Method, device and system for tracing analysis of electroencephalogram signals collected by robotic arm

Abstract

The present invention provides a method, device and system for traceability analysis of electroencephalogram signals collected by a robotic arm. The method includes: obtaining coordinate information of each electroencephalogram electrode in a first coordinate system; obtaining first coordinate information of each electroencephalogram electrode in a second coordinate system according to the coordinate information of each electroencephalogram electrode in the first coordinate system and the coordinate transformation relationship between the first coordinate system and the second coordinate system; calibrating the first coordinate information of each electroencephalogram electrode in the second coordinate system according to a calibration matrix to obtain second coordinate information of each electroencephalogram electrode in the second coordinate system; collecting electroencephalogram signals 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 signals. The method, device and system for traceability analysis of electroencephalogram signals collected by a robotic arm provided by the embodiments of the present invention improve the accuracy of traceability analysis.

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 electroencephalogram (EEG) signals are acquired 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 stimulating 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 a second coordinate system.

[0010] Perform source analysis based on the second coordinate information of each EEG electrode in the second coordinate system and the EEG signals.

[0011] Further, the steps of obtaining the calibration matrix include:

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

[0013] Obtain the point cloud data of each EEG electrode in the second coordinate system;

[0014] 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, establish a calibration matrix.

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

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

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

[0018] Register 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 to obtain the coordinate transformation relationship between the first coordinate system and the second coordinate system.

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

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

[0021] Perform coordinate interpolation based on the coordinate information of the preset EEG electrode 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 electrode among the EEG electrodes.

[0022] Further, the performing coordinate interpolation based on the coordinate information of the preset EEG electrode 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 electrodes in the first coordinate system to the spherical coordinate system to obtain the coordinates of the preset EEG electrodes in the spherical coordinate system;

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

[0025] 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.

[0026] Further, the 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] Perform coordinate interpolation on 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;

[0029] 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.

[0030] In a second aspect, the present invention provides a traceability analysis device for EEG signals collected by a robotic arm, including:

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

[0032] A conversion module, configured 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;

[0033] A calibration module, configured 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, configured to acquire electroencephalogram (EEG) signals through EEG electrodes; wherein, the EEG signals are acquired by a robotic arm carrying a stimulating device to move along a preset planned path to stimulate a preset target point on the brain of a subject; the preset planned path is planned based on the second coordinate information of the EEG electrodes in a second coordinate system.

[0035] A tracing analysis module, configured to perform tracing analysis based on the second coordinate information of each EEG electrode in the second coordinate system and the EEG signals.

[0036] Further, the tracing analysis device for EEG signals acquired based on a robotic arm according to an embodiment of the present invention further includes:

[0037] A second acquisition module, configured to acquire brain point cloud data of a subject in the second coordinate system.

[0038] A third acquisition module, configured to acquire point cloud data of each EEG electrode in the second coordinate system.

[0039] A building module, configured to build 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] Further, the tracing analysis device for EEG signals acquired based on a robotic arm according to an embodiment of the present invention further includes:

[0041] A fourth acquisition module, configured to acquire brain point cloud data of a subject in the second coordinate system.

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

[0043] An obtaining module, configured to register 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 to obtain the coordinate transformation relationship between the first coordinate system and the second coordinate system.

[0044] Further, the first acquisition module includes:

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

[0046] A coordinate interpolation unit, configured to perform coordinate interpolation based on the coordinate information of the preset EEG electrode 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 electrode among the EEG electrodes.

[0047] Further, the coordinate interpolation unit includes:

[0048] A first conversion subunit, configured to convert the coordinate information of a preset electroencephalogram (EEG) electrode in a first coordinate system to a spherical coordinate system, so as to obtain the coordinates of the preset EEG electrode in the spherical coordinate system;

[0049] An obtaining subunit, configured 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;

[0050] A second conversion subunit, configured to convert the coordinate information of each intermediate EEG electrode in the spherical coordinate system to the first coordinate system, so as to obtain the coordinate information of each intermediate EEG electrode in the first coordinate system.

[0051] Further, the calibration module includes:

[0052] A calibration unit, configured to calibrate the first coordinate information of a preset EEG electrode in a 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;

[0053] A coordinate interpolation unit, configured to perform coordinate interpolation on 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;

[0054] A weighted calculation unit, configured to perform a 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 traceability analysis system for EEG signals collected by a robotic arm, including the traceability analysis device for EEG signals collected by a robotic arm according to any one of the above embodiments, a computer, a robot, a stimulation device, a plurality of EEG electrodes, and a navigation device, wherein:

[0056] The computer is respectively connected to the robot, the stimulation device, the plurality of EEG electrodes, the navigation device, and the traceability analysis device for EEG signals collected by a robotic arm;

[0057] The plurality of EEG electrodes are deployed on the brain of a subject; the robot is configured to carry the stimulation device to stimulate a target point on the brain of the subject; the navigation device is configured to collect spatial position data of the EEG electrodes.

[0058] Fourthly, the present invention provides a computer device, including a memory, a processor, and a computer program stored on the memory. The processor executes the program to implement the traceability analysis method of the electroencephalogram signal collected by the robotic arm according to any of the above embodiments.

[0059] Fifthly, the present invention provides a computer-readable storage medium. The computer-readable storage medium stores a computer program / instructions, and when the computer program / instructions are executed by a processor, the traceability analysis method of the electroencephalogram signal collected by the robotic arm according to any of the above embodiments is implemented.

[0060] The traceability analysis method, device, and system of the electroencephalogram signal collected by the robotic arm provided by the embodiments of the present invention obtain the coordinate information of the electroencephalogram electrode in the first coordinate system; according to the coordinate information of the electroencephalogram electrode in the first coordinate system and the coordinate transformation relationship between the first coordinate system and the second coordinate system, obtain the first coordinate information of the electroencephalogram electrode in 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 the electroencephalogram electrode in the second coordinate system according to the calibration matrix to obtain the second coordinate information of the electroencephalogram electrode in the second coordinate system; wherein, the calibration matrix is obtained in advance; collect the electroencephalogram signal through the electroencephalogram electrode; wherein, the electroencephalogram signal is collected by the robotic arm carrying the stimulation device to stimulate the preset target point of the subject's brain according to the preset planned path; the preset planned path is planned based on the second coordinate information of the electroencephalogram electrode in the second coordinate system; perform traceability analysis according to the second coordinate information of the electroencephalogram electrode in the second coordinate system and the electroencephalogram signal. Since it can record the position of the electroencephalogram electrode corresponding to the individual brain region of the subject more accurately and collect the electroencephalogram signal more accurately, the accuracy of the traceability analysis is improved. Description of the Drawings

[0061] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained according to these drawings. In the drawings:

[0062] Figure 1 is a schematic flowchart of the traceability analysis method of the electroencephalogram signal collected by the robotic arm provided by the first embodiment of the present invention.

[0063] Figure 2 is a schematic flowchart of the traceability analysis method of the electroencephalogram signal collected by the robotic arm provided by the second embodiment of the present invention.

[0064] Figure 3It is a schematic flowchart of a traceability analysis method for electroencephalogram signals collected by a robotic arm provided in the third embodiment of the present invention.

[0065] Figure 4 It is a schematic flowchart of a traceability analysis method for electroencephalogram signals collected by a robotic arm provided in the fourth embodiment of the present invention.

[0066] Figure 5 It is a schematic flowchart of a traceability analysis method for electroencephalogram signals collected by a robotic arm provided in the fifth embodiment of the present invention.

[0067] Figure 6 It is a schematic flowchart of a traceability analysis method for electroencephalogram signals collected by a robotic arm provided in the sixth embodiment of the present invention.

[0068] Figure 7 It is a schematic structural diagram of a traceability analysis device for electroencephalogram signals collected by a robotic arm provided in the seventh embodiment of the present invention.

[0069] Figure 8 It is a schematic structural diagram of a traceability analysis device for electroencephalogram signals collected by a robotic arm provided in the eighth embodiment of the present invention.

[0070] Figure 9 It is a schematic structural diagram of a traceability analysis device for electroencephalogram signals collected by a robotic arm provided in the ninth embodiment of the present invention.

[0071] Figure 10 It is a schematic structural diagram of a traceability analysis device for electroencephalogram signals collected by a robotic arm provided in the tenth embodiment of the present invention.

[0072] Figure 11 It is a schematic structural diagram of a traceability analysis device for electroencephalogram signals collected by a robotic arm provided in the eleventh embodiment of the present invention.

[0073] Figure 12 It is a schematic structural diagram of a traceability analysis device for electroencephalogram signals collected by a robotic arm provided in the twelfth embodiment of the present invention.

[0074] Figure 13 It is a schematic structural diagram of a traceability analysis system for electroencephalogram signals collected by a robotic arm provided in the thirteenth embodiment of the present invention.

[0075] Figure 14 It is a schematic entity structure diagram of a computer device provided in the fourteenth embodiment of the present invention. Detailed implementation manners

[0076] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clearly understood, the following further describes the embodiments of the present invention in detail with reference to the accompanying drawings. Herein, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but not to limit the present invention. It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments can be arbitrarily combined with each other. In the technical solutions of the present application, the acquisition, storage, use, processing, etc. of data all comply with the relevant regulations 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, processing, etc. of the user information have obtained the authorization and consent of the customers.

[0077] To facilitate the understanding of the technical solutions provided by the present application, the following first describes the relevant content of the technical solutions of the present application.

[0078] Electroencephalography (EEG) is a technology used to record the electrical activities of the brain. When neurons in the brain are active, they generate tiny electric currents, which form weak potential changes on the scalp surface. EEG captures these potential changes by placing multiple electrodes on the scalp and converts them into visual graphs or data, thereby being able to 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 scope of application 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 positions usually relies on internationally recognized standard systems, 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 positions of electrodes through specific marking points. The following are the basic steps for determining electrode positions: First, calibrate the reference points on the head; second, measure the size of the head to ensure a properly sized electrode acquisition device, such as an EEG cap, EEG helmet, EEG bracket, etc., is worn; then use the 10-20 system or other standardized systems to determine the position of each electrode; finally, fine-tune the electrodes as needed. In current technical practices, the wearing of electrode acquisition devices often relies on the experience and intuition of operators, which limits the ability to precisely match the electrodes with specific regions of the cerebral cortex.

[0081] Mainstream EEG acquisitions all use EEG caps distributed according to the 10-10 or 10-20 system. The EEG cap comes with a general coordinate system, which has inaccurate positioning and is not personalized enough, and cannot be adjusted to adapt to different subjects. The EEG bracket with dry electrodes or the wearable device with built-in electrodes often has a height of about 2-3 cm, which is suitable for the rapid display of EEG signals or home use. The EEG electrode can be an intracranial electrode, which can be placed according to the position near the epileptic focus. The positioning can use a probe, and CT images are often used to determine it.

[0082] EEG data analysis usually adopts the source analysis method to explore the activity changes in specific brain regions. Source analysis needs to rely on the individual anatomical magnetic resonance imaging (MRI) data and electrode positions of the subject. However, the existing technical means are often limited to using a general EEG position template and do not fully consider the individual differences in the brain structure of the subject. By combining the individual MRI data with the personalized electrode position coordinates, this application achieves a more accurate source analysis, thus overcoming the limitations of traditional methods and providing a higher level of personalization and accuracy for EEG signal analysis.

[0083] This application uses a robotic arm to replace manual operation, sets a specific precise posture for each target point, ensures that the EEG electrode is not touched during the EEG signal acquisition process, avoids the offset of the electrode, and thus ensures the stability and reliability of data acquisition over a long time, thereby improving the acquisition quality of EEG data.

[0084] Figure 1 It is a schematic flowchart of the source analysis method of EEG signals collected based on a robotic arm provided by the first embodiment of the present invention. As Figure 1 shown, the source analysis method of EEG signals collected based on a robotic arm provided by the embodiment of the present invention includes:

[0085] S101. Obtain the coordinate information of each EEG electrode in the first coordinate system;

[0086] Specifically, the coordinate information of the EEG electrode in the first coordinate system can be obtained. The number of EEG electrodes is multiple, 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 the EEG electrodes placed on the scalp of the subject, 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, the CT image 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 and sits within the field of view of the camera. The spatial position data of each EEG electrode is collected through the camera, and the coordinate information of each EEG electrode in the first coordinate system can be obtained. Among them, the camera can be an infrared camera, a color camera, a structured light camera, etc., which can be selected according to actual needs, and the embodiments of the present invention do not make limitations. 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 points that the subject needs to be stimulated can be selected in the controller. It can be clicked and selected on the 3D model of the subject's brain, or the MRI coordinates can be input, and after selecting the coordinates, they are saved.

[0089] Precise positioning can be achieved on all EEG electrodes by using a probe, and the coordinate information of each EEG electrode in the first coordinate system can be collected. There are patterns with a certain arrangement order on the probe. 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, and thus the coordinate information of the tip of the probe in the camera space coordinate system can be further obtained. Click the middle position of each EEG electrode in sequence according to the set order; after each click on the middle position of the EEG electrode, the coordinate information of the current EEG electrode in the camera space coordinate system will be recorded, that is, the coordinate information of the EEG electrode in the first coordinate system. Among them, the click order of each EEG electrode can be set according to specific needs, and the embodiments of the present invention do not make limitations.

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

[0091] S102. 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; among them, 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 to obtain the first coordinate information of each EEG electrode in the second coordinate system. Among them, 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 subject's nuclear magnetic resonance image coordinate system.

[0093] S103. 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; among them, 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 source analysis of EEG signals based on TMS-EEG data, due to manual errors generated when the subject wears the EEG cap and the existence of systematic errors, there are errors in the first coordinate information of each EEG electrode in the second coordinate system. 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 obtained is beneficial to obtaining an accurate correspondence between each EEG electrode and the target point on the subject's head, thereby significantly improving the accuracy of the source analysis.

[0096] S104. Collect EEG signals through EEG electrodes; wherein, the EEG signals are collected by stimulating a preset target point on the subject's brain by a robotic arm carrying a stimulating device moving along a preset planned path; the preset planned path is planned based on the second coordinate information of the EEG electrodes in the second coordinate system.

[0097] Specifically, in order to improve the stability during the EEG signal collection process, the robotic arm can carry the stimulating device to move along a preset planned path to stimulate a preset target point on the subject's brain, and the EEG signals are collected through each EEG electrode. The preset planned path is set according to actual needs and is not limited in the embodiments of the present invention.

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

[0099] By reasonably planning the movement path of the TMS coil, the robotic arm can automatically move the TMS coil to the magnetic stimulation point of 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 and greatly improves the accuracy of EEG signal collection. In addition, it can also avoid the problem that the coil shakes caused by manual operation in the prior art, which in turn affects the accuracy of data collection.

[0100] For example, a robotic arm carries a TMS coil and stimulates each target point in sequence according to a preset planned path, with the target points corresponding one-to-one to the EEG electrodes. During transcranial magnetic stimulation, every time the robotic arm moves to a position for stimulating a target point, it will maintain the posture corresponding to the preset target point. If the subject's head moves or other situations occur, causing the TMS signal to weaken and resulting in the posture of the robotic arm deviating from the posture corresponding to the preset target point, then the transcranial magnetic stimulation of this target point will be paused, the posture of the robotic arm will be adjusted to the posture corresponding to the preset target point, and then the transcranial magnetic stimulation of this target point will be resumed. The posture corresponding to the preset target point can be determined by setting the preset range of the target distance, the preset range of the translation distance, the preset range of the normal angle, and the preset range of the rotation angle. If the target distance is within the preset range of the target distance, the translation distance of the TMS coil is within the preset range of the translation distance, the normal angle of the TMS coil is within the preset range of the normal angle, and the rotation angle of the TMS coil is within the preset range of the rotation angle, then the robotic arm maintains the posture corresponding to the preset target point. If the target distance is not within the preset range of the target distance, the translation distance of the TMS coil is not within the preset range of the translation distance, the normal angle of the TMS coil is not within the preset range of the normal angle, or the rotation angle of the TMS coil is not within the preset range of the rotation angle, then the posture of the robotic arm deviates from the posture corresponding to the preset target point, and the transcranial magnetic stimulation will be stopped, and the posture of the robotic arm will be adjusted.

[0101] S105. Perform source 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 analysis can be performed based on the second coordinate information of each EEG electrode in the second coordinate system and the EEG signal. Among them, the specific process of source analysis is prior art and will not be elaborated here.

[0103] The traceability analysis method for electroencephalogram (EEG) signals collected by a robotic arm provided in an embodiment of the present invention obtains the coordinate information of EEG electrodes in a first coordinate system; based on the coordinate information of the EEG electrodes in the first coordinate system and the coordinate transformation relationship between the first coordinate system and a second coordinate system, obtains the first coordinate information of the EEG electrodes in the second coordinate system, where 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 electrodes in the second coordinate system according to a calibration matrix to obtain the second coordinate information of the EEG electrodes in the second coordinate system, where the calibration matrix is obtained in advance; collects EEG signals through the EEG electrodes, where the EEG signals are collected 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, and the preset planned path is planned based on the second coordinate information of the EEG electrodes in the second coordinate system; performs traceability analysis according to the second coordinate information of the EEG electrodes in the second coordinate system and the EEG signals. Since it can record the position of the EEG electrodes corresponding to the individual brain regions of the subject more accurately and collect the EEG signals more accurately, the accuracy of the traceability analysis is improved.

[0104] Figure 2 is a schematic flowchart of the traceability analysis method for EEG signals collected by a robotic arm provided in the second embodiment of the present invention. As Figure 2 shown, on the basis of the above embodiments, further, the steps of obtaining the calibration matrix include:

[0105] S201. Obtain the brain point cloud data of the subject in the second coordinate system;

[0106] Specifically, based on the brain image of the subject, the brain point cloud data of the subject in the second coordinate system can be obtained. Among them, 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 is set according to actual needs and is not limited in the embodiments of the present invention.

[0107] S202. Obtain the point cloud data of each EEG electrode in the second coordinate system;

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

[0109] S203. 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.

[0110] Specifically, register 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 the calibration matrix.

[0111] For example, the Iterative Closest Point (ICP) algorithm can be used to register 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, and obtain a calibration matrix.

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

[0113] Figure 3 It is a schematic flowchart of the traceability analysis method of the EEG signal collected by the robotic arm provided in the third embodiment of the present invention. As Figure 3 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. Obtain the brain point cloud data of the subject in the second coordinate system;

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

[0116] S302. Obtain the brain point cloud data of the subject in the first coordinate system;

[0117] Specifically, by using a camera to collect the spatial position data of the subject's brain, the brain point cloud data of the subject in the first coordinate system can be obtained. Among them, the first coordinate system is the camera space coordinate system.

[0118] S303. Register 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, and obtain the coordinate transformation relationship between the first coordinate system and the second coordinate system.

[0119] Specifically, through a registration algorithm, 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 establish the 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, and obtain the coordinate transformation relationship between the first coordinate system and the second coordinate system. Among them, the registration algorithm used is selected according to actual needs, and the embodiments of the present invention do not make limitations.

[0120] Figure 4 This is a schematic flowchart of the traceability analysis method for electroencephalogram signals collected by a robotic arm according to the fourth embodiment of the present invention. As Figure 4 shown, on the basis of the above embodiments, further, the obtaining of the coordinate information of each electroencephalogram electrode in the first coordinate system includes:

[0121] S401. Obtain the coordinate information of a preset electroencephalogram electrode in the first coordinate system; wherein, the preset electroencephalogram electrode is an electroencephalogram electrode selected in a preset order.

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

[0123] For example, for a subject wearing an electroencephalogram cap and sitting within the field of view of a camera, the spatial position data of each preset electroencephalogram electrode is collected through the camera, and the coordinate information of each preset electroencephalogram electrode in the first coordinate system can be obtained.

[0124] For example, the electroencephalogram electrodes selected in the preset order are odd electrodes or even electrodes.

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

[0126] Specifically, based on the coordinate information of the preset electroencephalogram electrode in the first coordinate system, coordinate interpolation is performed to estimate the coordinate information of each intermediate electroencephalogram electrode in the first coordinate system, and the coordinate information of each intermediate electroencephalogram electrode in the first coordinate system can be obtained. Each intermediate electroencephalogram electrode is an electroencephalogram electrode other than the preset electroencephalogram electrode among electroencephalogram electrodes.

[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 means of linear interpolation, so as to obtain the coordinate information of each intermediate EEG electrode in the first coordinate system. Each EEG electrode can be considered to be evenly 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, and perform coordinate interpolation in the spherical coordinate system to obtain the coordinate information of each intermediate EEG electrode in the first coordinate system.

[0129] Figure 5 It is a schematic flowchart of the traceability analysis method for EEG signals collected by a robotic arm provided in the fifth embodiment of the present invention. As Figure 5 shown, on the basis of the above embodiments, further, the obtaining the coordinate information of each intermediate EEG electrode in the first coordinate system by performing coordinate interpolation according to the coordinate information of the preset EEG electrodes in the first coordinate system includes:

[0130] S501. Convert the coordinate information of the preset EEG electrodes in the first coordinate system to the spherical coordinate system to obtain the coordinates of the preset EEG electrodes in the spherical coordinate system;

[0131] Specifically, the first coordinate system is a Cartesian coordinate system. By converting the coordinate information of the preset EEG electrodes in the first coordinate system to the spherical coordinate system, the coordinates of the preset EEG electrodes in the spherical coordinate system can be obtained.

[0132] S502. Obtain the coordinates of each intermediate EEG electrode in the spherical coordinate system based on the coordinate information of the preset EEG electrodes 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, all EEG electrodes are arranged evenly on the sphere. For any EEG electrode, its positional relationship with the two adjacent EEG electrodes is known. Suppose the coordinates of EEG electrode a in the spherical coordinate system are , and the coordinates of the two adjacent EEG electrodes of EEG electrode a in the spherical coordinates are respectively and , then , and the coordinates of EEG electrode a in the spherical coordinates can be calculated when the coordinates of the two adjacent EEG electrodes of EEG electrode a in the spherical coordinates and μ are known. Wherein, r is the radius of the spherical coordinate, θ is the elevation angle of the spherical coordinate, is the azimuth angle of the spherical coordinate.

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

[0135] S503. Convert the coordinates 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.

[0136] Specifically, by converting the coordinates of each intermediate EEG electrode in the spherical coordinate system to the first coordinate system, the coordinate information of the intermediate EEG electrode in the first coordinate system can be obtained.

[0137] Figure 6 It is a schematic flowchart of the traceability analysis method for EEG signals collected based on a robotic arm provided in the sixth embodiment of the present invention. As Figure 6 shown, on the basis of the above embodiments, further, the 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. 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;

[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] By calibrating the first coordinate information of the preset EEG electrode in the second coordinate system based on the calibration matrix, the second coordinate information of the preset EEG electrode in the second coordinate system can be obtained. By calibrating the first coordinate information of each intermediate EEG electrode in the second coordinate system based on the calibration matrix, the second coordinate information of each intermediate EEG electrode in the second coordinate system can be obtained.

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

[0142] Specifically, convert the first coordinate information of the preset EEG electrodes in the second coordinate system to the spherical coordinate system to obtain the coordinates of the preset EEG electrodes in the spherical coordinate system; based on the coordinates of the preset EEG electrodes in the spherical coordinate system, obtain the coordinate information of each intermediate EEG electrode in the spherical coordinate system; convert the coordinate information of each intermediate EEG electrode in the spherical coordinate system 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, and will not be elaborated here.

[0143] S603. 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.

[0144] Specifically, for each intermediate EEG electrode, perform weighted calculation on 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, and the fourth coordinate information of the intermediate EEG electrode in the second coordinate system can be obtained. The fourth coordinate information of each intermediate EEG electrode in the second coordinate system is used for traceability analysis. Among them, the weights corresponding to the third coordinate information of the intermediate EEG electrode in the second coordinate system and the weights corresponding to the second coordinate information of the intermediate EEG electrode in the second coordinate system are set according to actual experience, and are not limited in the embodiments of the present invention.

[0145] The coordinate information of each intermediate EEG electrode in the first coordinate system is calculated by coordinate interpolation, and there is an error from 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 from the actual coordinates of each intermediate EEG electrode in the second coordinate system. By performing weighted calculation on 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 It is a schematic structural diagram of a traceability analysis device for EEG signals collected by a robotic arm provided in the seventh embodiment of the present invention, as Figure 7As shown in the figure, the traceability analysis device for electroencephalogram (EEG) signals collected by a robotic arm according to 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 traceability analysis module 705, where:

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

[0148] Specifically, the first acquisition module 701 can acquire the coordinate information of EEG electrodes in the first coordinate system. The number of EEG electrodes is multiple, and the specific number of EEG electrodes is set according to actual needs, which is not limited in the embodiments of the present invention. For EEG electrodes placed on the scalp of a subject, the spatial position data of the EEG electrodes can be acquired by a camera, and the first coordinate system is the camera spatial coordinate system; for intracranial electrodes, the spatial position data of the EEG electrodes can be determined using CT images, 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. Where 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 subject's nuclear magnetic resonance (NMR) image coordinate system.

[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 a calibration matrix to obtain the second coordinate information of each EEG electrode in the second coordinate system. Where the calibration matrix is obtained in advance.

[0151] In order to improve the stability during the acquisition of electroencephalogram (EEG) signals, a robotic arm can be used to carry a transcranial magnetic stimulation (TMS) coil and move it along a preset planned path to stimulate a preset target point on the brain of a subject. The signal acquisition module 704 can acquire EEG signals through each EEG electrode. The preset planned path is set according to actual needs and is not limited in the embodiments of the present invention.

[0152] After the traceability analysis module 705 obtains the second coordinate information of each of the above-mentioned EEG electrodes in the second coordinate system and acquires the EEG signals of the subject, it can perform traceability analysis based on the second coordinate information of each EEG electrode in the second coordinate system and the EEG signals. Among them, the specific process of traceability analysis is prior art and will not be elaborated here.

[0153] The traceability analysis device for EEG signals collected based on a robotic arm provided by the embodiments of the present invention acquires the coordinate information of EEG electrodes in the first coordinate system; obtains the first coordinate information of the EEG electrodes in the second coordinate system according to the coordinate information of the EEG electrodes in the first coordinate system and the coordinate transformation relationship between the first coordinate system and the second coordinate system, where 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 electrodes in the second coordinate system according to a calibration matrix to obtain the second coordinate information of the EEG electrodes in the second coordinate system, where the calibration matrix is obtained in advance; acquires EEG signals through the EEG electrodes, where the EEG signals are collected by moving a stimulation device carried by a robotic arm along a preset planned path to stimulate a preset target point on the brain of a subject; the preset planned path is planned based on the second coordinate information of the EEG electrodes in the second coordinate system; performs traceability analysis according to the second coordinate information of the EEG electrodes in the second coordinate system and the EEG signals. Since it can record the position of the EEG electrodes corresponding to the individual brain regions of the subject more accurately and collect EEG signals more accurately, the accuracy of traceability analysis is improved.

[0154] Figure 8 is a schematic structural diagram of the traceability analysis device for EEG signals collected based on a robotic arm provided by the eighth embodiment of the present invention. As Figure 8 shown, on the basis of the above embodiments, further, the traceability analysis device for EEG signals collected based on a robotic arm provided by the embodiments of the present invention further includes a second acquisition module 706, a third acquisition module 707, and a establishment module 708, where:

[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] Figure 9 It is a schematic structural diagram of a traceability analysis device for electroencephalogram signals collected by a robotic arm provided in the ninth embodiment of the present invention. As Figure 9 shown, on the basis of the above embodiments, further, the traceability analysis device for electroencephalogram signals collected by a robotic arm provided in the embodiments of the present invention further includes a fourth acquisition module 709, a fifth acquisition module 710, and an acquisition module 711, where:

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

[0158] Figure 10 It is a schematic structural diagram of a traceability analysis device for electroencephalogram signals collected by a robotic arm provided in the tenth embodiment of the present invention. As Figure 10 shown, on the basis of the above embodiments, further, the first acquisition module 701 includes an acquisition unit 7011 and a coordinate interpolation unit 7012, where:

[0159] The acquisition unit 7011 is configured to acquire coordinate information of a preset electroencephalogram electrode in a first coordinate system; wherein, the preset electroencephalogram electrode is an electroencephalogram electrode selected in a preset order; the coordinate interpolation unit 7012 is configured to perform coordinate interpolation according to the coordinate information of the preset electroencephalogram electrode in the first coordinate system to obtain coordinate information of each intermediate electroencephalogram electrode in the first coordinate system; wherein, each intermediate electroencephalogram electrode is an electroencephalogram electrode other than the preset electroencephalogram electrode among the electroencephalogram electrodes.

[0160] Figure 11 It is a schematic structural diagram of a traceability analysis device for electroencephalogram signals collected by a robotic arm provided in the eleventh embodiment of the present invention. As Figure 11 shown, on the basis of the above embodiments, further, the coordinate interpolation unit 7012 includes a first conversion subunit 70121, an acquisition subunit 70122, and a second conversion subunit 70123, where:

[0161] The first conversion subunit 70121 is configured to convert the coordinate information of a preset EEG electrode in the first coordinate system to the spherical coordinate system, so as to obtain the coordinates of the preset EEG electrode in the spherical coordinate system; the obtaining subunit 70122 is configured 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 configured to convert the coordinate information of each intermediate EEG electrode in the spherical coordinate system to the first coordinate system, so as to obtain the coordinate information of each intermediate EEG electrode in the first coordinate system.

[0162] Figure 12 FIG. 4 is a schematic structural diagram of a brain electrical signal traceability analysis device based on robotic arm acquisition provided by the twelfth embodiment of the present invention. As Figure 12 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, where:

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

[0164] The embodiments of the device provided by the embodiments of the present invention can specifically be used to execute the processing procedures of the above method embodiments, and their functions will not be elaborated herein. For details, reference can be made to the detailed descriptions of the above method embodiments.

[0165] Figure 13 FIG. 5 is a schematic structural diagram of a brain electrical signal traceability analysis system based on robotic arm acquisition provided by the thirteenth embodiment of the present invention. As Figure 13 shown, the brain electrical signal traceability analysis system based on robotic arm acquisition provided by the embodiments of the present invention includes the brain electrical signal traceability analysis device 1301, 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, where:

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

[0167] The plurality of electroencephalogram electrodes 1305 are deployed on the brain of the subject; the robot 1303 is used to carry the stimulation device 1304 to stimulate the target point on the brain of the subject; the navigation device 1306 is used to collect the spatial position data of the electroencephalogram electrodes.

[0168] Specifically, the plurality of electroencephalogram electrodes 1305 are arranged on the head of the subject, and the plurality of electroencephalogram electrodes 1305 can be arranged in an electroencephalogram cap to facilitate the wearing of the subject. The robot 1303 includes a control device and a robotic arm, and the control device controls the robotic arm to carry the stimulation device 1304 to stimulate the target point on the brain of the subject; the stimulation device 1304 can adopt a TMS coil. The navigation device 1306 is used to obtain the position information of each electroencephalogram 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 electroencephalogram signals of the subject. The navigation device 1306 can adopt devices including an infrared camera, a color camera, a structured light camera, etc.

[0169] Figure 14 It is a schematic physical structure diagram of a computer device provided by the fourteenth embodiment of the present invention. As Figure 14 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 can call the logical instructions in the memory 140 to execute the methods provided by the above method embodiments, for example, including: obtaining the coordinate information of each electroencephalogram electrode in a first coordinate system; obtaining the first coordinate information of each electroencephalogram electrode in a second coordinate system according to the coordinate information of each electroencephalogram 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 electroencephalogram electrode in the second coordinate system according to a calibration matrix to obtain the second coordinate information of each electroencephalogram electrode in the second coordinate system; wherein, the calibration matrix is obtained in advance; collecting electroencephalogram signals through each electroencephalogram electrode; wherein, the electroencephalogram signals are collected by carrying a stimulation device by a robotic arm to move along a preset planned path to stimulate a preset target point on the brain of the subject; the preset planned path is planned based on the second coordinate information of each electroencephalogram electrode in the second coordinate system; performing source analysis according to the second coordinate information of each electroencephalogram electrode in the second coordinate system and the electroencephalogram signals.

[0170] This embodiment discloses a computer program product, which includes computer programs / instructions stored on a computer-readable storage medium. When the computer programs / instructions are executed by a computer, the computer can execute the methods provided in the above 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, where 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, where the calibration matrix is obtained in advance; collecting EEG signals through each EEG electrode, where the EEG signals are collected by stimulating a preset target point in the brain of the subject by moving a stimulation device carried by a robotic arm along a preset planned path, and the preset planned path is planned based on the second coordinate information of each EEG electrode in the second coordinate system; performing source analysis according to the second coordinate information of each EEG electrode in the second coordinate system and the EEG signals.

[0171] This embodiment provides a computer-readable storage medium that stores computer programs / instructions. When the computer programs / instructions are executed by a processor, the computer is enabled to execute the methods provided in the above 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, where 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, where the calibration matrix is obtained in advance; collecting EEG signals through each EEG electrode, where the EEG signals are collected by stimulating a preset target point in the brain of the subject by moving a stimulation device carried by a robotic arm along a preset planned path, and the preset planned path is planned based on the second coordinate information of each EEG electrode in the second coordinate system; performing source analysis according to the second coordinate information of each EEG electrode in the second coordinate system and the EEG signals.

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

[0173] As Figure 14 shown, the processor 100 is sometimes also referred to as a controller or 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 the various components of the computer device 600.

[0174] Among them, the memory 140 may be, for example, one or more of a buffer, a flash memory, a hard drive, a removable medium, a volatile memory, a non-volatile memory, or other suitable devices. The above information related to failures can be stored, and in addition, programs for executing relevant information can also be stored. And the processor 100 can execute the program stored in the memory 140 to achieve information storage or processing, etc.

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

[0176] The memory 140 may be a solid-state memory, for example, a read-only memory (ROM), a random access memory (RAM), a SIM card, etc. It may also be such a memory that stores information even when powered off, can be selectively erased and has more data. 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, and the application / function storage unit 142 is used to store application programs and function programs or the processes for operating the computer device 600 through the processor 100.

[0177] The memory 140 may further include a data storage unit 143, and the data storage unit 143 is used to store 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 of the computer device for communication functions and / or for performing other functions of the computer device (such as a messaging application, an address book application, etc.).

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

[0179] Based on different communication technologies, in the same computer device, multiple communication modules 110 can be provided, such as a cellular network module, a Bluetooth module, and / or a wireless local area network module, etc. The communication module 110 is also coupled to the speaker 131 and the microphone 132 via the audio processor 130 to provide an audio output via the speaker 131 and receive an audio input from the microphone 132, thereby implementing normal telecommunication functions. The audio processor 130 can include any suitable buffers, decoders, amplifiers, etc. Additionally, 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] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can 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.) that contain computer-usable program code.

[0181] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0182] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0183] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, so that a series of operation steps are performed on the computer or other programmable apparatus to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 or steps of functions specified in multiple blocks.

[0184] In the description of this specification, descriptions with reference to the terms "one embodiment", "a specific embodiment", "some embodiments", "for example", "example", "specific example", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do 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 elaborate on the objectives, technical solutions, and beneficial effects of the present invention. It should be understood that the above description is only for the specific embodiments of the present invention and is not used to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the protection scope 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 planning path; the preset planning path is planned based on the second coordinate information of each EEG electrode in the second coordinate system; Performing source tracing analysis based on the second coordinate information of each EEG electrode in the second coordinate system and the EEG signal; 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.

2. 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.

3. 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.

4. The method according to claim 3, 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.

5. The method according to claim 3, 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.

6. A device for tracing and analyzing EEG signals collected by a robotic 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; A source tracing analysis module, used for performing source tracing analysis based on the second coordinate information of each EEG electrode in the second coordinate system and the EEG signal; 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.

7. The device according to claim 6, 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.

8. The device according to claim 6, 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.

9. The device according to claim 8, 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.

10. The device according to claim 8, 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.

11. 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, a computer, a robot, a stimulation device, a plurality of EEG electrodes and a navigation device according to any one of claims 6 to 10, 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.

12. 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 5.

13. 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 5 is implemented.

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