11 results about "Cerebral function" patented technology

The invention discloses a brain function training device and method, and belongs to the field of brain function training.The method comprises the steps that before training is started, the historical average value of resting state numerical values of target brain function indexes of a user and the current resting state numerical value are determined; determining a dynamic offset according to a difference value between the current resting state numerical value and a historical average value; adjusting and updating the reference threshold sequence through the dynamic offset to obtain a target threshold sequence; after training is started, a target stage corresponding to a real-time interval (the interval where a real-time numerical value of a target brain function index is located in a target threshold sequence) in the multi-stage feedback content can be determined; feedback content of the target stage is fed back to the user; on one hand, the target threshold sequence can be dynamically determined by referring to the current and historical resting state numerical values (of the target brain function index) of the user, the training effect is improved, on the other hand, the interestingness of brain function training is improved through the multi-stage feedback content, and the training enthusiasm of the user is improved.

The invention discloses a digital integrated brain injury nerve regulation diagnosis and treatment platform, and relates to the technical field of brain injury diagnosis and treatment, and the technical scheme is characterized in that the platform comprises a multi-mode brain function monitoring module used for collecting brain function data of a brain injury consciousness disorder patient in real time; the multi-sensory nerve regulation and control stimulation module is used for cooperatively applying multi-sensory stimulation to the patient; and the main control and data processing module receives and processes the multi-modal signals transmitted by the multi-modal brain function monitoring module, generates a personalized nerve regulation scheme by extracting brain function characteristics, and controls the multi-sensory nerve regulation stimulation module to execute the personalized nerve regulation scheme at the same time. According to the method, multi-sensory stimulation is cooperatively applied to the patient, the problem of pain points of traditional distributed non-standard stimulation is solved, the core requirement of the patient for multi-channel sensory input awakening is met, meanwhile, a complete closed loop of monitoring-analysis-intervention-feedback is formed, and dynamic evaluation and accurate intervention on the brain function state of the patient with acute brain injury consciousness disorder are achieved.

In brain function measurement using light, it is difficult to simultaneously install a light emitting probe that emits light, a light receiving probe that detects light, a light emitting and receiving probe having a function of emitting and detecting light, and the like along the scalp of a subject. To provide an installation means of a probe following a plurality of differently curved scalps for simultaneously, stably and correctly installing many probes on the scalps.SOLUTION: An arm 1-2 having a hole having a connecting function with an adjacent holder is arranged in a holder 1-1 for fixing a probe, and a plurality of holders are connected by using a fixture 1-3 for connecting these holes. The hole diameter of the arm and the diameter, length, and the like of the fixing tool are adjusted to provide a movable range in a three dimensional direction in the connection portion, and the holder is held so as to be perpendicular to the scalp of the subject. By attaching six arms to one holder at intervals of 60 degrees from the center, expansion in a two dimensional direction is enabled, and a measurement unit following a required measurement region can be realized.SELECTED DRAWING: Figure 1

The present application relates to a method for recognizing motor imagery based on cross-rhythm multilayer coupling brain network of electroencephalogram signals, and a plurality of kinds of motor imagery tasks of normal people are collected by multi-lead electroencephalogram (EEG). According to the collected signals, data preprocessing is carried out: after the node common average reference, a FIR filter band-pass filter is used to obtain the mu rhythm and beta rhythm which are active and have ERS / ERD phenomenon of motor imagery, and then an independent component analysis method is used to remove noise interference such as electrooculogram and electromyogram. On this basis, a multilayer functional brain network is established, the lead signal is used as the node, the phase-locked value is used as the connection, the adjacency matrix is established, and the brain function network features reflecting the activity characteristics of motor imagery are extracted. Three kinds of global network features in the mu rhythm and beta rhythm single-layer network and two kinds of interlayer feature parameters between networks are extracted, and after normalization, the multilayer network features for motor imagery recognition are generated, and the motor imagery is recognized by using a machine learning method such as a support vector machine and using the multilayer network features.

The invention provides a brain functional activity nonlinear modeling method and system and a storage medium, and relates to the technical field of functional magnetic resonance imaging data analysis, and the method comprises the steps: dividing a BOLD signal of a cerebral cortex in a task period into a plurality of task segments, and respectively mapping the BOLD signal to a group level unit spherical manifold and an individual level unit spherical manifold; obtaining a distance matrix between the BOLD signals according to the group horizontal unit spherical manifold; performing dimension reduction processing on the group horizontal unit spherical manifold according to the distance matrix, and distributing a functional neighborhood for each cerebral cortex vertex according to a low-dimensional embedded manifold obtained by the dimension reduction processing; and according to the average signal corresponding to the functional neighborhood, determining local synchronism measurement of the vertex of the cerebral cortex, and according to the local synchronism measurement, obtaining a related functional activation map of the cerebral cortex. According to the method, distance calculation and manifold learning are carried out on the group horizontal unit spherical manifold, so that the capacity of capturing nonlinear features of the brain function activity is enhanced, and the modeling precision of the brain function activity is improved.

A method and apparatus for processing MRI data on changes in local brain function and blood perfusion, the method comprising: (1) collecting T1-weighted imaging, T2-weighted imaging, diffusion-weighted imaging, high-resolution T1-weighted imaging, resting-state fMRI, and 3D-pCASL sequence imaging for each subject on an MRI scanner; (2) processing the resting-state fMRI to obtain the following indicators: local consistency ReHo, low-frequency amplitude ALFF, and low-frequency amplitude fraction fALFF; (3) processing the 3D-pCASL sequence imaging to obtain perfusion indicators in each brain region, including mean cerebral blood flow mCBF, arterial transit time ATT, and arterial cerebral blood volume aCBV; (4) performing statistical analysis between patients and healthy controls on the data obtained in steps (2) and (3), and using correlation analysis to determine the correlation between statistically significant indicators and scale scores.

The utility model provides a multi-mode stimulation device for promoting cerebral circulation, and aims to solve the problem of poor cerebral circulation improvement effect caused by single stimulation mode of equipment for promoting cerebral circulation in the prior art. A multi-mode stimulation device for promoting cerebral circulation comprises a glasses assembly which comprises a glasses frame and two glasses legs located on the left side and the right side of the glasses frame respectively, and the glasses frame is provided with two sets of LED lamp assemblies which correspond to the left eye and the right eye of a person respectively and emit light at the frequency of 40 HZ; the nose plug assembly comprises a mounting seat electrically connected with the glasses legs and two nose plugs arranged on the mounting seat, and a near-infrared lamp emitting light at the frequency of 40HZ is arranged in each nose plug; the earplug assembly comprises two earplugs capable of producing sound at the frequency of 40HZ, and the two earplugs are respectively arranged on the two glasses legs. According to the invention, through photoacoustic multi-mode synergistic stimulation, the effect of better improving the cerebral blood perfusion function can be achieved, so that the cerebral function is improved.

The application provides a brain function activity nonlinear modeling method, system and storage medium, relates to the functional magnetic resonance imaging data analysis technical field, and the method comprises the following steps: the BOLD signal of the brain cortex in a task cycle is divided into multiple task sections and is respectively mapped to a group level unit spherical flow form and an individual level unit spherical flow form; the distance matrix between the BOLD signals is obtained according to the group level unit spherical flow form; the group level unit spherical flow form is processed in dimension reduction according to the distance matrix, and a functional neighborhood is assigned to each brain cortex vertex according to the low-dimensional embedding flow form obtained by processing in dimension reduction; the local synchronism measure of the brain cortex vertex is determined according to the average signal corresponding to the functional neighborhood, and the related function activation atlas of the brain cortex is obtained according to the local synchronism measure. The application enhances the capturing ability of the nonlinear characteristics of brain function activity by carrying out distance calculation and flow form learning on the group level unit spherical flow form, and improves the modeling precision of brain function activity.

The application provides an intelligent glasses, which can improve the portability and comfort of the electroencephalogram acquisition device, and realize comprehensive evaluation of the brain function state of the user. The intelligent glasses comprise a glasses frame, a plurality of electroencephalogram acquisition electrodes, a sensory stimulation component and a processor. The glasses frame comprises a glasses frame and a glasses leg. The glasses leg comprises a main body part and a hanging ear part. The main body part is connected with the glasses frame. The hanging ear part is located on the side of the main body part away from the glasses frame and is connected with the main body part. The plurality of electroencephalogram acquisition electrodes, the sensory stimulation component and the processor are arranged on the glasses frame. The plurality of electroencephalogram acquisition electrodes are arranged at intervals and are used for acquiring the electroencephalogram signals of the user. At least one electroencephalogram acquisition electrode is arranged on the hanging ear part. The processor is electrically connected with the plurality of electroencephalogram acquisition electrodes and the sensory stimulation component. The processor is used for controlling the sensory stimulation component to send a sensory stimulation signal according to the electroencephalogram signals acquired by the plurality of electroencephalogram acquisition electrodes. The sensory stimulation signal is used for stimulating the user to change the brain function state of the user.

This invention provides a brain oxygen signal processing method and device based on endogenous low-frequency oscillations, belonging to the field of computer-aided design technology. The method includes: S1, preprocessing and concentration conversion of the original light intensity signal, performing sliding windowing and low-frequency sub-band analysis on the hemoglobin concentration change signal to obtain the low-frequency sub-band signal; S2, extracting the instantaneous phase information and amplitude envelope information of the low-frequency sub-band signal, and determining the amplitude-phase coordination quantity and amplitude envelope coordination quantity; S3, using consistency gating parameters for joint constraints, constructing a low-frequency coupling structure matrix, and generating low-frequency coupling feature parameters; S4, performing quantitative mapping, hierarchical characterization, and confidence output of brain functional states to achieve quantitative characterization of the brain oxygen signal characteristics of the current analysis window. This invention models the coordinated change characteristics of multi-channel brain oxygen signal data in the low-frequency range, determines the coordination and stability of the spatial distribution of brain oxygen signals, and realizes the output of brain oxygen signal feature labels.