Brain stimulation device and method including a navigation device for coil position guidance

Abstract

The present invention relates to a navigation device for coil position guidance, a brain stimulation device including the same, and a bio-navigation robot system. The navigation device for coil position guidance according to one embodiment of the present invention may include a 3D camera unit that photographs a user to obtain a 3D camera image; and a position data calculation unit that maps the camera image onto a 3D medical image including brain region information or maps the 3D medical image onto the camera image to obtain a mapped image, and calculates position data of the brain region to be stimulated from the mapped image.

Description

Technical Field

[0001] The present invention relates to a brain stimulation device and method including a coil position guiding navigation device, and more particularly to a navigation device that detects, selects, or guides a coil position using artificial intelligence (AI).

Background Art

[0002] Magnetic stimulation methods such as transcranial magnetic stimulation (TMS) are methods that non-invasively stimulate nerve cells in the brain using magnetic energy. By passing a strong magnetic field near the head through the skull to activate nerve cells, psychiatric treatments such as depression or neurological treatments such as dementia can be performed.

[0003] Conventionally, in order to position a coil that generates a magnetic field at the position of the brain to receive magnetic stimulation, medical personnel such as nurses have to directly position the coil. In this case, since a lot of time is required to accurately position the coil, the treatment efficiency is halved.

[0004] Also, before positioning the coil at the brain to receive magnetic stimulation, medical personnel such as doctors have to display landmarks such as ears and the glabella and the brain region to be actually stimulated on medical images such as MRI images, and manually position the coil on the top of the actual user's head based on the displayed images.

[0005] This requires separate time before receiving treatment, and it is also necessary to spend time searching for the corresponding position immediately before treatment, so it takes double time, and as a result, the treatment time is reduced and the treatment efficiency is lowered.

[0006] Therefore, there is a growing need for a navigation device that detects in real time the brain position where magnetic stimulation is actually received and the position on the top of the head corresponding to the brain position and guides the position of the magnetic stimulation device.

Prior Art Documents

[0007] [Patent Document 1] KR10-2020-0139536 A [Overview of the project] [Problems that the invention aims to solve]

[0008] The present invention aims to solve the aforementioned conventional problems and provides a brain stimulation device and method that includes a coil positioning navigation device capable of mapping an actual user's top-head image with a medical image and automatically guiding the brain's position to be magnetically stimulated and the corresponding top-head position. [Means for solving the problem]

[0009] A coil position guidance navigation device according to one embodiment of the present invention may include: a 3D camera unit that captures a user and acquires a 3D camera image; and a position data calculation unit that maps the camera image to a 3D medical image containing brain region information, or maps the 3D medical image to the camera image and calculates position data of the brain region to be stimulated from the mapped image.

[0010] On the other hand, in another aspect of the present invention, a control method for a navigation device that guides the position of a coil may include the steps of: capturing a user and acquiring a 3D camera image; mapping the camera image to a 3D medical image containing brain region information, or mapping the 3D medical image to the camera image to obtain a mapped image; and calculating positional data of the brain region to be stimulated from the mapped image using the positional data calculation unit.

[0011] According to yet another aspect of the present invention, a computer-readable recording medium can be provided which stores a program for executing a control method for a navigation device that guides the position of a coil on a computer. [Effects of the Invention]

[0012] According to one embodiment of the present invention, medical personnel do not need to manually detect the brain position to be magnetically stimulated and the corresponding upper head position each time before performing magnetic stimulation. This allows all the time and personnel that would have been spent on position calculation to be dedicated to treatment, thereby improving user convenience, increasing accuracy, and improving treatment efficiency.

[0013] Furthermore, because the device can automatically calculate its position, magnetic stimulation can be performed at home rather than in a hospital, thus increasing user convenience. [Brief explanation of the drawing]

[0014] [Figure 1] This diagram shows a flowchart illustrating a control method for a navigation device according to one embodiment of the present invention. [Figure 2] This is a simplified block diagram of a navigation device according to one embodiment of the present invention. [Figure 3] This shows an overall block diagram of a bio-navigation robot system according to one embodiment of the present invention. [Figure 4] This is a flowchart illustrating the operation of a face recognition module according to one embodiment of the present invention. [Figure 5] This is a flowchart showing the operation of a medical image analysis module according to one embodiment of the present invention. [Figure 6] This is a flowchart illustrating the operation of an image mapping module according to one embodiment of the present invention. [Figure 7] This diagram shows a flowchart illustrating how a navigation device according to one embodiment of the present invention guides the position of a robot arm. [Figure 8] The flowchart showing that the MT measurement module according to an embodiment of the present invention measures a motion threshold value is presented. [Figure 9] The overall block diagram regarding the brain stimulation device according to another embodiment of the present invention is shown. [Figure 10] The flowchart showing the operation of the face recognition module according to another embodiment of the present invention is presented. [Figure 11] The flowchart showing that the navigation device according to another embodiment of the present invention guides the position regarding the coil of the helmet-type magnetic stimulation unit is presented. [Figure 12] The block diagram regarding the navigation device according to still another embodiment of the present invention is briefly shown. [Figure 13] The layout diagram of the coil arranged in the helmet-type magnetic stimulation unit according to another embodiment of the present invention is briefly shown. [Figure 14] The structure of the coil in the helmet-type magnetic stimulation unit according to another embodiment of the present invention is shown.

Mode for Carrying Out the Invention

[0015] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. However, the embodiments of the present invention can be modified into several other forms, and the scope of the present invention is not limited to the embodiments described below. The shape, size, etc. of the elements in the drawings may be enlarged, reduced (or emphasized or simplified) for clearer explanation, and the elements denoted by the same reference numerals in the drawings are the same elements.

[0016] Hereinafter, a person who receives magnetic stimulation or a person who controls the magnetic stimulation system to receive magnetic stimulation is defined as a user. Dementia patients, cognitive impairment patients, etc. are examples of users, and users are not limited to patients. Also, the user includes a user who receives magnetic stimulation and a user who uses the device to receive magnetic stimulation, and the user in the following mainly means a user who receives magnetic stimulation.

[0017] Figure 1 is a simplified flowchart illustrating a control method for a navigation device that performs position guidance according to one embodiment of the present invention.

[0018] As shown in Figure 1, the navigation device can perform the following steps: acquire a 3D camera image obtained by real-time facial recognition and a previously stored 3D medical image (S1); generate mesh data using the camera image and display position information points (S2); use AI to display position information points and treatment positions on the medical image and map the position information points of the medical image to the position information points of the camera image (S3); and move the coil 160 to the upper head position corresponding to the treatment position in the mapped image (S4).

[0019] In particular, in the step of moving the coil 160 in S4, once position data of the treatment location is provided to the user, the coil 160 can be moved directly to the position data, or the coil 160 can be automatically moved to the position data by a robotic arm 161 connected to the coil 160, or the coil 160 placed at the position data can be driven via a helmet-type magnetic stimulation unit 162.

[0020] Therefore, a control method for a navigation device that guides the position of a coil 160 according to one embodiment of the present invention may include the steps of: capturing a user with a 3D camera unit 220 to acquire a 3D camera image; mapping the camera image to a 3D medical image including brain region information using a position data calculation unit 231, or mapping the 3D medical image to the camera image to obtain a mapped image; and calculating position data of the brain region to be stimulated from the mapped image using the position data calculation unit 231.

[0021] Specifically, the steps of obtaining the mapped image according to one embodiment of the present invention may include: detecting a positional information point or the top of the head that serves as a reference for positional data of the brain region to be stimulated using the camera image; detecting a mapping point or the top of the head from the face region of the medical image; and mapping the positional information point and the mapping point to obtain the position of the brain region to be stimulated and the top of the head corresponding to the brain region to be stimulated, or mapping the top of the head of each image to map the camera image and the medical image and obtain the mapped image.

[0022] By extracting location information points such as the nose, between the eyebrows, and earlobes, along with the contour lines of the upper head which differ for each user, image mapping can be performed considering specific points and specific shapes.

[0023] Furthermore, the step of calculating the position data of the stimulated brain region according to one embodiment of the present invention may further include the step of correcting a preset zero point in the camera image or medical image based on the mapped image, and generating real-time 3D coordinates in the mapped image based on the corrected zero point, or the step of detecting the position of the motor cortex or the stimulated brain region from the brain region of the medical image and calculating real-time 3D coordinates relating to the position of the motor cortex or the stimulated brain region from the mapped image.

[0024] This is because, in addition to positional data including the coordinates of the brain region to be stimulated, positional data of the motor cortex is calculated to determine the optimal magnetic field strength for the user, and magnetic field stimulation is performed to obtain information regarding the motor threshold (MT).

[0025] The following describes a navigation device that performs the above steps S1 to S3.

[0026] Figure 2 shows a simplified block diagram of a navigation device according to one embodiment of the present invention, and the navigation device for performing the above-described control may include the following configuration.

[0027] According to one embodiment of the present invention, the system may include a 3D camera unit 220 that captures a user and acquires a 3D camera image, and a position data calculation unit 231 that maps the camera image to a 3D medical image containing brain region information, or maps the 3D medical image to the camera image to obtain a mapped image, and calculates position data of the brain region to be stimulated from the mapped image. Preferably, a 3D medical image, which is a fixed image, can be mapped to a 3D camera image whose position changes according to the user's movement.

[0028] The 3D camera unit 220 can capture images of the user, preferably the upper part of the head including the brain region to be stimulated. It can capture the entire face including the upper part of the head, or it can capture only a portion of the upper surface of the head corresponding to the brain region.

[0029] In this case, a user who is photographing the top of their head can wear a hairband or a close-fitting hat so that the top of their head can be clearly recognized. A separate recognition identifier can be attached to the close-fitting band or hat so that it can be easily recognized by the 3D camera unit 220. The recognition identifier can be made using a material or receptor that can be easily recognized by the 3D camera unit 220, and the position of the top of the head or face can be accurately confirmed on the 3D camera image via the recognition identifier.

[0030] Furthermore, as shown in Figure 2, a navigation device for guiding the position of a coil 160 according to one embodiment of the present invention may include a 3D camera unit 220 that captures the upper head corresponding to the brain region being stimulated by the user in real time to acquire a 3D camera image, a 3D medical image storage unit 210 that stores the user's 3D medical image, and a position data calculation unit 231 that receives the camera image and the medical image, maps them after image processing, and calculates position data of the brain region being stimulated from the mapped image.

[0031] In one embodiment, the 3D medical image storage unit 210 can be omitted, and the user can provide a storage medium or recording medium on which the 3D medical images are stored, or the medical images can be transmitted from a separate server on which the 3D medical images are stored.

[0032] Specifically, the 3D camera unit 220 can be used to capture real-time images of the user, preferably the upper part of the user's head, and to capture the current position of the upper part of the user's head while they are sitting in the chair 10, as well as changes in the position of the upper part of the head in response to the user's movements. At this time, it is possible to capture the entire upper part of the head, including the face, or to capture only a part of the upper part of the head where the stimulated brain region is located.

[0033] Furthermore, the 3D camera unit 220 is a camera capable of depth measurement and can have n channels, allowing for three-dimensional imaging of the user's head through multiple n channels.

[0034] On the other hand, the 3D medical image storage unit 210 stores the user's 3D medical images, and these medical images refer to international standard medical imaging images (DICOM, Digital Imaging and Communications in Medicine), and may include, for example, MRI, PET, and CT images.

[0035] The 3D medical image stored in the 3D medical image storage unit 210 according to one embodiment of the present invention may be an image in which position information points are already displayed, or it may be a 3D medical image in which position information points are not displayed, and this can be input to the position data calculation unit 231 to automatically detect position information points.

[0036] The position data calculation unit 231 converts the input 3D medical image into mesh data, precisely divides the mesh data, and can detect the motor cortex or stimulated brain region. By obtaining the precisely divided mesh data, position information points can be automatically detected from the mesh data.

[0037] The 3D medical image storage unit 210 can be included in the navigation device, or it can exist separately as another server and transmit 3D medical images to the navigation device.

[0038] Furthermore, as shown in Figure 2, the position data calculation unit 231 according to one embodiment of the present invention may include a face recognition module 2311 that detects a position information point or the upper part of the head that serves as a reference for position data of the brain region to be stimulated using the camera image, a medical image analysis module 2312 that detects a mapping point or the upper part of the head in the face region of the medical image, and an image mapping module 2313 that maps the position information point and the mapping point to obtain the position of the brain region to be stimulated and the upper part of the head corresponding to the brain region to be stimulated, or maps the upper part of each image to map the camera image and the medical image and obtain the mapped image.

[0039] The position data calculation unit 231 can be included in the control unit 230 of the navigation device, as shown in Figure 2, or it can be included in a separate device.

[0040] Specifically, the face recognition module 2311 can generate multiple mesh data after image processing of a real-time camera image transmitted from the 3D camera unit 220 or a 3D medical image stored in the 3D medical image storage unit 210.

[0041] By applying a face recognition algorithm, facial features are detected from the camera image transmitted from the 3D camera unit 220. Multiple mesh data is then generated according to these facial features, so that the features move along with the user's face, multiple mesh data can be generated in accordance with the user's movements.

[0042] Here, facial features refer to facial protrusions or grooves, and these facial protrusions or grooves may include areas that have depth when captured by a 3D camera according to the three-dimensional structure of the user's face. In other words, these facial protrusions or grooves refer to key components that, when their position is determined, also determine the overall facial position of the user, even as the user's face moves. Examples of such components may include the eyes, nose, and brow bone.

[0043] Furthermore, the facial recognition module 2311 can detect location information points based on mesh data. By adjusting the mesh scale via the mesh data, precise image analysis is possible, and location information points can be detected even more easily based on the mesh data. In this case, the location information points can represent, for example, the top of the head, nose, glabella, ears, etc., as pre-set reference points that make it easier to detect the location of stimulated brain regions, and the location information points of the pre-set parts can include the 3D coordinates of each part.

[0044] Furthermore, the above-mentioned location information points may include pre-set zero points, and the face recognition module 2311 can detect these zero points from the mesh data.

[0045] The medical image analysis module 2312 shown in Figure 2 can receive 3D medical images stored from the 3D medical image storage unit 210, analyze the medical images, and detect mapping points such as the top of the head, nose, glabella, and ears.

[0046] Furthermore, the medical image analysis module 2312, like the face recognition module 2311, can generate mesh data using medical images.

[0047] Therefore, the position data calculation unit 231, specifically the face recognition module 2311 and the medical image analysis module 2312, can generate mesh data using a camera image in which a position information point is detected or a medical image in which a mapping point is detected, or generate mesh data using the camera image or medical image and detect the position information points or mapping points of the mesh data.

[0048] In other words, by more precisely separating camera images and medical images and calculating positional data accordingly, the accuracy and precision of the positional data can be improved.

[0049] Mesh data generation can be performed after displaying location information points or mapping points, or after mesh data generation, but it is preferable to display location information points or mapping points after mesh data generation in order to improve the accuracy of the points.

[0050] Furthermore, the medical image analysis module 2312 can detect positional data of stimulated brain regions and motor cortex locations from 3D medical images.

[0051] Image mapping module shown in Figure 2 2313The system can receive a camera image displaying location information points from the face recognition module 2311 and receive a medical image from the medical image analysis module 2312 displaying at least one of the location information points, location data of the stimulated brain region, and location data of the motor cortex.

[0052] By mapping the transmitted camera image's positional information points to the medical image's mapping points, the camera image and medical image can be integrated into a single image. In this integrated image, real-time 3D coordinates can be generated to obtain positional data of the stimulated brain region and the corresponding positional data in the upper head.

[0053] In other words, the medical image can be mapped onto the camera image based on positional information points, and based on the mapped image, zero point coordinates and 3D coordinates of the brain region to be stimulated based on the zero point coordinates can be generated and provided to the magnetic field generator 100.

[0054] In this case, when matching position information points and mapping points, the zero points of each image may be misaligned. The position data calculation unit 231 according to one embodiment of the present invention can correct the zero points pre-set in the camera image or medical image based on the mapped image, and generate real-time 3D coordinates in the mapped image based on the corrected zero points. When matching mapping points to position information points, the position data can be corrected to match the mapped image by correcting the zero points of the medical image to match the zero points of the camera image.

[0055] Furthermore, the above image mapping module 2313The motor cortex can acquire position data and corresponding position data at the top of the head and transmit it to the motion threshold control module 232. The motion threshold control module 232 can then measure the motion threshold via the received position data, or transmit the received motor cortex position data to the magnetic field generator 100, so that the motion threshold measurement module 1102 of the magnetic field generator 100 can measure the user's motion threshold (Motor Threshold, MT).

[0056] In other words, according to one embodiment of the present invention, the image mapping module 2313 includes a medical image analysis module 2312 that detects the motor cortex or the location of the brain region to be stimulated from the brain region of the medical image, generates 3D coordinates based on the mapped image with respect to zero-point coordinates, and can calculate or provide the 3D coordinate location of the brain region stimulated by the motor cortex or magnetic field generator from the mapped image.

[0057] On the other hand, according to one embodiment of the present invention, the position data calculation unit 231 may include an artificial intelligence model that has been learned via artificial intelligence using server data.

[0058] Specifically, the position data calculation unit 231 includes a deep learning model trained using a deep learning algorithm with server data. The position data calculation unit 231 can match at least one of the following data points with user information and save it to the server: position information points in the camera image which differ for each user, mapping points in the medical image which differ for each user, and matching points between the position information points and the mapping points. Alternatively, the learning results of the position data calculation unit can be saved to the server. The camera image or mapping points may be mesh data.

[0059] The artificial intelligence model described above learns the detected location information points or mapping points stored on the server described above, enabling it to more accurately and quickly search for location information points in the camera image and mapping points in the medical image. It also learns matching points between the location information points and mapping points, enabling it to more accurately and quickly extract matching points when integrating the camera image and the medical image.

[0060] Therefore, according to one embodiment of the present invention, the artificial intelligence model described above can be used to detect at least one of the location information points in the camera image, the mapping points in the medical image, and the matching points between the location information points and the mapping points.

[0061] Because the size and shape of the top of the head and brain differ from user to user, the position of the location information points differs each time the face recognition module 2311 generates mesh data, and the mapping points of the medical image in the medical image analysis module 2312 also differ from user to user.

[0062] Therefore, before performing magnetic field stimulation with the magnetic field generator 100, it becomes necessary to detect positional information points or mapping points from each image. This shortens the time required for stimulation, reduces stimulation efficiency, and causes inconvenience to the user.

[0063] Therefore, by matching and saving camera images with location information points, and further matching and saving medical images with the aforementioned mapping points, users with similar types of camera images or medical images can more quickly and accurately detect the location information points or mapping points for each image.

[0064] For example, a deep learning model can be trained using MRI images that display brain treatment areas and location information points that are typically stimulated by medical professionals such as doctors. By adjusting the internal weights according to the output, the accuracy and speed of detecting location information points can be improved. This enables user-customized exploration and maximizes magnetic stimulation efficiency.

[0065] As described above, conventional data can be stored on a server as a database so that deep learning models can utilize previously accumulated data as training data.

[0066] Furthermore, it may include a cloud server that receives and stores the data stored on the above server.

[0067] When conducting telemedicine or when a user uses a navigation device at home, the data can be stored on a cloud server so that a healthcare professional or administrator located outside the home can review and diagnose the information.

[0068] Figure 3 shows an overall block diagram of a brain stimulation device according to one embodiment of the present invention.

[0069] As shown in Figure 3, the brain stimulation device may include a magnetic field generator 100, a navigation device 200, an integrated operator 300, and a cognitive training device 400.

[0070] Alternatively, among the brain stimulation devices, the magnetic field generator 100 is merely one embodiment of stimulating the brain with magnetic field stimulation, and another embodiment of the brain stimulation device according to the present invention can be a brain neurological stimulation device.

[0071] The above-mentioned brain nerve stimulator may be a non-invasive magnetic field stimulator such as a TMS (Transcranial Magnetic Stimulation) device or a TDCS (Transcranial Direct Current Stimulation) device, or it may be a brain nerve stimulator such as an ultrasound device or an invasive stimulator for directly performing physical stimulation on the brain.

[0072] In the following, an embodiment of the present invention will be described, focusing on an embodiment relating to a magnetic field stimulator among brain nerve stimulators. This is merely an illustrative embodiment and does not limit the scope of the patent.

[0073] First, the magnetic field generator 100 can position a coil 160 on the side where the user's brain is located, relative to the chair 10 on which the user sits, and can be linked to the coil 160.

[0074] A magnetic field generator 100 according to one embodiment of the present invention is a device that determines and provides a magnetic field output to a coil 160 so that it can stimulate the user's brain with a magnetic field.

[0075] A magnetic field generator 100 according to one embodiment of the present invention may include a control unit 110 that determines a corresponding magnetic field considering user data including motor threshold (MT) and the brain region being stimulated, and a power module 120 that is connected to the control unit 110 and a coil 160 that generates a magnetic field and supplies power to the coil 160 to generate the determined magnetic field.

[0076] Furthermore, according to one embodiment of the present invention, the system may include a user interface 150 that includes an output module 152 that displays the output magnetic field to a user controlling the magnetic field generator 100, an input module 151 that allows the user to manually adjust the magnetic field output, a communication module 130 that communicates with an integrated operator 300 and a brain navigation system 200, and a cooling module 140 that monitors the temperature of the coil 160 and performs cooling if it exceeds a threshold.

[0077] On the other hand, according to one embodiment of the present invention, the cognitive training device 400 can perform cognitive training and brain nerve stimulation simultaneously or alternately in conjunction with a brain nerve stimulation device.

[0078] As one embodiment, the system may further include a cognitive training device 400 that works in conjunction with the magnetic field generator 100 to perform cognitive training by presenting pre-set problems corresponding to the brain regions stimulated by the magnetic field generator 100, so as to activate those brain regions after the magnetic field generator 100 has stimulated the brain. The system may further include an integrated operator 300 that communicates with the magnetic field generator 100 and the cognitive training device 400 and drives the magnetic field generator 100 and the cognitive training device 400 simultaneously or alternately.

[0079] A cognitive training device 400 according to one embodiment of the present invention can be driven alternately with the magnetic field generator 100 to stimulate the user's brain, and the cognitive training device 400 can further activate brain regions stimulated by the magnetic field generator 100, or complementarily activate brain regions that are not stimulated much by the magnetic field generator 100, thereby improving the brain stimulation efficiency, specifically, the treatment efficiency of degenerative brain diseases, for example.

[0080] A cognitive training device 400 according to one embodiment of the present invention includes a first memory 402 for storing user treatment data such as the user's personal information, cognitive training problems performed by the user, or cognitive training scores, and may include a user interface 401 that presents cognitive training problems and allows the user to provide feedback on their answers.

[0081] The user interface 401 described above can include a variety of user devices such as desktop computers, notebooks, PDAs, and tablet PCs, and can be a portable PC to enhance user convenience.

[0082] Furthermore, the integrated operator 300 according to one embodiment of the present invention is a device that works in conjunction with the cognitive training device 400 or the magnetic field generator 100, and controls the driving time, time interval, frequency, and intensity when the cognitive training device 400 and the magnetic field generator 100 are driven simultaneously or alternately.

[0083] To prepare for the loss of user data in the first memory 402, a second memory 302 can be included that stores the user's treatment history and personal information, and a user interface 301 can be included that allows a user who can control the magnetic stimulation system, such as a doctor or nurse, to manually control or confirm the operating time, time interval, frequency, and intensity.

[0084] The second memory 302 described above can be implemented not only as an internal or external storage device, but also as a cloud server-based database, allowing the user's treatment history and entered user information to be automatically linked and saved to the cloud server. In particular, it can consolidate and save user data during telemedicine to simplify data management and improve user convenience.

[0085] The user interface 301 described above can include various user devices such as desktop computers, notebooks, PDAs, and tablet PCs, and can be a portable PC to enhance user convenience.

[0086] Furthermore, a navigation device 200 according to one embodiment of the present invention is a device that, in conjunction with the magnetic field generator 100, detects the location of the brain region to be stimulated so that the magnetic field generator 100 can be accurately positioned at the location of the brain region to be stimulated by the user, and provides the brain region location information to the magnetic field generator 100 so that it can guide the position of the magnetic field generator 100.

[0087] A navigation device 200 according to one embodiment of the present invention may include a control unit 230 that includes a 3D medical image storage unit 210 in which 3D medical images are stored, a 3D camera unit 220 that captures a user sitting in a chair 10 in real time and acquires a camera image, and a position data calculation unit 231 that calculates position data for positioning the coil 160 by mapping the images acquired from the 3D medical image storage unit 210 and the 3D camera unit 220.

[0088] Furthermore, the system may further include a communication module 260 that communicates in conjunction with the magnetic field generator 100, and a power supply module 270 that supplies power to the above-described configuration.

[0089] Furthermore, as shown in Figure 3, when the coil 160 is connected to the robot arm 161, the system may further include an RC control unit 240 that controls the 5-axis drive of the robot arm 161, and a temperature monitoring unit 250 that monitors the motor temperature of the robot arm 161 to ensure that the heat generated by the motor drive does not exceed safety standards.

[0090] That is, a bionavigation robot system for guiding the position of a coil 160 corresponding to a stimulated region according to another aspect of the present invention may include a coil 160 that generates a magnetic field to stimulate a brain region, a robot arm 161 to which the coil 160 is connected and driven to move the position of the coil, a magnetic field generator 100 including a magnetic field adjustment module 1101 that adjusts magnetic field-related parameters to control the magnetic field output of the coil 160, and a motion threshold measurement module 1102 that measures the user's motion threshold using the magnetic field adjustment module, and a navigation device 200 that controls the robot arm 161 to move the coil 160 to a position corresponding to the brain region to be stimulated.

[0091] In this configuration, the coil 160 connected to the robot arm 161 can consist of one coil, or two or more coils 160 can be connected at one or more ends. Depending on the situation, the coils 160 can be connected in different ways, taking into consideration the size of the brain region to be stimulated or the target of treatment.

[0092] Furthermore, before the position data calculation unit 231 calculates the position data, the navigation device 200 can recognize the user's sitting height and adjust the height of the chair 10 in which the user is seated for treatment. This is because the robot arm 161 has a limited range of motion, and the user's height must be adjusted to the optimal range within which it can be driven. Therefore, the navigation device 200 senses the user's sitting height and uses a motor to adjust the height of the chair 10 so that the user can be positioned within the set range of motion for the robot arm 161. This ensures that the height of the user's head relative to the robot arm 161 remains constant, optimizing the operation of the robot arm 161.

[0093] Specifically, according to one embodiment of the present invention, the system may include an RC control unit 240 that receives the position data calculated by the position data calculation unit 231 and controls the direction of movement or rotation axis of the motor of the robot arm 161 according to the position data, and a temperature monitoring unit 250 that senses whether the temperature of the robot arm 161 exceeds a preset range.

[0094] In one embodiment, the coil 160 can be moved to a 3D coordinate position calculated by the user for a brain region to be stimulated manually. The navigation device may further include a laser scanner and a laser pointer to facilitate the manual locating of the position corresponding to the 3D coordinates. The laser scanner can scan the position of the brain region to be stimulated and the corresponding head position, and the laser pointer can display the position.

[0095] Alternatively, as shown in Figure 3, according to one embodiment of the present invention, the robot arm 161 can be driven to a predetermined position according to the position data value calculated by the position data calculation unit 231, thereby moving the coil 160 to the position determined by the position data. The position data may include a zero point, a position information point, the position of the brain region to be stimulated, or the motor cortex position.

[0096] According to one embodiment of the present invention, the robot arm 161 is capable of 5-axis drive, and the 5 axes may include the X, Y, and Z axes and tilting in the plane formed by each axis. The robot arm 161 moves to a predetermined position and tilts to correspond to the user's head to control the position of the coil 160, allowing for more precise control of the coil 160's position and enabling user-customized position control. The above embodiment is an exemplary embodiment, and 4-axis or 6-axis drive is also possible, and the scope of the claims is not limited to the above embodiment. However, preferably, the robot arm 161 can be driven in 5 or more axes to increase accuracy and precision.

[0097] At this time, the RC control unit 240 maps the zero point of the robot arm 161 to the zero point of the mapped image, and positions the robot arm 161 at the mapped zero point before moving the robot arm 161.

[0098] On the other hand, according to another embodiment, the position of the coil 160 can be controlled using a helmet-type magnetic stimulation unit 162, which will be described later.

[0099] Figures 4-8 below show flowcharts of the operations performed by each module of the position data calculation unit 231. The position data calculation unit 231 will be explained in detail with reference to Figures 4-8.

[0100] Figure 4 shows the image processing method of the camera image from the face recognition module 2311.

[0101] Specifically, as shown in Figure 4, the 3D camera unit 220 captures the user (S41), and if the face is not recognized from the captured camera image (No in S42), the 3D camera unit 220 captures the user again (S41), and if the face is recognized (Yes in S42), the camera image is split (S43).

[0102] The face recognition module 2311 according to one embodiment of the present invention divides the 3D camera image according to its resolution (S43), detects the positions of pre-set facial features for each divided image (S44), and then calculates average data of the positions of the facial features to determine the final position of the facial features in the camera image (S45).

[0103] For example, pre-defined facial features may include features that have depth, such as the nose, eyes, and ears. Once the positions of the facial features are detected from the divided images and the average value of the detected facial features is calculated to determine the camera image facial features (yes in S45), the camera image can be processed with multiple mesh using the facial features to generate mesh data (S46). On the other hand, if the facial features of the camera image are not determined (no in S45), for example, if the image is excessively shaky and positional data with significantly shifted facial features is obtained, the conditions can be changed and the process can be returned to the stage of dividing the camera image according to the resolution (S43).

[0104] In other words, according to one embodiment of the present invention, the position data calculation unit 231 divides the image according to the resolution of the camera image or medical image, detects the positions of pre-set facial protrusions or grooves for each divided image, determines the average value of the facial protrusion or groove positions as the final facial protrusion or groove position, and generates mesh data of the camera image or medical image taking the final facial protrusion or groove into consideration.

[0105] The facial features can vary depending on the user's settings, but in one embodiment of the present invention, it refers to facial protrusions or grooves, such as the brow bone or nose, or the area around the eyes that is recessed. Because the 3D camera senses depth, it can search for facial protrusions or grooves to sense the overall position and orientation of the user's face. Furthermore, it can detect positional information points that assist in detecting the position of the stimulated brain region based on the generated mesh data (S47). The positional information points are pre-set reference points and may include, for example, the size of the top of the head, the nose, ears, the space between the eyebrows, etc., and may include a zero point position that serves as a reference for the position coordinates of the stimulated brain region.

[0106] Alternatively, location points can be detected from the camera image, and then mesh data can be generated. The process is not constrained by chronological order; it can be done simultaneously or in a reversed order.

[0107] When position information points are detected from the generated mesh data (Yes in S47), zero points are set on the X, Y, and Z axes accordingly (S49), and the position of each position information point can be extracted based on the above zero points (S50). For example, position information points on an image are detected from the generated mesh data, and zero points with X, Y, and Z axes are set accordingly. Then, the above zero points are set to (0,0,0), and the coordinates (a,b,c) of each position information point can be obtained.

[0108] If no positional information points are detected from the generated mesh data (no in S47), the mesh scale can be increased by one step (S48), and multiple mesh processing and mesh data related to the camera image can be generated again (S46). The mesh data is adjusted according to the camera image to generate precise mesh data.

[0109] Through the process described above, the face recognition module 2311 can generate mesh data using camera images acquired via the 3D camera unit 220 and obtain positional data of positional information points, including the zero point.

[0110] Figure 5 shows the image processing method for medical images used by the medical image analysis module 2312.

[0111] Specifically, as shown in Figure 5, the system receives a 3D medical image acquired from the 3D medical image storage unit 210 (S51), recognizes the axial portion of the 3D medical image (S52), and recognizes the coronal portion (S53). The axial portion refers to the image viewed from the front of the 3D medical image, while the coronal portion refers to the image viewed from above, specifically from above.

[0112] Therefore, by recognizing the axial region (yes in S52) and the coronal region (yes in S53), it is possible to detect images of the face region and brain region simultaneously, or to separate the face region and brain region for image processing.

[0113] In other words, the medical image analysis module 2312 can detect mapping points or the top of the head from the facial region, and the location of the motor cortex or the brain region to be stimulated from the brain region, and combine these into a single image.

[0114] Alternatively, the face region and brain region can be detected separately. In this case, by using different mesh scales that take into account the size of the face region and brain region, more precise mesh data can be obtained.

[0115] In one embodiment of the present invention, as shown in Figure 5, when the face region and brain region are processed separately, once the user's face region is recognized from the acquired 3D medical image (yes in S54), the pixels of the face image in the 3D medical image can be amplified to improve noise (S55). This is because medical images inherently contain noise, which degrades image quality, and this is done to improve that.

[0116] On the other hand, if the axial shape cannot be recognized (No in S52), the coronal shape cannot be recognized (No in S53), or the user's face region cannot be recognized from the 3D medical image (No in S54), it is assumed that there is an abnormality in the 3D medical image, and the process returns to S51 to receive the 3D medical image again.

[0117] Next, similar to the image processing for the camera image of the face recognition module 2311, the facial feature portion of the image of the face region of the medical image is searched (S56), and from the facial feature portions of the image of the face region of the 3D medical image, the image facial feature portion of the face region of the 3D medical image can be determined (Yes in S57). At this time, the facial feature portion can mean a facial protrusion or groove, as described above. The facial protrusion or groove can be determined by detecting 3 or more points.

[0118] If the facial features of the 3D medical image's facial region cannot be determined (resulting in a "no" in S57), the image quality is expected to deteriorate, and the process returns to S55 to amplify the image pixels of the 3D medical image's facial region again and perform noise reduction.

[0119] Therefore, the determined 3D medical image of the face is subjected to multiple mesh processing (S58), and mapping points are detected from the mesh data obtained in this way (S59). Zero points are set at pre-set positions on the X, Y, and Z axes (S61), and the position of each mapping point can be extracted based on the above zero points (S62). For example, based on the zero point (0,0,0) in the 3D coordinate system, the coordinates (d,e,f) of each mapping point such as the nose, glabella, and ear can be obtained, and the position data of each mapping point can be acquired.

[0120] Alternatively, as mentioned above, mapping points can be detected from the facial region image first, and then multiple mesh data can be generated.

[0121] If no location points are detected (No in S59), the mesh scale can be increased by one level (S60) to adjust the scale of the mesh data and regenerate it.

[0122] On the other hand, 3D medical imaging can detect the facial appearance, that is, the positional information points of the upper head including the face, and extract positional data. Furthermore, it can also detect mapping points for the brain regions that are actually being stimulated.

[0123] In other words, the medical image analysis module 2312 according to one embodiment of the present invention can recognize the axial or coronal shape of the 3D medical image, detect the user face region or user brain region of the 3D medical image, and separately detect positional information points in the face region and positional information points and motor cortex positions in the brain region of the medical image.

[0124] In 3D medical imaging, the facial region and the brain region that is actually stimulated have different multi-image scales. When image processing is performed simultaneously, in other words, when mesh data is generated based on one region, the other region will not be scaled correctly, resulting in reduced image quality and making it impossible to detect accurate mapping points.

[0125] Therefore, according to one embodiment of the present invention, a 3D medical image can be classified into images of the face region and images of the brain region, and positional information points can be detected for each.

[0126] Specifically, as shown in Figure 5, the system receives a 3D medical image acquired from the 3D medical image storage unit 210 (S51), recognizes the axial portion of the 3D medical image (S52), and recognizes the coronal portion (S53).

[0127] Therefore, once axial images are recognized (yes in S52), coronal images are recognized (yes in S53), and a brain region is recognized from the acquired 3D medical image (yes in S63), the pixels of the brain region image in the 3D medical image can be amplified to improve noise (S64). This is because medical images inherently contain noise, which degrades image quality, and this process is intended to improve this.

[0128] On the other hand, if axial images cannot be recognized (no in S52), coronal images cannot be recognized (no in S53), or brain regions cannot be recognized from the 3D medical image (no in S63), it is assumed that there is an abnormality in the 3D medical image, and the process returns to S51 to receive the 3D medical image again.

[0129] Next, similar to the image processing for the camera image of the face recognition module 2311, the image feature area of ​​the brain region of the medical image is searched (S65), and from the searched brain image feature areas, the brain image feature area of ​​the 3D medical image can be determined (yes in S66). If the brain image feature area of ​​the 3D medical image cannot be determined (no in S66), the image quality is considered to be low, and the process returns to S64 to amplify the brain image pixels of the 3D medical image again and perform noise reduction. In this case, the feature area refers to the main part that can grasp the overall position of the brain even if the brain moves in response to the user's movement, similar to the face feature area described above.

[0130] Therefore, by performing multiple mesh processing on the brain region image of the determined 3D medical image (S67), and detecting mapping points from the mesh data obtained in this way (S68), zero points are set at pre-set positions on the X, Y, and Z axes (S70), and the positions of the motor cortex or the brain region to be stimulated can be detected based on the above zero points to determine the motor threshold (MT) based on the brain region. Therefore, the motor cortex position can be extracted based on the zero points (S71), and the brain treatment region to be stimulated can be extracted (S72).

[0131] For example, based on the zero point (0,0,0) in the 3D coordinate system, the coordinates (g,h,i) of the motor cortex can be obtained, thereby acquiring the position data of the motor cortex.

[0132] If no mapping points are detected (No in S68), the mesh scale can be increased by one level (S69) to adjust the scale of the mesh data and regenerate it.

[0133] Therefore, the medical image analysis module 2312 can extract facial images and brain images from 3D medical images, respectively, and detect mapping points based on these.

[0134] Figure 6 shows an image mapping module according to one embodiment of the present invention. 2313 This is a flowchart showing the operation of [the system / function].

[0135] According to one embodiment of the present invention, the image mapping module 2313 can generate real-time 3D coordinate data by mapping at least two or more positional information points or zero point coordinates of the magnetic stimulation coil 160, the face recognition module 2311, and the medical image analysis module 2312.

[0136] As an example, the above coil 160 may include a TMS coil, which will be described below as a TMS coil in Figure 6, but is not limited to this coil.

[0137] Specifically, as shown in Figure 6, the image mapping module 2313 The above TMS coil can be checked (S81) and recognized (S82). Image mapping module 2313 This allows you to check whether the TMS coil of the magnetic field generator 100 is connected or powered via the communication module 260.

[0138] Image mapping module 2313 When the TMS coil is recognized (Yes in S82), the TMS coil is moved to the zero point position (S83). The purpose of moving the TMS coil to the zero point position before moving it to a predetermined position is to ensure that it is moved to a more accurate coordinate.

[0139] Next, the zero point of the TMS coil can be mapped to the zero point of the position data calculation unit 231, that is, to the zero points of the X, Y, and Z axes set in the mapped image acquired by the face recognition module 2311 and the medical image analysis module 2312 (S84). The zero point set by the TMS coil can be mapped to the zero point in the camera image acquired by the face recognition module 2311 via the 3D camera unit 220, and to the zero points in the face image and brain image of the 3D medical image acquired by the medical image analysis module 2312 via the 3D medical image storage unit 210.

[0140] The camera images or 3D medical images that have been acquired and processed are zero-point mapped to integrate the actual user's medical image with the user's camera image that is currently moving in real time. The coil 160, which moves to the brain region that is actually being stimulated, is also zero-point mapped to synchronize the coil 160 with the acquired image.

[0141] Once the zero-point mapping of the X, Y, and Z axes is completed, the position information points of the face recognition module 2311 are mapped to the mapping points of the medical image analysis module 2312 (S85), image integration is completed, and real-time 3D coordinate data is generated for this (S86), allowing the TMS coil to move to the calculated 3D coordinate position.

[0142] As one embodiment of the present invention, the robot arm 161 can be positioned at a mapped zero point before moving to a calculated 3D coordinate position, thereby enabling more precise control of the robot arm 161's position.

[0143] On the other hand, as shown in Figure 6, the image mapping module 2313 can generate real-time 3D coordinate data and transmit the calculated 3D coordinate data and motor cortex position data to the motion threshold control module 232 to assist in motion threshold measurement.

[0144] The motion threshold control module 232 uses the calculated 3D coordinate data and motor cortex position data to allow the RC control unit 240 to move the robot arm 161 to the 3D coordinates of the motor cortex, and the motion threshold measurement module 1102 to measure the motion threshold.

[0145] Figure 7 shows a flowchart illustrating how a navigation device according to one embodiment of the present invention guides the position of the robot arm 161. As shown in Figure 7, the robot arm 161 can be moved to the zero point position (S91), and then moved to the motor cortex (S92).

[0146] When the robot arm 161 moves to the motor cortex and the coil 160 begins to apply magnetic field stimulation to the motor cortex, the motion threshold measurement module 1102 can measure TMS-MT (S93). This allows the user's motion threshold to be measured.

[0147] For magnetic stimulation to work, the user must remain motionless and stationary while simultaneously stimulating the brain. Therefore, the magnetic field output must be adjusted to be below the motor threshold (MT) at which movement occurs in the fingers or other body parts, while maintaining a magnetic field output close to the motor threshold to maximize brain stimulation efficiency.

[0148] Motor thresholds vary depending on the user's race, gender, and other factors, as well as their physical condition. Therefore, accurately determining the motor threshold immediately before treatment is crucial for accurate and safe treatment.

[0149] Therefore, the motor threshold measurement module 1102 can measure the motor threshold by adjusting the magnetic field strength in steps using the magnetic field adjustment module 1101, and determine the magnetic field parameters applied to brain stimulation based on the motor threshold.

[0150] If, despite going through the process described above, the motor cortex does not receive a motion threshold measurement sensor such as an ECG sensor or EMG sensor, or a finger response, it can be determined that the motor cortex is not being properly stimulated by a magnetic field. In this case, the RC control unit 240 can be driven to perform a position search by drawing a circle around the position data acquired that the robot arm 161 is the motor cortex. The robot arm 161 can draw a circle and move the coil 160 to detect the motor cortex position, and this position can be saved. Furthermore, the detected motor cortex position data can be used to train an artificial intelligence module to detect the motor cortex position more accurately and quickly, and to acquire a motion threshold.

[0151] Once the motion threshold measurement is complete, the robot arm 161 is moved back to the zero point position (S94). If the administrator approves the treatment (Yes in S95), the robot arm 161 can be moved to the treatment position (S96). This is to control the position of the robot arm 161 more precisely and increase treatment efficiency. If the administrator does not approve the treatment (No in S95), the robot arm 161 remains waiting at the zero point position.

[0152] The robot 161 can be moved to the treatment position, and the coil 160 can generate a magnetic field to perform brain stimulation therapy (S97).

[0153] When brain stimulation is performed, a total of six brain regions may be stimulated, including Broca's area, Wernicke's area, the left and right dorsolateral prefrontal cortex (DLPFC), and the left and right parietal somatosensory association cortex (PSAC).

[0154] If the system is configured to stimulate at least two of the above multiple brain regions, after performing the treatment (S97), it is determined whether or not treatment of all brain regions has been completed (S98). If treatment of all brain regions is completed (yes in S98), the treatment is terminated. If treatment of all brain regions is not completed (no in S98), the system returns to S94, moves the robot arm to the zero point position, and repeats steps S95 to S98.

[0155] With the configuration described above, there is no need for a separate assistant other than the user to help position the coil 160 to be stimulated in the brain region. The position of the coil 160 is automatically controlled in accordance with the user's movements, allowing the user to perform magnetic field stimulation alone. This reduces the time and personnel required, saves costs, and enables user-customized exploration through more precise position control of the coil 160, thereby increasing treatment efficiency.

[0156] On the other hand, Figure 8 shows a flowchart illustrating how the motor threshold measurement module 1102 according to one embodiment of the present invention measures the motor threshold.

[0157] The motor threshold measurement module 1102 uses a coil 160 to stimulate the motor cortex region of the brain, and then detects hand movements and changes in pulse rate to confirm whether the stimulation has been transmitted to the brain.

[0158] Specifically, a user's motor threshold varies from person to person, and even within the same user, it varies from day to day and depending on their condition. In particular, since the motor threshold of East Asians is formed to be much higher than that of Westerners, without a control method for accurately measuring the motor threshold, if there is no finger movement with the arbitrarily provided magnetic field output, or if the ECG sensor 500 cannot detect pulse variability, or if the EMG sensor cannot detect changes in muscle or nerve action potentials, the user in question could not receive further magnetic stimulation therapy.

[0159] Therefore, the motion threshold measurement module 1102 according to one embodiment of the present invention can measure the user's motion threshold by adjusting the magnetic field strength stepwise using the magnetic field adjustment module 1101, or, when the magnetic field strength reaches the maximum output of the magnetic field, it can increase the magnetic field frequency to a preset percentage and then adjust the magnetic field strength stepwise again to measure the user's motion threshold.

[0160] Furthermore, the magnetic field generating device according to one embodiment of the present invention may include an exercise threshold measuring sensor such as an ECG sensor 500 or an EMG sensor that senses the user's electrocardiogram so as to detect changes in the electrocardiogram when the magnetic field of the coil 160 generated by the magnetic field adjustment module 1101 exceeds the exercise threshold.

[0161] In the following description, the embodiment of the present invention will be explained as an embodiment in which the position of the coil 160 is automatically controlled using the robot arm 161, and therefore there is no separate personnel to observe the movement of the fingers, and the motor threshold is measured using the ECG sensor 500. The motor threshold can also be measured using the ECG sensor 500 when using the helmet-type magnetic stimulation unit 163 described later.

[0162] As shown in Figure 8, the MT measurement module 1102 according to one embodiment of the present invention can first output a magnetic field at a preset magnetic field strength (S501). For example, it is possible to output a magnetic field by setting an intermediate magnetic field strength or frequency within the range of possible magnetic field strengths or frequencies. This involves setting a reference point to measure the user's motion threshold.

[0163] Subsequently, if the ECG sensor 500 fails to measure the pulse rate change in the initial stage, resulting in no sensor response (No in S502), and the magnetic field strength is not at its maximum value (No in S503), the magnetic field frequency can be fixed, and the magnetic field strength can be adjusted by increasing it to a preset percentage (n%) (S505).

[0164] The magnetic field strength can be increased until the ECG sensor 500 can measure the change in pulse rate. When a reaction is detected by the ECG sensor (yes in S502), it is determined that the motor cortex of the user's brain has exceeded the motor threshold, and the magnetic field strength can be reduced and output by a preset percentage (m%) that is smaller than the preset percentage (n%) (S506).

[0165] At this time, if the ECG sensor reacts (yes in S507), it is determined that the threshold immediately preceding the motor threshold has not yet been reached, and the system returns to S506 to decrease the magnetic field strength and output the result. If the ECG sensor does not react (no in S507), the threshold immediately preceding the motor threshold can be detected. This allows the motor threshold to be determined (S508), and this motor threshold becomes the reference value for the magnetic field strength used for brain stimulation.

[0166] On the other hand, if the ECG sensor cannot measure changes in pulse rate even when the magnetic field strength is increased to its maximum value (yes in S503), the magnetic field frequency can be adjusted to increase the magnetic field output by increasing the magnetic field frequency (S504).

[0167] After increasing the magnetic field frequency to a preset percentage, the magnetic field strength returns to its initial level, outputting an intermediate magnetic field strength (S501). If no response is detected from the ECG sensor, the magnetic field strength is again increased to a preset percentage (n%) and adjusted until the ECG sensor can detect a change in pulse rate.

[0168] In this case, according to one embodiment of the present invention, if it is determined that the magnetic field frequency cannot be further improved by adjusting the magnetic field frequency in S504, it is determined that accurate magnetic field stimulation has not been transmitted to the motor cortex, and the motor cortex can be detected by drawing a circle around the point where the coil 160 is currently positioned. The newly discovered motor cortex location can be stored in a database or on a server, and an artificial intelligence module can be trained with this data.

[0169] In other words, a brain stimulation device according to one embodiment of the present invention may further include a motor threshold control module 232 that measures the user's motor threshold by adjusting the magnetic field strength or frequency of the coil after determining the position of the coil 160 at an upper head position corresponding to the motor cortex position of a brain region, or after determining the position of the coil 160 at an upper head position corresponding to the motor cortex position.

[0170] This allows all users to detect their own appropriate motor threshold (MT), set the threshold immediately preceding the MT threshold as the baseline value for the magnetic field strength used for brain stimulation, and perform magnetic stimulation at the maximum magnetic field output while controlling the user to remain still during the period when motor function is lost and brain stimulation is performed. This maximizes treatment efficiency while ensuring safety.

[0171] Although the above description is limited to the ECG sensor 500, this is merely an illustrative example, and the present invention can include all motor threshold measurement sensors that can sense the action potential of muscles or nerves and confirm the motor threshold response.

[0172] In the embodiment described above, the position of the coil 160 is adjusted by connecting the coil 160 to the robot arm 161 and driving the robot arm 161.

[0173] In the following, Figure 9 shows an overall block diagram of a brain stimulation device according to another embodiment of the present invention, and Figures 10 and 11 describe an embodiment in which a coil 161 is placed in a helmet-type magnetic stimulation unit 162 and the coil 160 generates a magnetic field at the location of the brain region to be stimulated. Configurations identical to those described above are omitted to avoid duplication of content.

[0174] As shown in Figure 9, a brain stimulation device that guides the position of a coil 160 corresponding to a stimulated region according to another embodiment of the present invention includes a plurality of coils 160 that generate a magnetic field to stimulate a brain region, a helmet-type magnetic stimulation unit 162 in which the plurality of coils 160 are densely arranged in a helmet-type fixing unit worn on the user's head, a magnetic field generator 100 including a magnetic field adjustment module 1101 that adjusts magnetic field-related parameters to control the magnetic field output of the coils 160, and a motor threshold measurement module 1102 that measures the user's motor threshold using the magnetic field adjustment module 1101, and a navigation device 200 that calculates position data of the brain region to be stimulated and determines the coil 160 positioned at the location corresponding to the brain region to be stimulated, the navigation device 200 may further include a multi-coil control unit 241 that selects at least one of the plurality of coils 160 according to the position data calculated by the position data calculation unit 231 and transmits an identification mark of the selected coil 160 to the magnetic field generator 100.

[0175] Furthermore, according to another embodiment, the helmet-type magnetic stimulation unit 162 includes a cribration bar 163 horizontally positioned at the lower end of the fixed part, and the navigation device can obtain the tilt angle of the cribration bar 163 or the distance to the position information point of the user's camera image using the 3D camera unit 220, correct the position information point considering the correction data calculated from the angle or distance of the cribration bar 163, and transmit an identification marker for at least one of the multiple coils 160 positioned to correspond to the brain region to be stimulated relative to the corrected position information point to the magnetic field generator 100.

[0176] Specifically, the helmet-type magnetic stimulator 162 makes close contact with the scalp according to the user's head position and can be worn after the hair is secured to the scalp via a separate rubber cap. Multiple coils 160 are densely arranged in the helmet-type magnetic stimulator 162, and when at least one of the coils 160 is driven, a magnetic field is generated, stimulating the brain region corresponding to the coil 160.

[0177] Furthermore, according to one embodiment of the present invention, the coils 160 can be arranged as circular coils, or as figure-eight coils, or they can be arranged in a way that each coil operates in a pair. In this case, the coils 160 constituting a pair can be connected so as to overlap each other.

[0178] For example, if the coil 160 is an eight-shaped TMS coil, a sharp waveform magnetic field is generated at the junction where two circles in the eight shape meet, and multiple coils 160 can be arranged so that the magnetic fields generated at the junction can magnetically stimulate the corresponding brain regions.

[0179] Furthermore, the multi-coil control unit 241 according to one embodiment of the present invention can control the switching of switches connected to each coil 160 to control the on or off state of all or some of the coils 160. For example, after turning off all of the coils 160, the switching can be turned on and operated only for selected coils.

[0180] Furthermore, the helmet-type magnetic stimulator 162 is configured such that coils 160 positioned at predetermined locations stimulate corresponding brain regions. If the helmet-type magnetic stimulator 162 is worn incorrectly or misaligned, other brain regions may be stimulated. Therefore, to compensate for this, a correction bar 163 can be positioned along the top of the head at the lower end of the helmet-type magnetic stimulator 162.

[0181] In other words, when the 3D camera unit 220 photographs a user wearing the helmet-type magnetic stimulation unit 162, the correction bar 163 is photographed horizontally. If the correction bar 163 is photographed at an angle due to incorrect wearing, the coordinates of the position information points can be calibrated to reflect this.

[0182] Specifically, for example, as shown in Figure 10, when the face recognition module 2311, which has acquired the camera image captured by the 3D camera unit 220, performs image processing and detects a location information point (yes in S47), an additional correction step can be performed.

[0183] If the correction lines formed by the correction bar 163 in the camera image or mesh data generated from the camera image are not straight lines (no in S491), it can be seen that the correction bar 163 is tilted.

[0184] Therefore, the angle between the correction line formed by the correction bar 163 and the horizontal line, and the distance between the correction line and the position information point are calculated (S492), and the correction value is reflected in the position information point to reflect the degree to which the correction line is tilted (S493), thereby obtaining the position data of the position information point.

[0185] Specifically, by comparing the straight line formed by the position information points with the straight line formed by the correction bar 163, it is possible to detect whether the distance difference between the two straight lines remains constant or changes, thereby sensing whether the correction bar 163 has tilted.

[0186] Furthermore, zero points for the X, Y, and Z axes can be set (S49), and the position of each position information point can be extracted based on these zero points (S50). Here, the zero points for the X, Y, and Z axes and each position information point can be position data that reflects the correction values ​​calculated above.

[0187] In other words, for example, if the position set as the zero point is shifted by the correction bar 163 and set to coordinates (x,y,z), the current position of the pre-set zero point is corrected to (0,0,0) by reflecting the correction value, and thereby the position information point (a,b,c) can be corrected to (a',b',c').

[0188] Furthermore, as shown in Figure 11, once the TMS coil check and recognition are complete (S81 and S82), the image mapping module 2313 turns off the multi-coil control unit 241 (S831). The multi-coil control unit 241 turns off all switches connected to the coil 160.

[0189] Then, the zero points of the X, Y, and Z axes of the TMS coil, face recognition module 2311, and medical image analysis module 2312 can be mapped (S84). Here, the zero points of the TMS coil and the face recognition module 2311 can be zero points that reflect correction values ​​using the correction bar 163.

[0190] Once zero-point mapping is complete, the position information points of the face recognition module 2311 and the medical image analysis module 2312 can be mapped (S85). Here, the position information point of the face recognition module 2311 can be the zero point that reflects the correction value using the correction bar 163.

[0191] Once the above image integration is complete, the multi-coil control unit 241 is turned on (S861), and at least one of the coils 160 located in the helmet-type magnetic stimulation unit 162 at the position corresponding to the position information point is controlled to generate a magnetic field. At this time, the multi-coil control unit 241 can be turned on for only the selected coil 160.

[0192] In one embodiment, the multi-coil control unit 241 can select different coils 160 to be turned on depending on the treatment method, and can select and turn on one or more coils. Furthermore, the multi-coil control unit 241 can control one or more coils 160 to change at least one of the frequency, period, and pulse pattern simultaneously or with a time difference.

[0193] Therefore, the position data calculation unit 231 can calculate position data including real-time 3D coordinates that reflect the correction value, transmit the position data to the motion threshold control module 232 to control the coil 160 positioned at a location corresponding to the motor cortex to generate a magnetic field in order to measure the motion threshold, or transmit the position data to the multi-coil control unit 241 to determine the position of each coil 160 corresponding to the brain region being stimulated.

[0194] On the other hand, according to yet another embodiment of the present invention, the brain stimulator includes a magnetic field generator 100 which includes a plurality of coils 160 that generate a magnetic field to stimulate brain regions, a helmet-type magnetic stimulator 162 in which the plurality of coils 160 are densely arranged in a helmet-type fixing part worn on the user's head, a magnetic field adjustment module 1101 that adjusts magnetic field-related parameters to control the magnetic field output of the coils 160, and a motor threshold measurement module 1102 that measures the user's motor threshold using the magnetic field adjustment module 1101, and a navigation device 200 which calculates positional data of the brain regions to be stimulated and determines the coils 160 that are positioned at the locations corresponding to the brain regions to be stimulated, wherein the navigation device 200 may further include a multi-coil control unit 241 that transmits an identification mark of at least one of the plurality of coils 160 to the magnetic field generator 100 according to the positional data calculated by the positional data calculation unit 231.

[0195] At this time, using at least one gyro sensor or acceleration sensor connected to the helmet-type magnetic stimulator 162, the occurrence of tilt of the helmet-type magnetic stimulator 162 can be detected, and the position information points of the camera image can be corrected considering the correction data calculated from the tilt angle of the helmet-type magnetic stimulator 162. Based on the corrected position information points, an identification marker for at least one of the multiple coils 160 positioned corresponding to the brain region to be stimulated can be transmitted to the magnetic field generator 100.

[0196] In other words, according to the present invention or another embodiment, a helmet-type magnetic stimulation unit 162 may be included in which the correction bar 163 is not connected.

[0197] As shown in Figure 12, the sensor unit 510 can be placed on the helmet-type magnetic stimulation unit 162 instead of the correction bar 163, and the sensor unit 510 may include a gyro sensor or an accelerometer. The sensor unit 510 may be provided with one or more sensors.

[0198] According to yet another embodiment of the present invention, the face recognition module 2311 can detect tilt from the sensor unit 510. Specifically, after detecting position information points (S47), setting the zero points of the X, Y, and Z axes (S49), and before extracting the position of each position information point (S50), if the sensor unit 510 detects that the helmet-type magnetic stimulator 162 has tilted, a correction value can be reflected in the position information points using the tilt angle obtained from the sensor unit 510.

[0199] Instead of using the 3D camera unit 220 to reflect the correction value, the sensor unit 510 can be used to accurately detect whether or not the device is being worn and perform calibration.

[0200] Alternatively, the correction bar 163 and the sensor unit 510 can all be placed on the helmet-type magnetic stimulation unit 162. The 3D camera unit 220 can be used to calculate the angle of inclination of the correction line of the correction bar 163 and the distance to each position information point, and a corrected position information point 1 can be obtained that reflects this. The gyro sensor or acceleration sensor of the sensor unit 510 can be used to calculate the inclination angle, and a corrected position information point 2 can be obtained that reflects this.

[0201] Then, by optimizing location information point 1 and location information point 2, it is possible to extract the final location information point and zero point that reflect all of them. By increasing the number of parameters to consider, it is possible to obtain location data for location points more accurately.

[0202] Furthermore, according to one embodiment of the present invention, if the location information points obtained using AI from a big data server differ from the final location information point values ​​obtained by reflecting the correction values, the coefficient for optimizing the location information points can be modified, and the location information points can be recalculated.

[0203] Through the process described above, it is possible to search for user-customized location information points by comprehensively considering the morphology of the upper head or brain, distance, etc., which differ for each user. This allows for more accurate detection of location points in a shorter time, saving costs and time, and further increasing treatment efficiency.

[0204] Furthermore, a navigation device using a robotic arm 161 according to one embodiment of the present invention can be used as hospital equipment, thereby reducing personnel and time, and a navigation device using a helmet-type magnetic stimulation unit 162 according to another embodiment of the present invention can be used as home equipment. Magnetic field stimulation can be performed without another medical person, and the results of the magnetic field stimulation can be saved via a server, allowing medical personnel to manage the magnetic field stimulation remotely.

[0205] On the other hand, Figure 13 is a simplified diagram showing the arrangement of the coil 160 in the helmet-type magnetic stimulation unit 162 according to another embodiment of the present invention, and Figure 14 shows the structure of the coil 160 in the helmet-type magnetic stimulation unit 162 according to another embodiment of the present invention.

[0206] Although shown in Figure 13 as a triangular shape, the helmet-type magnetic stimulation unit 162 can include any form that can be placed on the user's head and positioned to surround a brain region, and its form is not limited by the exemplary embodiment described above.

[0207] Furthermore, the helmet-type magnetic stimulation unit 162 has a correction bar 163 connected to its lower end, and by sensing if the correction bar 163 is tilted or misaligned, it can sense whether the user is wearing the helmet-type magnetic stimulation unit 162 in the correct position and provide information to correct the tilt.

[0208] As one embodiment, as shown in Figure 13(a), the coils 160 can be arranged in the helmet-type magnetic stimulation unit 162 at regular intervals. The above regular intervals can be adjusted in various ways, but it is preferable that they be densely arranged so that each coil can stimulate a brain region.

[0209] Furthermore, as an embodiment, as shown in Figure 13(b), the coil 160 can be made by arranging figure-eight coils at regular intervals. In a figure-eight coil, a sharp magnetic field is formed at the point where the two circles touch, allowing for precise stimulation only at the point where magnetic field stimulation is to be applied. The above figure-eight coils can be densely arranged within the helmet-type magnetic stimulation unit 162.

[0210] In this case, Figure 13(b) shows a figure-eight coil arrangement, and it appears that no coils are placed on the outside of the helmet-type magnetic stimulation unit 162. However, this is a cross-section of the helmet-type magnetic stimulation unit 162, and in reality, the helmet-type magnetic stimulation unit 162 has a three-dimensional form, and figure-eight coils can be densely arranged on the outside as well, with the direction of the coils changed.

[0211] Furthermore, in another embodiment, the coils 160 can be arranged to overlap, as shown in Figure 13(c). Using an eight-shaped coil as shown in Figure 13(b) is efficient for stimulating only specific locations because a sharp electromagnetic force is formed at the point where the two coils come into contact. Using a coil structure in an overlapping configuration as shown in Figure 13(c) increases the area affected by the magnetic field, thereby increasing the electromagnetic force that stimulates the brain with each unit coil.

[0212] Figure 13(c) also shows no coils on the outside of the helmet-type magnetic stimulation unit 162, but this is a cross-section of the helmet-type magnetic stimulation unit 162, and the actual helmet-type magnetic stimulation unit 162 has a three-dimensional form in which figure-eight coils can be densely arranged on the outside as well, with the direction of the coils changed.

[0213] As shown in Figure 13, when placing the coils 160 in the helmet-type magnetic stimulation unit 162, the coils 160 can be placed at regular intervals, paired figure-eight coils can be placed, or the coils 160 can be placed so that they overlap. Furthermore, the arrangement of the coils can be changed depending on the situation via the helmet coil structure shown in Figure 14.

[0214] In other words, a motor is connected to at least one of the coils 160a arranged in the helmet-type magnetic stimulation unit 162, and the multi-coil control unit 241 can control the motor so that the coil 160a to which the motor is connected overlaps with at least one of the surrounding coils 160b, thereby determining whether the coil 160a to which the motor is connected moves, the direction of movement, and the distance of movement.

[0215] The peripheral coils 160b refer to coils that are not connected to a motor and are positioned around coil 160a so that coil 160a, to which the motor is connected, can approach. In one embodiment shown in Figure 14, assuming nine coils make up one set, the eight coils located above, below, to the left, right, and diagonally opposite the central coil 160a are designated as peripheral coils 160b.

[0216] As shown in Figure 14, coils 160 are arranged at regular intervals in the helmet-type magnetic stimulation unit 162 (shown by solid lines). The coils 160 may include coils 160a, each having a motor attached to at least one of them, and coils 160b, which are fixed in their positions without motors (coils 160a are shown by thick solid lines, and coils 160b are shown by thin solid lines). The motor-equipped coils 160a are movable in the up, down, left, right, and diagonal directions, as indicated by the arrows, and can move toward the fixed coils 160b to form contacts in a pair or to overlap.

[0217] If the coil 160 is fixed in a specific position, it is difficult to change the position of the coil 160 even if it is not possible to accurately stimulate the brain. For example, if stimulation of the upper region of the brain is required while the helmet-type magnetic stimulator 162 is accurately worn via the correction bar 163, moving the motor-equipped coil 160a upwards and overlapping it with coil 160b increases the area over which the magnetic field reaches the upper region, thereby adjusting the position or area of ​​the brain region to be stimulated.

[0218] To give another example, if the brain region to be stimulated is located diagonally downwards, the motor-equipped coil 160a can be moved diagonally downwards, overlapping with coil 160b, and its area and position can be adjusted so that a magnetic field reaches the relevant region.

[0219] In Figure 14, a motor is mounted on coil 160a located in the center, with nine coils 160 forming a set. However, this is merely an exemplary embodiment, and modifications and substitutions are possible within the scope that can be obviously derived by an ordinary technician in the art.

[0220] In other words, the coil 160 can be selected from a variety of coils, such as a single circular coil or an eight-shaped coil, and the arrangement of the coils 160 can also be selected from a variety of configurations, such as arranging them at regular intervals, arranging them densely without intervals, or arranging them in a connected manner so as to overlap, and a motor can be attached to at least one coil to move the position of the coil. This can be determined by considering the area to be treated, such as the brain region to be stimulated, or the target of treatment.

[0221] The present invention is not limited by the embodiments described above and the accompanying drawings. The scope of the patent is to be limited by the accompanying claims, and it will be apparent to those with ordinary skill in the art that various forms of substitution, modification, and alteration are possible without departing from the technical idea of ​​the invention as described in the claims. [Explanation of Symbols]

[0222] 100 Magnetic field generator 110 Control unit 1101 Magnetic Field Adjustment Module 1102 Motor Threshold Measurement Module 120 power modules, 130 communication modules 140 Cooling Modules 150 User Interfaces 151 Input module 152 Output module 160 Coil 161 Robot Arm 162 Helmet-type magnetic stimulation unit 163 Correction bar 200 Navigation System 210 3D Medical Image Storage Unit 220 3D camera unit 230 Control unit 231 Position data calculation unit 2311 Face recognition module 2312 Medical Image Analysis Module 2313 Image Mapping Module 232 Motion threshold control module 240 RC control unit 241 Multi-coil control unit 250 Temperature monitoring unit 260 Communication Module 270 Power Module 300 Integrated Operator 301 User Interface 302 Second Memory 400 Cognitive Training Device 401 User Interface 402 First Memory 500 ECG sensor 510 Sensor unit

Claims

1. As a navigation device, A 3D camera unit that captures the user and acquires a 3D camera image; A coil position guidance navigation device including a position data calculation unit that maps the camera image to a 3D medical image containing brain region information, or maps the 3D medical image to the camera image to obtain a mapped image, and calculates real-time 3D coordinates as position data of the brain region to be stimulated from the mapped image; and This includes a magnetic field generator that performs magnetic stimulation on the brain region of the user, The position data calculation unit includes a medical image analysis module that detects the motor cortex and the location of the brain region to be stimulated from the brain region of the medical image, and calculates real-time 3D coordinates corresponding to the motor cortex and the location of the brain region to be stimulated from the mapped image and provides them to the magnetic field generator. The position data calculation unit corrects the zero points that are set in advance in the camera image or the medical image based on the mapped image, and calculates the real-time 3D coordinates in the mapped image based on the corrected zero points. The magnetic field generator performs magnetic stimulation on the user's brain region with a magnetic field strength determined according to the motion threshold measured in the real-time 3D coordinates corresponding to the motor cortex among the calculated real-time 3D coordinates. A brain stimulation device including a navigation device for guiding coil position.

2. The position data calculation unit, The image is divided according to the resolution of the camera image or the medical image, and the position of a pre-set facial protrusion or groove is detected for each of the divided images. A brain stimulation device including a coil position guidance navigation device according to claim 1, which determines the final position of the facial protrusion or groove by determining the average value of the positions of the facial protrusion or groove, and generates mesh data for the camera image or the medical image taking the final position of the facial protrusion or groove into consideration.

3. Brain stimulation device including a coil position guidance navigation device according to claim 1, wherein the position data calculation unit matches at least one piece of data—a position information point in the camera image which differs depending on the user, a mapping point in the medical image which differs depending on the user, and a matching point between the position information point and the mapping point—with user information and stores it on a server.

4. A brain stimulation device including a coil position guidance navigation device according to claim 3, further comprising a cloud server that receives and stores data stored on the aforementioned server.

5. The position data calculation unit, This includes an artificial intelligence model trained via artificial intelligence using data from the aforementioned server, A brain stimulation device including a coil position guidance navigation device according to claim 3, which uses the artificial intelligence model to extract at least one of a position information point in the camera image, a mapping point in the medical image, and a matching point between the position information point and the mapping point.

6. The aforementioned magnetic field generating device is A brain stimulation device including a coil position guidance navigation device according to claim 1, comprising: a coil that generates a magnetic field to stimulate a region of the user's brain; a robotic arm connected to the coil and driven to move the position of the coil; a magnetic field adjustment module that adjusts magnetic field-related parameters to control the magnetic field output of the coil; and a motion threshold measurement module that measures the user's motion threshold using the magnetic field adjustment module.

7. A brain stimulation device including a coil position guidance navigation device according to claim 6, which includes an RC control unit that receives position data calculated by the position data calculation unit and controls the direction of movement or rotation axis of the robot arm's motor according to the position data.

8. The RC control unit maps the zero point of the robot arm to the zero point of the mapped image, and drives the robot arm in five or more axes. A brain stimulation device including a coil positioning navigation device according to claim 7, wherein the robot arm is positioned at a mapped zero point before being moved.

9. The cognitive training device includes, in conjunction with the magnetic field generator, a device that performs cognitive training by presenting pre-set problems corresponding to the brain regions stimulated by the magnetic field generator, so as to activate those brain regions after the magnetic field generator has stimulated the brain, or, Brain stimulation device including a coil positioning navigation device according to claim 6, further comprising an integrated operator that is communicated with the magnetic field generator and the cognitive training device and drives the magnetic field generator and the cognitive training device simultaneously or alternately.

10. The system further includes a motor threshold control module that positions the coil at a corresponding position in the upper head region to the motor cortex position in the brain region. The motion threshold control module is A brain stimulation device including a coil position guidance navigation device according to claim 6, wherein, if a motor threshold is not measured, the RC control unit is driven so that the robot arm traces a circle within a preset range centered on the determined motor cortex position and the corresponding head position.

11. The aforementioned magnetic field generating device is Brain stimulation device including a coil position guidance navigation device according to claim 1, comprising: a plurality of coils that generate a magnetic field to stimulate a region of the user's brain; a helmet-type magnetic stimulation unit in which the plurality of coils are densely arranged in a helmet-type fixing unit worn on the user's head; a magnetic field adjustment module that controls the magnetic field output of the coils by adjusting magnetic field-related parameters; and a motor threshold measurement module that measures the user's motor threshold using the magnetic field adjustment module.

12. Brain stimulation device including a coil position guidance navigation device according to claim 11, further comprising a multi-coil control unit that selects at least one of a plurality of coils according to position data calculated by the position data calculation unit and transmits an identification mark of the selected coil to the magnetic field generator.

13. The multi-coil control unit is A brain stimulation device including a coil positioning navigation device according to claim 12, which controls the switching of switches connected to each coil to determine whether each coil is on or off.

14. A brain stimulation device including a coil positioning navigation device according to claim 12, wherein the coils are connected in a figure-eight coil configuration or each coil is connected so as to overlap the other coils.

15. The helmet-type magnetic stimulation unit includes a calibration bar horizontally positioned at the lower end of the fixed portion. The aforementioned navigation device is A brain stimulation device including a coil position guidance navigation device according to claim 11, wherein the tilt angle of the correction bar or the distance to a position information point in the camera image is obtained using the 3D camera unit, the position information point is corrected considering the correction data calculated from the angle or distance of the correction bar, and at least one identification marker of a plurality of coils positioned to correspond to a brain region to be stimulated based on the corrected position information point is transmitted to the magnetic field generator.

16. The aforementioned navigation device is Using at least one of the gyro sensor or acceleration sensor connected to the helmet-type magnetic stimulator, the tilt of the helmet-type magnetic stimulator is detected. A brain stimulation device including a coil position guidance navigation device according to claim 11, which corrects the position information points of the camera image taking into consideration correction data calculated from the tilt angle of the helmet-type magnetic stimulator, and transmits to the magnetic field generator an identification marker for at least one of a plurality of coils positioned to correspond to the brain region to be stimulated based on the corrected position information points.

17. A motor is connected to at least one of the coils arranged in the helmet-type magnetic stimulation unit. Brain stimulation device including a coil position guidance navigation device according to claim 12, wherein the multi-coil control unit controls the motor so that the coil to which the motor is connected overlaps with at least one of the surrounding coils, and determines at least one of the presence or absence of movement, direction of movement, and distance of movement of the coil to which the motor is connected.

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