50 results about "Magneto encephalography" patented technology

An array of optically pumped magnetometers includes a vapor cell arrangement having a wafer defining one or more cavities and alkali metal atoms disposed in the cavities to provide an alkali metal vapor; an array of light sources, each of the light sources arranged to illuminate a different portion of the one or more cavities of the vapor cell arrangement with light; at least one mirror arranged to reflect the light from the array of light sources after the light passes through the one or more cavities of the vapor cell arrangement; and an array of detectors to receive light reflected by the at least one mirror, wherein each of the detectors is arranged to receive light originating from one of the light sources.

A method of operating an optically pumped magnetometer (OPM) includes directing a light beam through a vapor cell of the OPM including a vapor of atoms; applying RF excitation to cause spins of the atoms to precess; measuring a frequency of the precession; for each of a plurality of different axes relative to the vapor cell, directing a light beam through the vapor cell, applying a magnetic field through the vapor cell along the axis, applying RF excitation to cause spins of the atoms to precess, and measuring a frequency of the precession in the applied magnetic field; determining magnitude and components of an ambient background magnetic field along the axes using the measured frequencies; and applying a magnetic field based on the components around the vapor cell to counteract the ambient background magnetic field to facilitate operation of the OPM in a spin exchange relaxation free (SERF) mode.

This invention discloses methods and apparatuses for 3D imaging in Magnetoencephalography (MEG), Magnetocardiography (MCG), and electrical activity in any biological tissue such as neural / muscle tissue. This invention is based on Field Paradigm founded on the principle that the field intensity distribution in a 3D volume space uniquely determines the 3D density distribution of the field emission source and vice versa. Electrical neural / muscle activity in any biological tissue results in an electrical current pattern that produces a magnetic field. This magnetic field is measured in a 3D volume space that extends in all directions including substantially along the radial direction from the center of the object being imaged. Further, magnetic field intensity is measured at each point along three mutually perpendicular directions. This measured data captures all the available information and facilitates a computationally efficient closed-form solution to the 3D image reconstruction problem without the use of heuristic assumptions. This is unlike prior art where measurements are made only on a surface at a nearly constant radial distance from the center of the target object, and along a single direction. Therefore necessary, useful, and available data is ignored and not measured in prior art. Consequently, prior art does not provide a closed-form solution to the 3D image reconstruction problem and it uses heuristic assumptions. The methods and apparatuses of the present invention reconstruct a 3D image of the neural / muscle electrical current pattern in MEG, MCG, and related areas, by processing image data in either the original spatial domain or the Fourier domain.

A collimator, and in particular a method for making a collimator for use with a small high resolution single-photon emission computed tomographic (SPECT) imaging tool for small animal research. The collimator is sized, both functionally and structurally, particularly smaller than known collimators and appropriately scaled to achieve a highly sensitive collimator which facilitates desired reconstruction resolutions for small animals, as well as compliments other functional imaging modalities such as positron emission tomography (PET), functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and event-related potential (ERP), magneto-encephalography (MEG), and near-infrared optical imaging.

The invention relates to a children ASD diagnosis device based on a magnetoencephalogram and an electroencephalogram. The children ASD diagnosis device comprises a magnetic shielding system, a head-mounted electroencephalogram and magnetoencephalogram array type sensor system, an electroencephalogram and magnetoencephalogram data acquisition system, a sensory stimulation system, a signal processing system and a data analysis system. The magnetic shielding system can effectively reduce background magnetic field noise. The head-mounted electroencephalogram and magnetoencephalogram array type sensor system can carry out whole-brain collection on a tested child in a combined nesting mode. The electroencephalogram and magnetoencephalogram data acquisition system can record brain electrical activity information. The sensory stimulation system can present visual and auditory sensory stimulation for the tested child. The signal processing system removes biological magnetic noise and backgroundmagnetic noise. The data analysis system can extract pathological features in the signals for analysis. The children ASD diagnosis device provided by the invention has the advantages of high sensitivity and specificity, multiple information sources, high signal quality, easy acceptance by children and the like. The children ASD diagnosis device has the advantages of high sensitivity and specificity in the aspect of ASD diagnosis of children.

The invention discloses an epilepsy magnetoencephalogram spinous wave automatic detection method and a traceability positioning system. The method comprises the following steps: 1) segmenting magnetoencephalogram data of each sample to obtain a plurality of magnetoencephalogram data segments; wherein each magnetoencephalogram data segment is a data set in the form of a two-dimensional matrix withthe size of M * N; 2) training a magnetoencephalogram multi-view spine wave detection model by using the magnetoencephalogram data segment; 3) performing artifact removal operation on the magnetoencephalogram signal to be processed, and then segmenting magnetoencephalogram data to obtain a plurality of magnetoencephalogram data segments; 4) respectively inputting the obtained magnetoencephalogramdata fragments into the trained magnetoencephalogram multi-view ratchet detection model to obtain ratchet classification results corresponding to the magnetoencephalogram data fragments; and 5) determining whether the to-be-processed magnetoencephalogram signal has the ratchet wave or not according to the obtained ratchet wave classification result. According to the invention, the working processof a doctor is simplified, and the doctor can be effectively assisted in carrying out preoperative evaluation on an epilepsy patient.

The invention discloses a magnetoencephalogram multi-modal image registration system based on MRI and OPM. The system comprises a double-mark combined type registration module, the registration modulecomprises an OPM brain magnetic imaging marking module and a nuclear magnetic resonance imaging marking module. The OPM brain magnetic imaging marking module comprises a flexible circuit board and acircular positioning coil arranged on the flexible circuit board. The nuclear magnetic resonance imaging marking module comprises a reference block which is made of a non-magnetic material and is internally provided with solid oil; the flexible circuit board is detachably arranged on the surface of the reference block; a positioning part of the flexible circuit board is arranged on the upper surface of the reference block; the reference point information of the position where the circular positioning coil is located in the magnetoencephalogram and the space coordinate system information of thereference point of the position where the solid oil of the MRI image is located are obtained; image registration can be carried out by adopting a basic and simple reference point positioning method,so that the registration precision is improved, the calculation time is greatly shortened, and the advancing pace of a new generation of magnetoencephalogram technology from an experimental design simulation stage to a medical clinical application stage is promoted.

A set of brain data representing a time series of neurophysiologic activity acquired by spatially distributed sensors arranged to detect neural signaling of a brain (such as by the use of magnetoencephalography) is obtained. The set of brain data is processed to obtain a dynamic brain model based on a set of statistically-independent temporal measures, such as partial cross correlations, among groupings of different time series within the set of brain data. The dynamic brain model represents interactions between neural populations of the brain occurring close in time, such as with zero lag, for example. The dynamic brain model can be analyzed to obtain the neurophysiologic assessment of the brain. Data processing techniques may be used to assess structural or neurochemical brain pathologies.

A visual stimulation presentation apparatus including: a specimen holding unit, made of a non-magnetic material, configured to hold multiple specimens of actual objects serving as specimens for presenting a subject with visual stimulation when running an apparatus to measure brain functions of the subject by detecting change in magnetic field; an actuator, made of a non-magnetic material, configured to selectively present multiple specimens of actual objects set in the specimen holding unit, by driving the specimen holding unit; and a control unit configured to control driving of the actuator; is used, whereby presenting time and presenting position can be precisely controlled and the delicate surface state of the objects with a high degree of sense of texture.

The invention provides a multi-channel SERF atomic magnetometer device for brain magnetic measurement and an application method. The multi-channel atomic magnetometer is designed by utilizing latticebeam splitting characteristics of a diffractive optical element, so that imaging and acquisition of a magnetoencephalogram are realized. Compared with a traditional SQUID magnetoencephalogram instrument, the multi-channel SERF atomic magnetometer device has higher sensitivity, higher signal-to-noise ratio and higher spatial resolution. Compared with an existing multi-channel SERF atomic magnetometer, the multi-channel SERF atomic magnetometer device is easier to integrate and miniaturize, and is not limited to array type photoelectric detectors and lower inter-channel signal crosstalk. The multi-channel SERF atomic magnetometer device is mainly applied to the field of magnetoencephalogram research, and has potential application prospects in the fields of material chemical component and structure analysis, mineral deposit detection, geomagnetic navigation, earthquake prediction and the like. Meanwhile, the multi-channel design of the multi-channel SERF atomic magnetometer device can further be used in other optical pump atomic magnetometers, and universality and innovativeness are achieved.

The invention discloses an automatic detection method for epilepsy electroencephalography (EEG) / magnetoencephalography (MEG) abnormal waves and a positioning system The method comprises the followingsteps: 1) segmenting EEG / MEG data of each sample to obtain a plurality of EEG / MEG data segments, wherein each EEG / MEG data segment is a data set in a two-dimensional matrix form; 2) training an EEG / MEG multi-view abnormal wave detection model by utilizing the EEG / MEG data fragments; 3) performing artifact removal operation on an EEG / MEG signal to be processed, and then segmenting the EEG / MEG datato obtain a plurality of EEG / MEG data segments; 4) respectively inputting the obtained EEG / MEG data fragments into the trained EEG / MEG multi-view abnormal wave detection model to obtain abnormal waveclassification results corresponding to the EEG / MEG data fragments; and 5) determining whether the EEG / MEG signal to be processed has abnormal waves or not according to the obtained abnormal wave classification result.

A shielding arrangement for a magnetoencephalography (MEG) system includes a passively shielded enclosure having a plurality of walls defining the passively shielded enclosure, each of the plurality of walls including passive magnetic shielding material to reduce an ambient background magnetic field within the passively shielded enclosure; a vestibular wall extending from a first vertical wall to define, and at least partially separate, a vestibular area of the passively shielded enclosure adjacent the doorway and a user area of the passively shielded enclosure; and active shield coils distributed within the passively shielded enclosure and configured to further reduce the ambient background magnetic field within the user area of the passively shielded enclosure.

The invention provides a magnetoencephalogram source positioning method and device based on Tucker decomposition and a ripple time window. The device comprises a magnetoencephalogram sensor which is used for obtaining a first magnetoencephalogram signal of a user; a ripple detection unit which is used for detecting the ripple time window in the first magnetoencephalogram signal through a root-mean-square method to serve as a time window for source positioning and obtaining the first magnetoencephalogram signal in the ripple time window to serve as a second magnetoencephalogram signal; a high-order orthogonal iteration based Tucker decomposition unit which is used for carrying out Tucker decomposition on the original tensor of the second magnetoencephalogram signal to calculate an estimated value of the original tensor; and a source positioning unit which is used for calculating a covariance matrix for the estimated value and calculating a source position corresponding to the second magnetoencephalogram signal through an LCMV inverse problem solving method in a beamforming method. According to the method, the influence of noise signals is eliminated, the calculation complexity is reduced, the consistency of each calculation result is ensured, and the positioning accuracy of the epileptogenic region is improved.

The invention discloses an epilepsy spine wave automatic detection and peak value positioning method. The method comprises the following steps: 1) splitting each magnetoencephalogram data into a plurality of data segments with the same size; 2) constructing a deep learning network model which comprises a single-channel coding module, a deep feature transmission module and a global decoding module, wherein the single-channel coding module is used for carrying out depth feature extraction on single-channel data in a data fragment to obtain a plurality of depth features of different sizes and sending the depth features to the depth feature transmission module for data dimension reduction, and the global coding module is used for carrying out convolution and up-sampling calculation on the depth features from the depth feature with the minimum size, and splicing the obtained depth features with the depth features with the correspondingly consistent size until the depth feature with the maximum size is processed; (3) training a deep learning network model by using each data segment, and (4) inputting magnetoencephalogram data to be processed into the trained deep learning network model to carry out ratchet wave detection and peak value positioning.

The technology provides a system and method for simulating and detecting bio signals such as brain bio-signals. The technology can be used for medical or non-medical purposes, for instance to simulate or evaluate certain medical conditions using a physical brain-type phantom body. A set of optical fibers provides modulated signals received from an optical signal modulator, which is managed by a controller to generate repeatable signals with high fidelity. The modulated signals are received by a set of emission elements such as photoreceivers or other optical electrodes disposed within or otherwise about the phantom body. The emission elements output electrical signals corresponding to the input modulated optical signals. The electrical signals are detected by a set of sensors. The sensors are coupled to a receiver device that is able to evaluate the electrical signals, such as for an electroencephalograph (EEG), electrocardiogram (ECG), electromyogram (EMG) or magnetoencephalography (MEG) diagnostic system.

The invention provides a magnetoencephalography system and a method of operating the magnetoencephalography system, and relates to the technical field of medical imaging. The magnetoencephalography system comprises a flexible brain magnetic cap having inserting grooves, and a limiting clamping sleeve which cooperates with the inserting grooves and comprises a fixing part, the fixing part is arranged on the surface, adjacent to the inserting grooves, of the limiting clamping sleeve, and the limiting clamping sleeve is used for fixing an atom magnetometer into the inserting grooves. According to the magnetoencephalography system provided by the invention, by virtue of the flexible brain magnetic cap with the inserting grooves, the limiting clamping sleeve cooperating with the inserting grooves and linkage matching between the limiting clamping sleeve and the fixing part on the adjacent surfaces of the inserting grooves, the purpose of portable detection of brain magnetic signals of a subject is achieved. The flexible brain magnetic cap provided by the invention can adapt to head contours of different sizes within a certain range, the portability of magnetoencephalography detection is improved, and the wearing experience is greatly improved.

Techniques are described for determining cognitive impairment, an example of which includes accessing a set of epochs of magnetoencephalography (MEG) data of responses of a brain of a test patient toa plurality of auditory stimulus events; processing the set of epochs to identify parameter values one or more of which is based on information from the individual epochs without averaging or otherwise collapsing the epoch data. The parameter values are input into a model that is trained based on the parameters to determine whether the test patient is cognitively impaired.

The invention discloses a high-precision multi-channelmagnetoencephalogram system based on an atom magnetometer, the system comprises a sensing module, a data collection module, a software module and a shielding module, in the shielding module, when external magnetic noise is within a certain range, the sensing module detects a brain magnetic signal and transmits the brain magnetic signal to the data collection module, the data collection module is used for processing the signal data, then the processed data are transmitted to the software module, and finally the software module is used for analyzing the data to obtain a detection result. The hardware system and the software system are optimized and integrated, the system can be operated through simple keys, direct linkage with third-party software can be achieved, the new-generation magnetoencephalogram system can be practically applied, liquid nitrogen or liquid helium does not need to be adopted for refrigeration, and the intelligent magnetoencephalogram software and hardware system is good in system application flexibility, high in sensitivity, wearable and high in integration.

The present invention provides a magnetic monitoring system for imaging, monitoring, scanning or mapping for brain or heart activity of subjects including children and adults, the system comprising of a magnetoencephalographic or magnetocardiographic system incorporating SQUID sensors for measuring brain activity or heart activity, the system including a plurality of Dewar helmets of variable sizes and shapes; and a plurality of monitoring interfaces; wherein the sensor system helmet is moveable by horizontal Dewar rotation. The sensor system includes configurations where the size and shape of helmets in the system may be different to accommodate different sized subjects for monitoring simultaneously.

The invention provides a method for carrying out low-intensity magnetic field space imaging based on semiconductor two-dimensional electron gas. The method comprises the following steps: S1, carryingout molecular beam epitaxial growth on a two-dimensional electron gas semiconductor heterojunction; s2, performing micro-nano processing on the two-dimensional electron gas semiconductor heterojunction to obtain a discrete Hall device of which the characteristic size is within the range of 10nm-1mm; and S3, integrating discrete Hall devices to obtain a linear array or area array weak magnetic detector so as to realize spatial imaging of a weak magnetic field. By utilizing the characteristic of high carrier mobility of semiconductor two-dimensional electron gas at room temperature, high-precision weak magnetic detection and imaging are carried out through a Hall effect principle, and the device can be used for weak magnetic detection and imaging of human bodies such as magnetocardiograms and magnetoencephalograms, and has the advantages of portability, low cost, high space and time resolution and the like.

The invention provides a neural network-based magnetoencephalogram eye movement artifact detection and a elimination method and an electronic device. The method comprises the following steps: cuttinga to-be-detected magnetoencephalogram signal, and drawing a plurality of magnetoencephalogram signal views according to a signal segment and a magnetoencephalogram sensor detection signal position; extracting signal space distribution characteristics of the magnetoencephalogram, and classifying the signal space distribution characteristics; obtaining an eye movement signal interference segment according to a fixed ratio and the eye movement electrooculogram signal segment at the corresponding time point of the magnetoencephalogram signal segment containing the eye movement artifact noise signal; subtracting the magnetoencephalogram signal segment containing the eye movement artifact noise signal from the eye movement signal interference segment, and restoring the obtained signal segment with removed the eye movement artifact noise signal to a corresponding position. According to the invention, the electrooculogram signal measured by an electrode is not needed during detection, and themagnetoencephalogram signal that is not influenced by the electrooculogram signal is not interfered during elimination, so that the information in the original magnetoencephalogram signal can be reserved to the maximum extent.

The invention discloses a Riemannian feature migration-based magnetoencephalogram signal classification method and device and a medium, and the method comprises the following steps: obtaining magnetoencephalogram signals, and carrying out the filtering of the magnetoencephalogram signals through a band-pass filter and a spatial filter, and obtaining filtered signals; constructing Riemannian features according to the sample covariance matrix of the filtering signal; introducing a discrimination subspace alignment method according to the tag information of the existing subjects, and aligning Riemannian features of the existing subjects and the target subject; and training a classifier according to the existing subject features after feature alignment and the labels, and predicting the category of the magnetoencephalogram signal of the target subject by adopting the trained classifier. According to the method, the feature distribution difference between the source domain and the target domain is reduced through the discriminant subspace alignment algorithm, the quality of model training features is improved, compared with a traditional cross-subject transfer learning method, the prediction accuracy can be better improved, and the method and device can be widely applied to the field of brain-computer interfaces.

The invention relates to the technical field of signal processing, in particular to a magnetoencephalogram decoding method based on image features. The method comprises the steps: giving a signal stimulation to the brain, obtaining the needed magnetoencephalogram data, carrying out the preprocessing of the magnetoencephalogram data, carrying out the spatial filtering of the magnetoencephalogram data, and obtaining the magnetoencephalogram data; the spatial filtering is used for reducing the dimension of the evoked potential, improving the signal-to-noise ratio of the evoked potential and further virtualizing the magnetoencephalogram data, the virtualized image is small in data volume during processing, the space-time dynamic process of magnetoencephalogram signals is considered in the formation of grids, that is, the spatial signals are arranged according to the time sequence, the classification precision is improved, and the classification efficiency is improved. Gist features are selected as image features of magnetoencephalogram decoding, due to the fact that the Gist features are biologically inspired features, a good effect is achieved in image classification, finally, a linear support vector machine classifier is adopted for classifying magnetoencephalogram signals, and the method solves the problem that in the prior art, precision is not high when magnetoencephalogram data are classified.