpha wave, and a fatigue index is calculated according to the ratio of the theta wave to the alpha wave; calculating a dynamic threshold value according to the fatigue resting state reference value; and generating a corresponding risk prompt according to whether the concentration index and the fatigue index deviate from their thresholds. According to the method, the limitation of traditional single-dimensional biofeedback is broken through, the safety and efficiency of complex task training are remarkably improved, the limitation of the traditional single-dimensional biofeedback is broken through, and a quantitative neurocognitive enhancement scheme is provided for special operation training.

The invention relates to the technical field of cognitive data processing, in particular to a physical stimulation driven lymphatic circulation and cognitive improvement method and system. The system comprises a physical stimulation frequency influence evaluation module, a stimulation mechanical vibration analysis module, a lymph circulation vibration calibration module and a stimulation frequency drive adjustment module. A pressure sensor and a temperature sensor can be used for monitoring corresponding physical stimulation pressure and stimulation skin surface temperature in real time and performing stimulation frequency influence evaluation and stimulation mechanical vibration analysis so as to generate a physical stimulation mechanical vibration effect; and acquiring a lymph circulation velocity and an electroencephalogram neural activity signal, performing neurocognitive level analysis and vibration response calibration, and performing lymphatic circulation cognitive regression analysis and stimulation frequency driving adjustment at the same time, so as to generate a physical stimulation frequency driving adjustment scheme corresponding to lymphatic circulation cognitive improvement. According to the method, the incidence relation among physical stimulation, lymphatic circulation and cognitive promotion can be accurately analyzed.

The invention discloses an upper limb rehabilitation control method and system based on a multimode coordination adaptive brain-computer interface, and belongs to the technical field of neural rehabilitation engineering and brain-computer interfaces. The system comprises a brain signal acquisition module, a self-adaptive residual filtering module, a feature extraction module, a predictive control module, an upper limb rehabilitation actuator and a self-adaptive updating module. The core is that a self-adaptive updating module constructs a composite error cost function by fusing kinematics errors of a physical layer and error correlation potentials of a neurocognitive layer, and on the basis of the composite error cost function, a front-end filtering weight and a network weight of a rear-end control model are synchronously adjusted, so that full-link parameter collaborative optimization from signal preprocessing to motion control is realized. According to the method, the framework limitation of single error feedback and independent parameter optimization of a traditional system is broken through, a closed-loop brain-computer interface system which can sense internal and external states and has system-level self-optimization capability is constructed, and the decoding robustness, the control precision and the practicability under long-term use are effectively improved.

The invention relates to the technical field of automatic driving, and discloses an end-to-end automatic driving system based on electroencephalogram intention modeling and machine mental reasoning, and the system comprises an electroencephalogram signal collection module which is used for collecting an electroencephalogram signal of a driver in real time and carrying out the preprocessing of the electroencephalogram signal; the electroencephalogram intention decoding module is used for extracting driving intention features and outputting structured intention vectors; the machine mental reasoning module is used for fusing the intention vector, the vehicle state and the environment perception information, deducing the mental state of the driver and outputting a mental state vector; and the end-to-end automatic driving control module is used for performing multi-modal fusion on the intention vector, the mental state vector, the environment perception characteristics and the vehicle dynamic state to generate a continuous vehicle control instruction. According to the method, the neurocognitive activity of the driver can be converted into decision-making elements which can be understood and utilized by a machine in real time, so that man-machine cognitive alignment and closed-loop cooperative control are realized.

The invention discloses a music teaching system based on artificial intelligence, and particularly relates to the technical field of artificial intelligence, and the music teaching system comprises a neurocognitive adaptation module, a music DNA map construction module, a cognitive load monitoring module, an anti-AI dependence adjustment module and a multi-source data fusion unit. According to the music teaching system based on artificial intelligence, a dynamically evolved personalized teaching model is constructed through multi-modal data fusion and real-time analysis driven by artificial intelligence. The neurocognitive adaptation module is combined with electroencephalogram feature analysis and physiological signal monitoring to accurately capture cognitive preferences and ability bottlenecks of the learner; the music DNA map is based on the quantum enhancement modeling technology, the skill development trajectory is continuously updated and predicted, the AI teaching strategy can realize millisecond-level dynamic adjustment according to the neural feedback and behavior data of the learner, the skill mastering efficiency and the knowledge retention rate are remarkably improved, and the limitation of staticization and simplification of a traditional teaching system is broken through.

A method and system for diagnosing an idiopathic psychosis patient and improving treatment targeting for that patient. Cognitive performance is measured on the patient. Pro- and anti-saccade signals are measured on the patient. Motor inhibition is measured on the patient. EEG signals are measured on the patient. Principal components analysis is applied to the measured signals and scales to determine the most significant features. The patient is evaluating on at least 11 dimensions of neuro-cognitive performance. A trained numerical taxonomy approach is used to classify the patient as belonging to a B-SNP psychosis Biotype and the patient's condition is categorized based on the classified Biotype. The B-SNIP psychosis Biotype is used to implement targeted treatment for an individual patient. The diagnostic algorithm is continuously re-trained using new cases and new laboratory tests to improve precision of B-SNIP psychosis Biotypes diagnosis and the accuracy of selecting treatments for individual patients.

The invention relates to the technical field of light atmosphere, and discloses a light atmosphere effect generation method, which comprises the following steps: generating an initial wave function according to an intensity field, deducing on the basis of a potential energy field to obtain a first wave function, performing intensity calculation and phase extraction from the first wave function to obtain a second wave function, updating the direction field based on the second wave function to obtain an updated direction field and an enhanced optical flow field; three core advantages of light atmosphere generation are realized, firstly, deep coupling of quantum optics and neurocognition is realized, real response of human eyes is simulated through a phase-sensitive light response model, and light atmosphere distribution is enabled to conform to quantum propagation rules and human visual cognition characteristics in combination with a cognition attention focusing mechanism of a DQN model; and 2, a dynamic self-adaptive mechanism runs through the whole process, and a light current coefficient and object motion data are adjusted in real time through the pupil diameter to feed back a new light flow field so as to ensure that the environment change can be quickly responded.

The present invention relates to a multifunctional portable device and system for physical and neurocognitive training. The device comprises a casing consisting of a casing body and a casing lid. The casing houses therein a visual interface, a controller with wireless connection, a battery, a vibrating motor, one or more sensors configured to measure at least one parameter selected from distance, acceleration, angular velocity in different axes, heart rate, blood oxygen level, force and weight. The multifunctional portable device comprises assembly elements located on the casing that are configured to allow a user to perform physical training and allow one or more users to perform neurocognitive training.

A method of managing a disorder associated with a circadian rhythm disorder in a subject by administering to the subject an effective amount of a beta glucan oligosaccharide and / or an arabinose oligosaccharide. More specifically, the management includes treating a symptom associated with a circadian rhythm disorder, primary preventing a symptom associated with a circadian rhythm disorder, secondary preventing a symptom associated with a circadian rhythm disorder, and / or delaying progression of a symptom associated with a circadian rhythm disorder. The symptoms to be managed include symptoms related to sleep, symptoms related to emotion, symptoms related to cognitive function decline and neurocognitive decline, and the like. In particular methods herein, the risk of developing a symptom associated with a circadian rhythm disorder in the subject is assessed prior to administration of the beta glucan oligosaccharide and / or arabinose oligosaccharide. Also provided are medicaments, nutritional formulations, nutritional supplements and pharmaceutical compositions comprising an effective amount of beta glucan oligosaccharides and / or arabinose oligosaccharides for use in such treatment, prevention and delay.

The application discloses a kit for predicting the risk of neurocognitive recovery delay and application thereof. The kit comprises reagents for detecting the expression level of lipid metabolism markers in a sample, wherein the lipid metabolism markers comprise at least one of TG (58:7 / 22:5), TG (54:2 / 18:1), PE (O-16:0 / 18:1) and CL (72:3 / 18:2). The application finds through experiments that, compared with non-neurocognitive recovery delay (non-dNCR) patients, the expression level of TG (58:7 / 22:5) and TG (54:2 / 18:1) in dNCR patients is down-regulated, and the expression level of PE (O-16:0 / 18:1) and CL (72:3 / 18:2) in dNCR patients is up-regulated. By detecting the expression level of the aforementioned lipid metabolism markers, the risk of dNCR of a patient can be confirmed before and / or in an early stage after surgery, early intervention and treatment are facilitated, and postoperative repair is promoted.

The present invention is directed to beneficially directing the bidirectional communication that exists between the brain and the gut so as to influence brain physiology, psychological responses and ultimately behavior in a positive manner by regulating an individual's mood, psychological symptoms, such as anxiety and depression and stress-related changes in brain function, by modifying the gut microbiome of an individual. In various embodiments, an individual's microbiome is modified in a manner to reduce the likelihood of stress, to reduce or treat symptoms affecting mental health and to promote the mental health of the individual. In certain embodiments, administration to an individual of at least three different bacteria species are combined to modify an individual's microbiome, selected from the group of Lacticaseibacillus paracasei, Coprococcus, Roseburia, Bifidobacterium, L. casei and Faecalibacterium prausnitzii, to reduce adverse psychological and / or physiological responses attendant to psychological stress.

The invention relates to a measuring system for repeatedly measuring reaction time curves in complex neurocognitive tasks. The measuring system comprises a measuring body, at least one force source, at least one holding device, at least one triggering unit, at least one first sensor unit for acceleration measurement, at least one second sensor unit, at least one interface for data transmission and at least one data processing unit. The invention likewise relates to a method for quantifying reaction times, in which a measuring system is used. Thereby, human influences in the implementation of the test are avoided as far as possible. By shifting the data processing, the measuring system can construct a growing and anonymous data base independently, which improves the accuracy through its continuously growing data volume. Thereby, conclusions about potentially risky changes in the reaction time can also be achieved up to the indication and / or recognition of neurodegenerative diseases.

The present device aims to create ideal conditions for performing human profiling, assessment and testing processes, in a controlled, simple, accurate, inclusive and distraction-free manner. In order to achieve this aim, the device offers a minimalist, dedicated interface, having a simplified physical keypad that can have various formats depending on the application. During the performance of the test, built-in or peripheral cameras and sensors can collect additional information relating to the attentional, cognitive, physiological and emotional state of the user. This data is processed by the device in order to generate information that can be combined with the other results to produce an even more in-depth assessment of the subject being tested. The entire assessment process can take place in online mode, allowing immediate synchronization with a server, or in offline mode, allowing subsequent synchronization with a server or the downloading of the data directly to a computer. In both cases, an administrative dashboard accessible via the device or via the web can be used to download or create new tests, update the existing tests, register users, view the results and manage the entire assessment process. Finally, the possibility of presenting the test stimuli by means of virtual reality goggles further increases the potential uses and versatility of the equipment.

The application discloses an enterprise capability evaluation method based on neural cognitive diagnosis technology, comprising the following steps: 1, dividing the technology achievement data into fields, and constructing negative samples of interactive data; 2, constructing a basic neural cognitive diagnosis enterprise capability evaluation learning module, obtaining embedded vector representations such as field mastery, technology achievement difficulty and discrimination, and performing representation learning on the target embedded vector; meanwhile, the embedded vector is interacted, and self-adaptive learning is performed after two full connection layers; 3, constructing a partial order sorting learning module, and constructing a BPR loss after a partial order learning module, an expected capability change module and an enterprise-technology achievement interactive result constraint design module; 4, using cross-entropy loss and contrast loss to optimize the self-adaptive diagnosis network of the whole model. The application utilizes enterprise-technology achievement interactive data to perform self-adaptive diagnosis on technology enterprise capability evaluation, thereby providing an effective method for enterprise capability evaluation in different fields.

1. Name of the Design Product: Therapeutic Apparatus (Head-mounted Remote-controlled Acousto-optic Dual-mode Neural Regulation). 2. Use of the Design Product: Mainly applied to clinical neurocognitive enhancement and promotion of nerve rehabilitation. 3. Design Key Points of the Design Product: Lies in the shape. 4. Picture or Photo that Best Illustrates the Design Key Points: Perspective view.

Methods and systems for automated neurocognitive training to extend relief of treatment-resistant mental disorders are described herein. An example method includes administering a drug having an antidepressant effect to a patient, and administering a neurocognitive training protocol to the patient during a critical time period following administration of the drug. Additionally, the step of administering the neurocognitive training protocol to the patient includes delivering, using a computing device, a plurality of automated neurocognitive training sessions to the patient. A plurality of conditioning sequences are presented to the patient during delivery of each of the automated neurocognitive training sessions, where each respective conditioning sequence includes a respective non-self-relevant stimulus and a respective self-relevant stimulus.

The present application relates to a kind of fusion cognitive transfer teaching evaluation sentiment analysis method, belong to the field of educational informationization.The method includes: the data collected is cleaned and preprocessed;Unstructured teaching evaluation text is carried out word embedding using BERT language model, it is input in bidirectional GRU network and learns, the context hidden memory information of output text;Student historical practice record is modeled using neural cognitive diagnosis model, and the personalized cognitive ability vector of student is obtained as prior knowledge representation;The text hidden memory information extracted is fused into cognitive transfer matrix with prior knowledge information, and prior knowledge is transferred into text memory by attention mechanism, and the real emotional characteristics contained in text are enhanced.The present application can accurately classify the sentiment of teaching evaluation text carrying conflictive emotional characteristics, solve the problem that sentiment is misclassified due to the existence of conflictive emotional characteristics in teaching evaluation.

The invention discloses an AI-based product ergonomics design method, and relates to the technical field of product ergonomics, and the method comprises the steps: collecting a real-time multi-modal data stream of a user, and carrying out the preprocessing; carrying out weighted fusion and feature extraction on the preprocessed multi-modal data flow by utilizing a multi-source data fusion network of an attention mechanism, and generating a current ergonomic state evaluation result of the user; when the current ergonomic state evaluation result of the user indicates that the risk exists, calling a personalized skeletal muscle digital twinborn model of the user, calculating the real-time stress distribution of the internal tissue of the user in combination with the multi-modal data stream, and analyzing the electroencephalogram signal in the multi-modal data stream to judge the neural adaptability level; and generating an intelligent collaborative intervention decision instruction. According to the method, biomechanical simulation and neurocognition evaluation are deeply fused, so that the spanning from macroscopic attitude regulation to microscopic stress optimization and from one-way intervention to adaptive learning is realized, and the accuracy, humanization and sustainable evolution ability of ergonomic design are improved.

The invention discloses a cognitive diagnosis method based on emotion perception field adaptation, which comprises the following steps of: 1, constructing a cognitive diagnosis relationship according to interaction records of students and exercises and association between the exercises and knowledge concepts; 2, constructing a source model and a target model, wherein the source model and the target model have similar structures in a student, practice and knowledge embedding layer and a plurality of full connection layers; 3, under the condition of no emotion label, comprehensively considering the emotion characteristics and practice difficulty of the student, and generating an emotion pseudo label in a source domain emotion perception training module; 4, training a source domain model by using a data set with emotion annotation, including an emotion prediction module, an emotion guessing module and a sliding module, reducing domain distribution differences based on an MMD method, and performing fine tuning on a target domain; and 5, integrating the emotion perception module with the basic neurocognitive diagnosis framework based on the DINA model to obtain an optimal cognitive diagnosis model. According to the method, emotion prediction and cognitive diagnosis can be realized without emotion tags, so that the accuracy and robustness of cognitive diagnosis are improved.

This invention discloses an AI-based product ergonomic design method, belonging to the field of product ergonomics technology. The method includes: collecting and preprocessing real-time multimodal data streams from users; using a multi-source data fusion network with an attention mechanism to perform weighted fusion and feature extraction on the preprocessed multimodal data streams to generate an assessment result of the user's current ergonomic state; when the assessment result indicates a risk, calling the user's personalized skeletal muscle digital twin model and combining it with the multimodal data stream to calculate the real-time stress distribution of the user's internal tissues, and analyzing the EEG signals in the multimodal data stream to determine the level of neural adaptability, generating intelligent collaborative intervention decision instructions. This invention, through the deep integration of biomechanical simulation and neurocognitive assessment, achieves a leap from macroscopic posture control to microscopic stress optimization, and from unidirectional intervention to adaptive learning, improving the accuracy, humanization, and continuous evolution capabilities of ergonomic design.

The application discloses application of diacylglycerol in preparation of medicines for improving nutritional composition of breast milk and promoting neural development of offspring, and belongs to the technical field of medicines. The complete technical chain of "maternal intake of DAG, remolding of breast milk lipids (enrichment of long-chain polyunsaturated ether lipids), activation of 2-AG signal pathways of offspring, and promotion of neural cognitive development" is provided, which provides a scientific basis for development of new maternal nutrition products, and has extremely high clinical application value and industrialization prospect.

A system and method operates for diagnosis of mild traumatic brain injury (mTBI) to prevent sequelae and improve neurocognitive outcomes. The system may have a processor that receives, from a magnetic resonance imaging machine, data corresponding to magnetic resonance imaging images. By using a machine learning classifier of the processor, such as a Bayesian machine learning classifier, the processor identifies mild traumatic brain injury in a person through cortico-cortical connectome mapping from magnetic resonance imaging. The processor can also generate a human readable screen display indicative of the identified mild traumatic brain injury.

This invention relates to the field of cognitive data processing technology, and more particularly to a method and system for physical stimulation-driven lymphatic circulation and cognitive enhancement. The system includes a physical stimulation frequency impact assessment module, a stimulation mechanical vibration analysis module, a lymphatic circulation vibration calibration module, and a stimulation frequency drive adjustment module. It utilizes pressure and temperature sensors to monitor the corresponding physical stimulation pressure and the surface temperature of the stimulated skin in real time, performing stimulation frequency impact assessment and stimulation mechanical vibration analysis to generate a physical stimulation mechanical vibration effect. It also acquires lymphatic fluid flow velocity and EEG neural activity signals, performing neurocognitive level analysis and vibration response calibration. Simultaneously, it performs lymphatic circulation cognitive regression analysis and stimulation frequency drive adjustment to generate a physical stimulation frequency drive adjustment scheme corresponding to lymphatic circulation cognitive enhancement. This invention can accurately analyze the correlation between physical stimulation and lymphatic circulation and cognitive enhancement.

Methods of treating Alzheimer's disease and other neurodegenerative and / or neurocognitive and / or neurodevelopmental diseases are described. The methods comprise the administration of compounds that modulate an activity of cell division control protein 42 (Cdc42), such as the interaction between Cdc42 and intersectin (ITSN). Exemplary modulator compounds include thioureas, disulfonamides of fused aromatic systems (e.g., benzofuran), and acyl hydrazones, among others. Some of the modulator compounds act as activators of Cdc42, while others act as inhibitors. In some cases, the modulator compound has dual functionality and the ability of the modulator compound to act as an inhibitor or activator depends on whether or not Cdc42 is already activated in a particular disease stage or biological environment by an upstream activating signal of Cdc42.

Described herein is an automated neurocognitive training method and system for extending the alleviation of treatment-resistant psychiatric disorders. An exemplary method includes administering a drug having an antidepressant effect to a patient, and administering a neurocognitive training protocol to the patient during a critical period after administration of the drug. Furthermore, administering the neurocognitive training protocol to the patient includes providing the patient with a plurality of automated neurocognitive training sessions using a computing device. During each of the automated neurocognitive training sessions, a plurality of conditioning sequences are presented to the patient, each conditioning sequence including a respective non-self-related stimulus and a respective self-related stimulus.

Exemplary system, method and computer-accessible medium can be provided to monitor electroencephalography (EEG) data from the patient during an emergence from a general anesthesia previously provided to the patient, and predicting neurocognitive impairment based on a slope of EEG power. The neurocognitive impairment predicted can be delirium or it may be a predictor of long-term impariment such as Alzheimers. Further, the system and method can be used to direct a medical intervention based on the predicted neurocognitive impairment.

The invention discloses a cognitive ability prediction method and system, electronic equipment and a readable storage medium. The method comprises the following steps: extracting frequency domain features of electroencephalogram signals; extracting functional connection characteristics of the electroencephalogram signals; constructing a neurocognitive double-effect hypothesis equation based on the frequency domain features and the functional connection features; calculating a cognitive ability value according to a neurocognitive double-effect hypothesis equation; and performing cognitive ability prediction based on the cognitive ability value to obtain a cognitive ability prediction result. According to the method, the overall neural calculation efficiency can be quantified by integrating neural energy consumption, network connection lines and task difficulty, and the accuracy of cognitive ability prediction can be improved.

System and method in field of human resource management, leadership development, executive succession planning, organizational culture modeling, recruitment, talent management, and individual capability profiling. System integrates memory certification protocols with neurocognitive and emotional profiling, creating a multi-dimensional platform for individual and organizational development through verified autobiographical, observational, and interpersonal memory artifacts. Provides a legally defensible foundation for employment, promotion, and succession decisions, additionally enabling potential use in broader legal contexts such as law enforcement, insurance underwriting, and compliance audits.

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.