21 results about "Magnetoencephalography" patented technology

The present application is drawn to a system and method, as well as method for manufacture of a device and system for determining the position and orientation of at least one magnetic field sensor comprising: a rigid structure comprising an array of at least five electromagnetic coils; at least one wire that connects to and powers the electromagnetic coils; wherein the placement and orientation of the electromagnetic coils on the rigid structure are predetermined; wherein the electromagnetic coils, each having a predefined magnetic moment per unit current, are constructed with a printed circuit board (PCB) comprising at least one conductive layer; and wherein the system is configured such that a stray magnetic field emanating from the at least one, as measured at the location of the at least one magnetic field sensor, generates substantially lower magnetic field intensity than that produced by each of the at least five electromagnetic coils.

This invention discloses a magnetoencephalogram (MEG) compatible preamplifier method and device, which allows the MEG preamplifier to be placed within a magnetically shielded device. This invention achieves weak magnetism in the preamplifier circuit through the design of component selection and distribution; improves anti-interference capability and transmission stability by designing the MEG amplification factor and signal conditioning process; implements secondary amplification, power supply, and acquisition outside the magnetically shielded device, placing strongly magnetic components away from the weak magnetic environment to complete the entire acquisition process; and adopts a modular design, reducing the number of channels on each circuit board by distributing electrode channels, thereby reducing the size and facilitating the arrangement of the preamplifier system within the limited magnetically shielded space. This invention achieves weak magnetism in the preamplifier circuit, enabling high-quality brain-computer magnetic synchronous acquisition when placed within a magnetically shielded space.

The application discloses a method and system for automatic identification and repair of bad segments of magnetoencephalography based on joint diagonalization, wherein the method comprises the following steps: acquiring original multi-channel magnetoencephalography signals of a measured object; segmenting the multi-channel magnetoencephalography signals to obtain a plurality of segmented data; calculating a covariance matrix and an average covariance matrix of each segmented data; identifying bad segment data in the segmented data based on the covariance matrix and the average covariance matrix; and repairing the bad segment data by using a joint diagonalization method. In the method, the collected multi-channel magnetoencephalography signals are segmented, the covariance matrix and the Euclidean distance are used to identify the bad segments, automatic identification of the bad segments is realized, and the method can be effectively popularized to other time series signals. In addition, the joint diagonalization analysis method is applied to the repair of the bad segments, and the shortcoming of reducing data capacity of a traditional interpolation method is overcome. Furthermore, the method does not need manual marking or input of other parameters, and can effectively reduce the identification and marking process.

This invention relates to a miniaturized triaxial SERF atomic magnetometer device with dual-pump light semi-transparent and semi-reflective beams. A single pump light is guided into the probe by a polarization-maintaining fiber. Then, using a half-wave plate, a polarization beam splitter, a right-angle mirror, and a quarter-wave plate, the pump light is split into two circularly polarized pump lights of equal intensity, which then pass perpendicularly through the same alkali metal gas cell. The pump light passing through the gas cell is then split by a semi-transparent and semi-reflective planar beam splitter; half of the pump light is detected by a photodetector to extract magnetic field information, while the other half returns along the same path and passes through the alkali metal gas cell a second time. This invention achieves high-sensitivity simultaneous measurement of triaxial magnetic fields in a miniaturized triaxial SERF atomic magnetometer, enhances atomic spin polarizability, and improves the uniformity of atomic spin polarizability within the gas cell. It addresses the technical challenge of achieving uniform spin polarizability in miniaturized SERF atomic magnetometer applications, and is beneficial for applications of array-type triaxial SERF atomic magnetometers in fields such as magnetocardiography and magnetoencephalography.

The invention discloses a self-adaptive subspace projection suppression method based on optical pump magnetometer external noise, and belongs to the technical field of neural magnetic imaging (MEG) signal processing.The method comprises the steps that brain magnetic signals are collected through a wearable optical pump magnetometer array and preprocessed, and a signal and noise subspace decomposition model is established; integrating a model-driven noise modeling method and a data-driven noise modeling method, and constructing a noise subspace base vector; constructing a signal subspace basis vector in combination with a guide field matrix and event correlation analysis; identifying residual noise components based on event correlation analysis, and perfecting noise subspace modeling; signal noise separation is realized by adopting a hierarchical projection strategy; and analyzing the time correlation of internal and external space signals, and constructing a time projection matrix to remove residual interference to obtain a clean MEG signal. According to the invention, various types of external noise interferences can be effectively suppressed, the signal-to-noise ratio and the reliability of brain magnetic signals are remarkably improved, and the method is particularly suitable for practical application of a wearable optical pump magnetometer system.

The application relates to a magnetoencephalography device and a method for registering the magnetoencephalography device and MRI, and belongs to the field of magnetoencephalography research. The method comprises the following steps: acquiring a head image of a subject wearing a magnetoencephalography device; point cloudizing the head image of the subject to obtain a scene point cloud; performing corresponding point clustering processing on the scene point cloud and a marker module model point cloud, identifying the marker module, and determining the position coordinates of the marker module; determining the sensor probe position according to the position coordinates and the relative position relationship between the marker module and the sensor array; acquiring a three-dimensional MRI image of the head of the subject, and separating the three-dimensional MRI image into a scalp three-dimensional image and a cerebral cortex anatomical structure; extracting an MRI facial image according to the scalp three-dimensional image; and registering the MRI facial image and the head image of the subject based on the sensor probe position, so that the sensor array and the cerebral cortex anatomical structure are in a unified coordinate system. The method improves the accuracy of registration.

The application relates to a magnetoencephalography rhythm separation method based on a genetic algorithm and a wavelet transform, and comprises the following steps: obtaining an initial magnetoencephalography signal to perform noise reduction processing to obtain a basic magnetoencephalography signal; performing iterative search on a coded wavelet function by using a genetic algorithm to obtain an optimal wavelet function and determine a decomposition layer number; performing wavelet decomposition and wavelet coefficient reconstruction on the pretreated magnetoencephalography signal by using the wavelet function and the decomposition layer number; and performing frequency detection on the reconstructed sub-signal to determine an ideal magnetoencephalography rhythm signal. According to the characteristics that the genetic algorithm can adaptively find a global optimal solution, the wavelet function with higher information matching degree between different types of magnetoencephalography signals and the magnetoencephalography signal to be separated is found, the reliability of wavelet function selection is improved, the dependence of the wavelet decomposition algorithm on work experience is reduced, the magnetoencephalography rhythm signal is decomposed by using the wavelet transform, different frequency signals are accurately separated, and the time frequency resolution capability and characteristics of the rhythm signal are retained.

The application relates to a mouse heart magnetocardiography and magnetoencephalography testing device and method based on a zero-field atomic magnetometer, and relates to the field of heart magnetocardiography and magnetoencephalography testing. The application solves the problems that the existing mouse heart magnetocardiography and magnetoencephalography testing device has a large volume, and the magnetic field signal is distorted due to the movement or struggle of the mouse, and motion artifacts are generated. A plurality of groups of tool fixing hole positions (1-1) are formed in pairs on the upper end face of a platform (1), a plurality of heart magnetometer mounting holes (1-2) are formed in the middle of the length direction of the lower end face of the platform (1), a heart magnetometer is mounted in the heart magnetometer mounting hole (1-2), one insert (2) is inserted in each group of tool fixing hole positions (1-1), the insert (2) is provided with a magnetoencephalography mounting hole (2-1) and a head mounting hole (2-2). The mouse heart magnetic signal and the magnetoencephalography signal are tested at the same time, and the error introduced by the environmental magnetic field change in the experiment process is reduced to the maximum extent. The application is used for mouse heart magnetocardiography and magnetoencephalography testing.

The application relates to a kind of based on magnetoencephalography stimulation combination electroencephalogram analysis method, method is by carrying out real stimulation and pseudo-stimulation control experiment, respectively obtains original mixed signal matrix and reference sensory artifact signal matrix;Then, the convolution kernel to be solved is introduced to construct convolution mixed mathematical model, and the modulation mechanism of sensory artifact is described in a mathematical way;Subsequently, two matrixes are input into the model, and the pure direct neural response signal matrix and individualized modulation convolution kernel matrix are separated out by applying joint iterative inversion calculation with space-time constraints;Finally, based on pure signal extraction multidimensional neurophysiological characteristics and combined with modulation mode analysis, generate comprehensive report.The method can effectively separate sensory artifact, and provide a new analysis approach for obtaining more reliable and direct cortical neuroelectrophysiological response.

The invention discloses a structural source interference-oriented spatial filtering brain magnetic signal denoising method and system, and belongs to the technical field of brain magnetic signal processing. According to the method, suppression of non-task related sources is realized through a two-stage subspace projection mechanism from a space domain to a time domain. The method comprises the following steps: firstly, acquiring an original multi-channel brain magnetic signal, limiting a lead field matrix source space based on space prior, and only reserving an ROI (Region of Interest) internal source point; secondly, through spatial domain filtering, the ROI source point lead field is expanded into a signal subspace, an original signal is projected to the subspace, and preliminary separation of a target signal and non-target brain region background interference is achieved; and finally, applying time domain subspace projection to the interference component, extracting a time domain interference subspace, and constructing a projection operator to eliminate residual interference. According to the method, the source reconstruction precision and the analysis reliability of downstream cognitive / clinical indexes are remarkably improved, and an efficient and accurate solution is provided for OPM-MEG task state signal processing.

The invention discloses a brain magnetic compatible near-infrared channel arrangement and modulation frequency distribution method, and belongs to the technical field of multi-mode brain function imaging. In order to solve the problems that in the prior art, personalized optrode arrangement optimization is difficult, standardized meta-information files are tedious to generate, and brain magnetic compatible frequency distribution efficiency is low, optrode coordinates are constructed based on individual head three-dimensional information, the positions of a light source and a detector are optimized through a greedy algorithm, and optrode two-dimensional coordinates are adjusted through dimension reduction and nonlinear optimization; and an automatic scheme is generated by using a method for carrying out brain magnetic compatible frequency allocation by using a graph coloring algorithm. According to the method, the experimental channel scheme of the whole brain or the region of interest can be quickly generated, the standard file and the channel visualization graph can be automatically generated, the brain magnetic compatibility and the high frequency utilization rate are considered at the same time, and the method is suitable for multi-mode brain imaging experiment preparation and personalized helmet or flexible cap optrode design.

Various embodiments disclosed herein comprise systems and methods to locate magnetic field sensors. In some examples, a system comprises a controller, a sensor mount, a coil set comprising one or more coils, and a magnetic field sensor. The sensor mount mounts the magnetic field sensor and constrains at least one degree of freedom of the magnetic field sensor in position or orientation. The controller supplies electric current to the coil set. The coil set generates magnetic waves that form at least one coil magnetic field in response to receiving the current. The magnetic field sensor measures the strength of the coil magnetic field. The controller locates the magnetic field sensor based on the constraint and the measured strength of the coil magnetic field.

The application provides a transcranial photomagnetic neuromodulation device, which comprises a magnetic stimulation module including a magnetic stimulation coil for applying transcranial magnetic stimulation, and a light stimulation module corresponding to the magnetic stimulation module, wherein the light stimulation module comprises a light source part and a diffusion assembly; the light source part emits near-infrared light; the diffusion assembly is arranged on the wearing side of the magnetic stimulation coil; the diffusion assembly receives the near-infrared light from the light source part and diffuses the near-infrared light; the diffused near-infrared light is emitted through the exit surface of the diffusion assembly to irradiate the head of a user; and the light source part is arranged at a position where the magnetic field intensity of the magnetic stimulation coil is less than a first threshold value. When the device is used, the interference between the light stimulation module and the magnetic stimulation module is significantly reduced, the light and magnetic stimulation can effectively cooperate to perform photomagnetic regulation on the target brain area in the time domain and the spatial domain, a wide brain volume and a deeper depth under the cerebral cortex can be stimulated, and the treatment effect is effectively improved.

This invention provides a method, apparatus, and device for issuing brain-computer interface commands related to language-motor co-imagination. The method includes: acquiring a user's magnetoencephalography (MEG) data during a language-motor co-imagination task, inputting this data into a language-motor co-decoding model to obtain motor intention results, and then issuing brain-computer interface commands. The adaptive position encoding module in the language-motor co-decoding model identifies the cognitive state in the MEG data and extracts motor imagination soft boundary features, semantic cue soft boundary features, and combined soft boundary features. These features provide the model with accurate boundary information, helping to distinguish different imagination tasks. The motor imagination decoding module in the model extracts time-frequency features using the motor imagination soft boundary features; the semantic decoding module in the model extracts discrete semantic encoded sequences based on the semantic cue soft boundary features. The combined decoding module integrates these features for intention decoding, significantly improving the discriminative power of different imagination tasks and the accuracy of intention decoding.

The application is suitable for the technical field of magnetoencephalography, and provides an analog front-end circuit applied to magnetoencephalography, which comprises a chopping modulation circuit, an amplifier, a chopping demodulation circuit, a first low-pass filter and a second low-pass filter connected with the chopping demodulation circuit respectively, and a single analog-to-digital converter; the first low-pass filter is used for outputting a magnetoencephalography signal containing a target low-frequency signal and a direct current offset signal; the second low-pass filter is used for outputting a magnetoencephalography signal containing only the direct current offset signal; the analog-to-digital converter is used for performing differential operation on the magnetoencephalography signal containing the target low-frequency signal and the direct current offset signal output by the first low-pass filter and the magnetoencephalography signal containing only the direct current offset signal output by the second low-pass filter, generating a magnetoencephalography signal after the direct current offset signal is eliminated, converting the magnetoencephalography signal after the direct current offset signal is eliminated into a digital signal, and outputting the digital signal to a processing unit. The analog front-end circuit can eliminate the direct current offset signal.

The application provides a local sensor array design method for brain magnetic source positioning. The method comprises the following steps: obtaining a scalp surface and a cortex surface of a subject based on a head nuclear magnetic resonance image, obtaining a grid of the scalp surface by using a three-dimensional reconstruction technology, and further generating a candidate sensor array; selecting a dipole source of a brain functional area of interest based on a Brodmann partition system, and calculating array sensitivity corresponding to the selected dipole source by using a Frobenius norm; determining an initial position of the local sensor array based on the array sensitivity, and determining the volume of the sensor and the distance between adjacent sensors based on a size radius and a spacing radius. The local sensor array design method realized by the application is simple and efficient, has strong practicability and universality, and can obtain more accurate source estimation under the condition that the number of sensors is limited.

The application discloses a magnetoencephalography compatible multi-channel near-infrared high sampling rate modulation method and system, and belongs to the field of multi-modal brain function imaging research.The method comprises the following steps: modulating a driving signal of an fNIRS light source to a high-frequency carrier; adopting a multi-channel frequency division multiplexing strategy, transmitting the modulated driving signal to each fNIRS light source, so that each fNIRS light source emits infrared light rays for detecting a target; and demodulating the detected infrared light rays to obtain the amplitude of the detected infrared light rays.The application can realize non-contact sensing of the target.The application can reduce electromagnetic interference in the process of MEG and fNIRS synchronous imaging, utilize specific frequency modulation technology to realize synchronous acquisition of magnetoencephalography signals and multi-channel high sampling rate near-infrared signals, and accurately and quickly demodulate the near-infrared signals.

A single-beam dual-channel atomic magnetometer system, through a combined polarization beam splitter set in a dual-channel meter head with a single-beam input interface, can split a single beam into a first pump beam and a second pump beam to act on the first alkali metal gas cell and the second alkali metal gas cell respectively. It can simultaneously obtain dual-channel magnetic field information, and has the characteristics of high sensitivity and high integration. It is conducive to forming a high-density magnetometer array and serving fields such as magnetoencephalography and magnetocardiography.

Various embodiments disclosed herein comprise systems and methods to locate magnetic field sensors. In some examples, a system comprises a controller, a sensor mount, a coil set comprising one or more coils, and a magnetic field sensor. The sensor mount mounts the magnetic field sensor and constrains at least one degree of freedom of the magnetic field sensor in position or orientation. The controller supplies electric current to the coil set. The coil set generates magnetic waves that form at least one coil magnetic field in response to receiving the current. The magnetic field sensor measures the strength of the coil magnetic field. The controller locates the magnetic field sensor based on the constraint and the measured strength of the coil magnetic field.

The application discloses a kind of biological magnetic imaging systems with adjustable spatial resolution, including detection unit, stimulation unit, optical pumping atomic magnetic field measurement unit and data acquisition processing device;Optical pumping atomic magnetic field measurement unit is set in magnetic shield room;Optical pumping atomic magnetic field measurement unit includes atomic gas chamber;Detection unit includes laser, diffractive optical element, collimating lens, imaging zoom lens group and multiple fixed pitch photodetector;Diffractive optical element and collimating lens are set along laser exit light path;Imaging zoom lens group is set behind the exit light path of atomic gas chamber;Photodetector receives signal light emitted by imaging zoom lens group;Data acquisition processing device is electrically connected with each photodetector.The application can save time and cost under the premise, adjust the spatial resolution of system conveniently and quickly, has wide application scene, can adapt to magnetocardiography, magnetoencephalography, muscle magnetism and different application needs, and is suitable for constructing atomic magnetometer array with adjustable pitch.

The present disclosure relates to a model training method, device and a source localization method for a magnetoencephalography system. The model training method comprises: obtaining a three-dimensional model of a brain of a subject and a relative position relationship between the brain and a sensor array; performing grid division on a preset region of interest in the three-dimensional model to obtain a plurality of simulation source points; generating at least one set of simulation source signals at the plurality of simulation source points in the three-dimensional model; determining, based on the at least one set of simulation source signals, at least one set of simulation sensor signals expected to be collected by the sensor array using a forward model, wherein the forward model is a mathematical model representing a relationship between electromagnetic activity of a source point in the brain and magnetoencephalography signals collected by the sensor array, and the forward model is determined based on the relative position relationship; and training a deep learning model to construct a magnetoencephalography source localization model by taking the at least one set of simulation sensor signals as input and the at least one set of simulation source signals as labels.