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 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 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.

Compositions and methods for diagnosing neurological disorders such as autism spectrum disorders are disclosed.

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 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.

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 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 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 provides a magnetoencephalogram single auditory induction signal detection method and an electronic device. The method comprises the steps: converting a to-be-detected brain magnetic signal into two-dimensional matrix data, sequentially taking each brain magnetic sensor as a selected sensor, and calculating the correlation coefficient of the selected sensor and each sensor in a set neighborhood; according to the two-dimensional matrix data of the selected sensor, setting the two-dimensional matrix data and the correlation coefficient of each brain magnetic sensor in the neighborhood, and calculating increasing signals of the selected sensors; obtaining a brain magnetic signal view according to the increasing signal and the position of each brain magnetic sensor; and extracting signal space distribution characteristics of the brain magnetic signal view, classifying the signal space distribution characteristics, and judging a single auditory induction signal or a noise signal contained in the to-be-detected signal. According to the method, the information of the original signal can be reserved to the maximum extent, rest information contained in the signal cannot be influenced, the detection is more accurate, and the calculation is simpler and more convenient.

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.