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45 results about "Cognitive neuroscience" patented technology
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Cognitive neuroscience is the scientific field that is concerned with the study of the biological processes and aspects that underlie cognition, with a specific focus on the neural connections in the brain which are involved in mental processes. It addresses the questions of how cognitive activities are affected or controlled by neural circuits in the brain. Cognitive neuroscience is a branch of both neuroscience and psychology, overlapping with disciplines such as behavioral neuroscience, cognitive psychology, physiological psychology and affective neuroscience. Cognitive neuroscience relies upon theories in cognitive science coupled with evidence from neurobiology, and computational modeling.
Encephalic electrode individualization locating method based on multimode medical image data fusion
InactiveCN103932796ARealize high-precision individual positioningPrecise positioningDiagnosticsSurgeryDiagnostic Radiology ModalityAnatomical structures
An encephalic electrode individualization locating method based on multimode medical image data fusion relates to the fields of medical instruments and medical image processing and neuroimaging. By means of multimode medical image data including magnetic resonance images, X-ray images and intranperative optical photos, the space position relation of an encephalic electrode and a brain tissue structure is comprehensively measured, a relation between the position of the encephalic electrode and a brain anatomical structure is established, and accurate and fast individualization locating of the encephalic electrode is achieved. The encephalic electrode individualization locating method based on multimode medical image data fusion can be used in the fields of cognitive neuroscience basic research, clinic neurosciences and the like, provide accurate brain space position information for an encephalic electroencephalogram signal, and enhance application value in the aspect of electrophysiological basis research.
Owner:BEIJING NORMAL UNIVERSITY
Individual brain function mapping method based on electrocorticogram high-frequency Gamma nerve oscillation
InactiveCN103932701AImprove understandingIndividualized Brain Function Mapping FastDiagnostic recording/measuringSensorsSystems analysisMedicine
The invention discloses an individual brain function mapping method based on electrocorticogram high-frequency Gamma nerve oscillation and belongs to the field of nerve engineering. The individual brain function mapping method based on electrocorticogram high-frequency Gamma nerve oscillation comprises the steps that collected ECoG data are processed, the correlation synchronization intensity of time-frequency events is calculated, statistical significance testing is conducted and a brain function index is extracted, and individual brain function mapping is conducted. According to the individual brain function mapping method based on electrocorticogram high-frequency Gamma nerve oscillation, through the deep mining of the ECoG data, relevant electroencephalogram data of brain function areas can be analyzed rapidly, accurately, comprehensively and systematically, the brain function index is obtained, individually targeted brain function mapping is achieved, people can better understand brain mechanisms for processing complicated cognition tasks, and great assistance is provided for study on cognitive neuroscience brain functions and fundamental study on clinic neurosciences.
Owner:BEIJING NORMAL UNIVERSITY
Emergency state detection system fused with brain electrical signal and environmental information
ActiveCN108693973AImprove securityImprove driving experienceInput/output for user-computer interactionAutomatic initiationsAutomatic controlHuman–robot interaction
The invention relates to an emergency state detection system fused with a brain electrical signal and environmental information and a related computation method thereof, which aim at improving the safety and driving experience of a brain-to-vehicle in an automatic drive process. According to the emergency state detection system fused with the brain electrical signal and the environmental information and the related computation method thereof, identification of an emergency state is implemented through brain electrical signal-based emergency brake intention detection in combination with environmental information-based obstacle detection to further enable the vehicle to brake emergently. The emergency state detection system fused with the brain electrical signal and the environmental information and the related computation method thereof are of great importance for improvement of the safety of brain-controlled drive and automatic drive and belong to an comprehensive application in the field of vehicle design as well as the fields of human-computer interaction science, cognitive neuroscience and automatic control.
Owner:BEIJING INSTITUTE OF TECHNOLOGYGY
Human action intention recognition training method based on cooperative computation of multiple brain areas
ActiveCN108304767AEnables cognitive function modelingPerform cognitive tasksInput/output for user-computer interactionPhysical realisationCategory recognitionHuman body
The invention belongs to the field of cognitive neuroscience, and specifically relates to a human action intention recognition training method based on cooperative computation of multiple brain areas.The human action intention recognition training method comprises the steps of 1, performing image collection on a human body action; 2, obtaining human body joint information, and recognizing the category of the human body action; 3, calculating a robot action strategy according to the category of the action executed by the human by adopting a mode of cooperative computation of multiple brain areas based on a brain-like computing model; 4, inputting a correctness judgment for the robot action strategy calculated in the step 3; 5, adjusting parameters of the brain-like computing model throughan STDP mechanism based on the correctness judgment inputted in the step 4; and 6, if the correctness judgment inputted in the step 4 shows that the robot action strategy is wrong, executing the step1 for repeated training until the correctness judgment inputted in the step 4 shows that the robot action strategy is correct. The human action intention recognition training method overcomes the defect of being not flexible enough because programming and the like need to be performed in advance in the traditional human-computer interaction technology, and improves the use experience.
Owner:INST OF AUTOMATION CHINESE ACAD OF SCI
Method of detecting braking intention of driver in emergency state based on neural signal
InactiveCN106022291AEasy to useImprove accuracyPhysiological signal biometric patternsDriver/operatorEngineering
The invention relates to a method of detecting a braking intention of a driver in an emergency state based on a neural signal. According to the method provided by the invention, body movements and languages are not required, and only the electroencephalogram (EEG) signal of the driver is required to be recorded, and by analyzing the EEG signal, the braking intention of the driver is predicted, and early braking decision making is facilitated. The method belongs to an integrated application in a cognitive neuroscience field and an information technology field.
Owner:BEIJING INSTITUTE OF TECHNOLOGYGY
Affair-relative light signal collection analysis system and lie detection method
The invention relates to a system for acquiring and analyzing event-related optical signals and a lie detecting method, and relates to recognition technology and a recognition method for honesty and cheat of a litigant in national security, public security, justice and civil dispute. The invention provides a lie detecting method using EROS by overcoming the defects of the prior lie detecting technology and products, absorbing the experiences of the prior lie detecting technology and the products, and also absorbing latest theory and technological achievement of the contemporary cognitive neuroscience and photoelectric technology. The system consists of a photoconductive cap, a near infrared laser, a scattered light signal acquisition control system, event-related optical signal processing software and lie detecting software, and plays a main role in acquiring objective data that whether a testee is honest to respond to detecting stimulation.
Owner:北京毫纳心脑测试诊断技术研究所
Combatant state monitoring system based on electroencephalogram signals
ActiveCN104490391AReduce casualtiesEasy to useSensorsTelemetric patient monitoringAutomatic controlMonitoring system
The invention relates to a method and a system for judging whether combatants meet an emergency or not through their electroencephalogram signals. By the method, without any body movement and languages, whether the combatants meet the emergency or not can be analyzed by recording the electroencephalogram signals of the combatants and analyzing the corresponding electroencephalogram signals, quick response and alarm can be made to prompt of others. The method and the system belong to comprehensive application of fields of cognitive neuroscience, information technology and automatic control.
Owner:BEIJING INSTITUTE OF TECHNOLOGYGY
A fast detection method of image region of interest based on EEG and eye-mover
InactiveCN108958489AHigh speedSmall amount of calculationInput/output for user-computer interactionCharacter and pattern recognitionImaging processingSwitching signal
The invention discloses a fast detection method of an image region of interest based on EEG and an eye mover, belonging to the technical field of cognitive neuroscience and image processing, which utilizes the EEG and the eye mover to realize the fast detection of an image region of interest which may contain a target object. The method utilizes the mixed mode of EEG and eye movement meter, takeseye movement signal as switch signal, makes full use of the information characteristics of EEG and eye movement meter, and combines with image segmentation technology to quickly and efficiently detectthe region of interest where the object is located.
Owner:SOUTHEAST UNIV +1
MI and SSVEP dual paradigm-based few-channel asynchronous control brain computer interface system
ActiveCN108459714AImprove classification accuracyEfficient extractionInput/output for user-computer interactionGraph readingInformation processingBrain computer interfacing
The invention discloses an MI and SSVEP dual paradigm-based few-channel asynchronous control brain computer interface system, and belongs to the technical field of cognitive neural science, information processing and automation control crossing. For a few-channel electroencephalogram signal BCI system, an MI paradigm is adopted as a switch module of the BCI system; an SSVEP paradigm is adopted asa BCI multi-choice module; the two modules are connected in series to form the asynchronous control BCI system; a few-channel EEG signal is decomposed into multiple intrinsic mode functions by utilizing a multi-variable empirical mode decomposition algorithm; based on a spectrum distribution characteristic of MI, the IMFs are preferentially selected as characteristics for realizing MI classification; an improved canonical correlation analysis method is proposed for calculating canonical correlation coefficients between the IMFs and SSVEP frequency templates; the optimal canonical correlation coefficient is preferentially selected out for realizing SSVEP classification; and therefore, the control effect and the classification accuracy of the few-channel BCI system can be improved.
Owner:SOUTHEAST UNIV
Mechanical arm writing device based on electroencephalogram control and control method
ActiveCN107212883AReduce wrong tasksImprove the quality of lifeInput/output for user-computer interactionProgramme-controlled manipulatorFeature extractionComputer science
The invention discloses a mechanical arm writing device based on electroencephalogram control and a control method, and relates to the technical field of cognitive neuroscience. The device is characterized by at least comprising electroencephalogram collection equipment, signal processing equipment and a mechanical arm executing the writing action; the signal processing equipment receives collection information of the electroencephalogram collection equipment, and the collection information is subjected to data processing; the specific data processing process sequentially comprises the steps of data filtering, wavelet filtering, feature extraction, classification and classification result conversion; the mechanical arm receives a control command of the signal processing equipment and executes the corresponding command action according to the control command. The mechanical arm writing device and the control method have the advantages of being easy to operate, safe to use, high in anti-noise capacity and good in stability, and a practical and feasible scheme is provided for achieving human-computer interaction.
Owner:TIANJIN UNIVERSITY OF TECHNOLOGY
P300 single extraction technique based on independent component analysis and Kalman smoothing
ActiveCN108784693AImprove signal-to-noise ratioImprove single extraction accuracyCharacter and pattern recognitionDiagnostic recording/measuringFeature vectorTime domain
The invention relates to a P300 single extraction technique based on independent component analysis and Kalman smoothing. The invention aims at improving efficiency and accuracy of a dynamic system based on P300. According to the P300 single extraction technique provided by the invention, by removing winking artifacts and random noise in electroencephalogram signals (EEG), a signal-to-noise ratioof the electroencephalogram signals (EEG) can be improved, so that the electroencephalogram signals can be recognized more easily; with time domain characteristics of the processed electroencephalogram signals (EEG) as classifying characteristics, a characteristic vector can be obtained; the characteristic vector undergoes dimension reduction and mode recognition, so as to judge whether the current electroencephalogram signals (EEG) belong to a P300 potential, and corresponding commands are outputted. The invention is significant for improving the efficiency and accuracy of the dynamic systembased on the P300. The invention belongs to comprehensive application of human-computer interaction science and cognitive neuroscience fields.
Owner:BEIJING INSTITUTE OF TECHNOLOGYGY
Question and answer method and system based on brain-like semantic hierarchical memory reasoning model
ActiveCN109657036ARetain the advantageImprove scalabilityInference methodsText database queryingNatural language understandingSmall sample
The invention belongs to the field of cognitive neuroscience, particularly relates to a question and answer method and system based on a brain-like semantic hierarchical memory reasoning model, and aims to solve the problem of small sample learning of natural language understanding tasks such as text generation and automatic question and answer. The method comprises the steps of acquiring and inputting a question text and an answer text; Performing time sequence pooling on the text to obtain a word vector matrix; Pooling the space and time of each word vector in the word vector matrix to obtain a binary word representation set of which each bit is 0 or 1 corresponding to the word vector; Performing brain-like learning on the text and the word set to obtain an optimized model; And independently inputting the question text, performing word reduction based on the cell prediction state in the model, obtaining an answer text, and outputting the answer text. According to the method, a semantic hierarchical time sequence memory model is combined, the model is constructed based on a learning mode of small sample data and knowledge reasoning, the requirement for the number of samples is low, a large number of parameters do not need to be adjusted, and the expandability of the model is improved.
Owner:INST OF AUTOMATION CHINESE ACAD OF SCI
Single-time P300 detection method based on matrix grey modeling
ActiveCN105718953AImprove accuracyImprove recognition accuracyCharacter and pattern recognitionSupport vector machine classifierModel parameters
The invention provides a single-time P300 detection method based on matrix grey modeling, belongs to the field of cognitive neuroscience and relates to a feature extraction and recognition detection method of an event related potential P300, in particular to a single-time P300 detection method based on matrix grey modeling in a grey theory.The method comprises the steps that 1, a original acquired electroencephalogram signal is preprocessed; 2, electrocardiographic lead combinations are selected, namely four electrocardiographic leads with most obvious top occipital region waveform differences are selected as optimal electrodes according to oscillograms of target stimulus and non-target stimulus of training set data; 3, segmented matrix grey modeling is conducted on the data of the four electrocardiographic leads, and model parameters are extracted to serve as feature vectors; 4, a Fisher ratio value method is utilized to perform optimal feature selection, and meanwhile the purpose of decreasing the number of feature vector dimensions is achieved; 5, a support vector machine classifier is utilized to classify feature vectors, and single-time P300 detection recognition is achieved.Experimental data tests show that the method can improve single-time P300 detection recognition rate, and the correct recognition rate can be further improved during less-time superposition.
Owner:NORTHWESTERN POLYTECHNICAL UNIV
Brain-computer interface system based on steady-state visual evoked potential physiological characteristics
ActiveCN107957780ASolve the problem that the classification accuracy rate needs to be improved due to the lack of consideration of the physiological characteristics of SSVEPImprove classification accuracyInput/output for user-computer interactionCharacter and pattern recognitionInformation processingAutomatic control
The invention discloses a brain-computer interface system based on steady-state visual evoked potential physiological characteristics, and belongs to the cross technical field of cognitive neural science, information processing and automatic control. The brain-computer interface system comprises a time delay reaction module, a CCA module, a typical correlation coefficient selection module and an output module. A delay reaction of SSVEP is modeled, a characteristic frequency point capable of reflecting the frequency spectrum energy change is selected as a frequency reference signal of SSVEP stimulation, all components of the frequency reference signal are linearly combined to obtain a spectral energy distribution model, and an analysis result of a CCA is optimized under the constraint of the ratio of the components of the frequency reference signal. The quality of SSVEP signals can be improved, the characteristics can be effectively extracted, the analysis capability of the CCA is improved, and finally the classification accuracy of a BCI system is improved.
Owner:SOUTHEAST UNIV
Universal model of gesture action intention detection based on electroencephalogram signal
ActiveCN108874137AImprove securityImprove driving experienceInput/output for user-computer interactionGraph readingAutomatic controlHuman–robot interaction
The invention relates to a universal model of gesture action intention detection based on an electroencephalogram signal. Specifically, by processing the collected electroencephalogram signal, a universal model is constructed by a convolutional neural network method to detect whether a subject has an intention to perform a hand action. The model proposed by the invention is a universal model, which is different from a personal model in the previous work. The model does not train the electroencephalogram signal of a participant to directly participate in the test, the training data are from theother participants, and an experimenter obtains the accuracy of the model by analyzing the electroencephalogram signal. The invention belongs to the comprehensive application of the computer field, the vehicle design field, the human-computer interaction science, the psychology science, the cognitive neuroscience and the automatic control field.
Owner:BEIJING INSTITUTE OF TECHNOLOGYGY
Calculating method based on brain-like polysensory attention switching
ActiveCN108197711ARealization of human-like behaviorVersatileBiological neural network modelsInference methodsVisual cortexPattern recognition
The invention belongs to the artificial intelligence and cognitive neuroscience integration field and especially relates to a calculating method based on brain-like polysensory attention switching. The method is used to solve the problem of reliable information selection in a multi-sensory information input environment. The method comprises the following steps of S1, based on a cerebral visual cortex model, carrying out the content identification of a digital image and acquiring a visual digital sequence; S2, based on a cerebral auditory cortex model, carrying out the content identification ofa digital audio and acquiring an auditory digital sequence; S3, based on the digital sequences, using a digital inference model to carry out digital inductive inference, and calculating and storing arule between the digital sequences; and S4, based on a visual-auditory attention switching model, selecting information with a high weight as current reliable modal information and carrying out inference calculation, and acquiring an identification result. In the invention, a series of humanoid behaviors such as vision, an auditory sense, inference, attention switching and the like can be completed simultaneously, and under the different environments, the reliable information is accurately selected for further processing.
Owner:INST OF AUTOMATION CHINESE ACAD OF SCI
TMS coil pose map generation method based on electromagnetic simulation calculation
ActiveCN112704486ARapid positioningPrecise positioningMedical simulationMedical imagingCoil arrayEngineering
The invention belongs to the technical field of cognitive neuroscience, particularly relates to a TMS coil pose map generation method, system and device based on electromagnetic simulation calculation, and aims to solve the problem that an existing TMS coil cannot be quickly and accurately positioned according to an electromagnetic regulation and control effect. The method comprises the following steps: constructing coil array sites and directions on the surface of scalp in an MNI standard space, and matching the coil array sites and directions to an individual brain space to obtain coil array sites and directions of the individual brain space; simulating coil array sites of the individual brain space by a finite element calculation method to obtain brain tissue induced electric field distribution in different coil directions; in combination with brain tissue induced electric field distribution, obtaining an optimal regulation and control effect; and obtaining coil sites and directions corresponding to the optimal regulation and control effect to serve as optimal coil poses of all subareas of the individual brain area, and constructing a TMS pose map of the individual. Rapid and accurate positioning of the TMS coil is realized.
Owner:INST OF AUTOMATION CHINESE ACAD OF SCI
Brain link mining system based on document analysis and functional nuclear magnetic resonance imaging analysis
InactiveCN103678895AFast operationReduce in quantitySpecial data processing applicationsDocument analysisBiological activation
Owner:BEIJING INSTITUTE OF TECHNOLOGYGY
An individualized brain function mapping method based on cortical EEG high-frequency gamma neural oscillations
InactiveCN103932701BImprove understandingIndividualized Brain Function Mapping FastDiagnostic recording/measuringSensorsNeural oscillationCortical eeg
Owner:BEIJING NORMAL UNIVERSITY
Non-language graph symbol communication method
The invention discloses a non-language graph symbol communication method. The method comprises the steps of firstly determining a communication content range and constructing a contextual database; secondly according to the contextual database, designing a non-language symbol system in an initial stage; thirdly performing a cognitive experiment, screening out graph symbols and sentence expressionswith high correlation, and analyzing characteristics of the graph symbols and the sentence expressions; and through linguistics, cognitive psychology, cognitive neuroscience, semiology, plane designand animation design knowledge establishment rules, performing re-design, re-experiment and repeated iteration to achieve a certain effect, summarizing a method and a mode, performing computer programming, and converting a result into the graph symbols and the rules. The communication identification capability of the provided graph symbols is that a receiver can understand and identify an intention to be expressed by a transmitter through the graph symbols, and the original intention of the transmitter is reflected as more as possible.
Owner:YUNNAN UNIVERSITY OF FINANCE AND ECONOMICS
Emotion recognition method and device based on variational phase amplitude coupling
PendingCN114343635AEfficient extractionImprove accuracySensorsPsychotechnic devicesMoodPhase amplitude coupling
The invention belongs to the crossing field of cognitive neuroscience and information technology, and particularly relates to an emotion recognition method, device and platform based on variational phase amplitude coupling and a computer readable storage medium. The emotion recognition method based on variational phase-amplitude coupling comprises a data acquisition step, a preprocessing step, a variational mode decomposition step, a phase-amplitude coupling analysis step, a significance test step and a recognition step. The invention discloses an emotion recognition device based on variational phase-amplitude coupling. The emotion recognition device comprises a data acquisition module, a preprocessing module, a variational mode decomposition module, a phase-amplitude coupling analysis module, a significance test module and a recognition module. According to the invention, the phase-amplitude coupling value which is tested to be significant is averagely distributed to the dual-frequency coupling map, so that the emotion of the testee is identified. According to the method, the electroencephalogram signal characteristics in different emotional states can be effectively extracted, and the accuracy and reliability of emotion recognition are improved.
Owner:BEIJING INSTITUTE OF TECHNOLOGYGY
Brain-computer interface system with few channels and asynchronous control based on mi and ssvep dual paradigm
ActiveCN108459714BImprove classification accuracyEfficient extractionInput/output for user-computer interactionGraph readingInformation processingAutomatic control
The invention discloses a few-channel asynchronous control brain-computer interface system based on MI and SSVEP dual paradigms, and belongs to the technical field intersecting cognitive neuroscience, information processing, and automatic control. For the BCI system with few channels of EEG signals, the system adopts the motor imagery paradigm as the switch module of the BCI system, uses the steady-state visual evoked potential paradigm as the BCI multi-selection module, and connects the two modules in series to form an asynchronous control BCI system. The variable empirical mode decomposition algorithm decomposes the few-channel EEG signal into multiple intrinsic mode functions. Based on the spectrum distribution characteristics of MI, IMF is selected as the feature to realize MI classification, and an improved canonical correlation analysis method is proposed to calculate the relationship between IMF and each SSVEP frequency template. The typical correlation coefficient of SSVEP is optimized, and the optimal typical correlation coefficient is selected to realize the classification of SSVEP, which can improve the control effect and classification accuracy of the few-channel BCI system.
Owner:SOUTHEAST UNIV
Textual emotion marking method, device and system
InactiveCN105678325AImprove accuracyShorten the timeCharacter and pattern recognitionComputer scienceCognitive neuroscience
The application provides a textual emotion marking method, device and system. According to the present invention, a tester reads the to-be-classified texts, a brain electrical signal of a text reader is acquired, and then the emotion mark is carried out on the text according to the brain electrical signal, so that the emotion of a marker can be reflected really from a cognitive neuroscience angle, and a very high accuracy is guaranteed. Moreover, by the application, the marking personnel do not need the long-time training, when a text emotion analysis system is developed, a lot of time and funds can be saved.
Owner:HARBIN INST OF TECH SHENZHEN GRADUATE SCHOOL
Affair-relative light signal collection analysis system
The invention relates to a system for acquiring and analyzing event-related optical signals and a lie detecting method, and relates to recognition technology and a recognition method for honesty and cheat of a litigant in national security, public security, justice and civil dispute. The invention provides a lie detecting method using EROS by overcoming the defects of the prior lie detecting technology and products, absorbing the experiences of the prior lie detecting technology and the products, and also absorbing latest theory and technological achievement of the contemporary cognitive neuroscience and photoelectric technology. The system consists of a photoconductive cap, a near infrared laser, a scattered light signal acquisition control system, event-related optical signal processingsoftware and lie detecting software, and plays a main role in acquiring objective data that whether a testee is honest to respond to detecting stimulation.
Owner:北京毫纳心脑测试诊断技术研究所
Brain Connection Mining System Based on Literature Analysis and Functional Magnetic Resonance Image Analysis
InactiveCN103678895BFast operationReduce in quantitySpecial data processing applicationsDocument analysisComputers technology
Owner:BEIJING INSTITUTE OF TECHNOLOGYGY
A General Model for Gesture Action Intention Detection Based on EEG Signals
ActiveCN108874137BImprove securityImprove driving experienceInput/output for user-computer interactionGraph readingAutomatic controlMedicine
Owner:BEIJING INSTITUTE OF TECHNOLOGYGY
Transcranial magnetic stimulation coil position and posture positioning device, method and equipment for brain map navigation
ActiveCN114073820BAccurate locationAccurate directionElectrotherapyMagnetotherapy using coils/electromagnetsMedicineEngineering
The invention belongs to the technical field of cognitive neuroscience, and specifically relates to a transcranial magnetic stimulation coil position and posture positioning device, method, and equipment for brain atlas navigation, aiming to solve the problem that the prior art cannot realize quantitative and accurate scalp maps based on brain atlases Problems describing the position and orientation of the stimulation coil. The method includes obtaining the location and direction of the stimulating coil array in the individual brain space; registering the structural magnetic resonance image with the brain network group atlas, and mapping with the stimulating coil array in the individual brain space after registration to obtain the scalp atlas map ; Calculate the conversion relationship between the visual sensor and the stimulating coil array in the individual brain space; obtain the real-time pose of the stimulating coil in the stimulating coil array in the individual brain space, if it is consistent with the position and direction of the stimulating coil array in the individual brain space If the difference is greater than the set difference threshold, the pose of the stimulation coil is adjusted. The invention realizes the quantification and accurate description of the position and direction of the stimulation coil based on the scalp map based on the brain atlas.
Owner:INST OF AUTOMATION CHINESE ACAD OF SCI
Question answering method and system based on brain-inspired semantic hierarchical temporal memory reasoning model
ActiveCN109657036BRetain the advantageImprove scalabilityInference methodsText database queryingNatural language understandingWord representation
Owner:INST OF AUTOMATION CHINESE ACAD OF SCI
An image scaling and dragging method based on eye movement signals
ActiveCN109799908BMove fastReduce operating intensityInput/output for user-computer interactionGraph readingImaging processingComputer graphics (images)
The invention discloses an image zooming and dragging method based on an eye movement signal, and belongs to the technical field intersecting cognitive neuroscience and image processing. The present invention utilizes the eye tracker to acquire gaze point as the eye movement signal, and uses the gaze area as the zooming target area during the image zooming operation; and uses the gaze area to indicate the dragging direction during the image dragging operation, so that the sufficient eye movement signal is fast and convenient Features, combined with image processing technology and mouse button input, can achieve fast and efficient image zooming and dragging, effectively reducing the operator's operating intensity and time.
Owner:SOUTHEAST UNIV +1
Transcranial real-time alternating current stimulation device and current control method
PendingCN113018683AProtection securityProtection stabilityElectrotherapyArtificial respirationHemt circuitsEngineering
The invention discloses a transcranial real-time alternating current stimulation device and current control method, and belongs to the technical field of cognitive neuroscience. The alternating current stimulation device comprises an electrode plate and a controller. A circuit board in the controller is integrated with: a power supply circuit electrically connected with the electrode plate, and used for providing transcranial alternating current for regulating cerebral cortex neuron activity; a main control circuit used for controlling the magnitude of the output current of the power supply circuit, wherein the main control circuit comprises a control system consisting of a single chip microcomputer, a DAC conversion chip and an operational amplifier; and a protection circuit used for suppressing high-frequency noise signals in the circuit and controlling the output voltage of the power supply circuit not to exceed a threshold value. An alternating current signal with a stable peak value is provided through the power supply circuit, and the waveform, the mode and the frequency of an output signal are accurately adjusted through the main control circuit, so that the safety of a tested patient during electrical stimulation is ensured.
Owner:安徽效隆科技有限公司
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