Target region self-adaption-based time coherent electrical stimulation regulation and control method and device

Abstract

The invention relates to a time coherence electrical stimulation regulation and control method based on target region self-adaption. The method comprises the following steps: acquiring image information of a user and constructing a craniocerebral nerve three-dimensional model according to the image information; adding a simulation electrode in the craniocerebral nerve three-dimensional model, and configuring stimulation attributes of the simulation electrode; obtaining position information of a target region, and mapping the target region into the craniocerebral nerve three-dimensional model through a pre-constructed mapping matrix; calculating the volume of the target region according to a preset volume calculation algorithm, obtaining a corresponding electrode layout instruction from a pre-constructed layout mapping library according to the volume of the target region, and configuring the simulation electrode in a corresponding craniocerebral nerve three-dimensional model according to the electrode layout instruction; and configuring a corresponding optimal stimulation parameter through a preset parameter adaptation sub-strategy so as to enable the envelope modulation electric field in the craniocerebral nerve three-dimensional model to be matched with the target region. TI electrical stimulation parameters can be adaptively adjusted, and the problem that existing TI electrical stimulation parameters are difficult to set is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of campus information management, and more specifically, to a method and device for regulating time-coherent electrical stimulation based on target area adaptability. Background Art

[0002] Neurological diseases, including epilepsy, cerebrovascular diseases, depression, and traumatic brain / spinal cord injuries, etc., lead to a series of functional impairments such as walking difficulties and sensory numbness in patients, which are the main causes of global disability and seriously affect the physical and mental health of patients. As a widely used neuroregulation method, electrical stimulation has been proven to have significant effects in regulating abnormal neural activities and has become an important method for treating neurological diseases. (Mueller M, Morgan D. New insights into health financing: First results of the international data collection under the System of Health Accounts 2011 framework. Health Policy, 2017, 121(7): 764-769. And Ye H, Hendee J, Ruan J, et al. Neuron matters: neuromodulation with electromagnetic stimulation must consider neurons as dynamic identities[J]. Journal of NeuroEngineering and Rehabilitation, 2022, 19(1): 116.)

[0003] Traditional electrical stimulation techniques mainly include invasive and non-invasive ones. Compared with the disadvantages of invasive electrical stimulation techniques such as high surgical risks and high costs, non-invasive electrical stimulation is more widely used clinically due to its high safety and low cost. However, for different nerve stimulation target areas, especially deep nerve tissue target areas, its stimulation accuracy is low and the neural effect amount is small, so the treatment effect is limited.

[0004] Temporal Interference (TI) electrical stimulation, as an emerging neuromodulation method, activates deep neural tissues by applying two groups of medium-frequency currents with different frequencies (0 < Δf < 100 Hz) on the skin surface, making them interfere with each other in a specific area and forming a confined low-frequency envelope modulation electric field, thus taking into account non-invasiveness, precision, and the characteristics of activating deep neural tissues. (Grossman N, Bono D, Dedic N, et al. Noninvasive Deep Brain Stimulation via Temporally Interfering Electric Fields[J]. Cell, 2017, 169(6): 1029-1041.e16.). However, due to the limited area of the envelope modulation electric field of TI electrical stimulation and its great influence by neural tissue anatomical parameters and electrical parameters, accurate TI electrical stimulation parameters are required if precise stimulation of the target area is needed.

[0005] The target area of nerve injury is crucial for determining electrical stimulation parameters because it directly affects the distribution of current, the coverage of stimulation, and the effectiveness on target tissues. Smaller injuries require precise low-intensity stimulation to avoid affecting adjacent healthy tissues, while larger injuries require a more extensive stimulation layout and optimized intensity parameters to ensure uniform coverage of the entire injury area. At the same time, the injury volume also changes the electrical conductivity characteristics of local tissues, affecting the current path and stimulation depth. Therefore, reasonable adjustment of stimulation parameters (such as intensity, frequency, and phase) is the key to achieving maximum therapeutic effect. However, the envelope electric fields generated by different stimulation parameters of existing TI electrical stimulation technologies vary greatly, making it difficult to accurately change parameters according to the characteristics of the target area for precise regulation. Therefore, it is urgent to develop a time-coherent electrical stimulation regulation method based on target area self-adaptation. Summary of the Invention

[0006] In view of this, the purpose of the present invention is to provide a time-coherent electrical stimulation regulation method based on target area self-adaptation.

[0007] To solve the above technical problems, the technical solution of the present invention is:

[0008] A time-coherent electrical stimulation regulation method based on target area self-adaptation,

[0009] Step S1, obtain user image information and construct a three-dimensional model of cranial nerves according to the image information;

[0010] Step S2, add simulated electrodes to the three-dimensional model of cranial nerves and configure the stimulation attributes of the simulated electrodes;

[0011] Step S3: Obtain the target area position information and map the target area into the three-dimensional model of cranial nerves through a pre-constructed mapping matrix;

[0012] Step S4: Calculate the volume of the target area according to a preset volume calculation algorithm, obtain the corresponding electrode layout instruction from a pre-constructed layout mapping library according to the volume of the target area, and configure the simulated electrodes in the corresponding three-dimensional model of cranial nerves according to the electrode layout instruction;

[0013] Step S5: Configure the corresponding optimal stimulation parameters through a preset parameter adaptation sub-strategy so that the envelope modulation electric field in the three-dimensional model of cranial nerves matches the target area.

[0014] Furthermore, the user image information includes cranial CT images and MRI images.

[0015] Furthermore, the stimulation attribute of the simulated electrode includes the model response conductivity, and a corresponding conductive effect engine for the three-dimensional model of cranial nerves is generated according to the model response conductivity, and the model response conductivity is generated according to the electrical properties of nerve tissue and the electrical properties of the electrode.

[0016] Furthermore, the volume calculation algorithm is configured as

[0017]

[0018] where V is the volume of the target area, (x1, y1, z1) is the coordinate of the first boundary point of the target area, (x2, y2, z2) is the coordinate of the second boundary point of the target area, (x3, y3, z3) is the coordinate of the third boundary point of the target area, and (x4, y4, z4) is the coordinate of the fourth boundary point of the target area.

[0019] Furthermore, the parameter adaptation sub-strategy includes

[0020] Step S5-1: Obtain new stimulation frequency values and stimulation intensity values and output them in the simulated electrode;

[0021] Step S5-2: Calculate the corresponding total envelope volume through a preset envelope volume calculation algorithm, and calculate the corresponding envelope center coordinates through a preset envelope center coordinate calculation algorithm;

[0022] Step S5-3: Calculate the volume deviation between the total envelope volume and the target area volume and the center coordinate deviation between the envelope center coordinates and the target area center coordinates. If the volume deviation is less than a preset reference volume value and the center coordinate deviation is less than a preset reference center coordinate deviation value, then enter Step S5-4, otherwise return to Step S5-1;

[0023] Step S5-4: Output the current stimulation frequency value and stimulation intensity value as the optimal stimulation parameters.

[0024] Furthermore, the envelope volume calculation algorithm includes

[0025] Calculating the modulation envelope amplitude of the three-dimensional model of cranial nerves under the action of the current simulation electrode, discretizing the space corresponding to the three-dimensional model of cranial nerves to obtain a number of voxels, calculating the voxel signal value of each voxel according to the modulation envelope amplitude, screening the voxels with voxel signal values higher than the preset reference voxel threshold, and calculating the total volume of the screened voxels to obtain the envelope total volume.

[0026] Furthermore, the method for calculating the modulation envelope amplitude is

[0027] R = sqrt(X 2 + Y 2 + Z 2 ), where

[0028]

[0029] wherein, and are the electric fields generated by the first electrode pair and the second electrode pair in the x direction, and are the electric fields generated by the first electrode pair and the second electrode pair in the y direction, and are the electric fields generated by the first electrode pair and the second electrode pair in the z direction. R is the modulation envelope amplitude of the unit vector r(x, y, z).

[0030] Furthermore, the envelope center coordinate calculation algorithm is:

[0031]

[0032] wherein, X i 、Y i 、Z i are the coordinates of each point in the voxels with voxel signal values higher than the preset reference voxel threshold, W i is the corresponding normalized modulation envelope amplitude magnitude, and (X, Y, Z) is the envelope center coordinate.

[0033] The present invention also provides a device adopting the time-coherent electrical stimulation regulation method based on target area self-adaptation, including a simulation electrode, a coherent electrical generating device, and a calculation component, wherein,

[0034] The simulation electrode is connected to the coherent electrical generating device through a lead;

[0035] The calculation component is used to obtain the optimal stimulation parameters according to the time-coherent electrical stimulation regulation method based on target area self-adaptation;

[0036] A coherent electric generating device generates coherent electricity applied to an analog electrode based on the determined optimal electrical stimulation parameters.

[0037] The technical effects of the present invention are mainly reflected in the following aspects: providing a method for regulating time-coherent electrical stimulation based on target area self-adaptation, which can adaptively adjust the stimulation parameters of TI electrical stimulation by confirming the spatial coordinate information of the target area and the envelope electric field characteristics of TI electrical stimulation, and solving the problem of difficult setting of stimulation parameters for existing TI electrical stimulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a schematic diagram of the overall scheme of a method for regulating time-coherent electrical stimulation based on target area self-adaptation of the present invention.

[0039] Figure 2 It is a flowchart of the adaptive adjustment algorithm for TI electrical stimulation parameters;

[0040] Figure 3 It is a schematic diagram of the configuration of a three-dimensional geometric electrical stimulation model for TI electrical stimulation of nerve tissue;

[0041] Figure 4 It is a schematic diagram of TI electrical stimulation parameters for different volume target areas. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] The following further details the specific embodiments of the present invention in conjunction with the drawings, so that the technical solutions of the present invention are easier to understand and master.

[0043] A method for regulating time-coherent electrical stimulation based on target area self-adaptation,

[0044] Step S1, obtaining user image information and constructing a three-dimensional model of cranial nerves according to the image information; the user image information includes cranial CT images and MRI images.

[0045] Through radiomics data, determine the basic three-dimensional spatial coordinate information of the target area, and use the formula to obtain the mapped spatial coordinate information of the target area in the three-dimensional geometric model of the simulation software.

[0046]

[0047] Among them, XMRI, YMRI, and ZMRI are the three-dimensional spatial coordinate information of the target area in the radiomics data, Xsimulation, Ysimulation, and Zsimulation are the three-dimensional spatial coordinate information mapped to the three-dimensional geometric model, and A is the affine transformation matrix from the radiomics coordinate system to the three-dimensional geometric model coordinate system.

[0048] Based on cranial CT and MRI data, a three-dimensional geometric model of cranial nerve tissue is constructed through the GUI geometric modeling module of the simulation software. Electrodes are added to the scalp surface, the anode and cathode are set, and at the same time the tissue conductivity is set to construct a three-dimensional geometric model of TI electrical stimulation of cranial nerve tissue. Figure 3 as the corresponding model.

[0049] Step S2: Add simulated electrodes to the three-dimensional model of cranial nerves and configure the stimulation attributes of the simulated electrodes; the stimulation attributes of the simulated electrodes include the model response conductivity, and a conductive effect engine corresponding to the three-dimensional model of cranial nerves is generated according to the model response conductivity, and the model response conductivity is generated according to the electrical properties of nerve tissue and the electrical properties of electrodes. The specific method is to input literature data into the database to generate a deduction model. Such as bones, muscles, nerves, skin, etc. Then, the conductivity is output according to the input attribute values. For example, the skin conductivity is 0.0025, the fat conductivity is 0.04, the thoracic cavity conductivity is 0.25, the muscle conductivity is 0.5, the vertebral body conductivity is 0.02, and the spinal cord conductivity is 0.72. According to the configuration results, the conductivity distribution can be obtained.

[0050] Step S3: Obtain the target area position information, and map the target area to the three-dimensional model of cranial nerves through the pre-constructed mapping matrix; through the cranial MRI radiomics information, obtain the individualized MRI voxel coordinate information of the target area-reticular system.

[0051] Step S4: Calculate the volume of the target area according to the preset volume calculation algorithm, and obtain the corresponding electrode layout instruction from the pre-constructed layout mapping library according to the volume of the target area, and configure the simulated electrodes in the corresponding three-dimensional model of cranial nerves according to the electrode layout instruction; the volume calculation algorithm is configured as

[0052] ||x4 y4 z4 1||

[0053] where V is the volume of the target area, (x1,y1,z1) is the coordinate of the first boundary point of the target area, (x2,y2,z2) is the coordinate of the second boundary point of the target area, (x3,y3,z3) is the coordinate of the third boundary point of the target area, and (x4,y4,z4) is the coordinate of the fourth boundary point of the target area. After obtaining the mapping space coordinate information of the target area in the three-dimensional geometric model of the simulation software through the above equation, and then obtaining the target area volume information V according to the equation, through the TI electrical stimulation parameter adaptive adjustment algorithm, the TI electrical stimulation electrode spatial layout is obtained, including the number of electrodes and the spatial layout.

[0054] Based on the above constructed TI electrical stimulation electrode spatial layout, adaptively adjust the TI electrical stimulation parameters, calculate the size of the envelope modulation electric field spatial volume, obtain the three-dimensional geometric center coordinate information of the envelope modulation electric field, and perform matching so that the envelope modulation electric field coincides with the simulation geometric area where the target area is located to obtain the optimal TI electrical stimulation parameters.

[0055] Step S5: Configure the corresponding optimal stimulation parameters through a preset parameter adaptation sub-strategy so that the envelope modulation electric field in the three-dimensional cranial nerve model matches the target area. Import the obtained central coordinate points of the envelope modulation amplitude electric field and the central coordinate points of the reticular tissue into the TI electric stimulation parameter adaptive adjustment algorithm, and adaptively adjust the electric stimulation parameters, including the electric stimulation frequency and the electric stimulation intensity, so that the envelope modulation electric field coincides with the simulated geometric area where the reticular tissue is located, and obtain the optimal TI electric stimulation parameters. The parameter adaptation sub-strategy includes

[0056] Step S5-1: Obtain new stimulation frequency values and stimulation intensity values and output them in the simulation electrode;

[0057] Step S5-2: Calculate the corresponding total envelope volume through a preset envelope volume calculation algorithm, and calculate the corresponding envelope center coordinates through a preset envelope center coordinate calculation algorithm;

[0058] The envelope volume calculation algorithm includes

[0059] Calculate the modulation envelope amplitude of the three-dimensional cranial nerve model under the action of the current simulation electrode, discretize the corresponding space of the three-dimensional cranial nerve model to obtain a number of voxels, calculate the voxel signal value of each voxel according to the modulation envelope amplitude, screen the voxels with voxel signal values higher than the preset reference voxel threshold, and calculate the total volume of the screened voxels to obtain the total envelope volume.

[0060] Calibrate the spatial coordinates of the anatomical landmark physical coordinate system in the MRI and the corresponding local coordinates in the simulation software, obtain the affine transformation matrix of the MRI physical coordinate system - simulation software local coordinate system, and convert the three-dimensional spatial coordinate information of the reticular system obtained in the above steps into three-dimensional spatial coordinate information in the three-dimensional geometric model, and calculate its volume size. Import the obtained reticular system volume size into the TI electric stimulation parameter adaptive adjustment algorithm, and then perform algorithm matching to obtain an electric stimulation layout consistent with the envelope modulation amplitude volume, including the number of electrodes and the electrode phase.

[0061] The method for calculating the modulation envelope amplitude is

[0062] R = sqrt(X 2 + Y 2 + Z 2 ), where

[0063]

[0064] where and are the electric fields generated by the first electrode pair and the second electrode pair in the x direction, and is the electric field generated by the first electrode pair and the second electrode pair in the y direction, and is the electric field generated by the first electrode pair and the second electrode pair in the z direction. R is the modulation envelope amplitude of the unit vector r(x, y, z).

[0065] After obtaining the modulation envelope amplitude R through the above equation, the volume of its spatial distribution is estimated based on the voxel unit. In three-dimensional space, the continuous spatial distribution is discretized and represented by voxels. Each voxel is a basic unit in three-dimensional space, containing a value representing the signal amplitude at that position, and its volume V voxel is the product of the resolutions in the three directions of the grid.

[0066] V voxel = Δx·Δy·Δz

[0067] where Δx, Δy, and Δz are the resolutions in the three directions. By calculating the number of voxels n with signal values greater than the threshold and multiplying by the volume of a single voxel, the total volume V can be obtained.

[0068] V = n·V voxel

[0069] Generally, a higher resolution can improve the calculation accuracy, but it will significantly increase the computational amount, resulting in an increase in calculation time and memory requirements. Therefore, in practical applications, the resolution setting needs to be reasonably optimized based on the accuracy requirements of the model to achieve a balance between calculation accuracy and computational resource consumption. To accurately capture the spatial distribution characteristics of the electric field, the resolution setting should be significantly smaller than the geometric size of the target area. Taking the hippocampus as an example, its typical size is about 3×1×1 cm3, and the resolution should reach at least the 1 mm3 level to ensure an accurate description of the electric field distribution within the target area.

[0070] The envelope center coordinate calculation algorithm is as follows:

[0071] Among them, X i 、Y i 、Z i are the coordinates of each point in the voxels where the voxel signal value is higher than the preset reference voxel threshold, W i is the corresponding normalized modulation envelope amplitude magnitude, and (X, Y, Z) is the envelope center coordinate.

[0072] Determine the stimulation frequency:

[0073] Construct a three-dimensional geometric model of TI electrical stimulation of nerve tissue at different stimulation frequencies in sequence. By solving the equation, calculate the spatial volume size and three-dimensional geometric coordinate information of the envelope-modulated electric field at this stimulation frequency. According to the optimization principle, compare the results at different stimulation frequencies, and select the stimulation frequency with the smallest volume phase difference as the optimal stimulation frequency.

[0074] Determine the stimulation intensity:

[0075] Construct a three-dimensional geometric model of TI electrical stimulation of nerve tissue at different stimulation intensities in sequence. Respectively, by solving the equation, calculate the spatial volume size and three-dimensional geometric coordinate information of the envelope-modulated electric field at this stimulation intensity. According to the optimization principle, compare the results at different stimulation intensities, and select the stimulation intensity with the smallest volume phase difference as the optimal stimulation intensity.

[0076] Step S5-3: Calculate the volume deviation between the total envelope volume and the target area volume, and the central coordinate deviation between the envelope center coordinate and the target area center coordinate. If the volume deviation is less than the preset reference volume value and the central coordinate deviation is less than the preset reference central coordinate deviation value, then enter step S5-4; otherwise, return to step S5-1.

[0077] Step S5-4: Output the current stimulation frequency value and stimulation intensity value as the optimal stimulation parameters.

[0078] The specific experimental data are as follows: Example 1: Determine that the target nerve tissue is the reticular tissue, and its MRI coordinates are: (-28, -7, 22), (-30, -9, 10), (-36, -13, 11), (-29, -4, 22), (-32, -11, 8), (-27, -15, 14); Import the six-point coordinates into the TI electrical stimulation parameter adaptive adjustment algorithm, and use the affine transformation matrix algorithm therein to obtain the approximate spatial coordinates in the simulation software as: (0.2050, 0.2755, -0.1816), (0.2000, 0.2708, -0.2090), (0.1850, 0.2616, -0.2048), (0.2025, 0.2824, -0.1816), (0.1950, 0.2662, -0.2111), (0.2075, 0.2569, -0.1984), and run the TI electrical stimulation parameter adaptive adjustment algorithm to obtain its volume size of 2.20 cm3; Automatically input the volume size obtained in step 3, that is, 2.20 cm3, into the TI electrical stimulation parameter adaptive adjustment algorithm to obtain the spatial layout of the TI electrical stimulation electrodes. Among them, the number of electrodes is 4, the electrical stimulation frequencies are 1000 Hz and 1030 Hz, and the electrical stimulation intensities of the two pairs of electrodes are 4 mA and 4 mA respectively. The selected electrode layout is as Figure 4As shown in Fig. a, the obtained envelope volume is 2.25 cm3, and the central coordinates are: X = 0.1976, Y = 0.2458, Z = -0.1901. The TI electrical stimulation parameter adaptive adjustment algorithm is used to adjust the stimulation intensity and stimulation frequency to optimize the stimulation efficiency. The obtained results are that the electrical stimulation frequencies are 1000 Hz and 1042 Hz, and the electrical stimulation intensities of the two groups of electrodes are 5.3 mA and 2.7 mA respectively. The central coordinates are: X = 0.1986, Y = 0.2724, Z = -0.2002, as Figure 4 shown in Fig. b.

[0079] Example 2: Stimulate the target area, and determine that the MRI coordinates of the targeted nerve tissue are: (-42, 1, -27), (-36, -7, -37), (-31, -9, -24), (-40, -3, -28), (-34, -5, -30), (-38, -7, -27); import the six-point coordinates into the TI electrical stimulation parameter adaptive adjustment algorithm, and use the affine transformation matrix algorithm therein to obtain that the spatial coordinates in the simulation software are approximately: (0.1700, 0.2940, -0.2850), (0.1850, 0.2755, -0.3061), (0.1975, 0.2708, -0.2787), (0.1750, 0.2847, -0.2871), (0.1900, 0.2801, -0.2913), (0.1800, 0.2755, -0.2850), and run the convex hull algorithm in the TI electrical stimulation parameter adaptive adjustment algorithm to obtain its volume size of 1.73 cm3; automatically input the volume size obtained in step 3 into the TI electrical stimulation parameter adaptive adjustment algorithm to obtain the spatial layout of the TI electrical stimulation electrodes. Among them, the number of electrodes is 8, the stimulation frequencies are 1000 Hz, 1020 Hz and 1000 Hz, 1020 Hz, and the electrical stimulation intensities of the electrodes are 4 mA, 4 mA; 4 mA, 4 mA respectively. The electrode layout is as Figure 4 shown in Fig. c, the obtained envelope volume is 1.79 cm3, and the central coordinates are: X = 0.2008, Y = 0.2570, Z = -0.2596. The TI electrical stimulation parameter adaptive adjustment algorithm is used to adjust the stimulation intensity and stimulation frequency to optimize the stimulation efficiency. The obtained results are that the electrical stimulation frequencies are 1000 Hz, 1010 Hz and 1000 Hz, 1030 Hz, and the electrical stimulation intensities of the two groups of electrodes are 5.3 mA, 2.7 mA; 6 mA, 2 mA respectively. The central coordinates are: X = 0.1841, Y = 0.2825, Z = -0.2914, as Figure 4 shown in Fig. d.

[0080] The present invention also provides a time-coherent electrical stimulation regulation device based on target area self-adaptation. Such a device includes a simulation electrode, a coherent electrical generation device, and a calculation component. During use, the simulation electrode is fixed at a suitable position on the human back, and at this time, it can be called a surface electrode and is connected to the coherent electrical generation device through a lead; the calculation component is used to obtain the optimal stimulation parameters according to the time-coherent electrical stimulation regulation method based on target area self-adaptation; the coherent electrical generation device generates coherent electricity applied to the simulation electrode based on the determined optimal electrical stimulation parameters.

[0081] Of course, the above are only typical examples of the present invention. In addition, the present invention can also have many other specific implementation manners. Any technical solutions formed by equivalent replacement or equivalent transformation fall within the scope of protection required by the present invention.

Claims

1. A time-coherent electrical stimulation control method based on target area adaptation, characterized in that: Step S1, obtaining user image information and constructing a cranial nerve three-dimensional model based on the image information; Step S2, adding simulated electrodes to the three-dimensional model of cranial nerves, and configuring stimulation properties of the simulated electrodes; Step S3, obtaining the target area position information, and mapping the target area to the cranial nerve three-dimensional model through a pre-constructed mapping matrix; Step S4, calculating the target volume according to a preset volume calculation algorithm, and obtaining corresponding electrode layout instructions from a pre-built layout mapping library according to the target volume, and configuring the simulated electrodes in the corresponding cranial nerve three-dimensional model according to the electrode layout instructions; Step S5: configuring the corresponding optimal stimulation parameters through a preset parameter adaptation sub-strategy to match the envelope modulation electric field in the cranial nerve three-dimensional model with the target area.

2. A method for controlling target area-adaptive temporal coherent electrical stimulation according to claim 1, characterized in that: The user image information includes cranial CT images and MRI images.

3. A method for controlling target area-adaptive temporal coherent electrical stimulation according to claim 2, characterized in that: The stimulation properties of the simulated electrode include model response conductivity, and a conductive effect engine corresponding to the cranial nerve three-dimensional model is generated according to the model response conductivity, wherein the model response conductivity is generated according to the electrical properties of the nerve tissue and the electrode.

4. The method for controlling target-area-adaptive temporally coherent electrical stimulation according to claim 1, characterized in that: The volume calculation algorithm is configured as Among them, V is the target volume, (x1, y1, z1) is the coordinate of the first boundary point of the target area, (x2, y2, z2) is the coordinate of the second boundary point of the target area, (x3, y3, z3) is the coordinate of the third boundary point of the target area, and (x4, y4, z4) is the coordinate of the fourth boundary point of the target area.

5. The method for controlling target area-adaptive temporal coherent electrical stimulation according to claim 1, characterized in that: The parameter adaptation sub-strategy includes Step S5-1, obtaining new stimulation frequency value and stimulation intensity value and outputting them in the simulation electrode; Step S5-2, calculating the corresponding envelope total volume by a preset envelope volume calculation algorithm, and calculating the corresponding envelope center coordinates by a preset envelope center coordinate calculation algorithm; Step S5-3, calculating the volume deviation between the total volume of the envelope and the volume of the target area and the center coordinate deviation between the center coordinate of the envelope and the center coordinate of the target area. If the volume deviation is less than the preset reference volume value and the center coordinate deviation is less than the preset reference center coordinate deviation value, then proceed to step S5-4, otherwise return to step S5-1; Step S5-4: output the current stimulation frequency value and stimulation intensity value as the optimal stimulation parameters.

6. A method for controlling target area-adaptive temporal coherent electrical stimulation according to claim 5, characterized in that: The envelope volume calculation algorithm includes Calculate the modulation envelope amplitude of the cranial nerve three-dimensional model under the action of the current simulated electrode, discretize the space corresponding to the cranial nerve three-dimensional model to obtain a number of voxels, calculate the voxel signal value of each voxel according to the modulation envelope amplitude, screen the voxels whose voxel signal values ​​are higher than the preset benchmark voxel threshold and calculate the total volume of the screened voxels to obtain the total envelope volume.

7. A method for controlling target area-adaptive temporal coherent electrical stimulation according to claim 6, characterized in that: The modulation envelope amplitude calculation method is R = sqrt (X 2 +Y 2 +Z 2 ),have, in, and is the electric field generated by the first electrode pair and the second electrode pair in the x direction, and is the electric field generated by the first electrode pair and the second electrode pair in the y direction, and is the electric field generated by the first electrode pair and the second electrode pair in the z direction. R is the modulation envelope amplitude of the unit vector r(x,y,z).

8. The method for controlling target-area-adaptive temporally coherent electrical stimulation according to claim 7, characterized in that: The envelope center coordinate calculation algorithm is: Among them, X i , Y i , Z i is the coordinates of each point in the voxel whose voxel signal value is higher than the preset reference voxel threshold, W i is the corresponding normalized modulation envelope amplitude, and (X, Y, Z) is the envelope center coordinate.

9. A device using the target area adaptive time-coherent electrical stimulation control method according to any one of claims 1 to 8, characterized in that: It includes simulation electrodes, coherent electrical generating devices and computing components, wherein: The analog electrodes are connected via a lead coherent electrical generator; A calculation component, used for obtaining optimal stimulation parameters according to the time-coherent electrical stimulation control method based on target area adaptation; The coherent electricity generating device generates coherent electricity applied to the simulation electrode based on the determined optimal electrical stimulation parameters.

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