CN114305730B - Method and device for searching hand movement hot spot based on brain network group map - Google Patents
Method and device for searching hand movement hot spot based on brain network group mapInfo
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- CN114305730B CN114305730B CN202111593302.0A CN202111593302A CN114305730B CN 114305730 B CN114305730 B CN 114305730B CN 202111593302 A CN202111593302 A CN 202111593302A CN 114305730 B CN114305730 B CN 114305730B
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Abstract
The invention provides a method and a device for searching hand movement hot spots based on brain network group maps, wherein the method comprises the steps of determining a hand movement region by registering the brain network group maps to medical image data of a tested person, planning a N positioning target spot matrix on the scalp of the tested person according to the hand movement region, positioning coils of a transcranial magnetic stimulator arranged on a mechanical arm on each positioning target spot of the positioning target spot matrix one by one, acquiring the maximum peak value at each positioning target spot, and determining the hand movement hot spot according to the position of each positioning target spot and the corresponding maximum peak value. According to the invention, the function of automatically searching the hand movement hot spot is realized by combining the medical data of the tested person, the brain network group map, the visual sensor, the mechanical arm, the transcranial magnetic stimulation instrument and the like, so that the manpower and the operation time are saved, and the treatment efficiency is improved.
Description
Technical Field
The invention relates to the technical field of medical treatment, in particular to a method and a device for searching for hand movement hot spots based on brain network group maps.
Background
Transcranial magnetic stimulation (TRANSCRANIAL MAGNETIC Stimulation, TMS) is a non-invasive neuromodulation technique used to study human neurophysiology, as well as treatment of neurological disorders. The hand exercise hotspots (Hand Motor Hotspot, hMHS) refer to the cerebral cortex under TMS where exercise evoked potentials (Motor Evoked Potential, MEP) are most easily elicited, and are used to determine the resting (resting) or active (active) exercise Threshold (MT) of the subject individual. The intensity of the stimulus that induces MEPs is often used as a reference value for determining individual specific stimulus intensity. Therefore, determining the hand movement hot spot is a common operation in TMS treatment, and the positioning accuracy directly affects the stimulation parameters, thereby affecting the curative effect of TMS. In existing transcranial magnetic stimulation clinical practice, finding hMHS is typically done manually. The medical staff manually adjusts the position of the coil according to the navigation system to continuously try by mistake, judges whether the coil is found according to the response of the tested person to the stimulus, and the coil has certain weight, so that the process is time-consuming and labor-consuming, the working efficiency of the medical staff is reduced, and the uncomfortable feeling of the tested person is increased.
Disclosure of Invention
The invention provides a method and a device for searching a hand movement hot spot based on a brain network group map, which are used for solving the defects of low detection efficiency and increased discomfort of a tested person in the prior art, realizing the purposes of saving manpower and operation time and improving the treatment efficiency.
In a first aspect, the present invention provides a method for searching for a hand movement hotspot based on a brain network group map, including:
Registering the brain network group map to the medical image data of the tested person to determine a hand movement region;
planning a N-by-N positioning target matrix on the scalp of a tested person according to the hand movement area;
Positioning a coil of a transcranial magnetic stimulation instrument arranged on a mechanical arm on each positioning target point of the positioning target point matrix;
obtaining the maximum peak value at each positioning target point;
and determining a hand movement hot spot according to the position of each positioning target point and the corresponding maximum peak value.
Further, according to the method for searching for a hand movement hot spot based on the brain network group map provided by the invention, the registering of the brain network group map to the medical image data of the tested person determines a hand movement region, and the method specifically comprises the following steps:
mapping an upper limb movement region of a brain network group map onto medical image data of the tested person, and taking a region formed by the center of the brain region to the projection point of the medical image of the tested person on the surface of the cortex as a hand movement region.
Further, according to the method for searching for a hand movement hot spot based on a brain network group map provided by the invention, the positioning target matrix of n×n is planned on the scalp of the tested person according to the hand movement region, which specifically comprises:
Taking the central position of the manual movement area as an initial target point;
constructing an initial path according to the initial target point and the point normal vector direction of the initial target point;
Taking the intersection point of the initial path and the scalp three-dimensional model as a central position;
constructing an N-by-N planar target matrix based on the central position;
constructing an initial target matrix according to the N-N planar target matrix;
determining the nearest point of each target point on the scalp surface according to the initial target point matrix;
and determining an N positioning target matrix according to the nearest point.
Further, according to the method for searching for a hand movement hot spot based on the brain network group map provided by the invention, the method for positioning the coils of the transcranial magnetic stimulation instrument arranged on the mechanical arm on each positioning target point of the positioning target point matrix one by one specifically comprises the following steps:
constructing a space mapping relation between the testee and the mechanical arm;
acquiring a head relative movement result of a tested person monitored in real time by a vision sensor;
correcting the spatial motion relation according to the relative motion result to obtain a final spatial conversion relation;
and positioning a coil of the transcranial magnetic stimulation instrument arranged on the mechanical arm to each positioning target point of the positioning target point matrix according to the space conversion relation.
Further, according to the method for searching for a hand motion hot spot based on a brain network group map provided by the present invention, the determining a hand motion hot spot according to the position of each positioning target point and the corresponding maximum peak value specifically includes:
acquiring a first three-dimensional coordinate of each positioning target point in the initial target point matrix;
Converting the first three-dimensional coordinates into spherical coordinates;
performing three-dimensional surface fitting according to a two-dimensional coordinate formed by zenith angles and azimuth angles in the spherical coordinates and the maximum peak value corresponding to each positioning target point to obtain a three-dimensional surface;
Determining a first two-dimensional coordinate corresponding to a point with the largest peak value on the three-dimensional curved surface;
Converting the first two-dimensional coordinates to second three-dimensional coordinates;
and determining the point closest to the second three-dimensional coordinate on the scalp of the tested person as a hand movement hot spot.
Further, according to the method for searching for a hand movement hot spot based on the brain network group map provided by the invention, the construction of the spatial mapping relationship between the testee and the mechanical arm specifically comprises the following steps:
acquiring first coordinates of probes with tracking and positioning markers at a plurality of facial feature points of a tested person through a visual sensor;
collecting second coordinates of the facial feature points in the space of the testee;
determining a first transformation matrix according to the first coordinate and the second coordinate;
Acquiring third coordinates of a plurality of position points of the tracking and positioning marker on the mechanical arm in the visual sensor near the head of the tested person and fourth coordinates in the space of the mechanical arm;
determining a second transformation matrix according to the third coordinate and the fourth coordinate;
and determining a spatial mapping relation between the space of the tested person and the space of the mechanical arm according to the first conversion matrix and the second conversion matrix.
In a second aspect, the present invention provides a device for searching for a hand movement hotspot based on a brain network group map, including:
the manual movement region determining module is used for registering the brain network group map to the medical image data of the tested person to determine a hand movement region;
the positioning target matrix determining module is used for planning an N-by-N positioning target matrix on the scalp of the tested person according to the hand movement area;
the fixing module is used for positioning the coils of the transcranial magnetic stimulation instrument arranged on the mechanical arm on each positioning target point of the positioning target point matrix one by one;
the peak value acquisition module is used for acquiring the maximum peak value at each positioning target point;
And the hand movement hot spot acquisition module is used for determining hand movement hot spots according to the position of each positioning target point and the corresponding maximum peak value.
In a third aspect, the present invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the method for searching for hand motion hotspots based on brain network group map as described in any one of the above when executing the program.
In a fourth aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of a method of finding a hand motion hotspot based on a brain network group map as described in any one of the above.
In a fifth aspect, the present invention also provides a computer program product comprising a computer program which when executed by a processor performs the steps of a method of finding a hand motion hotspot based on a brain network group map as described in any one of the above.
The invention provides a method and a device for searching hand movement hot spots based on a brain network group map, which are used for determining a hand movement region by registering medical image data of a tested person on the brain network group map, planning a N positioning target point matrix on the scalp of the tested person according to the hand movement region, positioning a coil of a transcranial magnetic stimulator arranged on a mechanical arm on each target point of the positioning target point matrix, acquiring the maximum peak value at each positioning target point, and determining the hand movement hot spot according to the position of each positioning target point and the corresponding maximum peak value. According to the invention, the function of automatically searching the hand movement hot spot is realized by combining the medical data of the tested person, the brain network group map, the visual sensor, the mechanical arm, the transcranial magnetic stimulation instrument and the like, so that the manpower and the operation time are saved, and the treatment efficiency is improved.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method for searching for hand movement hot spots based on brain network group map;
FIG. 2 is a schematic diagram of a method for determining a hand movement hot spot according to the position of each positioning target point and the corresponding maximum peak value;
fig. 3 is a schematic structural diagram of a device for searching for hand movement hot spots based on brain network group map provided by the invention;
fig. 4 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The following describes a method for searching for hand movement hot spots based on brain network group map with reference to fig. 1, which comprises the following steps:
Step 100, registering a brain network group map to medical image data of a tested person to determine a hand movement region;
Specifically, registering medical image data of a tested person onto a brain network group map, and determining a movement region and hand junction positions.
Step 200, planning N positioning target matrixes on the scalp of a tested person according to the hand movement area;
Specifically, N x N positioning target matrixes are planned on the scalp of the tested person according to the hand movement area, and are used for collecting myoelectric signals on each target matrix.
Step 300, positioning coils of a transcranial magnetic stimulation instrument arranged on a mechanical arm on each positioning target point of the positioning target point matrix one by one;
specifically, a coil of the transcranial magnetic stimulation instrument is fixed on a support with a tracking and positioning marker at the tail end of a mechanical arm, the mechanical arm is automatically positioned to a target point of a target point matrix, and the transcranial magnetic stimulation instrument is controlled to automatically stimulate each time when the mechanical arm is positioned to one target point.
Step 400, obtaining the maximum peak value at each positioning target point;
specifically, the transcranial magnetic stimulation instrument is controlled to automatically give single pulse stimulation, meanwhile, the electromyographic signals of the tested person at the target point are collected, and the maximum peak-to-peak value of the electromyographic signals is calculated.
And 500, determining a hand movement hot spot according to the position of each positioning target point and the corresponding maximum peak value.
Specifically, after all target points of the target point matrix are positioned, stimulated and electromyographic signal peaks and peaks are calculated, curve fitting is performed, and the point with the largest peak and peak value in the coverage area of the target point matrix is calculated, wherein the point is the found hand movement hot spot.
The invention provides a method for searching a hand movement hot spot based on a brain network group map, which comprises the steps of registering medical image data of a tested person to the brain network group map to determine a hand movement region, planning a positioning target point matrix of N x N on the scalp of the tested person according to the hand movement region, positioning a coil of a transcranial magnetic stimulator arranged on a mechanical arm to each target point of the positioning target point matrix, acquiring the maximum peak value at each target point, and determining the hand movement hot spot according to the position of each target point and the corresponding maximum peak value. According to the invention, the function of automatically searching the hand movement hot spot is realized by combining the medical data of the tested person, the brain network group map, the visual sensor, the mechanical arm, the transcranial magnetic stimulation instrument and the like, so that the manpower and the operation time are saved, and the treatment efficiency is improved.
Further, according to the method for searching for a hand movement hot spot based on the brain network group map provided by the invention, the registering of the brain network group map to the medical image data of the tested person determines a hand movement region, and the method specifically comprises the following steps:
mapping an upper limb movement region of a brain network group map onto medical image data of the tested person, and taking a region formed by the center of the brain region to the projection point of the medical image of the tested person on the surface of the cortex as a hand movement region.
Specifically, the brain network group map is registered to the medical image data of the tested person, and the hand junction position is determined, which is characterized in that the movement region (the left side number 57 and the right side number 58) of the brain network group map is mapped to the image of the individual, and the projection point from the center of the brain region to the surface of the cortex is taken as a center target point, namely the hand movement region.
Further, according to the method for searching for a hand movement hot spot based on a brain network group map provided by the invention, the positioning target matrix of n×n is planned on the scalp of the tested person according to the hand movement region, which specifically comprises:
Taking the central position of the manual movement area as an initial target point;
constructing an initial path according to the initial target point and the point normal vector direction of the initial target point;
Taking the intersection point of the initial path and the scalp three-dimensional model as a central position;
constructing an N-by-N planar target matrix based on the central position;
constructing an initial target matrix according to the N-N planar target matrix;
determining the nearest point of each target point on the scalp surface according to the initial target point matrix;
and determining an N positioning target matrix according to the nearest point.
Specifically, an initial path is planned. On a three-dimensional model of the gray matter of a tested person, a path is planned by taking the central position of a hand movement area as an initial target point, the path direction is the point normal vector direction of the target point, and the path is taken as the initial path. Because the three-dimensional model is a triangular mesh model, when the initial target point is a vertex on the triangular mesh model, the normal vector of the point is the average value of the normal vectors of all triangular patches sharing the vertex, and when the initial target point is on the triangular patch, the normal vector of the point is the normal vector of the triangular patch where the point is located.
Planning an initial target matrix. The intersection point of the initial path and the scalp three-dimensional model is taken as the central position of the target matrix, the normal vector of the point at the central position of the matrix points along the direction of the inner side of the scalp, the point 500mm away from the central position of the matrix is taken as the origin point of the spherical coordinate system, the normal vector direction of the point at the center of the matrix is the Z-axis direction of the spherical coordinate system, and the central position of the matrix is on the spherical surface. Setting the row spacing and the column spacing of the target point matrix to be d mm, setting the row and the column spacing of the target point matrix to be N, setting the normal vector of the plane where the matrix is located perpendicular to the central position of the matrix, and projecting the target point matrix onto the spherical surface according to the position of the target point in the matrix and the conversion relation between the spherical coordinate system and the rectangular coordinate system, so that N-times-N target points are uniformly distributed on the spherical surface. The center position of the matrix is kept unchanged, and the radius of the sphere where the target point matrix is located and the direction of the whole target point matrix on the X, Y, Z axis taking the center of the matrix as the rotation center are finely adjusted, wherein the X axis direction is the direction of a coil handle, so that targets on the target point matrix approximately fall on the surface of the scalp. The target matrix at this time is the initial target matrix.
Planning and positioning a target matrix. And respectively calculating the nearest point on the scalp surface to the target point on the target point matrix and the normal vector of the nearest point on the scalp, wherein the nearest point on the scalp is the target point for final positioning, and the normal vector direction of the nearest point on the scalp is the direction perpendicular to the coil surface when the nearest point reaches the target point, so as to obtain the N-by-N positioning target point matrix.
Further, according to the method for searching for a hand movement hot spot based on the brain network group map provided by the invention, the positioning of the coil of the transcranial magnetic stimulation device arranged on the mechanical arm to each target point of the positioning target point matrix specifically comprises the following steps:
constructing a space mapping relation between the testee and the mechanical arm;
acquiring a head relative movement result of a tested person monitored in real time by a vision sensor;
correcting the spatial motion relation according to the relative motion result to obtain a final spatial conversion relation;
and positioning the coils of the transcranial magnetic stimulation instrument arranged on the mechanical arm on each positioning target point of the positioning target point matrix one by one according to the space conversion relation.
Specifically, a spatial mapping relation between the tested person and the mechanical arm is constructed, namely, the space of the tested person and the space of the mechanical arm are mutually converted, so that the path from the mechanical arm to the tested person is determined. The subject space is registered. The coordinates of the probe tip can be obtained by a visual sensor using a probe with a tracking and positioning marker. The probe tip is placed at a plurality of facial feature points (the number of points is more than or equal to 4) of a tested person, wherein any 4 points are not coplanar, and coordinates of the facial feature points under a vision sensor are collected. Under the medical image space, acquiring coordinates of facial feature points corresponding to a tested person under the tested person space, registering the coordinates of two groups of facial feature points through SVD algorithm to obtain a conversion matrix of the tested person space and the vision sensor space
And registering the space of the mechanical arm. Dragging the tail end of the mechanical arm, moving the tracking and positioning marker on the tool at the tail end of the mechanical arm to a plurality of positions (the number of the positions is more than or equal to 4) near the head of a tested person in the visual field of the visual sensor, acquiring the coordinates of the tracking and positioning marker in the space of the visual sensor and the space of the mechanical arm simultaneously when any 4 points are not coplanar and move to one position, registering the two groups of coordinates through SVD algorithm to obtain a conversion matrix of the space of the mechanical arm and the space of the tested person
Obtaining the conversion relation between the space of the tested person and the space of the mechanical arm according to the conversion matrix between the space of the tested person and the space of the visual sensor and the result of the conversion matrix between the space of the mechanical arm and the space of the tested person
The method comprises the specific steps of fixing a head binding band with a tracking and positioning marker on the head of a tested person, and ensuring that the positioning marker on the head binding band does not move relatively to the head of the tested person in the treatment process. Real-time acquisition of pose of head strap tracking and positioning marker under vision sensor space through vision sensorCalculating a conversion matrix of head strap positioning marker space and subject spaceAcquiring pose of moving back head strap tracking positioning marker under vision sensor spaceCalculating the change of the position and the posture of the head binding belt tracking and positioning marker before and after movement Calculating the change of the pose of the testee before and after movement Calculating a conversion matrix of the space of the subject after movement and the space of the vision sensorCalculating a conversion matrix of the space of the mechanical arm and the space of the tested person after movingCalculating pose of target point in space of mechanical arm after movementAnd obtaining the target pose of the mechanical arm after motion compensation at the target point.
And further, according to the compensated target pose, determining a moving target of the mechanical arm.
Further, as shown in a-C of fig. 2, the method for searching for a hand motion hotspot based on a brain network group map provided by the present invention, wherein the determining a hand motion hotspot according to the position of each positioning target and the corresponding maximum peak value specifically includes:
acquiring a first three-dimensional coordinate of each positioning target point in the initial target point matrix;
Converting the first three-dimensional coordinates into spherical coordinates;
performing three-dimensional surface fitting according to a two-dimensional coordinate formed by zenith angles and azimuth angles in the spherical coordinates and the maximum peak value corresponding to each positioning target point to obtain a three-dimensional surface;
Determining a first two-dimensional coordinate corresponding to a point with the largest peak value on the three-dimensional curved surface;
Converting the first two-dimensional coordinates to second three-dimensional coordinates;
and determining the point closest to the second three-dimensional coordinate on the scalp of the tested person as a hand movement hot spot.
Specifically, a target point on a spherical surface in an initial target point matrix is converted into a spherical coordinate system according to the conversion relation between a three-dimensional rectangular coordinate system and the spherical coordinate system, and the radius r of the target point in the spherical coordinate system is the same on the initial target point matrix, so that the zenith angle theta and the azimuth angle of the spherical coordinate of the target point are determinedAs two-dimensional coordinates of the target. Two-dimensional coordinates of the target after transformationAs x and y coordinates, a three-dimensional surface fitting is performed using a thin-plate spline interpolation method in combination with the maximum peak value p of the electromyographic signal at the target point as a z coordinate. Finding out the point with the maximum peak value on the curved surface, and using the two-dimensional coordinates of the pointThe point is transformed into three-dimensional space in combination with the radius r of the spherical coordinates. Finding the nearest point of the scalp surface to the above point, which is the found hand movement hot spot
Further, according to the method for searching for a hand movement hot spot based on the brain network group map provided by the invention, the construction of the spatial mapping relationship between the testee and the mechanical arm specifically comprises the following steps:
acquiring first coordinates of probes with tracking and positioning markers at a plurality of facial feature points of a tested person through a visual sensor;
collecting second coordinates of the facial feature points in the space of the testee;
determining a first transformation matrix according to the first coordinate and the second coordinate;
Acquiring third coordinates of a plurality of position points of the tracking and positioning marker on the mechanical arm in the visual sensor near the head of the tested person and fourth coordinates in the space of the mechanical arm;
determining a second transformation matrix according to the third coordinate and the fourth coordinate;
and determining a spatial mapping relation between the space of the tested person and the space of the mechanical arm according to the first conversion matrix and the second conversion matrix.
Specifically, the subject is spatially registered. The coordinates of the probe tip can be obtained by a visual sensor using a probe with a tracking and positioning marker. The probe tip is placed at a plurality of facial feature points (the number of points is more than or equal to 4) of a tested person, wherein any 4 points are not coplanar, and coordinates of the facial feature points under a vision sensor are collected. Under the medical image space, acquiring coordinates of facial feature points corresponding to a tested person under the tested person space, registering the coordinates of two groups of facial feature points through SVD algorithm to obtain a conversion matrix of the tested person space and the vision sensor space
And registering the space of the mechanical arm. Dragging the tail end of the mechanical arm, moving the tracking and positioning marker on the tool at the tail end of the mechanical arm to a plurality of positions (the number of the positions is more than or equal to 4) near the head of a tested person in the visual field of the visual sensor, acquiring the coordinates of the tracking and positioning marker in the space of the visual sensor and the space of the mechanical arm simultaneously when any 4 points are not coplanar and move to one position, registering the two groups of coordinates through SVD algorithm to obtain a conversion matrix of the space of the mechanical arm and the space of the tested person
Obtaining the conversion relation between the space of the tested person and the space of the mechanical arm according to the conversion matrix between the space of the tested person and the space of the visual sensor and the result of the conversion matrix between the space of the mechanical arm and the space of the tested person
As shown in fig. 3, the present invention provides a device for searching for a hand movement hot spot based on a brain network group map, comprising:
a manual movement region determining module 31 for registering the brain network group map to the medical image data of the subject to determine a hand movement region;
a positioning target matrix determining module 32, configured to plan a positioning target matrix of n×n on the scalp of the subject according to the hand movement region;
a fixing module 33, configured to position the coils of the transcranial magnetic stimulation device disposed on the mechanical arm onto each positioning target point of the positioning target point matrix one by one;
A peak value acquisition module 34, configured to acquire a maximum peak value at each of the positioning targets;
The hand movement hot spot obtaining module 35 is configured to determine a hand movement hot spot according to the position of each positioning target point and the corresponding maximum peak value.
Since the apparatus provided by the embodiment of the present invention may be used to perform the method described in the above embodiment, its working principle and beneficial effects are similar, so that details will not be described herein, and reference will be made to the description of the above embodiment.
The device for searching for the hand movement hot spots based on the brain network group map comprises a step of determining a hand movement area by registering medical image data of a tested person to the brain network group map, a step of planning an N positioning target point matrix on the scalp of the tested person according to the hand movement area, a step of positioning a coil of a transcranial magnetic stimulator arranged on a mechanical arm to each target point of the positioning target point matrix, a step of obtaining the maximum peak value at each target point, and a step of determining the hand movement hot spots according to the position of each target point and the corresponding maximum peak value. According to the invention, the function of automatically searching the hand movement hot spot is realized by combining the medical data of the tested person, the brain network group map, the visual sensor, the mechanical arm, the transcranial magnetic stimulation instrument and the like, so that the manpower and the operation time are saved, and the treatment efficiency is improved.
Further, according to the device for searching for a hand movement hot spot based on the brain network group map provided by the present invention, the manual movement region determining module 31 is specifically configured to:
mapping an upper limb movement region of a brain network group map onto medical image data of the tested person, and taking a region formed by the center of the brain region to the projection point of the medical image of the tested person on the surface of the cortex as a hand movement region.
Further, according to the device for searching for a hand movement hot spot based on the brain network group map provided by the invention, the positioning target matrix determining module 32 is specifically configured to:
Taking the central position of the manual movement area as an initial target point;
constructing an initial path according to the initial target point and the point normal vector direction of the initial target point;
Taking the intersection point of the initial path and the scalp three-dimensional model as a central position;
constructing an N-by-N planar target matrix based on the central position;
constructing an initial target matrix according to the N-N planar target matrix;
determining the nearest point of each target point on the scalp surface according to the initial target point matrix;
and determining an N positioning target matrix according to the nearest point.
Further, according to the device for searching for a hand movement hot spot based on the brain network group map provided by the invention, the fixing module 33 is specifically configured to:
constructing a space mapping relation between the testee and the mechanical arm;
acquiring a head relative movement result of a tested person monitored in real time by a vision sensor;
correcting the spatial motion relation according to the relative motion result to obtain a final spatial conversion relation;
and positioning the coils of the transcranial magnetic stimulation instrument arranged on the mechanical arm on each positioning target point of the positioning target point matrix one by one according to the space conversion relation.
Further, according to the device for searching for a hand movement hot spot based on the brain network group map provided by the present invention, the hand movement hot spot acquisition module 35 is specifically configured to:
acquiring a first three-dimensional coordinate of each positioning target point in the initial target point matrix;
Converting the first three-dimensional coordinates into spherical coordinates;
performing three-dimensional surface fitting according to a two-dimensional coordinate formed by zenith angles and azimuth angles in the spherical coordinates and the maximum peak value corresponding to each positioning target point to obtain a three-dimensional surface;
Determining a first two-dimensional coordinate corresponding to a point with the largest peak value on the three-dimensional curved surface;
Converting the first two-dimensional coordinates to second three-dimensional coordinates;
and determining the point closest to the second three-dimensional coordinate on the scalp of the tested person as a hand movement hot spot.
Further, according to the device for searching for a hand movement hot spot based on the brain network group map provided by the invention, the fixing module 33 is further specifically configured to:
acquiring first coordinates of probes with tracking and positioning markers at a plurality of facial feature points of a tested person through a visual sensor;
collecting second coordinates of the facial feature points in the space of the testee;
determining a first transformation matrix according to the first coordinate and the second coordinate;
Acquiring third coordinates of a plurality of position points of the tracking and positioning marker on the mechanical arm in the visual sensor near the head of the tested person and fourth coordinates in the space of the mechanical arm;
determining a second transformation matrix according to the third coordinate and the fourth coordinate;
and determining a spatial mapping relation between the space of the tested person and the space of the mechanical arm according to the first conversion matrix and the second conversion matrix.
Fig. 4 illustrates a physical schematic diagram of an electronic device, as shown in fig. 4, which may include a processor (processor) 410, a communication interface (Communications Interface) 420, a memory (memory) 430, and a communication bus 440, where the processor 410, the communication interface 420, and the memory 430 perform communication with each other through the communication bus 440. The processor 410 may invoke logic instructions in the memory 430 to perform a method for finding a hand movement hotspot based on a brain network group map, the method comprising registering medical image data of a subject to the brain network group map to determine a hand movement region, planning a localization target matrix of N x N on a scalp of the subject according to the hand movement region, locating a coil of a transcranial magnetic stimulator provided on a robotic arm to each target of the localization target matrix, obtaining a maximum peak-to-peak value at each target, and determining the hand movement hotspot according to a position of each target and the corresponding maximum peak-to-peak value.
Further, the logic instructions in the memory 430 described above may be implemented in the form of software functional units and may be stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. The storage medium includes a U disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, an optical disk, or other various media capable of storing program codes.
In another aspect, the invention further provides a computer program product, the computer program product comprises a computer program, the computer program can be stored on a non-transitory computer readable storage medium, the computer program, when being executed by a processor, can execute a method for searching for hand movement hot spots based on brain network group atlas, the method comprises registering medical image data of a tested person onto the brain network group atlas to determine a hand movement area, planning a positioning target spot matrix of N x and N on scalp of the tested person according to the hand movement area, positioning a coil of a transcranial magnetic stimulator arranged on a mechanical arm onto each target spot of the positioning target spot matrix, acquiring a maximum peak value at each target spot, and determining the hand movement hot spot according to the position of each target spot and the corresponding maximum peak value.
In yet another aspect, the present invention further provides a non-transitory computer readable storage medium having stored thereon a computer program which when executed by a processor is implemented to perform a method of finding a hand motion hotspot based on a brain network group map provided by the above methods, the method comprising registering medical image data of a subject onto a brain network group map to determine a hand motion region, planning a localization target matrix of n×n on a scalp of the subject according to the hand motion region, locating a coil of a transcranial magnetic stimulator provided on a robotic arm onto each target of the localization target matrix, obtaining a maximum peak-to-peak value at each target, and determining a hand motion hotspot according to a position of each target and the corresponding maximum peak-to-peak value.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
It should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention, and not for limiting the same, and although the present invention has been described in detail with reference to the above-mentioned embodiments, it should be understood by those skilled in the art that the technical solution described in the above-mentioned embodiments may be modified or some technical features may be equivalently replaced, and these modifications or substitutions do not make the essence of the corresponding technical solution deviate from the spirit and scope of the technical solution of the embodiments of the present invention.
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