47 results about "Cognitive behaviour" patented technology

A user monitoring device system includes a user monitoring device with a microphone and sensors to determine air quality, sound level / quality, light quality and ambient temperature near the user. A movement detection device detects a user's movement information. The movement detection device and the monitoring system assist to determine user sleep information and sleep behavior information. The microphone records user movement sounds detected by the movement detection device. The movement detection device is configured to cause the microphone to stop recording user movement sounds when the movement sounds are not directed to a sleep related parameter. In response to determining user sleep information or sleep behavior information the system is used for treatment of sleep or psychiatric disorders.

The invention discloses a vascular basis-brain connection and cognitive behavior model construction method based on fMRI. The method comprises the following steps: S1, preprocessing brain function magnetic resonance data by using SPM12 and NIT; S2, finding out a gradient analysis and hierarchical function connection difference brain region as a region of interest, and extracting a gradient value and a hierarchical function connection value corresponding to the region of interest; S3, depicting a vascular aging state by using a kidney medulla R2<*> value; S4, collecting the score of a tested behavior cognition test; S5, performing Pearson's correlation analysis on the functional connection value of the region of interest and indexes for depicting the vascular aging, and performing Pearson'scorrelation analysis on the functional connection value of the region of interest and the score of the behavior cognition test; and S6, carrying out Pearson correlation analysis on the indexes of thevascular aging and the scores of the behavior cognition test. According to the invention, based on functional magnetic resonance, a brain aging research model of vascular basis-brain connection-cognitive behaviors is constructed from the perspective of a hierarchical network, and new evidences are provided for understanding of a brain aging function connection mechanism.

The invention discloses an individual cognitive ability prediction method and system based on dynamic function connection. The method comprises the following steps: acquiring functional magnetic resonance imaging data in a resting state; extracting an average time sequence signal of each brain region through a brain template after preprocessing of the functional magnetic resonance imaging data; calculating and constructing a dynamic function connection matrix by using a sliding time window; with the dynamic function connection matrix as input high-dimensional dynamic brain description originaldata, constructing a model combining convolution and a long-short-term memory network; and substituting a dynamic function matrix and corresponding cognitive behavior data into the model for trainingand testing so as to realize prediction of cognitive competence. According to the invention, dynamic information of brain function connection is fully utilized, the advantages of a deep learning method in big data processing are utilized, calculation is rapid, prediction effect is ideal, various behavior data of a population can be predicted, dependence on the absolute value of the amplitude of imaging signals is avoided, migrations among different MRI machines can be realized, and prediction performance is excellent.

The technology disclosed relates to a system and method for remembering content received from a patient for future use and understood by computerized natural language processing during a chatbot therapy session. The system includes a graph of entities and relationships in an artificial memory graph data structure. The entity nodes in the graph represent entities that are related to a patient root node representing the patient. The entity nodes are connected to patient root node by one or more relationship edges that have named roles. The entity nodes and / or relationship edges can be slotted for at least a distinguishing name, a patient sentiment towards the entity and an entity state.

The invention relates to a BDI modeling method and device based on a knowledge graph, equipment and a medium. The method comprises the steps that: a simulation task of a simulation model is acquired; perception elements are extracted from the simulation task, and a perception space map is established according to the perception elements; action elements are extracted from the simulation task and the sensing space map, and an action space map is established according to the action elements; cognitive elements are extracted from the simulation task, the perception space map and the action space map, and a cognitive space map is established according to the cognitive elements; according to the perception space map, a belief in BDI is constructed; according to the perception space map, the action space map and the cognitive space map, wishes and intentions in BDI are constructed; and according to the constructed belief, wish, intention and action space atlas, a cognitive behavior atlas of the simulation model agent is modeled. By adopting the method, the behaviors and the relationship between the behaviors can be described, and the method is realized in a mapping low-code mode.

A method and system are disclosed for a novel architecture in which competing suggestions, possibly generated by competing systems, are selected by a Cognitive Unit (CU). The CU observes the user context and learns which contextual circumstances affect the user's cognitive behaviour. Majority of the traditional models trained over multiple users fail to represent the individual because (1) they ignore personal bias toward certain decisions and (2) they don't have complete visibility of all options available to users (i.e. from competitive systems). The invention is ideally suited to interact with several other products as more and more modern products are using AIs to drive the user experience. That shifts traditional HCI towards a novel form of interaction that we call human-AI interaction (HAII). When applied to user experience, predictive models make decisions on users' behalf attempting to minimise user interaction while guiding them toward the completion of predefined funnels. This invention presents a novel approach using a personal model capable of partially replicating cognitive behaviours by learning personal situational biases using the CU. By leveraging the personal biases, the system allows the AI to learn situational biases otherwise not available to predictive models. Once trained cognitive unit can supplement the decision-making process of the user.

The invention discloses a distributed near-end strategy optimization method based on cognitive behavior knowledge and application thereof, and the method comprises the following steps: employing cognitive behavior knowledge to establish a cognitive behavior model of an Agent, introducing the cognitive behavior model into deep reinforcement learning, and constructing a deep reinforcement learning framework based on cognitive behavior knowledge; based on the deep reinforcement learning framework, providing a distributed near-end strategy optimization algorithm based on cognitive behavior knowledge; and quantitatively designing a guide mode of the cognitive behavior model for Agent strategy updating, and achieving continuous learning of the Agent on the basis of cognitive behavior knowledge. According to the method provided by the invention, cognitive behavior knowledge can be effectively utilized, and strategy updating is carried out on the basis, so that the learning efficiency of the Agent is improved.

The invention discloses a training system based on cognitive behavior therapy, relates to the technical field of medical instruments, integrates theoretical advantages of the cognitive behavior therapy and interaction advantages of a software system, improves interestingness and acceptability of the cognitive behavior therapy through online interaction training, and further improves training experience of a user. The system comprises: a storage unit which is used for storing multiple groups of cognitive behavior training schemes; an interaction unit which is used for displaying the training scheme selected by the user to the user through a display according to a preset rule and implementing cognitive training; and a feedback unit which is used for acquiring interaction actions generated by the user based on the cognitive training process and feeding back a cognitive judgment result to the user in real time through the display according to the real-time content of the cognitive training and the corresponding interaction actions.

The invention discloses a research method for evaluating the cognitive performance of a driver based on driving behaviors. The method comprises the following steps: step one, carrying out data preprocessing of a collected experimental database; step two, in a regression function, selecting features by using a Pearson coefficient, constructing functions of lasso regression and rid regression, and performing cross validation to improve the accuracy and obtain predicted cognitive performance; step three, predicting cognitive behaviors of the driver through two methods; and step four, analyzing behaviors of the driver, namely analyzing an MMSE target, and performing predicting in an overall road, a residence and an intersection, especially in a residence road and an intersection.

The invention discloses a device for evaluating the treatment effect of online cognitive behavior therapy and a using method, and relates to the technical field of cognitive behavior measurement. Thedevice comprises a peripheral server, and the peripheral server is connected with a mobile device through radio. The upper side of the mobile device is rotationally connected with a display device through a spring hinge; the mobile device and the display device are provided with a series of equipment, so that the state of the patient during online cognitive therapy can be dynamically collected; related data are transmitted to the server side, and the state and the effect of the patient in the online cognitive therapy process can be dynamically mastered. The device is novel in design, can be conveniently moved, and can well perform remote evaluation and processing; meanwhile, while the effect of the therapy is guaranteed, different data can be regulated and controlled, so that the data canbe well transmitted and recognized; accuracy and quickness of scheme making are guaranteed, the evaluation effect is guaranteed, and accuracy and stability of evaluation data are improved.

The invention provides a global perceptual behavior detecting device. The global perceptual behavior detecting device comprises an open field, a display screen, a shading part and an image pick-up part, wherein the open field is of a box body structure with an open top and is composed of a bottom plate and a plurality of side plates which are connected end to end through enclosing; the display screen is arranged at the top of the open field, a display surface of the display screen faces to the surface of the bottom plate of the open field, and dynamic approach images are displayed on the display screen and comprise either images maintaining topological attributes or images transforming the topological attributes; the shading part is arranged on the surface of the bottom plate of the open field and is provided with a shading space; and the image pick-up part is arranged on the open field and is used for monitoring dynamic behaviors in the open field in real time. The behavior detectingdevice is a subconscious visual-stimulation detecting device, can be used for testing influence on animal behaviors caused by subconscious topological perceptions and can be used for reflecting relevance between the animal behaviors and global attribute perceptions to certain extent. The invention further provides an animal cognitive behavior testing method.

Method and System for Enabling Responsive Cognitive Behavioral Therapy by automatic monitoring of patients' behavior, determining significant changes of behavior and the progress of therapy and engaging with patients and / or therapists.

The invention specifically relates to a driver steering control method based on a brain emotional learning loop model. The driver steering control method is characterized in that the driver steering control method adopts the following steps that firstly, driver steering preview models at a far point and a near point are used for collecting a sensory signal SI and an emotional signal EC; then the brain emotional learning loop model is established based on neurophysiology, the sensory signal SI and the emotional signal EC which are obtained through the driver steering models are inputted into the brain emotional learning loop model to obtain a steering wheel angle, and correction is conducted continuously to realize accurate tracking of a road track; and finally, a linear two-degree-of-freedom vehicle dynamic model is established to input the corrected steering wheel angle to the vehicle model for steering control. According to the driver steering control method based on the brain emotional learning loop model, cognitive behaviors of a driver in reality can be simulated, so that the model has good consistency with the cognitive behaviors of human beings, and better accurate tracking for the vehicle can be realized accordingly, and the vehicle is safer.

The invention provides a deep Q network reinforcement learning method and device for cognitive behavior model acceleration, and the method comprises the steps of obtaining state information from an environment through a cognitive behavior model, obtaining cognitive behavior knowledge according to the state information, and transmitting the cognitive behavior knowledge to a heuristic strategy network; acquiring state information from the environment by using a deep reinforcement learning model; obtaining a heuristic strategy value according to the state information and the cognitive behavior knowledge by using a heuristic strategy network, and sending the heuristic strategy value to a deep Q network; using the deep Q network to obtain and execute an action according to the state information and the heuristic strategy value; using a deep reinforcement learning model to acquire a return from the environment, and performing iterative updating on the heuristic strategy network and the deep Q network; and cyclically executing the operation, and ending reinforcement learning in response to determination of depth Q network convergence. Convergence of the deep Q network is accelerated through the cognitive behavior model and the heuristic strategy network, and the influence of huge state space and sparse reward return on learning efficiency is effectively relieved.

The invention discloses an online learning behavior model mining system based on process mining and a mining method thereof, and the system comprises: a data grouping module which divides online behavior data of students into an excellent group, a good group, a medium group and a poor group according to student scores; the two-layer event log generation module that is used for respectively acquiring each group of student cognitive behavior event logs with excellent, good, medium and poor performance and a specific online behavior event log of each cognitive behavior according to a known mapping relationship between the online behaviors and the cognitive behaviors, namely, two layers of event logs; and the two-layer behavior model generation module that is used for generating a two-layer behavior process model by taking the two-layer event log as input and utilizing a process mining algorithm. The invention provides a new system and method for discovering a student behavior process model. The two-layer behavior process model serves as an effective means for student behavior analysis in education data analysis, an effective online learning mode can be found more accurately, and the method has guiding significance for development of the online education industry.

The embodiment of the invention discloses a CBT(cognitive behavioral therapy)-based psychological therapy control method. The method comprises the following steps: acquiring a current learned psychological learning module of a user according to an unlocking instruction input by the user; obtaining the recent unlocking time of the learned psychological learning module, and judging whether the difference between the recent unlocking time and the current time is greater than or equal to a preset interval duration or not; if so, selecting one psychological learning module from unlearned psychological learning modules according to a preset learning sequence to serve as a psychological learning module to be learned; unlocking the psychological learning module to be learned, and displaying pathological explanation data and self-training data of the psychological learning module to be learned to the user in a man-machine conversation mode, wherein the psychological learning module is designedon the basis of the diagnosis standard and cognitive behavior therapy of the fifth-edition psychosis statistical diagnosis manual on the post-traumatic stress disorder. The method can help the user torelieve PTSD symptoms based on the cognitive behavior therapy.

Described is a system for predicting the behavior of an autonomous system. The system identifies a taxonomic state of a motion condition of an autonomous vehicle based on a spatiotemporal location of the autonomous vehicle and elements of a driving scenario. Behavior of the autonomous vehicle is predicted based on the taxonomic state of the motion condition. The autonomous vehicle makes and implements a driving operation decision based on the predicted behavior.

The invention provides a depression cognitive behavior training system, which comprises a login module used for acquiring user login request information to realize login; a cognitive behavior training module, which is used for realizing cognitive behavior training on a user in a training interface according to the current training stage of the user and the training content corresponding to the training stage after successful login; and an emotion recording module, which is used for entering an audio recording page before each training stage is started and after each training stage is completed, and performing analysis according to the voice data recorded by the user to obtain a depression scale score of the user. In the training process, the data fed back by the user is obtained comprehensively, objectivity is high, and accuracy is high. The invention further provides a voice data processing method which can accurately recognize the emotion change of the user.

The invention provides an EBAS (Environmental Enrichment Based Acquisition System) evaluation system and discloses a comprehensive testing method for rat cognitive behaviors. The method is a comprehensive testing method for cognitive behaviors such as emotions, anxiety, society and the like of rats on the basis of EE (Environmental Enrichment), the testing is carried out under the condition of weakening the external stress environment without artificial separation, the rat cognitive behaviors are completely instinctive exploratory behaviors, and the method can be used for exploring material basis of neural circuit of hippocampus CA1 / CA3 and prefrontal cortex (PFC), is scientific for evaluating animal behavior change under actions of various drugs and medical intervention and can offer assistance for investigation of influence of drugs or medical intervention on change of cranial nerve or synaptic transmitter.

To provide a an animal with schizophrenic sensorimotor and behavioral abnormalities, a specific protein factor inhibiting development of brain function is administrated to a juvenile animal in the stage of its development and an animal exhibiting sensorimotor and behavioral abnormalities is prepared. As the sensorimotor and behavioral abnormalities observed in the animal of the present invention is very similar to schizophrenia, the animal is useful for development of an anti-schizophrenic medicine and a diagnostic agent for schizophrenia.

A tinnitus management system and a computer-implemented method for managing tinnitus are described. The system comprises a survey developing unit, a progress determining unit, a performance evaluation unit, and a feedback unit. The survey developing unit develops and / or adapts, after a first training section, a subsequent, second training section or a following part of a survey based on a performance indicator determined for the first training section.

The invention provides an MOOC learner cognitive behavior recognition method based on a BERT model, and the method comprises the steps of obtaining learner discussion text data in an MOOC forum, and generating a professional corpus in the field of MOOC comments; preprocessing the corpus, and forming pre-training data containing the professional knowledge in the MOOC field; in combination with the pre-training data, using an MLM strategy and an NSP strategy to re-train the BERT model to obtain MOOC-BERT; constructing an MOOC learner cognitive behavior annotation data set; and performing fine adjustment on parameters and weights in the MOOC-BERT by using the annotation data set, and generating a cognitive behavior recognition model oriented to the MOOC learner. The MOOC learner cognitive behavior recognition method based on the BERT model is used for improving the recognition ability of learner cognitive behaviors in an online learning environment and effectively helping teachers to analyze the cognitive behavior types of MOOC learners in a large-scale scene.

An animal cognitive behavior test device and test method based on multimodal stimulation, the device includes: a multi-arm maze, including a plurality of passages as arms of the maze, extending from the central area of ​​the maze to different directions, wherein one or more The entrance of the passage is provided with a display screen and a sound source, and the end of the passage is closed; the camera device is located above the multi-arm maze, and is used to obtain images of animals in the multi-arm maze; the controller is connected with the multi-arm maze. The display screen, the sound source are connected to the camera device, and are used to control the image displayed on the display screen and the sound emitted by the sound source, and to record and count the image data obtained by the camera device. The invention can meet the requirements of more complex animal learning and memory experiments.

An online insomnia intervention system based on a cognitive behavior theory relates to the technical field of chronic insomnia intervention, and performs online real-time information collection and automatic work and rest calculation on insomnia people through APP behaviors to realize work and rest intervention. Consultation communication between the insomnia crowd and a consultant and video education for the insomnia crowd are provided to realize cognitive education, an online APP is used as a carrier, a communication bridge between the insomnia crowd and the consultant is constructed, and the subjective judgment of the insomnia crowd on the insomnia condition and the objective judgment of the consultant on the insomnia condition of the insomnia crowd are combined to realize cognitive education. The online insomnia intervention system carries out automatic calculation on data in an objective mode, and work and rest intervention and cognitive education are carried out on the insomnia people.