Tracing analysis method, device and system based on electroencephalogram signals collected by mechanical arm

Abstract

The invention provides a traceability analysis method, device and system based on electroencephalogram signals collected by a mechanical arm. The method comprises the steps that coordinate information of all electroencephalogram electrodes in a first coordinate system is obtained; according to the coordinate information of each electroencephalogram electrode in the first coordinate system and the coordinate transformation relation between the first coordinate system and the second coordinate system, obtaining the first coordinate information of each electroencephalogram electrode in the second coordinate system; calibrating the first coordinate information of each electroencephalogram electrode in the second coordinate system according to the calibration matrix to obtain second coordinate information of each electroencephalogram electrode in the second coordinate system; electroencephalogram signals are acquired through each electroencephalogram electrode; and performing traceability analysis according to the second coordinate information of each electroencephalogram electrode in the second coordinate system and the electroencephalogram signal. According to the traceability analysis method, device and system based on the electroencephalogram signals collected by the mechanical arm, the accuracy of traceability analysis is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of medical image processing, and in particular to a method, device and system for tracing and analyzing electroencephalogram (EEG) signals collected by a robotic arm. Background Art

[0002] Electroencephalography (EEG) is widely used in medical monitoring and diagnosis, providing doctors with an effective tool to monitor brain electrical activity non-invasively and in real time.

[0003] In the process of collecting EEG signals, the subject can wear an EEG cap of appropriate size and select the site to be stimulated in the subject's cerebral cortex; through TMS technology, a pulsed magnetic field is used to generate local currents in these specific areas, thereby stimulating brain activity, collecting EEG activity induced by the magnetic field, and obtaining EEG signals. In the prior art, the wearing of the EEG cap depends on the operator's experience and intuition, which limits the ability to accurately match electrodes with specific areas of the cerebral cortex. In addition, the traditional manual operation method has many inconveniences. The operator needs to hold the TMS coil for a long time, and the subject must remain still during the test. Any slight movement may cause the coil to be repositioned. The shaking of the handheld coil, as well as the contact and friction between the coil and the EEG electrode, may cause the electrode to shift, thereby affecting the accuracy of data collection. Therefore, how to obtain more accurate EEG signals for traceability analysis has become an important issue that needs to be solved in this field. Summary of the invention

[0004] In response to the problems in the prior art, the embodiments of the present invention provide a method, device and system for tracing and analyzing EEG signals collected by a robotic arm, which can at least partially solve the problems in the prior art.

[0005] In a first aspect, the present invention proposes a source tracing analysis method based on EEG signals collected by a robotic arm, comprising:

[0006] Obtaining coordinate information of each EEG electrode in the first coordinate system;

[0007] Obtaining first coordinate information of each EEG electrode in the second coordinate system according to coordinate information of each EEG electrode in the first coordinate system and a coordinate transformation relationship between the first coordinate system and the second coordinate system; wherein the coordinate transformation relationship between the first coordinate system and the second coordinate system is obtained in advance;

[0008] Calibrate the first coordinate information of each EEG electrode in the second coordinate system according to the calibration matrix to obtain the second coordinate information of each EEG electrode in the second coordinate system; wherein the calibration matrix is ​​obtained in advance;

[0009] The EEG signals are acquired by collecting the EEG electrodes; wherein the EEG signals are collected by stimulating the preset target points of the subject's brain by moving the stimulation device carried by the robotic arm along the preset planning path; the preset planning path is planned based on the second coordinate information of each EEG electrode in the second coordinate system;

[0010] A source tracing analysis is performed based on the second coordinate information of each EEG electrode in the second coordinate system and the EEG signal.

[0011] Furthermore, the step of obtaining the calibration matrix includes:

[0012] Acquire brain point cloud data of the subject in a second coordinate system;

[0013] Obtaining point cloud data of each EEG electrode in a second coordinate system;

[0014] A calibration matrix is ​​established based on the brain point cloud data of the subject in the second coordinate system and the point cloud data of each EEG electrode in the second coordinate system.

[0015] Furthermore, establishing a coordinate transformation relationship between the first coordinate system and the second coordinate system includes:

[0016] Acquire brain point cloud data of the subject in a second coordinate system;

[0017] Acquire brain point cloud data of the subject in a first coordinate system;

[0018] The brain point cloud data of the subject in the second coordinate system and the brain point cloud data of the subject in the first coordinate system are registered to obtain a coordinate transformation relationship between the first coordinate system and the second coordinate system.

[0019] Furthermore, obtaining coordinate information of each EEG electrode in the first coordinate system includes:

[0020] Obtaining coordinate information of a preset EEG electrode in a first coordinate system; wherein the preset EEG electrode is an EEG electrode selected in a preset order;

[0021] Coordinate interpolation is performed according to the coordinate information of the preset EEG electrodes in the first coordinate system to obtain the coordinate information of each intermediate EEG electrode in the first coordinate system; wherein each intermediate EEG electrode is an EEG electrode other than the preset EEG electrodes.

[0022] Further, performing coordinate interpolation according to the coordinate information of the preset EEG electrodes in the first coordinate system to obtain the coordinate information of each intermediate EEG electrode in the first coordinate system includes:

[0023] Convert the coordinate information of the preset EEG electrode in the first coordinate system to the spherical coordinate system to obtain the coordinates of the preset EEG electrode in the spherical coordinate system;

[0024] Based on the coordinates of the preset EEG electrodes in the spherical coordinate system, the coordinates of each intermediate EEG electrode in the spherical coordinate system are obtained;

[0025] The coordinate information of each intermediate EEG electrode in the spherical coordinate system is converted to the first coordinate system to obtain the coordinate information of each intermediate EEG electrode in the first coordinate system.

[0026] Further, calibrating the first coordinate information of each EEG electrode in the second coordinate system according to the calibration matrix to obtain the second coordinate information of each EEG electrode in the second coordinate system includes:

[0027] Calibrate the first coordinate information of the preset EEG electrode in the second coordinate system according to the calibration matrix to obtain the second coordinate information of the preset EEG electrode in the second coordinate system; and calibrate the first coordinate information of each intermediate EEG electrode in the second coordinate system according to the calibration matrix to obtain the second coordinate information of each intermediate EEG electrode in the second coordinate system;

[0028] Performing coordinate interpolation on the second coordinate information of the preset EEG electrodes in the second coordinate system to obtain third coordinate information of each intermediate EEG electrode in the second coordinate system;

[0029] The third coordinate information of each intermediate EEG electrode in the second coordinate system and the second coordinate information of each intermediate EEG electrode in the second coordinate system are weightedly calculated to obtain the fourth coordinate information of each intermediate EEG electrode in the second coordinate system.

[0030] In a second aspect, the present invention provides a source tracing and analyzing device for EEG signals collected by a robotic arm, comprising:

[0031] A first acquisition module, used to acquire coordinate information of each EEG electrode in a first coordinate system;

[0032] A conversion module, used to obtain first coordinate information of each EEG electrode in a second coordinate system according to the coordinate information of each EEG electrode in the first coordinate system and the coordinate transformation relationship between the first coordinate system and the second coordinate system; wherein the coordinate transformation relationship between the first coordinate system and the second coordinate system is obtained in advance;

[0033] A calibration module, used to calibrate the first coordinate information of each EEG electrode in the second coordinate system according to the calibration matrix to obtain the second coordinate information of each EEG electrode in the second coordinate system; wherein the calibration matrix is ​​obtained in advance;

[0034] A signal acquisition module, used for acquiring EEG signals through EEG electrodes; wherein the EEG signals are acquired by stimulating preset target points of the subject's brain by moving the stimulation device carried by a robotic arm along a preset planned path; the preset planned path is planned based on the second coordinate information of the EEG electrodes in a second coordinate system;

[0035] The source tracing analysis module is used to perform source tracing analysis based on the second coordinate information of each EEG electrode in the second coordinate system and the EEG signal.

[0036] Furthermore, the source tracing and analyzing device for EEG signals collected by a robotic arm provided by an embodiment of the present invention further includes:

[0037] A second acquisition module is used to acquire brain point cloud data of the subject in a second coordinate system;

[0038] The third acquisition module is used to acquire point cloud data of each EEG electrode in the second coordinate system;

[0039] A module is established to establish a calibration matrix based on the brain point cloud data of the subject in the second coordinate system and the point cloud data of each EEG electrode in the second coordinate system.

[0040] Furthermore, the source tracing and analyzing device for EEG signals collected by a robotic arm provided by an embodiment of the present invention further includes:

[0041] A fourth acquisition module is used to acquire brain point cloud data of the subject in a second coordinate system;

[0042] a fifth acquisition module, used to acquire brain point cloud data of the subject in a first coordinate system;

[0043] The acquisition module is used to align the brain point cloud data of the subject in the second coordinate system with the brain point cloud data of the subject in the first coordinate system to obtain the coordinate transformation relationship between the first coordinate system and the second coordinate system.

[0044] Furthermore, the first acquisition module includes:

[0045] An acquisition unit, used to acquire coordinate information of a preset EEG electrode in a first coordinate system; wherein the preset EEG electrode is an EEG electrode selected in a preset order;

[0046] The coordinate interpolation unit is used to perform coordinate interpolation according to the coordinate information of the preset EEG electrodes in the first coordinate system to obtain the coordinate information of each intermediate EEG electrode in the first coordinate system; wherein each intermediate EEG electrode is an EEG electrode other than the preset EEG electrodes.

[0047] Furthermore, the coordinate interpolation unit includes:

[0048] A first conversion subunit is used to convert the coordinate information of the preset EEG electrode in the first coordinate system into the spherical coordinate system to obtain the coordinates of the preset EEG electrode in the spherical coordinate system;

[0049] An obtaining subunit, used for obtaining the coordinates of each intermediate EEG electrode in the spherical coordinate system based on the coordinates of the preset EEG electrode in the spherical coordinate system;

[0050] The second conversion subunit is used to convert the coordinate information of each intermediate EEG electrode in the spherical coordinate system to the first coordinate system to obtain the coordinate information of each intermediate EEG electrode in the first coordinate system.

[0051] Furthermore, the calibration module comprises:

[0052] a calibration unit, configured to calibrate the first coordinate information of the preset EEG electrode in the second coordinate system according to the calibration matrix to obtain the second coordinate information of the preset EEG electrode in the second coordinate system; and to calibrate the first coordinate information of each intermediate EEG electrode in the second coordinate system according to the calibration matrix to obtain the second coordinate information of each intermediate EEG electrode in the second coordinate system;

[0053] A coordinate interpolation unit, used for performing coordinate interpolation on the second coordinate information of the preset EEG electrodes in the second coordinate system to obtain third coordinate information of each intermediate EEG electrode in the second coordinate system;

[0054] The weighted calculation unit is used to perform weighted calculation on the third coordinate information of each intermediate EEG electrode in the second coordinate system and the second coordinate information of each intermediate EEG electrode in the second coordinate system to obtain the fourth coordinate information of each intermediate EEG electrode in the second coordinate system.

[0055] In a third aspect, the present invention provides a source tracing and analysis system for EEG signals collected by a robotic arm, comprising a source tracing and analysis device for EEG signals collected by a robotic arm, a computer, a robot, a stimulation device, a plurality of EEG electrodes and a navigation device as described in any of the above embodiments, wherein:

[0056] The computer is respectively connected to the robot, the stimulation device, the plurality of EEG electrodes, the navigation device, and the source tracing and analyzing device based on the EEG signals collected by the robot arm;

[0057] The multiple EEG electrodes are deployed in the subject's brain; the robot is used to carry the stimulation device to stimulate the target point in the subject's brain; and the navigation device is used to collect spatial position data of the EEG electrodes.

[0058] In a fourth aspect, the present invention provides a computer device comprising a memory, a processor and a computer program stored in the memory, wherein the processor executes the program to implement the method for tracing and analyzing EEG signals collected by a robotic arm as described in any of the above embodiments.

[0059] In a fifth aspect, the present invention provides a computer-readable storage medium, which stores a computer program / instruction. When the computer program / instruction is executed by a processor, it implements the method for tracing and analyzing EEG signals collected by a robotic arm as described in any of the above embodiments.

[0060] The embodiment of the present invention provides a source tracing analysis method, device and system for EEG signals collected by a robotic arm, which obtains coordinate information of an EEG electrode in a first coordinate system; obtains first coordinate information of the EEG electrode in a second coordinate system according to the coordinate information of the EEG electrode in the first coordinate system and the coordinate transformation relationship between the first coordinate system and the second coordinate system; wherein the coordinate transformation relationship between the first coordinate system and the second coordinate system is obtained in advance; calibrates the first coordinate information of the EEG electrode in the second coordinate system according to a calibration matrix to obtain second coordinate information of the EEG electrode in the second coordinate system; wherein the calibration matrix is ​​obtained in advance; obtains EEG signals through EEG electrode collection; wherein the EEG signals are collected by stimulating preset targets of the subject's brain by moving a stimulation device carried by a robotic arm along a preset planned path; the preset planned path is planned based on the second coordinate information of the EEG electrode in the second coordinate system; performs source tracing analysis based on the second coordinate information of the EEG electrode in the second coordinate system and the EEG signal, and improves the accuracy of source tracing analysis because it can more accurately record the position of the EEG electrode corresponding to the individual brain area of ​​the subject and more accurately collect EEG signals. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0062] Figure 1 It is a flow chart of a method for tracing and analyzing EEG signals collected by a robotic arm provided in the first embodiment of the present invention.

[0063] Figure 2 It is a flow chart of a method for tracing and analyzing EEG signals collected by a robotic arm provided in the second embodiment of the present invention.

[0064] Figure 3It is a flowchart of a method for tracing and analyzing EEG signals collected by a robotic arm provided in the third embodiment of the present invention.

[0065] Figure 4 It is a flowchart of a method for tracing and analyzing EEG signals collected by a robotic arm provided in the fourth embodiment of the present invention.

[0066] Figure 5 It is a flowchart of a method for tracing and analyzing EEG signals collected by a robotic arm provided in the fifth embodiment of the present invention.

[0067] Figure 6 It is a flowchart of a method for tracing and analyzing EEG signals collected by a robotic arm provided in the sixth embodiment of the present invention.

[0068] Figure 7 It is a schematic diagram of the structure of a source tracing and analyzing device based on EEG signals collected by a robotic arm provided in the seventh embodiment of the present invention.

[0069] Figure 8 It is a schematic diagram of the structure of a source tracing and analyzing device based on EEG signals collected by a robotic arm provided in the eighth embodiment of the present invention.

[0070] Fig. 9 It is a schematic diagram of the structure of a source tracing and analyzing device based on EEG signals collected by a robotic arm provided in the ninth embodiment of the present invention.

[0071] Fig.10 It is a structural schematic diagram of a source tracing and analysis device based on EEG signals collected by a robotic arm provided in the tenth embodiment of the present invention.

[0072] Fig.11 It is a structural schematic diagram of a source tracing and analysis device based on EEG signals collected by a robotic arm provided in the eleventh embodiment of the present invention.

[0073] Fig.12 It is a schematic structural diagram of a source tracing and analyzing device based on EEG signals collected by a robotic arm provided in the twelfth embodiment of the present invention.

[0074] Fig.13 It is a structural schematic diagram of a system for tracing and analyzing EEG signals collected by a robotic arm provided in the thirteenth embodiment of the present invention.

[0075] Fig.14 It is a schematic diagram of the physical structure of a computer device provided in the fourteenth embodiment of the present invention. DETAILED DESCRIPTION

[0076] In order to make the purpose, technical scheme and advantages of the embodiments of the present invention clearer, the embodiments of the present invention are further described in detail with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention. It should be noted that, in the absence of conflict, the embodiments in this application and the features in the embodiments can be combined with each other arbitrarily. The acquisition, storage, use, and processing of data in the technical scheme in this application comply with the relevant provisions of laws and regulations. The user information in the embodiments of the present application is obtained through legal and compliant channels, and the acquisition, storage, use, and processing of user information are authorized and agreed by the customer.

[0077] In order to facilitate understanding of the technical solution provided by this application, the relevant contents of the technical solution of this application are first explained below.

[0078] Electroencephalography (EEG) is a technology used to record the electrical activity of the brain. When neurons in the brain are active, they generate tiny currents, which form weak potential changes on the surface of the scalp. EEG captures these potential changes by placing multiple electrodes on the scalp and converts them into visual graphics or data, which can reflect the functional state of the brain.

[0079] Transcranial Magnetic Stimulation (TMS) is a non-invasive and painless green treatment technology. The magnetic signal can penetrate the skull without attenuation and directly act on the cerebral cortex. In practical applications, the application scope of TMS is not limited to brain stimulation. It can also stimulate peripheral nerves and muscles, providing an effective tool for the diagnosis and treatment of various neurological diseases.

[0080] When using EEG, the determination of electrode position usually relies on an internationally recognized standard system, which can ensure the comparability of results between different studies and clinical experiments. The commonly used standard system is the 10-20 system, which determines the position of the electrode through specific marking points. The following are the basic steps to determine the electrode position: first, calibrate the reference point of the head; second, measure the size of the head to ensure that the electrode acquisition device of the appropriate size is worn, such as an EEG cap, EEG helmet, EEG bracket, etc.; then use the 10-20 system or other standardized systems to determine the position of each electrode; finally, fine-tune the electrode as needed. In current technical practices, the wearing of electrode acquisition devices often relies on the operator's experience and intuition, which limits the ability to accurately match electrodes to specific areas of the cerebral cortex.

[0081] Mainstream EEG acquisition uses EEG caps with 10-10 or 10-20 system distribution. EEG caps come with a universal coordinate system, which is not accurate in positioning and not personalized enough, and cannot be adjusted to suit different subjects. EEG holders loaded with dry electrodes or wearable devices with built-in electrodes are often about 2-3 cm in height and are suitable for rapid display of EEG signals or home use. EEG electrodes can be intracranial electrodes, which can be placed according to the location near the epileptic focus. Probes can be used for positioning, which is often determined by CT images.

[0082] The analysis of EEG data usually uses traceability analysis methods to explore changes in activity in specific brain regions. Tracing analysis relies on the individualized anatomical Magnetic Resonance Imaging (MRI) data and electrode positions of the subjects, but existing technical means are often limited to the use of universal EEG position templates and fail to fully consider individual differences in the brain structure of the subjects. This application achieves more accurate traceability analysis by combining individualized MRI data with personalized electrode position coordinates, thereby overcoming the limitations of traditional methods and providing a higher level of personalization and accuracy for the analysis of EEG signals.

[0083] This application replaces manual operation with a robotic arm and sets a specific precise posture for each target point to ensure that the EEG electrodes are not touched during the EEG signal acquisition process, avoiding electrode deviation, thereby ensuring the stability and reliability of data acquisition over a long period of time, thereby improving the acquisition quality of EEG data.

[0084] Figure 1 is a flow chart of a method for tracing and analyzing EEG signals collected by a robotic arm provided in the first embodiment of the present invention, such as Figure 1 As shown, the source tracing analysis method based on EEG signals collected by a robotic arm provided in an embodiment of the present invention includes:

[0085] S101, obtaining coordinate information of each EEG electrode in a first coordinate system;

[0086] Specifically, the coordinate information of the EEG electrode in the first coordinate system can be obtained. There are multiple EEG electrodes, and the specific number of EEG electrodes is set according to actual needs, which is not limited in the embodiment of the present invention. For EEG electrodes placed on the subject's scalp, the spatial position data of the EEG electrodes can be collected by a camera, and the first coordinate system is the camera space coordinate system; for intracranial electrodes, CT images can be used to determine the spatial position data of the EEG electrodes, and the first coordinate system is the CT image coordinate system.

[0087] For example, the subject wears an EEG cap, sits within the field of view of the camera, and uses the camera to collect spatial position data of each EEG electrode, and can obtain the coordinate information of each EEG electrode in the first coordinate system. Among them, the camera can be an infrared camera, a color camera, a structured light camera and other equipment, which can be selected according to actual needs, and the embodiment of the present invention does not limit it. The first coordinate system is the camera space coordinate system. There are multiple EEG electrodes.

[0088] It is understandable that before the subject wears the EEG cap, the target point that the subject needs to stimulate can be selected in the controller, and the selection can be made by clicking on the subject's brain 3D model, or by entering the MRI coordinates and saving them after selecting the coordinates.

[0089] The probe can be used to accurately locate all EEG electrodes, so as to collect the coordinate information of each EEG electrode in the first coordinate system. There are patterns in a certain arrangement order on the probe, and the camera collects the image information on the probe in real time. Through the image processing algorithm, the pose matrix of the probe in the camera space coordinate system can be calculated, so as to further obtain the coordinate information of the tip of the probe in the camera space coordinate system. Use the tip of the probe to click on the middle position of each EEG electrode in turn according to the set order; each time the middle position of the EEG electrode is clicked, the coordinate information of the current EEG electrode in the camera space coordinate system, that is, the coordinate information of the EEG electrode in the first coordinate system, will be recorded. Among them, the order of clicking each EEG electrode can be set according to specific needs, and the embodiment of the present invention is not limited.

[0090] It is understandable that for a structured light camera, a probe needs to be set with a recognizable pattern, and for an infrared camera, a probe needs to be set with a reflective ball.

[0091] S102, obtaining first coordinate information of each EEG electrode in the second coordinate system according to coordinate information of each EEG electrode in the first coordinate system and a coordinate transformation relationship between the first coordinate system and the second coordinate system; wherein the coordinate transformation relationship between the first coordinate system and the second coordinate system is obtained in advance;

[0092] Specifically, according to the coordinate transformation relationship between the first coordinate system and the second coordinate system, the coordinate information of each EEG electrode in the first coordinate system is converted to the second coordinate system, and the first coordinate information of each EEG electrode in the second coordinate system is obtained. The coordinate transformation relationship between the first coordinate system and the second coordinate system is obtained in advance, and the first coordinate system is different from the second coordinate system. For example, the second coordinate system is the coordinate system of the subject's nuclear magnetic resonance imaging.

[0093] S103, calibrating each EEG electrode in the second coordinate system according to the first coordinate information of the calibration matrix to obtain the second coordinate information of each EEG electrode in the second coordinate system; wherein the calibration matrix is ​​obtained in advance;

[0094] Specifically, in order to obtain more accurate coordinates of each EEG electrode in the second coordinate system, the first coordinate information of each EEG electrode in the second coordinate system is calibrated based on the calibration matrix to obtain the second coordinate information of each EEG electrode in the second coordinate system. The calibration matrix is ​​obtained in advance.

[0095] For example, for the traceability analysis of EEG signals based on TMS-EGG data, due to manual errors and system errors when the subjects wear the EEG cap, the first coordinate information of each EEG electrode obtained in the second coordinate system has errors. By calibrating the first coordinate information of each EEG electrode in the second coordinate system, the second coordinate information of each EEG electrode in the second coordinate system is obtained, which is conducive to obtaining the precise correspondence between each EEG electrode and the target point on the subject's head, thereby significantly improving the accuracy of the traceability analysis.

[0096] S104, acquiring an electroencephalogram signal by collecting electroencephalogram electrodes; wherein the electroencephalogram signal is collected by stimulating a preset target point in the subject's brain by moving a stimulation device carried by a robotic arm along a preset planned path; the preset planned path is planned based on the second coordinate information of the electroencephalogram electrodes in a second coordinate system;

[0097] Specifically, in order to improve the stability during the EEG signal acquisition process, the stimulation device can be carried by the robotic arm and moved along the preset planning path to stimulate the preset target points in the subject's brain, and the EEG signals can be acquired through the various EEG electrodes. The preset planning path is set according to actual needs and is not limited in the embodiments of the present invention.

[0098] For example, the stimulation device may be a TMS coil, and the parameters of the TMS coil stimulation are set based on experience, which is not limited in the embodiment of the present invention. The parameters of the TMS coil stimulation include, but are not limited to, pulse frequency, interval time, number of repetitions, etc. The preset planning path may be planned based on the second coordinate information of each EEG electrode in the second coordinate system; when the preset planning path is set, a reasonable distance between the TMS coil and each TMS EEG electrode is guaranteed to avoid the displacement of the EEG electrode caused by the TMS coil touching the EEG electrode. When setting the preset planning path, the motion threshold of the TMS coil may be set, and the motion threshold is proportional to the distance between the TMS coil and the target. The farther the TMS coil is from the target, the greater the motion threshold should be. The motion threshold is set according to actual needs, which is not limited in the embodiment of the present invention. When setting the preset planning path, the posture of the robot arm reaching the target may be set, including but not limited to the target distance, translation distance, normal angle, rotation angle, etc. The standard for reaching the target may be set individually for each target, or may be set in batches, and may be selected according to actual needs, which is not limited in the embodiment of the present invention. Setting the posture of the robotic arm for each target point is beneficial to avoid touching the EEG electrodes during transcranial magnetic stimulation and can effectively avoid electrode deviation.

[0099] By rationally planning the movement path of the TMS coil, the robotic arm can automatically move the TMS coil to the magnetic stimulation point on the subject's brain for stimulation and collect EEG signals. The automatic movement process of the robotic arm carrying the TMS coil simplifies the complex operations that previously required frequent manual positioning, greatly improving the accuracy of EEG signal collection. In addition, it can also avoid the problem of coil shaking caused by manual operation in the prior art, which in turn affects the accuracy of data collection.

[0100] For example, the robotic arm carries a TMS coil and stimulates each target point in turn according to the preset planning path. The target points correspond to the EEG electrodes one by one. During the transcranial magnetic stimulation process, each time the robotic arm moves to a position to stimulate a target point, it will maintain the preset posture corresponding to the target point; if the subject's head moves, the TMS signal is weakened, causing the posture of the robotic arm to deviate from the preset posture corresponding to the target point, then the transcranial magnetic stimulation of the target point will be suspended, the posture of the robotic arm will be adjusted to the preset posture corresponding to the target point, and then the transcranial magnetic stimulation of the target point will be resumed. The posture corresponding to the preset target can be determined by setting a preset range of target distance, a preset range of translation distance, a preset range of normal angle, and a preset range of rotation angle. If the target distance is within the preset range of target distance, the translation distance of the TMS coil is within the preset range of translation distance, the normal angle of the TMS coil is within the preset range of normal angle, and the rotation angle of the TMS coil is within the preset range of rotation angle, then the robotic arm maintains the posture corresponding to the preset target; if the target distance is not within the preset range of target distance, the translation distance of the TMS coil is not within the preset range of translation distance, the normal angle of the TMS coil is not within the preset range of normal angle, or the rotation angle of the TMS coil is not within the preset range of rotation angle, then the robotic arm deviates from the posture corresponding to the preset target, transcranial magnetic stimulation will be stopped, and the posture of the robotic arm will be adjusted.

[0101] S105 , performing source tracing analysis based on the second coordinate information of each EEG electrode in the second coordinate system and the EEG signal.

[0102] Specifically, after obtaining the second coordinate information of each EEG electrode in the second coordinate system and collecting the EEG signal of the subject, source tracing analysis can be performed based on the second coordinate information of each EEG electrode in the second coordinate system and the EEG signal. The specific process of source tracing analysis is prior art and will not be described in detail here.

[0103] The embodiment of the present invention provides a source tracing analysis method for EEG signals collected by a robotic arm, which obtains coordinate information of an EEG electrode in a first coordinate system; obtains first coordinate information of the EEG electrode in a second coordinate system according to the coordinate information of the EEG electrode in the first coordinate system and the coordinate transformation relationship between the first coordinate system and the second coordinate system; wherein the coordinate transformation relationship between the first coordinate system and the second coordinate system is obtained in advance; calibrates the first coordinate information of the EEG electrode in the second coordinate system according to a calibration matrix to obtain second coordinate information of the EEG electrode in the second coordinate system; wherein the calibration matrix is ​​obtained in advance; obtains EEG signals through EEG electrode collection; wherein the EEG signals are collected by stimulating preset targets of the subject's brain by moving a stimulation device carried by a robotic arm along a preset planned path; the preset planned path is planned based on the second coordinate information of the EEG electrode in the second coordinate system; performs source tracing analysis based on the second coordinate information of the EEG electrode in the second coordinate system and the EEG signal, and improves the accuracy of source tracing analysis because it can more accurately record the position of the EEG electrode corresponding to the individual brain area of ​​the subject and more accurately collect EEG signals.

[0104] Figure 2 is a flow chart of a method for tracing and analyzing EEG signals collected by a robotic arm provided in a second embodiment of the present invention, such as Figure 2 As shown, based on the above embodiments, further, the step of obtaining the calibration matrix includes:

[0105] S201, obtaining brain point cloud data of the subject in a second coordinate system;

[0106] Specifically, the brain point cloud data of the subject in the second coordinate system can be obtained based on the brain image of the subject. The brain image of the subject can be an MRI image or a CT image. The obtained brain point cloud data can be dozens of point cloud data, hundreds of point cloud data, or more point cloud data, which can be set according to actual needs and is not limited in the embodiment of the present invention.

[0107] S202, obtaining point cloud data of each EEG electrode in a second coordinate system;

[0108] Specifically, based on the coordinate information of each EEG electrode in the second coordinate system, point cloud data of each EEG electrode in the second coordinate system can be obtained.

[0109] S203 , establishing a calibration matrix based on the brain point cloud data of the subject in the second coordinate system and the point cloud data of each EEG electrode in the second coordinate system.

[0110] Specifically, the brain point cloud data of the subject in the second coordinate system and the point cloud data of each EEG electrode in the second coordinate system are registered to obtain a calibration matrix.

[0111] For example, an iterative closest point (ICP) algorithm may be used to align the brain point cloud data of the subject in the second coordinate system and the point cloud data of each EEG electrode in the second coordinate system to obtain a calibration matrix.

[0112] Traditional registration algorithms are all designed to establish a conversion relationship between two different coordinate systems to achieve coordinate transformation. In this application, brain point cloud data and EEG electrode point cloud data from different sources in the same second coordinate system are registered to achieve calibration of the coordinates of the EEG electrodes in the second coordinate system.

[0113] Figure 3 is a flow chart of a method for tracing and analyzing EEG signals collected by a robotic arm provided in a third embodiment of the present invention, such as Figure 3 As shown, on the basis of the above embodiments, further, establishing the coordinate transformation relationship between the first coordinate system and the second coordinate system includes:

[0114] S301, obtaining brain point cloud data of the subject in a second coordinate system;

[0115] Specifically, based on the subject's brain image, the subject's brain point cloud data in a second coordinate system is obtained. The subject's brain image may be an MRI image or a CT image. The second coordinate system is the subject's medical image coordinate system, such as the subject's nuclear magnetic resonance image coordinate system or the CT image coordinate system.

[0116] S302, obtaining brain point cloud data of the subject in a first coordinate system;

[0117] Specifically, by collecting spatial position data of the subject's brain through a camera, point cloud data of the subject's brain in a first coordinate system can be obtained, wherein the first coordinate system is a camera space coordinate system.

[0118] S303, registering the brain point cloud data of the subject in the second coordinate system with the brain point cloud data of the subject in the first coordinate system to obtain a coordinate transformation relationship between the first coordinate system and the second coordinate system.

[0119] Specifically, the brain point cloud data of the subject in the second coordinate system and the brain point cloud data of the subject in the first coordinate system are registered through the registration algorithm, and a transformation relationship between the brain point cloud data of the subject in the second coordinate system and the brain point cloud data of the subject in the first coordinate system is established to obtain a coordinate transformation relationship between the first coordinate system and the second coordinate system. The registration algorithm used is selected according to actual needs and is not limited in the embodiment of the present invention.

[0120] Figure 4 is a flow chart of a method for tracing and analyzing EEG signals collected by a mechanical arm provided in a fourth embodiment of the present invention, such as Figure 4 As shown, based on the above embodiments, further, obtaining the coordinate information of each EEG electrode in the first coordinate system includes:

[0121] S401, obtaining coordinate information of preset EEG electrodes in a first coordinate system; wherein the preset EEG electrodes are EEG electrodes selected according to a preset order;

[0122] Specifically, in the process of obtaining the coordinate information of each EEG electrode in the first coordinate system, a probe can be used to collect the position of each EEG electrode. If the probe is used to click each EEG electrode one by one, it will take a long time. Therefore, the present application improves the process of obtaining the coordinate information of each EEG electrode in the first coordinate system. The positions of some EEG electrodes are selected by the probe, and the positions of the remaining EEG electrodes can be obtained by calculation, so as to improve the efficiency of obtaining the coordinate information of each EEG electrode in the first coordinate system. The preset EEG electrodes are EEG electrodes selected in a preset order. The preset order is set according to actual needs, and the embodiments of the present invention are not limited.

[0123] For example, when the subject wears an EEG cap and sits within the field of view of the camera, the spatial position data of each preset EEG electrode is collected through the camera, and the coordinate information of each preset EEG electrode in the first coordinate system can be obtained.

[0124] For example, the EEG electrodes selected according to a preset order are odd-numbered electrodes or even-numbered electrodes.

[0125] S402, coordinate interpolation is performed according to the coordinate information of the preset EEG electrodes in the first coordinate system to obtain the coordinate information of each intermediate EEG electrode in the first coordinate system; wherein each intermediate EEG electrode is an EEG electrode other than the preset EEG electrodes among all EEG electrodes.

[0126] Specifically, coordinate interpolation is performed based on the coordinate information of the preset EEG electrodes in the first coordinate system, and the coordinate information of each intermediate EEG electrode in the first coordinate system is estimated, so that the coordinate information of each intermediate EEG electrode in the first coordinate system can be obtained. Each intermediate EEG electrode is an EEG electrode other than the preset EEG electrode.

[0127] For example, when the number of EEG electrodes is less than or equal to the set number, the coordinate information of each intermediate EEG electrode in the first coordinate system can be calculated directly based on the coordinate information of the preset EEG electrodes in the first coordinate system by linear interpolation to obtain the coordinate information of each intermediate EEG electrode in the first coordinate system. Each EEG electrode can be considered to be uniformly distributed in the first coordinate system. The set number is set according to actual experience and is not limited in the embodiments of the present invention.

[0128] For example, when the number of EEG electrodes is greater than or equal to the set number, it is necessary to convert the coordinate information of the preset EEG electrodes in the first coordinate system to the spherical coordinate system, perform coordinate interpolation in the spherical coordinate system, and obtain the coordinate information of each intermediate EEG electrode in the first coordinate system.

[0129] Figure 5 is a flow chart of a method for tracing and analyzing EEG signals collected by a robotic arm provided in a fifth embodiment of the present invention, such as Figure 5 As shown, on the basis of the above embodiments, further, performing coordinate interpolation according to the coordinate information of the preset EEG electrodes in the first coordinate system to obtain the coordinate information of each intermediate EEG electrode in the first coordinate system includes:

[0130] S501, converting coordinate information of a preset EEG electrode in a first coordinate system into a spherical coordinate system to obtain coordinates of the preset EEG electrode in the spherical coordinate system;

[0131] Specifically, the first coordinate system is a Cartesian coordinate system, and the coordinate information of the preset EEG electrode in the first coordinate system is converted into the spherical coordinate system, so as to obtain the coordinates of the preset EEG electrode in the spherical coordinate system.

[0132] S502, based on the coordinate information of the preset EEG electrodes in the spherical coordinate system, obtaining the coordinates of each intermediate EEG electrode in the spherical coordinate system; wherein each intermediate EEG electrode is an EEG electrode other than the preset EEG electrodes among all EEG electrodes;

[0133] Specifically, each EEG electrode is evenly arranged on a spherical surface. For any EEG electrode, the positional relationship between it and two adjacent EEG electrodes is known. The coordinates of EEG electrode a in the spherical coordinate system are set to , the coordinates of the two adjacent EEG electrodes of EEG electrode a in spherical coordinates are and ,So , the coordinates of EEG electrode a in spherical coordinates can be calculated when the coordinates of two adjacent EEG electrodes of EEG electrode a in spherical coordinates and μ are known. Where r is the radius of the spherical coordinates, θ is the elevation angle of the spherical coordinates, is the azimuth in spherical coordinates.

[0134] For any middle EEG electrode, two adjacent EEG electrodes can be obtained from the preset EEG electrodes. The coordinates of the preset EEG electrodes in the spherical coordinate system have been calculated. For example, if μ is 0.5, the coordinates of each middle EEG electrode in the spherical coordinate system can be calculated.

[0135] S503 , converting the coordinates of each intermediate EEG electrode in the spherical coordinate system into the first coordinate system, and obtaining coordinate information of each intermediate EEG electrode in the first coordinate system.

[0136] Specifically, the coordinate information of each intermediate EEG electrode in the spherical coordinate system is converted to the first coordinate system, so as to obtain the coordinate information of the intermediate EEG electrode in the first coordinate system.

[0137] Figure 6 is a flow chart of a method for tracing and analyzing EEG signals collected by a robotic arm provided in a sixth embodiment of the present invention, such as Figure 6 As shown, on the basis of the above embodiments, further, calibrating the first coordinate information of each EEG electrode in the second coordinate system according to the calibration matrix to obtain the second coordinate information of each EEG electrode in the second coordinate system includes:

[0138] S601, calibrating the first coordinate information of the preset EEG electrode in the second coordinate system according to the calibration matrix to obtain the second coordinate information of the preset EEG electrode in the second coordinate system; and calibrating the first coordinate information of each intermediate EEG electrode in the second coordinate system according to the calibration matrix to obtain the second coordinate information of each intermediate EEG electrode in the second coordinate system;

[0139] Specifically, after obtaining the coordinate information of the preset EEG electrode in the first coordinate system and the coordinate information of each intermediate EEG electrode in the first coordinate system, the first coordinate information of the preset EEG electrode in the second coordinate system can be obtained according to the coordinate information of the preset EEG electrode in the first coordinate system and the coordinate transformation relationship between the first coordinate system and the second coordinate system, and the first coordinate information of each intermediate EEG electrode in the second coordinate system can be obtained according to the coordinate information of each intermediate EEG electrode in the first coordinate system and the coordinate transformation relationship between the first coordinate system and the second coordinate system.

[0140] The first coordinate information of the preset EEG electrode in the second coordinate system is calibrated based on the calibration matrix, and the second coordinate information of the preset EEG electrode in the second coordinate system can be obtained. The first coordinate information of each intermediate EEG electrode in the second coordinate system is calibrated based on the calibration matrix, and the second coordinate information of each intermediate EEG electrode in the second coordinate system can be obtained.

[0141] S602, performing coordinate interpolation on the second coordinate information of the preset EEG electrode in the second coordinate system to obtain third coordinate information of each intermediate EEG electrode in the second coordinate system;

[0142] Specifically, the first coordinate information of the preset EEG electrode in the second coordinate system is converted to the spherical coordinate system to obtain the coordinates of the preset EEG electrode in the spherical coordinate system; based on the coordinates of the preset EEG electrode in the spherical coordinate system, the coordinate information of each intermediate EEG electrode in the spherical coordinate system is obtained; the coordinate information of each intermediate EEG electrode in the spherical coordinate system is converted to the second coordinate system to obtain the third coordinate information of each intermediate EEG electrode in the second coordinate system. The specific implementation process of this step is similar to the process of obtaining the coordinate information of each intermediate EEG electrode in the first coordinate system in step S402, which will not be repeated here.

[0143] S603, performing weighted calculation on the third coordinate information of each intermediate EEG electrode in the second coordinate system and the second coordinate information of each intermediate EEG electrode in the second coordinate system to obtain fourth coordinate information of each intermediate EEG electrode in the second coordinate system.

[0144] Specifically, for each intermediate EEG electrode, the third coordinate information of the intermediate EEG electrode in the second coordinate system and the second coordinate information of each intermediate EEG electrode in the second coordinate system are weightedly calculated to obtain the fourth coordinate information of the intermediate EEG electrode in the second coordinate system. The fourth coordinate information of each intermediate EEG electrode in the second coordinate system is used for source tracing analysis. Among them, the weight corresponding to the third coordinate information of the intermediate EEG electrode in the second coordinate system and the weight corresponding to the second coordinate information of the intermediate EEG electrode in the second coordinate system are set according to actual experience, and the embodiment of the present invention does not limit it.

[0145] The coordinate information of each intermediate EEG electrode in the first coordinate system is calculated by coordinate interpolation, and there is an error with the actual coordinates of each intermediate EEG electrode in the first coordinate system; the third coordinate information of each intermediate EEG electrode in the second coordinate system is calculated by coordinate interpolation, and there is an error with the actual coordinates of each intermediate EEG electrode in the second coordinate system. By weighting the third coordinate information of the intermediate EEG electrode in the second coordinate system obtained by different methods and the second coordinate information of the intermediate EEG electrode in the second coordinate system, the overall error of the fourth coordinate information of each intermediate EEG electrode in the second coordinate system can be reduced.

[0146] Figure 7 is a schematic diagram of the structure of a source tracing and analyzing device based on EEG signals collected by a mechanical arm provided in the seventh embodiment of the present invention, such as Figure 7As shown, the source tracing and analyzing device for EEG signals collected by a mechanical arm provided in an embodiment of the present invention includes a first acquisition module 701, a conversion module 702, a calibration module 703, a signal acquisition module 704 and a source tracing and analyzing module 705, wherein:

[0147] The first acquisition module 701 is used to obtain the coordinate information of each EEG electrode in the first coordinate system; the conversion module 702 is used to obtain the first coordinate information of each EEG electrode in the second coordinate system according to the coordinate information of each EEG electrode in the first coordinate system and the coordinate transformation relationship between the first coordinate system and the second coordinate system; wherein the coordinate transformation relationship between the first coordinate system and the second coordinate system is obtained in advance; the calibration module 703 is used to calibrate the first coordinate information of each EEG electrode in the second coordinate system according to the calibration matrix to obtain the second coordinate information of each EEG electrode in the second coordinate system; wherein the calibration matrix is ​​obtained in advance; the signal acquisition module 704 is used to obtain EEG signals through EEG electrode acquisition; wherein the EEG signals are acquired by stimulating the preset target points of the subject's brain by a mechanical arm carrying a stimulation device and moving along a preset planned path; the preset planned path is planned based on the second coordinate information of the EEG electrode in the second coordinate system; the source tracing analysis module 705 is used to perform source tracing analysis based on the second coordinate information of each EEG electrode in the second coordinate system and the EEG signal.

[0148] Specifically, the first acquisition module 701 can obtain the coordinate information of the EEG electrode in the first coordinate system. There are multiple EEG electrodes, and the specific number of EEG electrodes is set according to actual needs, which is not limited in the embodiment of the present invention. For EEG electrodes placed on the subject's scalp, the spatial position data of the EEG electrodes can be collected by a camera, and the first coordinate system is the camera space coordinate system; for intracranial electrodes, CT images can be used to determine the spatial position data of the EEG electrodes, and the first coordinate system is the CT image coordinate system.

[0149] The conversion module 702 converts the coordinate information of each EEG electrode in the first coordinate system to the second coordinate system according to the coordinate transformation relationship between the first coordinate system and the second coordinate system, and obtains the first coordinate information of each EEG electrode in the second coordinate system. The coordinate transformation relationship between the first coordinate system and the second coordinate system is obtained in advance, and the first coordinate system is different from the second coordinate system. For example, the second coordinate system is the coordinate system of the subject's nuclear magnetic resonance imaging.

[0150] In order to obtain more accurate coordinates of each EEG electrode in the second coordinate system, the calibration module 703 calibrates the first coordinate information of each EEG electrode in the second coordinate system based on the calibration matrix to obtain the second coordinate information of each EEG electrode in the second coordinate system. The calibration matrix is ​​obtained in advance.

[0151] In order to improve the stability of the EEG signal acquisition process, the TMS coil can be carried by the mechanical arm and moved along the preset planning path to stimulate the preset target point of the subject's brain, and the signal acquisition module 704 can acquire the EEG signal through each EEG electrode. The preset planning path is set according to actual needs and is not limited in the embodiment of the present invention.

[0152] After obtaining the second coordinate information of each EEG electrode in the second coordinate system and collecting the EEG signal of the subject, the source analysis module 705 can perform source analysis based on the second coordinate information of each EEG electrode in the second coordinate system and the EEG signal. The specific process of source analysis is prior art and will not be described in detail here.

[0153] The embodiment of the present invention provides a source tracing and analysis device for EEG signals collected by a robotic arm, which obtains coordinate information of an EEG electrode in a first coordinate system; obtains first coordinate information of the EEG electrode in a second coordinate system according to the coordinate information of the EEG electrode in the first coordinate system and the coordinate transformation relationship between the first coordinate system and the second coordinate system; wherein the coordinate transformation relationship between the first coordinate system and the second coordinate system is obtained in advance; calibrates the first coordinate information of the EEG electrode in the second coordinate system according to a calibration matrix to obtain second coordinate information of the EEG electrode in the second coordinate system; wherein the calibration matrix is ​​obtained in advance; obtains EEG signals through EEG electrode collection; wherein the EEG signals are collected by stimulating preset targets of the subject's brain by moving a stimulation device carried by a robotic arm along a preset planned path; the preset planned path is planned based on the second coordinate information of the EEG electrode in the second coordinate system; performs source tracing analysis based on the second coordinate information of the EEG electrode in the second coordinate system and the EEG signal, and improves the accuracy of source tracing analysis because it can more accurately record the position of the EEG electrode corresponding to the individual brain area of ​​the subject and more accurately collect EEG signals.

[0154] Figure 8 is a schematic diagram of the structure of a source tracing and analyzing device based on EEG signals collected by a mechanical arm provided in the eighth embodiment of the present invention, such as Figure 8 As shown, on the basis of the above embodiments, further, the source tracing analysis device based on the EEG signal collected by the robot arm provided in the embodiment of the present invention further includes a second acquisition module 706, a third acquisition module 707 and an establishment module 708, wherein:

[0155] The second acquisition module 706 is used to acquire the brain point cloud data of the subject in the second coordinate system; the third acquisition module 707 is used to acquire the point cloud data of each EEG electrode in the second coordinate system; the establishment module 708 is used to establish a calibration matrix based on the brain point cloud data of the subject in the second coordinate system and the point cloud data of each EEG electrode in the second coordinate system.

[0156] Fig. 9 is a schematic diagram of the structure of a source tracing and analyzing device based on EEG signals collected by a mechanical arm provided in the ninth embodiment of the present invention, such as Fig. 9 As shown, on the basis of the above embodiments, further, the source tracing analysis device based on the EEG signal collected by the robot arm provided in the embodiment of the present invention further includes a fourth acquisition module 709, a fifth acquisition module 710 and an acquisition module 711, wherein:

[0157] The fourth acquisition module 709 is used to acquire the brain point cloud data of the subject in the second coordinate system; the fifth acquisition module 710 is used to acquire the brain point cloud data of the subject in the first coordinate system; the acquisition module 711 is used to align the brain point cloud data of the subject in the second coordinate system with the brain point cloud data of the subject in the first coordinate system to obtain the coordinate transformation relationship between the first coordinate system and the second coordinate system.

[0158] Fig.10 is a schematic diagram of the structure of a source tracing and analyzing device based on EEG signals collected by a mechanical arm provided in the tenth embodiment of the present invention, such as Fig.10 As shown, based on the above embodiments, further, the first acquisition module 701 includes an acquisition unit 7011 and a coordinate interpolation unit 7012, wherein:

[0159] The acquisition unit 7011 is used to obtain the coordinate information of the preset EEG electrodes in the first coordinate system; wherein, the preset EEG electrodes are EEG electrodes selected according to a preset order; the coordinate interpolation unit 7012 is used to perform coordinate interpolation according to the coordinate information of the preset EEG electrodes in the first coordinate system, and obtain the coordinate information of each intermediate EEG electrode in the first coordinate system; wherein, each intermediate EEG electrode is the EEG electrode other than the preset EEG electrodes.

[0160] Fig.11 FIG. 1 is a schematic diagram of a source tracing and analyzing device based on EEG signals collected by a mechanical arm according to an eleventh embodiment of the present invention. Fig.11 As shown, based on the above embodiments, the coordinate interpolation unit 7012 further includes a first conversion subunit 70121, an acquisition subunit 70122 and a second conversion subunit 70123, wherein:

[0161] The first conversion subunit 70121 is used to convert the coordinate information of the preset EEG electrode in the first coordinate system to the spherical coordinate system, and obtain the coordinates of the preset EEG electrode in the spherical coordinate system; the acquisition subunit 70122 is used to obtain the coordinates of each intermediate EEG electrode in the spherical coordinate system based on the coordinates of the preset EEG electrode in the spherical coordinate system; the second conversion subunit 70123 is used to convert the coordinate information of each intermediate EEG electrode in the spherical coordinate system to the first coordinate system, and obtain the coordinate information of each intermediate EEG electrode in the first coordinate system.

[0162] Fig.12 FIG. 1 is a schematic diagram of a source tracing and analyzing device based on EEG signals collected by a mechanical arm according to a twelfth embodiment of the present invention. Fig.12 As shown, on the basis of the above embodiments, further, the calibration module 703 includes a calibration unit 7031, a coordinate interpolation unit 7032 and a weighted calculation unit 7033, wherein:

[0163] The calibration unit 7031 is used to calibrate the first coordinate information of the preset EEG electrode in the second coordinate system according to the calibration matrix to obtain the second coordinate information of the preset EEG electrode in the second coordinate system; and to calibrate the first coordinate information of each intermediate EEG electrode in the second coordinate system according to the calibration matrix to obtain the second coordinate information of each intermediate EEG electrode in the second coordinate system; the coordinate interpolation unit 7032 is used to coordinate interpolate the second coordinate information of the preset EEG electrode in the second coordinate system to obtain the third coordinate information of each intermediate EEG electrode in the second coordinate system; the weighted calculation unit 7033 is used to perform weighted calculation on the third coordinate information of each intermediate EEG electrode in the second coordinate system and the second coordinate information of each intermediate EEG electrode in the second coordinate system to obtain the fourth coordinate information of each intermediate EEG electrode in the second coordinate system.

[0164] The embodiments of the apparatus provided in the embodiments of the present invention can be specifically used to execute the processing flow of the above-mentioned method embodiments, and its functions are not described in detail here, and reference can be made to the detailed description of the above-mentioned method embodiments.

[0165] Fig.13 1 is a schematic diagram of the structure of a system for tracing and analyzing EEG signals collected by a mechanical arm according to the thirteenth embodiment of the present invention. Fig.13 As shown, the source tracing and analysis system of EEG signals collected by a robot arm provided in an embodiment of the present invention comprises the source tracing and analysis device 1301 of EEG signals collected by a robot arm, a computer 1302, a robot 1303, a stimulation device 1304, a plurality of EEG electrodes 1305 and a navigation device 1306 described in any of the above embodiments, wherein:

[0166] The computer 1302 is respectively connected to the robot 1303, the stimulation device 1304, the plurality of EEG electrodes 1305, the navigation device 1306 and the source tracing analysis device 1301 based on the EEG signals collected by the robot arm;

[0167] A plurality of EEG electrodes 1305 are deployed in the subject's brain; a robot 1303 is used to carry a stimulation device 1304 to stimulate target points in the subject's brain; and a navigation device 1306 is used to collect spatial position data of the EEG electrodes.

[0168] Specifically, a plurality of EEG electrodes 1305 are arranged on the subject's head, and the plurality of EEG electrodes 1305 can be arranged in an EEG cap to facilitate wearing by the subject. The robot 1303 includes a control device and a mechanical arm, and the control device controls the mechanical arm to carry a stimulation device 1304 to stimulate the target point of the subject's brain; the stimulation device 1304 can use a TMS coil. The navigation device 1306 is used to obtain the position information of each EEG electrode 1305 and the position information of the stimulation device 1304. The computer 1302 constructs a 3D model of the subject's head based on the image data of the subject's brain, and obtains the subject's EEG signal. The navigation device 1306 can use devices including infrared cameras, color cameras, structured light cameras, etc.

[0169] Fig.14 is a schematic diagram of the physical structure of a computer device provided in the fourteenth embodiment of the present invention. Fig.14 As shown, the computer device 600 may include: a processor 100 and a memory 140. The memory 140 is coupled to the processor 100. The processor 100 may call the logic instructions in the memory 140 to execute the methods provided by the above-mentioned various method embodiments, for example, including: obtaining the coordinate information of each EEG electrode in the first coordinate system; obtaining the first coordinate information of each EEG electrode in the second coordinate system according to the coordinate information of each EEG electrode in the first coordinate system and the coordinate transformation relationship between the first coordinate system and the second coordinate system; wherein the coordinate transformation relationship between the first coordinate system and the second coordinate system is obtained in advance; calibrating the first coordinate information of each EEG electrode in the second coordinate system according to the calibration matrix to obtain the second coordinate information of each EEG electrode in the second coordinate system; wherein the calibration matrix is ​​obtained in advance; acquiring EEG signals through each EEG electrode; wherein the EEG signals are acquired by stimulating the preset target point of the subject's brain by moving the stimulation device with the mechanical arm according to the preset planning path; the preset planning path is planned based on the second coordinate information of each EEG electrode in the second coordinate system; and performing source tracing analysis according to the second coordinate information of each EEG electrode in the second coordinate system and the EEG signal.

[0170] The present embodiment discloses a computer program product, which includes a computer program / instruction stored on a computer-readable storage medium. When the computer program / instruction is executed by a computer, the computer can execute the methods provided by the above-mentioned method embodiments, for example, including: obtaining coordinate information of each EEG electrode in a first coordinate system; obtaining first coordinate information of each EEG electrode in a second coordinate system according to the coordinate information of each EEG electrode in the first coordinate system and the coordinate transformation relationship between the first coordinate system and the second coordinate system; wherein the coordinate transformation relationship between the first coordinate system and the second coordinate system is obtained in advance; calibrating the first coordinate information of each EEG electrode in the second coordinate system according to a calibration matrix to obtain second coordinate information of each EEG electrode in the second coordinate system; wherein the calibration matrix is ​​obtained in advance; acquiring EEG signals through each EEG electrode; wherein the EEG signals are acquired by stimulating a preset target point in the brain of a subject by moving a stimulation device carried by a robotic arm along a preset planned path; the preset planned path is planned based on the second coordinate information of each EEG electrode in the second coordinate system; and performing source tracing analysis based on the second coordinate information of each EEG electrode in the second coordinate system and the EEG signal.

[0171] The present embodiment provides a computer-readable storage medium, which stores a computer program / instruction. When the computer program / instruction is executed by a processor, the computer executes the methods provided by the above-mentioned method embodiments, for example, including: obtaining coordinate information of each EEG electrode in a first coordinate system; obtaining first coordinate information of each EEG electrode in a second coordinate system according to the coordinate information of each EEG electrode in the first coordinate system and the coordinate transformation relationship between the first coordinate system and the second coordinate system; wherein the coordinate transformation relationship between the first coordinate system and the second coordinate system is obtained in advance; calibrating the first coordinate information of each EEG electrode in the second coordinate system according to a calibration matrix to obtain second coordinate information of each EEG electrode in the second coordinate system; wherein the calibration matrix is ​​obtained in advance; acquiring EEG signals through each EEG electrode; wherein the EEG signals are acquired by stimulating a preset target point in the subject's brain by moving a stimulation device carried by a robotic arm along a preset planned path; the preset planned path is planned based on the second coordinate information of each EEG electrode in the second coordinate system; and performing source tracing analysis based on the second coordinate information of each EEG electrode in the second coordinate system and the EEG signal.

[0172] like Fig.14 As shown, the computer device 600 may also include: a communication module 110, an input unit 120, an audio processor 130, a display 160, and a power supply 170. It is worth noting that the computer device 600 does not necessarily have to include Fig.14In addition, the computer device 600 may also include Fig.14 For components not shown in the figure, reference may be made to the prior art. It should be noted that the figure is exemplary; other types of structures may also be used to supplement or replace the structure to achieve telecommunication functions or other functions.

[0173] like Fig.14 As shown, the processor 100 is sometimes also referred to as a controller or an operation control, and may include a microprocessor or other processor devices and / or logic devices. The processor 100 receives inputs and controls the operations of various components of the computer device 600 .

[0174] The memory 140 may be, for example, one or more of a cache, a flash memory, a hard drive, a removable medium, a volatile memory, a non-volatile memory or other suitable devices. The above-mentioned information related to the failure may be stored, and a program for executing the relevant information may also be stored. The processor 100 may execute the program stored in the memory 140 to implement information storage or processing, etc.

[0175] The input unit 120 provides input to the processor 100. The input unit 120 is, for example, a key or touch input device. The power supply 170 is used to provide power to the computer device 600. The display 160 is used to display display objects such as images and text. The display 160 can be, for example, an LCD display, but is not limited thereto.

[0176] The memory 140 may be a solid-state memory, such as a read-only memory (ROM), a random access memory (RAM), a SIM card, etc. It may also be a memory that saves information even when the power is off, can be selectively erased, and is provided with more data, and examples of the memory 140 are sometimes referred to as EPROMs, etc. The memory 140 may also be some other type of device. The memory 140 includes a buffer 141 (sometimes referred to as a buffer memory). The memory 140 may include an application / function storage unit 142, which is used to store application programs and function programs or processes for executing the operation of the computer device 600 through the processor 100.

[0177] The memory 140 may also include a data storage unit 143 for storing data, such as contacts, digital data, pictures, sounds, and / or any other data used by the computer device. The driver storage unit 144 of the memory 140 may include various drivers for the communication function of the computer device and / or for executing other functions of the computer device (such as a messaging application, a contact book application, etc.).

[0178] The communication module 110 includes a transmitter / receiver for transmitting and receiving signals via an antenna 111. The communication module 110 is coupled to the processor 100 to provide input signals and receive output signals, which may be the same as in the case of a conventional mobile communication terminal.

[0179] Based on different communication technologies, multiple communication modules 110 may be provided in the same computer device, such as a cellular network module, a Bluetooth module and / or a wireless local area network module. The communication module 110 is also coupled to a speaker 131 and a microphone 132 via an audio processor 130 to provide an audio output via the speaker 131 and receive an audio input from the microphone 132, thereby realizing a common telecommunication function. The audio processor 130 may include any suitable buffer, decoder, amplifier, etc. In addition, the audio processor 130 is also coupled to the processor 100, so that recording can be performed on the local machine through the microphone 132, and the sound stored on the local machine can be played through the speaker 131.

[0180] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0181] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0182] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0183] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0184] In the description of this specification, the description with reference to the terms "one embodiment", "a specific embodiment", "some embodiments", "for example", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0185] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for tracing and analyzing the electroencephalogram signals collected by a robotic arm, characterized in that: include: Obtaining coordinate information of each EEG electrode in the first coordinate system; Obtaining first coordinate information of each EEG electrode in the second coordinate system according to coordinate information of each EEG electrode in the first coordinate system and a coordinate transformation relationship between the first coordinate system and the second coordinate system; wherein the coordinate transformation relationship between the first coordinate system and the second coordinate system is obtained in advance; Calibrate the first coordinate information of each EEG electrode in the second coordinate system according to the calibration matrix to obtain the second coordinate information of each EEG electrode in the second coordinate system; wherein the calibration matrix is ​​obtained in advance; The EEG signals are acquired by collecting the EEG electrodes; wherein the EEG signals are collected by stimulating the preset target points of the subject's brain by moving the stimulation device carried by the robotic arm along the preset planned path; the preset planned path is planned based on the second coordinate information of each EEG electrode in the second coordinate system; A source tracing analysis is performed based on the second coordinate information of each EEG electrode in the second coordinate system and the EEG signal.

2. The method according to claim 1, characterized in that: The step of obtaining the calibration matrix comprises: Acquire brain point cloud data of the subject in a second coordinate system; Obtaining point cloud data of each EEG electrode in a second coordinate system; A calibration matrix is ​​established based on the brain point cloud data of the subject in the second coordinate system and the point cloud data of each EEG electrode in the second coordinate system.

3. The method according to claim 1, characterized in that Establishing the coordinate transformation relationship between the first coordinate system and the second coordinate system includes: Acquire brain point cloud data of the subject in a second coordinate system; Acquire brain point cloud data of the subject in a first coordinate system; The brain point cloud data of the subject in the second coordinate system and the brain point cloud data of the subject in the first coordinate system are registered to obtain a coordinate transformation relationship between the first coordinate system and the second coordinate system.

4. The method according to claim 1, characterized in that The step of obtaining coordinate information of each EEG electrode in the first coordinate system includes: Obtaining coordinate information of a preset EEG electrode in a first coordinate system; wherein the preset EEG electrode is an EEG electrode selected in a preset order; Coordinate interpolation is performed according to the coordinate information of the preset EEG electrodes in the first coordinate system to obtain the coordinate information of each intermediate EEG electrode in the first coordinate system; wherein each intermediate EEG electrode is an EEG electrode other than the preset EEG electrodes.

5. The method according to claim 4, characterized in that The performing coordinate interpolation according to the coordinate information of the preset EEG electrodes in the first coordinate system to obtain the coordinate information of each intermediate EEG electrode in the first coordinate system comprises: Convert the coordinate information of the preset EEG electrode in the first coordinate system to the spherical coordinate system to obtain the coordinates of the preset EEG electrode in the spherical coordinate system; Based on the coordinates of the preset EEG electrodes in the spherical coordinate system, the coordinates of each intermediate EEG electrode in the spherical coordinate system are obtained; The coordinate information of each intermediate EEG electrode in the spherical coordinate system is converted to the first coordinate system to obtain the coordinate information of each intermediate EEG electrode in the first coordinate system.

6. The method according to claim 4, characterized in that The step of calibrating the first coordinate information of each EEG electrode in the second coordinate system according to the calibration matrix to obtain the second coordinate information of each EEG electrode in the second coordinate system comprises: Calibrate the first coordinate information of the preset EEG electrode in the second coordinate system according to the calibration matrix to obtain the second coordinate information of the preset EEG electrode in the second coordinate system; and calibrate the first coordinate information of each intermediate EEG electrode in the second coordinate system according to the calibration matrix to obtain the second coordinate information of each intermediate EEG electrode in the second coordinate system; Performing coordinate interpolation on the second coordinate information of the preset EEG electrodes in the second coordinate system to obtain third coordinate information of each intermediate EEG electrode in the second coordinate system; The third coordinate information of each intermediate EEG electrode in the second coordinate system and the second coordinate information of each intermediate EEG electrode in the second coordinate system are weightedly calculated to obtain the fourth coordinate information of each intermediate EEG electrode in the second coordinate system.

7. A device for tracing and analyzing the electroencephalogram signals collected by a mechanical arm, characterized in that: include: A first acquisition module, used to acquire coordinate information of each EEG electrode in a first coordinate system; A conversion module, used to obtain first coordinate information of each EEG electrode in a second coordinate system according to the coordinate information of each EEG electrode in the first coordinate system and the coordinate transformation relationship between the first coordinate system and the second coordinate system; wherein the coordinate transformation relationship between the first coordinate system and the second coordinate system is obtained in advance; A calibration module, used to calibrate the first coordinate information of each EEG electrode in the second coordinate system according to the calibration matrix to obtain the second coordinate information of each EEG electrode in the second coordinate system; wherein the calibration matrix is ​​obtained in advance; A signal acquisition module, used for acquiring EEG signals through EEG electrodes; wherein the EEG signals are acquired by stimulating a preset target point in the subject's brain by moving a stimulation device carried by a robotic arm along a preset planned path; the preset planned path is planned based on the second coordinate information of the EEG electrodes in a second coordinate system; The source tracing analysis module is used to perform source tracing analysis based on the second coordinate information of each EEG electrode in the second coordinate system and the EEG signal.

8. The device according to claim 7, characterized in that Also includes: A second acquisition module is used to acquire brain point cloud data of the subject in a second coordinate system; The third acquisition module is used to acquire point cloud data of each EEG electrode in the second coordinate system; A module is established to establish a calibration matrix based on the brain point cloud data of the subject in the second coordinate system and the point cloud data of each EEG electrode in the second coordinate system.

9. The device according to claim 7, characterized in that Also includes: A fourth acquisition module is used to acquire brain point cloud data of the subject in a second coordinate system; a fifth acquisition module, used to acquire brain point cloud data of the subject in a first coordinate system; The acquisition module is used to align the brain point cloud data of the subject in the second coordinate system with the brain point cloud data of the subject in the first coordinate system to obtain the coordinate transformation relationship between the first coordinate system and the second coordinate system.

10. The device according to claim 7, characterized in that The first acquisition module includes: An acquisition unit, used to acquire coordinate information of a preset EEG electrode in a first coordinate system; wherein the preset EEG electrode is an EEG electrode selected in a preset order; The coordinate interpolation unit is used to perform coordinate interpolation according to the coordinate information of the preset EEG electrodes in the first coordinate system to obtain the coordinate information of each intermediate EEG electrode in the first coordinate system; wherein each intermediate EEG electrode is an EEG electrode other than the preset EEG electrodes.

11. The device according to claim 10, characterized in that The coordinate interpolation unit comprises: A first conversion subunit is used to convert the coordinate information of the preset EEG electrode in the first coordinate system into the spherical coordinate system to obtain the coordinates of the preset EEG electrode in the spherical coordinate system; An obtaining subunit, used for obtaining the coordinates of each intermediate EEG electrode in the spherical coordinate system based on the coordinates of the preset EEG electrode in the spherical coordinate system; The second conversion subunit is used to convert the coordinate information of each intermediate EEG electrode in the spherical coordinate system to the first coordinate system to obtain the coordinate information of each intermediate EEG electrode in the first coordinate system.

12. The device according to claim 10, characterized in that The calibration module comprises: a calibration unit, configured to calibrate the first coordinate information of the preset EEG electrode in the second coordinate system according to the calibration matrix to obtain the second coordinate information of the preset EEG electrode in the second coordinate system; and to calibrate the first coordinate information of each intermediate EEG electrode in the second coordinate system according to the calibration matrix to obtain the second coordinate information of each intermediate EEG electrode in the second coordinate system; A coordinate interpolation unit, used for performing coordinate interpolation on the second coordinate information of the preset EEG electrodes in the second coordinate system to obtain third coordinate information of each intermediate EEG electrode in the second coordinate system; The weighted calculation unit is used to perform weighted calculation on the third coordinate information of each intermediate EEG electrode in the second coordinate system and the second coordinate information of each intermediate EEG electrode in the second coordinate system to obtain the fourth coordinate information of each intermediate EEG electrode in the second coordinate system.

13. A source tracing analysis system based on electroencephalogram signals collected by a robotic arm, characterized in that: The device comprises a source tracing and analyzing device for EEG signals collected by a robot arm according to any one of claims 7 to 12, a computer, a robot, a stimulation device, a plurality of EEG electrodes and a navigation device, wherein: The computer is respectively connected to the robot, the stimulation device, the plurality of EEG electrodes, the navigation device, and the source tracing and analyzing device based on the EEG signals collected by the robot arm; The multiple EEG electrodes are deployed in the subject's brain; the robot is used to carry the stimulation device to stimulate the target point in the subject's brain; and the navigation device is used to collect spatial position data of the EEG electrodes.

14. A computer device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the method according to any one of claims 1 to 6.

15. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program / instruction, and when the computer program / instruction is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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