18 results about "Temporal lobe" patented technology

The invention discloses a cognitive feature extraction and classification method and system based on electroencephalogram signals, and the method comprises the steps: constructing a cognitive divergence mapping network, so as to integrate a multi-branch brain region topology module and a neurodynamics physical information network module; the multi-branch brain region topology module divides detection branches of five brain regions (frontal lobe, central lobe, parietal lobe, occipital lobe and temporal lobe) according to 10-20 systems, and through feature extraction of different brain region branches, the feature learning ability of the Alzheimer's disease patient under the condition of cross-brain region signal heterogeneity is remarkably improved; the neurodynamics physical information network module can effectively extract changes of low-frequency and high-frequency components in electroencephalogram signals of the Alzheimer's disease patient by introducing frequency band separation, Fourier transform power spectrum constraint, an adaptive weighting mechanism and neural representation embedding in a frequency spectrum congruence space. The accuracy and generalization of electroencephalogram signal analysis are remarkably improved, and an efficient and non-invasive detection tool is provided for early diagnosis of the Alzheimer's disease.

The invention discloses an emotion analysis method and system based on multi-mode electroencephalogram eye movement fusion. An emotional induction stimulation sequence is alternately or synchronously displayed through a stimulation presentation module according to preset time sequences such as 5-second vision and 3-second auditory sense, a 64 conductive electrode cap (10-20 system layout, the sampling rate is larger than or equal to 1000 Hz) is triggered to collect electroencephalogram data of a prefrontal lobe, a temporal lobe and the like, and meanwhile eye movement data are obtained through an infrared pupil tracking technology (the sampling frequency is larger than or equal to 120 Hz). 0.5-70 Hz band-pass filtering and ICA artifact removal processing are carried out on the electroencephalogram data, smooth interpolation and Kalman filtering optimization are carried out on the eye movement data, and then electroencephalogram alpha / beta / gamma wave power spectrums, eye movement pupil change rates and other characteristics are extracted respectively. A Transform model based on an attention mechanism is adopted, deep fusion of electroencephalogram eye movement features is realized through feature embedding and multi-head self-attention calculation, and emotion recognition accuracy greater than or equal to 85% is achieved through confusion matrix optimization and five-fold cross validation in combination with an SVM or DNN classifier.

The invention provides a method and system for evaluating the instant curative effect of acupuncture head acupoints on cerebral stroke cognitive impairment based on electroencephalogram signals, and the method comprises the steps: collecting the electroencephalogram signals before, during and after acupuncture in stages, and synchronously combining a MoCA / MMSE scale and a cognitive task test to obtain subjective curative effect data; an insulating acupuncture needle is adopted to reduce interference on electroencephalogram signals, and 4-8-conduction portable dry electrode electroencephalogram equipment is matched to collect signals in an area avoiding acupuncture points of the head, so that acupuncture operation and electroencephalogram collection are ensured not to influence each other. A condition vector is generated by using acupuncture point parameters and acupuncture manipulation, and a space-time Transform-GNN model is driven to dynamically focus alpha / theta / beta frequency band time sequence characteristics and a brain network connection mode of cognitive related brain regions such as a prefrontal lobe, a parietal lobe and a temporal lobe. According to the method, a multi-modal feature vector containing electroencephalogram frequency domain features, time domain components and clinical scale scores is constructed through an electroencephalogram-acupoint-curative effect triple data training model of at least 100 patients, and an obvious / effective / invalid level is output.

The present invention relates to a device for preventing, alleviating or treating degenerative brain diseases by inducing brain wave synchronization through acoustic vibration tactile stimulation and bone conduction music, and a method thereof. More specifically, the present invention relates to a wearable device which is worn on the head of a wearer, stimulates the brain by providing Vibroussis composed of 40 Hz vibration and sound to the forehead lobe and the temporal lobe of the wearer, and recovers the gamma oscillation of the brain to normal by increasing the cerebral blood flow. Therefore, the device and the method thereof can prevent, relieve or treat degenerative brain diseases (such as mild cognitive impairment or early Alzheimer's disease (dementia)).

The present application discloses a system and interactive method for evaluating the cognitive function of a subject based on fNIRS. The head cap and near-infrared light emitting / receiving probe in the system enable the imaging range to cover the frontal lobe, temporal lobe, and occipital lobe; the cognitive assessment paradigm interactive device sequentially executes the inhibitory control assessment paradigm, the alert attention assessment paradigm, the selective attention assessment paradigm, the core attention network assessment paradigm, the working memory assessment paradigm, and the cognitive control assessment paradigm in a single-block mode in an order of execution from simple to difficult; the signal acquisition device collaboratively collects near-infrared brain function imaging time series data during the sequential execution of each assessment paradigm; the processing device evaluates the cognitive function of the subject based on the near-infrared brain function imaging time series data and the behavioral data generated based on the assessment paradigm. The present application can obtain brain function data of more dimensions associated with cognitive function in a relatively short period of time, which is convenient for clinical evaluation and analysis of the cognitive function of the subject from multiple angles based on fNIRS.

The application discloses a nasopharyngeal carcinoma radioactive brain damage image auxiliary judgment method, equipment and medium, the method is: collecting MRI image and preprocessing, segmenting the temporal lobe region, using the temporal lobe region and corresponding lesion annotation training level prediction model of MRI image, the probability that a single temporal lobe image region exists radioactive brain damage lesion is predicted;With the probability that each subject all layers contain lesions output by the level prediction model as input, whether the subject exists radioactive brain damage as output, training patient level prediction model;Finally, the trained level prediction model and patient level prediction model are used to obtain the incidence probability of radioactive brain damage of a single nasopharyngeal carcinoma subject, when multiple modes coexist, the average of multiple mode prediction result outputs is taken as the final prediction result. The application can judge whether the corresponding nasopharyngeal carcinoma brain MRI image exists radioactive brain damage according to the input, provide reference for clinical doctors to diagnose, and reduce the missed diagnosis of nasopharyngeal carcinoma radioactive brain damage.

The present invention relates to a head cover for electrical stimulation, comprising a head cover connected to the front of the original head of a car seat, and characterized in that it also includes an electrode portion capable of covering the temporal lobe area of ​​the driver's head, an electrode fixing portion connected to the head cover and connected to the electrode portion to fix the electrode portion, and a steering wheel having two flexible pole pieces respectively connected to the left and right ends of the steering wheel and an embedded chip. Compared with the existing technology, the present invention has the advantage that when the driver holds both sides of the steering wheel body, both palms need to simultaneously contact the flexible pole pieces on both sides for a certain period of time or more, and the duration needs to be manually set. The electrocardiogram detection module inside the embedded chip converts the electrical signal transmitted by the flexible pole piece into the required electrocardiogram signal. The electrocardiogram signal is input into a neural network module to judge the mental state, such as anxiety or non-anxiety, and then outputs an alternating current signal, such as 40Hz, to the electrode portion to relieve the driver's mood.

The invention discloses a helmet type multi-target transcranial magnetic stimulation system based on a time interference theory. The helmet type multi-target transcranial magnetic stimulation system comprises a power supply module, an interaction module, a control circuit module, a stimulation main circuit module and a magnetic stimulation coil module, the interaction module is connected with the control circuit module, the control circuit module is connected with the stimulation main circuit module, the stimulation main circuit module is connected with the magnetic stimulation coil module, and the power supply module is connected with the interaction module, the control circuit module, the stimulation main circuit module and the magnetic stimulation coil module. The magnetic stimulation coil module is a coil array composed of 15 magnetic stimulation coils, the coil array is arranged in a partitioned mode according to the frontal-temporal-apical brain area, four coils are densely arranged in the outer side area of the back of the prefrontal lobe, three coils are distributed on the upper portion of the temporal lobe, and for an auditory sense and memory integration function area, eight coils are intensively arranged on the rear portion of the central groove of the apical lobe. And preset focusing and induced electric field intensity are realized in a target region, and accurate transcranial magnetic stimulation of an individual is finally realized.

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

Methods for preventing or slowing the progression of cognitive impairment or preventing the occurrence of or reducing the rate of cognitive competence decline. A method for slowing volume atrophy or reduction in a medial temporal lobe subregion. Methods for slowing volumetric atrophy or reduction of the endometrial cortex (ERC). A method for slowing volume atrophy or reduction across the endometrial cortex (BA35). The methods comprise administering to an APOE4 non-carrier subject one or more of levetiracetam, brivaracetam, or cetriracetam, or a pharmaceutically acceptable salt thereof, or administering a pharmaceutical composition comprising levetiracetam, brivaracetam, or cetriracetam, or a pharmaceutically acceptable salt thereof, and a pharmaceutically acceptable carrier.

Diagnosis of dementia A method for diagnosing dementia subtypes is described. The method comprises obtaining brain imaging data relating to one or more patients, analysing the data using a deep learning model and classifying the one or more patients between a plurality of classes comprising a first class of patients having a first subtype of dementia and a second class of patients having a second subtype of dementia, using the deep learning model. The deep learning model has been trained using brain imaging data from patients, the brain imaging data comprising a first set of images showing evidence of temporo-parietal hypo-metabolism, and a second set of images showing evidence of hypo-metabolism in regions of the brain other than the temporal and preictal regions instead or in addition to the temporal and parietal regions, wherein the first set of images is labeled as associated with the first sub-type of dementia and the second set of images is labeled as associated with the second subtype of dementia. Related systems and methods are also described.

The invention discloses a method for analyzing an epilepsy suppression and interruption effect of an ultrafast electromagnetic pulse, and belongs to the technical field of bioelectromagnetism. The method comprises the following steps: S1, irradiating a brain model by adopting ultrafast electromagnetic pulses; s2, pulse parameters are adjusted, and the electric field distribution, the energy absorption amount and the temperature change of the temporal lobe area in the brain are changed; s3, detecting and analyzing the electric field intensity variation, the specific absorption rate (SAR), the temperature and the neural electrical activity response of the temporal lobe area, and determining optimal action parameters; and S4, evaluating inhibition and interruption effects of the ultrafast electromagnetic pulse on abnormal discharge of the temporal lobe epilepsy. According to the method, the action mechanism of the ultrafast electromagnetic pulse on the temporal lobe is researched, and technical support is provided for application research of the ultrafast electromagnetic pulse in the epilepsy replacement therapy.

The invention discloses a cross-modal sEEG-to-iEEG generation method based on a multi-scale condition regularization stream, and the method comprises the steps: obtaining sEEG and iEEG signals which are collected synchronously, and carrying out the preprocessing, and obtaining qualified condition input and target signals; then, a multi-scale conditional regularization flow model containing a multi-scale framework, multiple processes and a core reversible transformation module is constructed, and iEEG signal distribution conversion is achieved through reversible channel hybrid operation and a conditional affine coupling layer; training the model by using a maximum likelihood estimation method, and optimizing parameters until convergence; and after a new sEEG signal is preprocessed, inputting the trained model, and generating a corresponding iEEG signal through inverse transformation. According to the method, complex probability distribution is modeled through conditional regularization flow, mode collapse is avoided, nerve activity randomness is reserved, deep temporal lobe full-region iEEG generation is achieved by combining a multi-scale framework with a self-attention mechanism, high-fidelity iEEG is generated in a non-invasive mode, medical risks and cost are reduced, and the method is suitable for large-scale popularization and application. And reliable technical support is provided for epileptic focus positioning and cognitive neuroscience research.

The application provides an electroencephalogram emotion recognition method based on double-flow time-space asymmetry physiological region division. The recognition method comprises the following steps: step one, after frequency division extraction of the electroencephalogram signal, the signal is sent to a dynamic time layer; step two, the electroencephalogram signal with extracted time-frequency features is divided into four regions of frontal lobe, temporal lobe, parietal lobe and occipital lobe according to physiology, and is sent to an asymmetry space layer as a first flow; step three, the original electroencephalogram signal is first divided into four regions of frontal lobe, temporal lobe, parietal lobe and occipital lobe, and is sent to an asymmetry space layer; step four, the signal with extracted space features is sent to a dynamic time layer as a second flow; step five, five regions of the four regions in the first flow plus global electroencephalogram region and five regions of the second flow are sent to a high-level fusion layer for fusion. Compared with the prior art, the application realizes weight distribution of different physiological regions on specific emotions, so that each region of the electroencephalogram is more sensitive to emotion recognition.

The present application relates to a neuromodulation device for treating hippocampus-related brain diseases. The neuromodulation device comprises a phototherapy part and a transcranial alternating current stimulation (tACS) part. The phototherapy part irradiates near-infrared light toward at least a frontal lobe or a temporal lobe, such that the near-infrared light acts on at least a part of the hippocampus. The tACS part applies tACS of a second frequency, and an electric field action range covers at least a part of the hippocampus. When the near-infrared light is continuous light, the second frequency is in one of five representative frequency bands of brain waves. When the near-infrared light is pulsed light having a first frequency, the first frequency and the second frequency also satisfy a preset frequency relationship. The preset frequency relationship comprises: a deviation being less than a threshold, or having a preset frequency band coupling relationship. Transcranial electrical stimulation can produce analgesic and relaxing effects, which can reduce the discomfort of a subject during treatment. Therefore, the treatment time can be prolonged and / or the power density of near-infrared light can be increased as needed, so as to improve the therapeutic effect. The photoelectric bimodal stimulation can improve modulation effects on endogenous oscillations of the brain.

The invention relates to an occlusion target detection method, a neural network model and a calculation program product. The method comprises the following steps: acquiring a feature matrix corresponding to a to-be-recognized image; on the basis of the feature matrix and the frontal lobe output matrix, updating the activation state of temporal lobe neurons to obtain a temporal lobe output matrix; on the basis of the temporal lobe output matrix, updating an activation state of a frontal lobe neuron to obtain a new frontal lobe output matrix; first iteration operation is executed until a first ending condition is met, the first iteration operation is stopped, a first steady-state temporal lobe neural network model is obtained, and the first iteration operation comprises updating the activation state of the temporal lobe neurons and updating the activation state of the frontal lobe neurons; and processing the to-be-recognized image based on the first steady-state temporal lobe neural network model to obtain a recognition result. According to the method provided by the embodiment of the invention, the recognition precision can be adaptively maintained when different types of shielding are faced, and the recognition accuracy and stability are enhanced.

The present invention provides systems and methods for treating a subject for a neurologic disorder, a psychiatric disorder, a development disorder, or age-associated changes including comparing the imaged brain activity to a database of virtual representations of brain networks, wherein the virtual representations were generated by applying a multivariate coordinate-based meta-analysis (CBMA) algorithm, wherein the CBMA algorithm comprises a Low-dimensionality Meta-analytic Independent Component Analysis (Low-d M-ICA) algorithm; and making one or more determinations based on the results of the comparison, including where to place a treatment device.

The present application provides a transcranial physical stimulation apparatus for treating diseases related to a target site of the brain. The transcranial physical stimulation apparatus at least comprises a phototherapy part and an alternating current transcranial electrical stimulation part. The phototherapy part irradiates transcranial near-infrared light onto at least a frontal lobe and a temporal lobe of the head of a subject, or irradiates transcranial near-infrared light within an irradiation range containing the target site and a peripheral brain region thereof. The alternating current transcranial electrical stimulation part comprises a first scalp electrode pair and a second scalp electrode pair. A pair of electrodes constituting the first scalp electrode pair forms an electric field of a first frequency and acts on the target site, and a pair of electrodes constituting the second scalp electrode pair forms an electric field of a second frequency and acts on the target site. The second frequency is greater than the first frequency, and the ratio of the frequency difference to the first frequency is 8% or less, and the frequency difference is within the range of 1 Hz to 80 Hz. The apparatus performs, by means of near-infrared light, comprehensive, gentle, and comfortable transcranial physical treatment on a plurality of disease-related brain regions, and performs, by means of transcranial alternating current, precise targeted treatment on a disease-related target site; the two cooperate synergistically to enable a better therapeutic effect.