270 results about "Magnetic brain stimulation" patented technology

A coil configuration and method for transcranial magnetic stimulation enabling stimulation of deep regions of the brain without excessively stimulating the cortex is provided. The coil configuration utilizes at least one coil to produce an off-plane magnetic field to enhance the magnetic field from a top TMS coil. In one configuration at least a single variable position coil referred to as the Variable Halo Coil and positionable vertically and / or angularly is used.

A system for administering transcranial magnetic stimulation in which two or more coils are applied to the patient's body. The coils each may emit a magnetic field which when positioned in one or more configurations result in field overlapping. Magnetic field overlap achieves therapeutic effects otherwise difficult, or impossible, to achieve from traditional single coil TMS devices.

The delivery of neurostimulation to a subject using a closed-loop neurostimulation device (e.g., using a brain stimulation device to provide neurostimulation to a subject's brain) is controlled based on a global optimization-based temporal prediction framework. As a result, the brain stimulation device (e.g., a transcranial magnetic stimulation (“TMS”) device) is synchronized with the ongoing neural state (e.g., brain state) in real time. For instance, a brain recording is analyzed to extract the brain process of interest (e.g., frequency of brain oscillations) and used train a prediction algorithm. After that, a stimulation stage is implemented, in which the individual brain state is analyzed in real-time, the occurrence of the biomarkers (e.g., brain oscillation phase) is predicted, and the stimulation is triggered at the expected time.

The invention provides a transcranial stimulation magnetic therapy closed-loop control method and system, and the method comprises the steps: determining a multi-modal physiological signal of a user, the multi-modal physiological signal at least comprising an electroencephalogram signal, an autonomic nerve physiological signal and a subjective feedback signal; constructing an individual dynamic baseline spectrum based on user multi-state data collected before treatment; the method comprises the following steps: preprocessing a multi-modal physiological signal collected in a treatment process, and extracting a real-time feature vector; calculating a comprehensive deviation index of the real-time feature vector and the individual dynamic baseline spectrum, and determining a deviation type based on the comprehensive deviation index; the adjustment amount of transcranial magnetic stimulation parameters is dynamically calculated according to the deviation type, the individual response characteristics and the historical treatment data, stimulation operation is conducted according to the adjustment amount of the transcranial magnetic stimulation parameters, and the transcranial magnetic stimulation parameters at least comprise the stimulation frequency, the intensity, the pulse width and the stimulation duration. Parameters of transcranial magnetic stimulation are adaptively changed according to changes of neuron oscillation of a patient in the treatment process.

The invention relates to a transcranial magnetic stimulation high-precision positioning method, device and equipment based on optical navigation. Comprising the steps of selecting non-coplanar reference points based on a three-dimensional brain model of a patient, obtaining image coordinates and physical coordinates of all the reference points, carrying out corresponding point matching through the image coordinates and the physical coordinates, calculating and generating an optimal rigid transformation matrix, carrying out target registration error calculation, and realizing registration of an image coordinate system and a physical coordinate system. And according to the registered brain tissue conductivity parameters, calculating electric field space distribution induced by the transcranial magnetic stimulation coil in a target brain area, dynamically correcting stimulation target point coordinates of the virtual coil, and according to a completed coordinate system registration result, dynamically displaying the position and direction of the virtual coil corresponding to the transcranial magnetic stimulation coil on the three-dimensional brain model. And synchronously updating the brain slice view based on the corrected target point coordinates, and highlighting the actually stimulated brain region boundary. According to the method, adaptive neural navigation is driven through electric field remapping, and compensation target point correction is achieved.

The invention discloses a transcranial magnetic navigation and curative effect evaluation system based on electroencephalogram power spectrum analysis, particularly relates to the technical field of electroencephalogram signal processing, and is used for solving the technical problem that existing transcranial magnetic stimulation treatment lacks interference evaluation and stimulation path optimization on a cortical collaborative area. According to the method, electroencephalogram signals of a testee in a resting state and a task state are collected, phase-amplitude coupling indexes between frequency bands are extracted, a frequency-crossing coupling matrix is constructed, a nested chain structure with modulation direction consistency is identified, a stable resonance channel group is extracted from a channel intersection set to form a collaborative active region, and the collaborative active region is constructed. And after mapping to a standard brain map, carrying out space matching with a TMS target spot, evaluating an interference risk level, formulating a stimulation avoidance strategy, recording side reactions during treatment, and constructing a curative effect scoring window in a normalization manner, so as to realize synchronous optimization of stimulation planning and curative effect evaluation.

The invention discloses a transcranial magnetic stimulation target region recommendation method based on craniocerebral position estimation. The method comprises the following steps: constructing a face key point cloud based on binocular stereo vision; reconstructing the face key point cloud into a cranial surface model by using a pre-trained generative model; the method comprises the following steps: collecting magnetic resonance imaging data of patients with various diseases, establishing a transcranial magnetic stimulation target region standardized template with disease specificity, and determining a stimulation target region of each disease in a standard space; and based on the transcranial magnetic stimulation target region standardization template, mapping the corresponding stimulation target region from the standard space brain region to the scalp of the patient according to the disease type of the patient so as to realize recommendation. According to the method, the graph neural network is innovatively combined with the SHAP algorithm, the scientificity and interpretability of target spot selection are improved, important brain region target spots are obtained by calculating the contribution value of classification model features to classification decision of each sample, and then intervention target spots are sorted and selected to obtain an optimal treatment target spot recommendation scheme.

The invention provides a control method and device for a transcranial magnetic robot. The control method comprises the steps that whether the current pressure borne by a transcranial magnetic stimulation racket at the tail end of a robot arm of the transcranial magnetic robot is zero or not is monitored; if the current pressure is not zero, determining a current control strategy of the transcranial magnetic robot according to a relationship between the current pressure and a preset pressure threshold range; and controlling the mechanical arm of the transcranial magnetic robot to move according to the current control strategy. Therefore, the movement of the mechanical arm is adjusted according to the current pressure borne by the transcranial magnetic stimulation racket, so that the transcranial magnetic stimulation racket is ensured not to be separated from the target spot and be tightly attached to the to-be-attached part of the patient, and the treatment experience of the patient is improved.

The invention belongs to the technical field of transcranial magnetic stimulation coil design, and particularly provides a transcranial magnetic stimulation coil design method and system based on an inverse boundary element method.The method comprises the steps that firstly, a stream function calculation formula based on the inverse boundary element method and a regulation and control mechanism of current density constraint on wire spacing are deduced; and completing the design of the rat frontal and parietal lobe targeted stimulation coil. Aiming at the frontal top lobe area of a rat, a reverse method of an inverse boundary element method is adopted, the interference of the coil on experimental observation is reduced, and a small cambered surface TMS coil is designed. Compared with a circular coil and an 8-shaped coil of a conventional human body commercial coil which is reduced in equal ratio, the half-value volumes of the coil are respectively reduced by 79.78% and 57.14%, and the focusing degree of stimulation is remarkably improved; meanwhile, by adding the current density constraint, on the premise that the influence on the stimulation effect is small, the minimum distance between the wires is increased to 1.02 mm from 0.39 mm, and the feasibility of coil winding is ensured.

The invention discloses a transcranial magnetic stimulation positioning system based on a deep effect brain region, and the system comprises the steps: obtaining the data of a tested magnetic resonance image, which comprises a resting state functional image and a high-resolution T1 structure image; performing data preprocessing on the function image and the structure image, and establishing an individual space; the deep effect brain region template is converted to an individual space through nonlinear registration, and a target region of interest is defined; calculating functional connections between voxels of the deep effect brain region and the cortical region by adopting a Granger causality analysis method based on wavelet transformation; and screening Top block masses according to the functional connection strength, calculating the gravity centers of the Top block masses, and determining individualized stimulation targets in combination with the skull surface distance. According to the method, spontaneous brain activity function variation of the brain of an individual and the brain signal propagation direction are fully considered, accurate positioning of different individual levels is achieved, relatively stable cortex stimulation targets are obtained, and therefore the clinical curative effect of TMS is optimized.

The invention discloses a transcranial stimulation magnetic therapy coil navigation method, a transcranial stimulation magnetic therapy coil navigation system, a storage medium and equipment. The method comprises the following steps: acquiring three-dimensional structure information of the head of a target object, magnetic resonance imaging (MRI) data of an individual target object, or three-dimensional model data obtained by matching from a general MRI template library; real-time surface geometric information of the head of the target object is collected through an infrared optical tracking system; performing registration fusion on the three-dimensional structure information and the real-time surface geometric information, and generating an individualized three-dimensional brain model synchronized with a real space coordinate system on a navigation interface; the spatial position and posture of the optical marker fixed on the magnetic therapy coil are tracked in real time through an infrared optical tracking system and correspondingly mapped to the individualized three-dimensional brain model, and visual navigation of the magnetic therapy coil relative to the brain anatomical structure is achieved. Through the individualized three-dimensional navigation and real-time visualization technology, the problems that a traditional TMS is low in positioning precision, invisible in operation and poor in treatment repeatability are solved.

The invention discloses an MEP automatic measurement and threshold discrimination method and system based on a mechanical arm. The MEP automatic measurement and threshold discrimination method comprises the following steps: constructing a scalp hotspot probability distribution map based on a brain map; dividing the hotspot scalp map into a plurality of sub-regions, and selecting candidate points from the plurality of sub-regions to obtain a candidate scalp stimulation point list; carrying out transcranial magnetic stimulation according to a point position sequence of the candidate scalp stimulation point list, simultaneously collecting a motor evoked potential signal triggered by each stimulation, and simultaneously collecting a motor evoked potential signal triggered by each stimulation; preprocessing and feature extraction are carried out on the collected motor evoked potential signals, whether stimulation evokes effective MEP response or not is judged through a response judgment method, and a candidate point-MEP response database is formed; screening an optimal motion hotspot point location in the candidate area, and taking the optimal motion hotspot point location as a target site; and searching an individualized resting motion threshold value on the optimal motion hotspot point location.

The invention relates to a heterogeneous human head model construction method and system oriented to multi-physics field simulation, based on real human head T1 weighted magnetic resonance image data, key tissues such as white matter, gray matter and cerebrospinal fluid are accurately segmented, and a three-dimensional geometric model used for generating carrying tissue identification information is researched and developed; converting the model data into a file format conforming to the NASTRAN standard by utilizing an independently developed format conversion program, and completely retaining organization classification information; finally, different tissue areas are automatically recognized through physical field simulation software, corresponding frequency dependent material attributes are distributed, and a finite element model capable of being directly used for simulation is formed. According to the method, seamless integration of the high-precision heterogeneous human head model and the simulation platform is achieved, tedious manual repairing and assignment operation is not needed, the method has the advantages of being high in precision, high in efficiency and good in compatibility, and the authenticity and reliability of biomedical simulation such as transcranial magnetic stimulation and radio frequency coil design can be remarkably improved.

The invention discloses an optical and neural feedback multi-modal data analysis method for a nerve regulation target, and belongs to the technical field of cranial nerve treatment, and the method specifically comprises the steps: receiving a head movement instruction of a patient through an interactive interface, pausing transcranial magnetic stimulation after receiving the instruction, and switching to a head movement monitoring state; an infrared optical navigation device is combined with a magnetic resonance image to construct an individualized brain three-dimensional model, head position changes are tracked in real time, and autonomic nerve feedback signals are collected at the same time; synchronously aligning the head coordinates with the neural feedback signals to generate a multi-modal data set, and analyzing relevance to obtain real-time regulation and control parameters; the positioning and stimulation intensity of the transcranial magnetic stimulation coil are adaptively adjusted according to the parameters, and related information is displayed on a treatment interface; after the head of the patient finishes moving and is stable, a rapid re-calibration process is automatically triggered, high-precision monitoring is recovered, and magnetic stimulation output is reactivated; according to the invention, the treatment stability and adaptability are improved.

Offline prior to operation, an optimised control sequence is derived for a pulse system comprising a reactive circuit for generating electromagnetic pulses, such as a transcranial magnetic stimulation circuit, and cascaded switching modules for switchably connecting capacitive discharge elements to provide a multi-level output voltage for the reactive circuit. A discrete-time model predicts an electrical state of the pulse system. A target profile for an electromagnetic pulse is received. For respective time-steps of the control sequence taken in succession, an optimal path of switching states over a window of time-steps starting with the respective time-step is derived, optimising a cost function having a deviation cost contribution representing deviation of an electrical state of the pulse system predicted by the discrete-time model from the target profile over the window. The switching state of the determined path at the respective time-step is selected for the control sequence.

The invention discloses a task state brain-computer interface training system for closed-loop transcranial magnetic stimulation, and particularly relates to the field of cognitive rehabilitation assistion.The task state brain-computer interface training system comprises the steps that multi-channel electroencephalogram signals and brain function activation records are synchronously collected in the rehabilitation training process, task segments are divided, and frequency domain energy characteristics of all channels are extracted; identifying a state transition candidate segment based on the frequency band energy distribution change; the method comprises the following steps: constructing a cross-channel phase synchronization matrix, and inputting a graph convolutional neural network to generate an activation topology vector reflecting a brain region cooperation mode; the system constructs an activation state recognizer by taking a topological vector and a brain function activation label as supervision data, and realizes real-time judgment of different function states. The recognition result drives a stimulation parameter recommendation module, a preset stimulation strategy mapping table is inquired according to the recognition state, recommended stimulation parameters are dynamically generated and transmitted to a magnetic stimulation execution interface, and personalized closed-loop nerve regulation and control are achieved.

The invention discloses a voice control-based augmented reality precise transcranial magnetic stimulation system, which comprises augmented reality equipment, a voice recognition and control module and transcranial magnetic stimulation TMS equipment, and is characterized in that a magnetic resonance structure image of a tested head is projected to a real head, precise intracranial intervention sites are visualized, precise placement of a TMS coil is guided online, and the accuracy of the TMS coil is improved. The accuracy of transcranial magnetic stimulation is effectively improved, and the TMS equipment can be controlled through voice to switch a preset stimulation target, a stimulation mode, stimulation duration and the like according to a testee; the operation platform is transferred from a far-end computer screen to a tested actual head, a transcranial magnetic stimulation practitioner only needs to place a coil according to a visual model, the operation difficulty is greatly reduced, dependence on expensive and non-portable existing neural navigation hardware is reduced, and the transcranial magnetic stimulation system has the advantages of being easy and convenient to operate, portable, movable, low in cost, easy to popularize and suitable for popularization and application. And the use efficiency and the application range of the TMS equipment are greatly improved.

The invention discloses an auxiliary decision-making system of a transcranial magnetic stimulation mode, and the system comprises an obtaining module which is used for obtaining the personal feature information of a patient; the determination module is used for calling a preset evaluation model to calculate the brain function retention degree of the patient by adopting the personal characteristic information, and determining the treatment mode of the patient according to the brain function retention degree; wherein the preset evaluation model is a classification model constructed based on demographic characteristic parameters, behavioral evaluation characteristic parameters, neural electrophysiological characteristic parameters and brain image characteristic parameters as independent variables. The brain function retention degree is calculated by using the model, and the transcranial magnetic stimulation mode is determined according to the brain function retention degree without relying on subjective calculation of a doctor, so that the accuracy of determining the treatment mode can be improved; meanwhile, multiple evaluation, detection and calculation are not needed for processing, the processing time can be shortened, the processing efficiency and precision can be further improved, the diagnosis and subsequent treatment of the patient are prevented from being affected, and precise treatment is achieved.

The invention discloses a closed-loop transcranial magnetic stimulation brain regulation and control method based on multi-model fusion and individualized learning. Dynamic optimization and accurate regulation and control of TMS stimulation parameters are achieved. According to the technical scheme, the method comprises the following steps: collecting and preprocessing a multi-guide EEG signal in real time, and extracting frequency domain and time domain features and brain network topology indexes; the EEG state in the future 0.5-2 seconds is predicted by using depth sequential networks such as LSTM and the like, and an individualized stimulation parameter strategy is generated in combination with reinforcement learning and Bayesian optimization; tMS stimulation is triggered based on a prediction result, brain network indexes and reward evaluation, and long-term adaptive adjustment is realized through an individual memory pool. The traditional passive feedback mode is broken through, an active closed-loop mechanism of prediction-learning-regulation is realized, the TMS regulation efficiency and the individual adaptability are remarkably improved, and the method can be widely applied to scenes such as mental disease intervention, cognitive regulation and nerve rehabilitation.

The invention discloses a result verification method for a transcranial magnetic stimulator calibration device, and relates to the technical field of medical equipment detection, and the method comprises the following steps: collecting pulse magnetic field parameters outputted by a TMS therapeutic instrument in real time through constructing a multipath parallel magnetic field distribution perception array composed of a plurality of coil type magnetic field sensors; designing a three-dimensional calibration platform to perform multi-dimensional dynamic calibration on the magnetic field distribution sensing array, calibrating the relationship between the induced electromotive force and the magnetic induction intensity of the sensor, and verifying whether the measurement error is less than + / -0.1% or not; and comparing the actually measured magnetic field data with the human brain magnetic field distribution data simulated by the finite element simulation model, analyzing the difference value between the simulation data and the actually measured data, and correcting the system according to the data deviation degree. According to the transcranial magnetic stimulator calibration device and the result verification method, real-time acquisition and high-precision calibration of dynamic parameters are realized through a multi-path synchronous magnetic field sensing array, and the calibration reliability is verified based on finite element simulation and actually measured data comparison.

The invention discloses a brain-computer interface-based closed-loop transcranial magnetic stimulation treatment system and method, and the system comprises an electroencephalogram monitoring module which is used for collecting an electroencephalogram signal of a subject in real time; the transcranial magnetic stimulation module is used for transmitting pulse stimulation to a brain target spot of a subject; the control module is in communication connection with the electroencephalogram monitoring module and the transcranial magnetic stimulation module, and the control module is configured to receive the electroencephalogram signals output by the electroencephalogram monitoring module, preprocess the electroencephalogram signals by adopting a signal processing algorithm to remove electromagnetic interference, and send the preprocessed electroencephalogram signals to the transcranial magnetic stimulation module; the signal processing algorithm comprises but is not limited to fast continuous wavelet transform (FCWT) and fast independent component analysis; according to the method, a closed-loop monitoring mechanism is adopted, electroencephalogram oscillation is recognized in real time, stimulation is dynamically triggered, the stimulation opportunity is accurately matched with the brain excitation state, and the treatment pertinence is improved; the signals are preprocessed through FCWT and an algorithm, electromagnetic interference and artifacts are effectively removed, and the accuracy of electroencephalogram oscillation feature extraction is guaranteed.

The invention discloses an auxiliary artificial olfaction compensation method and device based on a brain-computer interface. The method comprises the steps that a scalp electroencephalogram cap is combined with a nasal cavity near infrared spectrum sensor to synchronously collect non-invasive signals; performing time-frequency analysis on the non-intrusive signal, and converting an alpha wave, a gamma wave and an individualized characteristic frequency band into a Poincare map and nonlinear kinetic parameters; according to the individualized olfactory brain network connection atlas, transcranial magnetic stimulation and transcranial direct current stimulation, setting a targeted stimulation position and intensity for a specific brain region related to olfactory perception; presenting a preset odor stimulus to the subject, evaluating the attention, emotion and olfactory perception state of the subject, and adaptively adjusting the intensity, frequency and odor concentration of the nerve stimulus and artificial olfactory stimulus to optimize the compensation effect. The olfactory functions of different regions of the brain of the olfactory disorder patient are collected through the brain-computer interface, and the regions corresponding to the brain are simulated and stimulated through gases with different smells to assist in stimulation and recovery of olfaction.

The invention provides an individualized anesthesia optimization method and system based on transcranial magnetic stimulation-induced electroencephalogram, and relates to the technical field of medical equipment control. According to the technical scheme provided by the invention, the target phase window corresponding to the electroencephalogram rhythm frequency band is predicted by using the autoregression model, and the target stimulation moment is accurately calculated according to the inherent delay of the stimulation equipment, so that closed-loop phase-locked stimulation of the transcranial magnetic pulse is triggered in a specific phase state; and it is ensured that the collected electroencephalogram response signals can accurately reflect cortical function characteristics of an individual in a specific nerve excitation state. Multi-dimensional biological characteristics are extracted from electroencephalogram response signals, an anesthesia reaction prediction model is input to calculate the individualized anesthesia reaction index, individual nerve function differences are fully considered in an anesthesia optimization scheme generated based on the individualized anesthesia reaction index, and compared with a traditional evaluation method of population statistics, the evaluation method has the advantages that the evaluation accuracy is high, and the evaluation efficiency is high. The accuracy of anesthesia response evaluation is remarkably improved, and therefore the accuracy of an anesthesia scheme can be improved.

Disclosed is a method for determining a treatment to be applied to a brain of a patient, such as determining a transcranial magnetic stimulation (TMS) treatment location(s) and treatment strength to be applied to a brain of a patient suffering from depression. A search of the brain, based on coarse-scale parcellations, treatment metric and one or more anatomical metrics, is conducted to select the treatment location(s). In one embodiment, this involves progressively varying a value of a parameter associated with a gyrus threshold and for each value, identifying candidate treatment locations based on a functional connectivity of a subgenual anterior cingulate cortex during resting-state functional magnetic resonance imaging (fMRI) recorded over a plurality of multimodal brain imaging sessions, and selecting as the respective treatment location the candidate location that is closest to all other candidate treatment locations.

The invention discloses a transcranial magnetic stimulation robot hybrid calibration method and device, equipment, a medium and a product, and relates to the field of transcranial magnetic stimulation, and the method comprises the steps: obtaining a first transformation matrix from a camera coordinate system to a robot base coordinate system, so as to achieve the global calibration of a camera and a robot base; acquiring a second transformation matrix from the coil marker coordinate system to the coil coordinate system to realize local calibration of the coil; on the basis of global calibration of the camera and the robot base, global preliminary positioning from a robot end effector to the head of the patient is completed; and based on the local calibration of the coil and the global preliminary positioning, completing local positioning of the brain stimulation target from the coil to the head of the patient, thereby improving the positioning precision of the brain stimulation target.

The invention provides a machine learning-based acupuncture combined transcranial magnetic stimulation scheme selection method, which comprises the following steps of: performing acupuncture on an object, recording acupuncture data, and obtaining acupuncture text characteristics; the acupuncture data comprises acupuncture object data and acupuncture operation data, the acupuncture object data comprises gender, age, disease name, symptom, medical history and living habit, and the acupuncture operation data comprises body position, acupuncture point, acupuncture sequence, needle inserting, needle moving and duration; performing transcranial magnetic stimulation on the needled object for multiple times to obtain transcranial magnetic stimulation data, the transcranial magnetic stimulation data including hot spot positioning, working parameters, process data and effect data, and obtaining transcranial magnetic stimulation features; establishing association between acupuncture text features and transcranial magnetic stimulation features, constructing a database storing multiple groups of acupuncture combined transcranial magnetic stimulation schemes, and selecting a layered random forest regression model for training; and selecting an acupuncture combined transcranial magnetic stimulation scheme from the database according to actual data by using a reverse prediction method.

The invention discloses a method and a device for evaluating anesthesia depth based on joint disturbance and electroencephalogram signals. According to the method, transcranial magnetic stimulation and transcranial ultrasonic stimulation are sequentially applied to a cortex target spot and a subcortex target spot; collecting first multi-channel electroencephalogram data and second multi-channel electroencephalogram data; based on the first multi-channel electroencephalogram data and the second multi-channel electroencephalogram data, reconstructing a cortex source activity time sequence and a subcortex source activity time sequence; calculating a disturbance complexity index according to the first multichannel electroencephalogram data and a source positioning algorithm; calculating a cortex-to-subcortex directional coherence value and a subcortex-to-cortex directional coherence value according to the cortex source activity time sequence and the subcortex source activity time sequence; and generating an anesthesia depth index based on the disturbance complexity index, the cortical-to-subcortical directional coherence value and the subcortical-to-cortical directional coherence value. By implementing the technical scheme provided by the invention, the problem of insufficient accuracy between different anesthetics and individuals is solved, and more stable and reliable anesthesia depth monitoring is realized.

A transcranial magnetic stimulation (TMS) treatment system is provided. The system includes a sensor device that senses EEG signals from a subject through one or more leads and a server device configured to receive EEG data corresponding to the subject. The server includes an analysis module configured to process the EEG data and determine a personalized resonant brain frequency and a minimum neuronal activation threshold of the subject based at least in part on EEG data corresponding to one or more leads of the sensor device. The analysis module is also configured to determine a TMS treatment protocol where the treatment protocol includes at least a frequency based on the personalized resonant brain frequency and an amplitude based on the minimum neuronal activation threshold. The system also includes a treatment device configured to deliver a TMS treatment to the subject based on the TMS treatment protocol received from the server.

The invention discloses a multifunctional transcranial therapeutic apparatus and a control method thereof. The transcranial therapeutic apparatus relates to the field of medical equipment and solves the problem of single function of a traditional transcranial therapeutic apparatus. The transcranial electrical stimulation module can transmit direct current stimulation or alternating current stimulation; the transcranial magnetic stimulation module can provide a pulsed magnetic field; the ultrasonic stimulation module generates ultrasonic waves through an ultrasonic transducer. The multiple stimulation heads are used for being distributed in different areas of the head, an electrical stimulation electrode slice of the transcranial electrical stimulation module, a magnetic stimulation coil of the transcranial magnetic stimulation module and an ultrasonic transducer of the ultrasonic stimulation module are integrated in each stimulation head, and signal generators of all the modules are controlled in a unified mode through the main controller. A single stimulation mode or combined work of multiple stimulation modes is selected according to the illness state and treatment requirements of a patient, the different stimulation combination modes synergistically act on a target brain area, the treatment effect is improved, and the problems that a traditional transcranial therapeutic apparatus only supports a single stimulation mode and is poor in treatment effect are solved.

The invention provides an evaluation system based on a transcranial magnetic stimulation treatment effect of refractory depression, and belongs to the field of transcranial magnetic stimulation treatment evaluation. The problem that the objectivity and interpretability of an evaluation result are insufficient due to the fact that multi-modal data are not effectively integrated in the prior art is solved. The system comprises a neural navigation module which is used for determining an individualized transcranial magnetic stimulation target spot through a resting state functional magnetic resonance imaging technology and a remote isolation effect principle; the periodic treatment module is used for carrying out cranial magnetic stimulation frequency setting by adopting an alternate theta burst stimulation scheme; the data acquisition and processing module is used for acquiring multi-modal data before and after treatment and performing feature extraction; and the treatment evaluation module is used for establishing a multi-modal fusion curative effect prediction model through a support vector machine, and the model is used for evaluating the treatment effect and predicting the symptom relieving degree after being trained by a training data set. The method is mainly used in data evaluation field.