Track type nerve regulation and control positioning navigation system and method

Abstract

The invention discloses a track type nerve regulation and control positioning navigation system and method, and particularly relates to the field of medical equipment, and the track type nerve regulation and control positioning navigation system comprises a treatment chair, a track, a mechanical arm, a coil adapter, a transcranial magnetic coil, an upper computer support, an upper computer, an optical locator support and an optical locator; the transcranial magnetic coil is fixedly installed on the coil adapter, the coil adapter is fixedly installed on the mechanical arm, the track is fixedly installed on the treatment chair, the mechanical arm is installed on the track in a sliding mode, the upper computer is fixedly installed on the upper computer support, and the optical locator is fixedly installed on the optical locator support. Whole-brain multi-target automatic and high-precision nerve regulation and control treatment is realized, the treatment effect and the positioning accuracy are greatly improved, the working intensity of doctors is reduced, and personal errors and off-target risks are avoided.

Description

Technical Field

[0001] This invention relates to the field of medical devices, and more specifically, to a track-type neural modulation positioning and navigation system and method. Background Technology

[0002] With the development of technology, a non-invasive neuromodulation technique—transcranial magnetic stimulation (TMS)—has gained increasing recognition in the clinical neuropsychiatric disorders and rehabilitation fields. It is non-invasive and painless, and can also be used to treat some neurological diseases. The basic principle of TMS is to use a rapidly changing magnetic field to generate an electric field to stimulate human neurons. Short current pulses generated in a specially designed transcranial magnetic coil create a magnetic field above the stimulation target. The induced magnetic field passes through the skull into the body and induces an electric field, which in turn stimulates neurons and triggers brain activity.

[0003] In the current field of medical equipment, the operation of transcranial magnetic stimulation (TMS) therapy devices is mostly based on a method described in CN201980001087.5, which uses a TMS coil combined with a navigation system to stimulate specific brain regions. This method cannot cover the entire brain and therefore cannot achieve the desired therapeutic effect. When stimulating multiple brain regions, methods such as CN202021057415.X, which uses TMS to treat post-stroke motor disorders, involve using a TMS positioning cap and manually controlling the TMS coil through manual operation or a support to fix it in place. Manual operation is inconvenient, requiring prolonged holding of the coil or fixation at a specific angle using a support. This results in a poor patient experience, is prone to missing the target, and necessitates repositioning. Manual positioning is also cumbersome and imprecise, significantly reducing the therapeutic effect and limiting its application in multi-brain region treatment due to the difficulty in achieving target coverage across the entire brain.

[0004] To address the aforementioned problems, a technical solution is provided. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide a track-based neural modulation positioning and navigation system and method to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A track-type neuromodulation positioning and navigation system includes: a treatment chair, a track, a robotic arm, a coil adapter, a transcranial magnetic coil, a host computer support, a host computer, an optical positioning device support, and an optical positioning device;

[0008] The transcranial magnetic coil is fixedly mounted on the coil adapter, the coil adapter is fixedly mounted on the robotic arm, the track is fixedly mounted on the treatment chair, the robotic arm is slidably mounted on the track, the host computer is fixedly mounted on the host computer bracket, and the optical positioning device is fixedly mounted on the optical positioning device bracket.

[0009] A track-based neural modulation positioning and navigation method for implementing the aforementioned track-based neural modulation positioning and navigation system includes the following steps:

[0010] Step S1: The coil adapter has a tracking marker that can be recognized by the optical locator. There is also a tracking marker attached to the patient's head and a tracking marker on the handheld probe. The position of the tracking marker in the optical locator space is obtained by the optical locator.

[0011] Step S2: The host computer collects the pose information of the tracking marker of the coil adapter in the robotic arm space, as well as the pose information of the tracking marker and the patient's facial feature points identified by the optical locator in the optical locator space, and obtains the spatial transformation matrix between the patient space and the robotic arm space.

[0012] Step S3: Using the spatial transformation matrix between the patient space and the robotic arm space, multiple target points planned on the patient's medical data are transformed into the robotic arm space. In the host computer, based on the transformation matrix between the patient space and the robotic arm space, the 3D models of the equipment and the patient are placed in the correct positions in the simulation environment. The robotic arm's running path is simulated to ensure that the robotic arm does not collide during its movement to the target point.

[0013] In a preferred embodiment, in step S1, the host computer reads the patient's medical image data and performs preprocessing. Based on the patient's treatment needs, multiple treatment target points are planned on the two-dimensional medical images and the three-dimensional model, and multiple facial feature point information of the patient is obtained from the patient's three-dimensional model data.

[0014] In a preferred embodiment, the patient's medical imaging data includes two-dimensional medical imaging data and three-dimensional model data. The two-dimensional medical imaging data is presented in the axial, coronal, and sagittal planes of the medical images in the host computer, and the three-dimensional model data is obtained by three-dimensional reconstruction of the two-dimensional medical imaging data.

[0015] The coordinates of facial feature points within the patient's spatial area are collected and picked up from the patient's two-dimensional medical image data and three-dimensional model data.

[0016] In a preferred embodiment, in step S2, the spatial transformation relationship between the patient space and the optical positioning device space is obtained, and the spatial transformation relationship between the robotic arm space and the optical positioning device space is obtained. The spatial transformation relationship between the patient space and the optical positioning device space is called patient space registration, and the spatial transformation relationship between the robotic arm space and the optical positioning device space is called robotic arm space registration.

[0017] Based on the results of patient space registration and robotic arm space registration, the transformation matrix between patient space and robotic arm space is calculated.

[0018] In a preferred embodiment, during patient space registration, a handheld probe is used. Within the field of view of the optical locator, the tip of the handheld probe is placed at the patient's facial feature points, requiring at least 4 points, and at least 4 points are not coplanar. The coordinates of the tip of the handheld probe in the optical locator space are collected, and the coordinates of the patient's facial feature points in the optical locator space are obtained. The coordinates of the corresponding facial feature points in the patient space and the optical locator space are registered using the SVD algorithm, and finally the spatial transformation relationship between the patient space and the optical locator space is obtained.

[0019] In a preferred embodiment, during the robotic arm space registration, the robotic arm is dragged to place the tracking marker of the coil adapter within the field of view of the optical locator. Simultaneously, the poses of the marker of the coil adapter in the optical locator space and the robotic arm space are acquired. The poses of the marker in the optical locator space and the robotic arm space are spatially registered to obtain the transformation relationship between the robotic arm space and the optical locator space.

[0020] In a preferred embodiment, in step S3, the host computer controls the robotic arm to move to the target pose. If it is found during the simulation that the target point is not within the working range of the robotic arm, the robotic arm is manually or automatically controlled to move along the track so that the target point is within the working range of the robotic arm.

[0021] The technical effects and advantages of the track-type neural modulation positioning and navigation system and method of the present invention are as follows:

[0022] 1. By using an optical locator as a medium, a spatial mapping is established between the optical locator space, the patient space, and the robotic arm. The patient's medical data is preprocessed in the host computer to determine multiple treatment target points. The robotic arm positioning process is simulated in a simulation environment to ensure that the movement path of the robotic arm will not collide. Then, the robotic arm is moved along the track to ensure that the target point is within the working range of the robotic arm. The robotic arm is controlled to move its end point to the target point on the patient's head through the transcranial magnetic coil installed through the coil adapter for treatment.

[0023] 2. During the treatment, the patient's head movement is monitored in real time by an optical locator. The spatial transformation relationship is fed back to the robotic arm for motion compensation to prevent off-target. The system uses a robotic arm combined with a track for navigation and positioning, which can perform multi-target and multi-brain region treatment, improve the treatment effect, reduce the workload of doctors, reduce positioning errors caused by human factors, and make transcranial magnetic coil positioning more accurate. Attached Figure Description

[0024] Figure 1 This is a schematic diagram of the structure of a track-type neural modulation positioning and navigation system according to the present invention.

[0025] Figure 2 This is a schematic flowchart of a track-based neural modulation positioning and navigation method according to the present invention.

[0026] In the diagram, 1. Treatment chair; 2. Track; 3. Robotic arm; 4. Coil adapter; 5. Transcranial magnetic coil; 6. Upper computer support; 7. Upper computer; 8. Optical positioning device support; 9. Optical positioning device. Detailed Implementation

[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0028] Example 1

[0029] Figure 1 The present invention provides a track-type neuromodulation positioning and navigation system, comprising: a treatment chair 1, a track 2, a robotic arm 3, a coil adapter 4, a transcranial magnetic coil 5, a host computer support 6, a host computer 7, an optical positioning device support 8, and an optical positioning device 9;

[0030] The transcranial magnetic coil 5 is fixedly mounted on the coil adapter 4, the coil adapter 4 is fixedly mounted on the robotic arm 3, the track 2 is fixedly mounted on the treatment chair 1, the robotic arm 3 is slidably mounted on the track 2, the host computer 7 is fixedly mounted on the host computer bracket 6, and the optical positioning device 9 is fixedly mounted on the optical positioning device bracket 8.

[0031] It should be noted that the present invention integrates the robotic arm 3 directly onto the treatment chair 1 to form an integrated structure, which not only makes the equipment layout more compact, but also helps to ensure the stability of the relative position between the robotic arm 3 and the patient's head, thereby improving the positioning accuracy of the transcranial magnetic coil 5 and the reliability of the treatment process.

[0032] The robotic arm 3 is mounted on the track 2 and can move or lock along the track 2. After moving along the track 2, the working range of the robotic arm 3 can cover the entire brain. The track 2 is a guide rail structure. The bottom of the robotic arm 3 is fixedly installed with a sliding block that is adapted to the track 2. The sliding block is embedded in the guide rail groove of the track 2 to realize the sliding of the robotic arm 3 along the track 2. At the same time, the sliding block integrates an electromagnetic lock. When it is necessary to move the robotic arm 3, the power supply of the electromagnetic lock is turned off, and the sliding block can slide freely along the track 2. When the robotic arm 3 moves to the target position, the power supply of the electromagnetic lock is turned on, and the position of the robotic arm 3 on the track 2 is locked by electromagnetic attraction. In addition, the sliding block can also be replaced with an electric slider, which is electrically connected to the host computer 7, and the movement control of the robotic arm 3 is performed by the host computer 7.

[0033] Figure 2 This invention provides a track-based neural modulation positioning and navigation method for implementing the aforementioned track-based neural modulation positioning and navigation system, characterized by comprising the following steps:

[0034] Step S1: The coil adapter 4 has a tracking marker that can be recognized by the optical locator 9. There is also a tracking marker attached to the patient's head and a tracking marker on the handheld probe. The position and pose of the tracking marker in the space of the optical locator 9 are obtained by the optical locator 9.

[0035] Step S2: The host computer 7 collects the pose information of the tracking marker of the coil adapter 4 in the space of the robotic arm 3, as well as the pose information of the tracking marker and the patient's facial feature points identified by the optical locator 9 in the space of the optical locator 9, and obtains the spatial transformation matrix between the patient space and the robotic arm space.

[0036] Step S3: Using the spatial transformation matrix between the patient space and the robotic arm space, multiple target points planned on the patient's medical data are transformed into the robotic arm space. In the host computer 7, based on the transformation matrix between the patient space and the robotic arm space, the 3D models of the equipment and the patient are placed in the correct positions in the simulation environment. The running path of the robotic arm 3 is simulated to ensure that the robotic arm 3 will not collide during its movement to the target point.

[0037] In step S1, the host computer 7 reads the patient's medical image data and performs preprocessing. Based on the patient's treatment needs, it plans multiple treatment target points on the two-dimensional medical images and the three-dimensional model, and obtains multiple facial feature point information of the patient on the patient's three-dimensional model data.

[0038] Patient medical imaging data includes two-dimensional medical imaging data and three-dimensional model data. The two-dimensional medical imaging data is CT, MRI or standard atlas data in formats such as nii, nii.gz, dcm, dicom, etc. The two-dimensional medical imaging data is presented in the axial, coronal and sagittal planes of the medical images in the host computer 7. The three-dimensional model data is obtained by three-dimensional reconstruction of the two-dimensional medical imaging data.

[0039] Planning multiple treatment targets is done by doctors based on the patient's two-dimensional medical imaging data and three-dimensional model data. Multiple treatment targets can be planned on the data of the cerebral cortex and then mapped onto the scalp, or targets can be planned directly on the scalp data.

[0040] The coordinates of facial feature points within the patient's spatial area are collected and picked up from the patient's two-dimensional medical image data and three-dimensional model data.

[0041] In step S2, the spatial transformation relationship between the patient space and the optical positioning device space is obtained, and the spatial transformation relationship between the robotic arm space and the optical positioning device space is obtained. The spatial transformation relationship between the patient space and the optical positioning device space is called patient space registration, and the spatial transformation relationship between the robotic arm space and the optical positioning device space is called robotic arm space registration.

[0042] Based on the results of patient space registration and robotic arm space registration, the transformation matrix between patient space and robotic arm space is calculated.

[0043] In patient space registration, there are two methods to obtain the coordinates of the patient's facial feature points under the optical locator. One method uses a handheld probe, placing the tip of the handheld probe at the patient's facial feature point within the field of view of the optical locator 9. The number of points must be ≥4, and at least 4 points must not be coplanar. The coordinates of the tip of the handheld probe under the optical locator space are collected, thus obtaining the coordinates of the patient's facial feature points under the optical locator 9. By collecting the coordinates of facial feature points in the patient space as described above, they can be picked from the patient's two-dimensional medical image data and three-dimensional model data. The coordinates of the facial feature points under the patient space can be obtained. The coordinates of the corresponding facial feature points under the patient space and the optical locator space are registered using the SVD algorithm, and finally the spatial transformation relationship between the patient space and the optical locator space is obtained.

[0044] Obtain the coordinates of the same set of facial feature points in two spaces: Select at least four non-coplanar facial feature points from the patient space of the patient's CT / MRI images and record their positions; Use a handheld probe to contact these feature points on the patient's actual face and record the positions of these points in the instrument space using an optical locator; Ensure that the two sets of coordinates correspond one-to-one.

[0045] The core of the SVD algorithm is to calculate the combination of rotations and translations so that corresponding points in two spaces can be aligned. The steps are:

[0046] Calculate the average position, i.e. the centroid, of the two sets of feature points in their respective spaces;

[0047] Subtract the center point of your own space from the coordinates of each point, and keep only the relative position;

[0048] Calculate the correlation between the relative positions of the two batches of points to obtain a covariance matrix;

[0049] Performing SVD decomposition on this matrix yields two orthogonal matrices;

[0050] Using the decomposed matrix, calculate the rotation that will align the two spaces;

[0051] Based on the previous center point, calculate the translation distance between the two spatial center points.

[0052] By following the steps above, any point in the patient space can be rotated according to the calculated rotation method and then moved according to the translation distance to correspond to the position in the optical positioning instrument space. This rotation and translation rule is the transformation relationship between the two spaces, which can be used to realize the coordinate mapping between the two spaces later.

[0053] In the robotic arm space registration, the robotic arm 3 is dragged to place the tracking marker of the coil adapter 4 within the field of view of the optical locator 9. At the same time, the poses of the marker of the coil adapter 4 in the optical locator space and the robotic arm space are collected. The poses of the marker in the optical locator space and the robotic arm space are spatially registered to obtain the transformation relationship between the robotic arm space and the optical locator space.

[0054] The host computer 7 preprocesses the patient's medical data, plans multiple treatment targets, and establishes the spatial transformation relationship between the optical positioning instrument space, the patient space, and the robotic arm space. The host computer 7 then transfers the multiple treatment targets planned in the patient space to the robotic arm space and simulates the robotic arm positioning process in a simulation environment to ensure that the robotic arm's movement path does not collide.

[0055] In step S3, the host computer 7 controls the robotic arm 3 to move to the target pose. If the target point is found to be outside the working range of the robotic arm 7 during the simulation, the robotic arm 7 is manually or automatically controlled to move along the track 2 so that the target point is within the working range of the robotic arm 7.

[0056] During the positioning process of the robotic arm 3 and during the patient treatment process, the pose of the tracking and positioning marker attached to the patient's head is acquired in real time by the optical positioning instrument 9. Based on the information collected by the optical positioning instrument 9, the host computer 7 can calculate the real-time pose of the current patient's spatial coordinate system in the optical positioning instrument space. According to the spatial transformation relationship, the real-time target pose of the robotic arm 3 can be obtained, thereby controlling the robotic arm 3 to perform motion compensation, which can avoid the coil from falling off the target due to the shaking of the patient's head.

[0057] Working principle:

[0058] The host computer 7 reads the patient's CT, MRI, and other two-dimensional medical image data. After preprocessing, it generates a three-dimensional model of the patient's head using a three-dimensional reconstruction algorithm. It simultaneously presents two-dimensional images and a three-dimensional model in axial, coronal, and sagittal planes, providing an intuitive reference for diagnosis and treatment. Based on treatment needs, doctors can plan multiple treatment targets in the target brain region of the three-dimensional model or two-dimensional image. Cortical targets can be mapped to corresponding locations on the scalp, or targets can be directly selected on the scalp model. Simultaneously, at least four non-coplanar facial feature points are picked from the three-dimensional model, and their coordinates in the patient's spatial coordinate system based on the medical images are recorded.

[0059] Using the optical locator 9 as the core medium, precise registration of three coordinate systems—patient space, robotic arm space, and optical locator space—is achieved to obtain the spatial transformation matrix. A tracking marker is attached to the patient's head, and a handheld probe with the tracking marker is placed within the field of view of the optical locator 9. The operator uses the probe to sequentially touch the patient's facial feature points, and the optical locator 9 collects the coordinates of these feature points in its space in real time. The host computer 7 calls the SVD algorithm to perform registration calculations on the two sets of coordinates of the feature points in the patient space and the optical locator space, solving for the rotation matrix and translation vector to obtain the transformation relationship between the two. The robotic arm 3 is dragged to move the tracking marker on the coil adapter 4 into the field of view of the optical locator 9. The host computer 7 simultaneously collects the pose data of the marker in the robotic arm space (based on the base of the robotic arm 3) and the pose data of the same marker in its own space collected by the optical locator 9. Spatial registration is performed on the two sets of data to obtain the transformation relationship between the robotic arm space and the optical locator space. Based on the above two sets of transformation relationships, the host computer 7 derives the transformation matrix between the patient space and the robotic arm space through coordinate transformation formulas, thereby achieving precise mapping of the three coordinate systems.

[0060] The host computer 7 uses a transformation matrix between patient space and robotic arm space to convert all pre-planned treatment target points from patient space coordinates to robotic arm space coordinates, clarifying the precise position of each target point in the recognizable coordinate system of robotic arm 3. Subsequently, a three-dimensional simulation environment is constructed, including treatment chair 1, track 2, robotic arm 3, and patient head. The equipment and patient 3D models are placed according to the transformation matrix. The motion path of robotic arm 3 from its initial position to each target point is planned and simulated based on the target point coordinates, with real-time detection of collision risks. If a target point is found to be outside the working range of robotic arm 3, the host computer 7 automatically controls the electric slider at the bottom of robotic arm 3 to slide along track 2, or prompts the operator to manually move and lock robotic arm 3 until all target points fall within the working range, ensuring treatment without blind spots.

[0061] After successful simulation verification, the host computer 7 sends control commands, and the robotic arm 3 moves along the planned path, driving the coil adapter 4 and transcranial magnetic coil 5 to move sequentially to the precise poses of each target point, ensuring that the relative positions of the transcranial magnetic coil 5 and the target point meet the treatment requirements. During treatment, the optical locator 9 continuously monitors the patient's head tracking markers, acquiring real-time changes in the head's pose in the optical locator space. If the patient's head moves, the host computer 7 quickly calculates the coordinate offset of the target point in the robotic arm space based on the spatial transformation matrix and sends compensation commands to the robotic arm 3. The robotic arm 3 adjusts its end-effector pose in real time to ensure that the transcranial magnetic coil 5 is always aligned with the target point, avoiding target misses. For contralateral brain region target points that cannot be covered by the unilateral track 2, the robotic arm 3 is controlled to slide along track 2 and relock, expanding the working range. Combined with the multi-degree-of-freedom movement of the robotic arm 3, precise stimulation of any target point in the whole brain can be achieved. After treatment, the host computer 7 controls the robotic arm 3 to sequentially detach from each target point and return to the initial position along the planned path, while simultaneously controlling the robotic arm 3 to slide along track 2 to the preset storage position.

[0062] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0063] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0064] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0065] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing embodiments, and will not be repeated here.

[0066] In the several embodiments provided in this application, it should be understood that the disclosed systems and devices can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between devices or units, and may be electrical, mechanical, or other forms.

[0067] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0068] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0069] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0070] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0071] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A track-based neural modulation positioning and navigation system, characterized in that, include: Treatment chair (1), track (2), robotic arm (3), coil adapter (4), transcranial magnetic coil (5), host computer support (6), host computer (7), optical positioning device support (8) and optical positioning device (9); The transcranial magnetic coil (5) is fixedly mounted on the coil adapter (4), the coil adapter (4) is fixedly mounted on the robotic arm (3), the track (2) is fixedly mounted on the treatment chair (1), the robotic arm (3) is slidably mounted on the track (2), the host computer (7) is fixedly mounted on the host computer bracket (6), and the optical positioning device (9) is fixedly mounted on the optical positioning device bracket (8).

2. A track-based neural modulation positioning and navigation method for implementing the track-based neural modulation positioning and navigation system of claim 1, characterized in that, Includes the following steps: Step S1: The coil adapter (4) has a tracking marker that can be recognized by the optical locator (9), as well as a tracking marker attached to the patient's head and a tracking marker on the handheld probe. The position of the tracking marker in the space of the optical locator (9) is obtained by the optical locator (9). Step S2: The host computer (7) collects the pose information of the tracking marker of the coil adapter (4) in the space of the robotic arm (3), and the pose information of the tracking marker and the patient's facial feature points identified by the optical locator (9) in the space of the optical locator (9), and obtains the spatial transformation matrix between the patient space and the robotic arm space. Step S3: Using the spatial transformation matrix between the patient space and the robotic arm space, multiple target points planned on the patient's medical data are transformed into the robotic arm space. In the host computer (7), based on the transformation matrix between the patient space and the robotic arm space, the three-dimensional models of the equipment and the patient are placed in the correct positions in the simulation environment. The running path of the robotic arm (3) is simulated to ensure that the robotic arm (3) will not collide during its movement to the target point.

3. The orbital neural modulation positioning and navigation method according to claim 2, characterized in that: In step S1, the host computer (7) reads the patient's medical image data and performs preprocessing. Based on the patient's treatment needs, it plans multiple treatment target points on the two-dimensional medical image and the three-dimensional model, and obtains multiple facial feature point information of the patient on the patient's three-dimensional model data.

4. The orbital neural modulation positioning and navigation system according to claim 3, characterized in that: The patient's medical imaging data includes two-dimensional medical imaging data and three-dimensional model data. The two-dimensional medical imaging data is presented in the axial plane, coronal plane and sagittal plane of the medical image in the host computer (7). The three-dimensional model data is obtained by three-dimensional reconstruction of the two-dimensional medical imaging data. The coordinates of facial feature points within the patient's spatial area are collected and picked up from the patient's two-dimensional medical image data and three-dimensional model data.

5. The orbital neural modulation positioning and navigation system according to claim 4, characterized in that: In step S2, the spatial transformation relationship between the patient space and the optical positioning device space is obtained, and the spatial transformation relationship between the robotic arm space and the optical positioning device space is obtained. The spatial transformation relationship between the patient space and the optical positioning device space is called patient space registration, and the spatial transformation relationship between the robotic arm space and the optical positioning device space is called robotic arm space registration. Based on the results of patient space registration and robotic arm space registration, the transformation matrix between patient space and robotic arm space is calculated.

6. The orbital neural modulation positioning and navigation system according to claim 5, characterized in that: In patient space registration, a handheld probe is used. Within the field of view of the optical locator (9), the tip of the handheld probe is placed at the facial feature point of the patient. The number of points is required to be ≥4, and at least 4 points are not coplanar. The coordinates of the tip of the handheld probe in the optical locator space are collected, and the coordinates of the facial feature point of the patient in the optical locator (9) are obtained. The coordinates of the corresponding facial feature points in the patient space and the optical locator space are registered using the SVD algorithm, and finally the spatial transformation relationship between the patient space and the optical locator space is obtained.

7. The orbital neural modulation positioning and navigation system according to claim 6, characterized in that: In the robotic arm space registration, the robotic arm (3) is dragged to place the tracking marker of the coil adapter (4) within the field of view of the optical locator (9). At the same time, the poses of the markers of the coil adapter (4) in the optical locator space and the robotic arm space are collected. The poses of the markers in the optical locator space and the robotic arm space are spatially registered to obtain the conversion relationship between the robotic arm space and the optical locator space.

8. The orbital neural modulation positioning and navigation system according to claim 7, characterized in that: In step S3, the host computer (7) controls the robotic arm (3) to move to the target pose. If the target point is found to be outside the working range of the robotic arm (7) during the simulation, the robotic arm (7) is manually or automatically controlled to move along the track (2) so that the target point is within the working range of the robotic arm (7).

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