A target region self-adaptive based time-coherent electrical stimulation regulation method and device

Abstract

The application relates to a target region self-adaptive time-coherent electric stimulation regulation method, which comprises the following steps: acquiring user image information and constructing a cranial nerve three-dimensional model according to the image information; adding simulation electrodes in the cranial nerve three-dimensional model and configuring stimulation attributes of the simulation electrodes; acquiring target region position information and mapping the target region to the cranial nerve three-dimensional model through a pre-constructed mapping matrix; calculating a target region volume according to a preset volume calculation algorithm, acquiring corresponding electrode layout instructions from a pre-constructed layout mapping library according to the target region volume, and configuring the simulation electrodes in the corresponding cranial nerve three-dimensional model according to the electrode layout instructions; and configuring optimal stimulation parameters through a preset parameter adaptation sub-strategy to match an envelope modulation electric field in the cranial nerve three-dimensional model with a target region area. The method can self-adaptively adjust TI electric stimulation stimulation parameters and solves the problem of difficulty in setting the TI electric stimulation stimulation parameters.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of campus information management, more particularly, to a target region adaptive time-coherent electrical stimulation regulation method and device. BACKGROUND

[0002] Neurological diseases, including epilepsy, cerebrovascular disease, depression, and traumatic brain / spinal cord injury, cause patients to have difficulty walking, numbness, and a series of other functional disorders, which are the main causes of global disability and seriously affect the physical and mental health of patients. Electrical stimulation, as a widely used method of neural regulation, has been proven to have a significant effect in regulating abnormal neural activity 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 methods. Compared with invasive electrical stimulation techniques, which have high surgical risks and high costs, non-invasive electrical stimulation is more widely used in clinical practice due to its high safety and low cost. However, its stimulation accuracy is low, and the neural effect is small when targeting different neural stimulation target regions, especially deep neural tissue target regions, thus limiting the treatment effect.

[0004] Temporal Interference (TI) electrical stimulation is a new emerging neuromodulation method. It applies two groups of intermediate frequency currents with different frequencies (0 < Δf < 100 Hz) on the skin surface, and makes them interfere with each other in a specific area to form a limited low-frequency envelope modulation electric field, thereby activating deep neural tissues. It has the advantages of non-invasiveness, precision and deep neural tissue activation. (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 the great influence of the anatomical parameters and electrical parameters of the neural tissue, if precise stimulation of the target area is required, accurate TI electrical stimulation parameters are needed.

[0005] The target area of nerve injury is crucial for determining the electrical stimulation parameters, as it directly affects the distribution of electric current, the coverage of stimulation, and the effectiveness on the target tissue. 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 volume of the injury also changes the electrical conductivity properties of the local tissue, affecting the current path and stimulation depth, so reasonable adjustment of stimulation parameters such as intensity, frequency and phase is the key to maximizing the therapeutic effect. However, the envelope electric field generated by different stimulation parameters in existing TI electrical stimulation technology differs greatly, making it difficult to accurately change the parameters according to the characteristics of the target area for precise regulation. Therefore, it is urgent to develop a target area adaptive TI electrical stimulation regulation method. SUMMARY

[0006] Therefore, the purpose of the present application is to provide a target area adaptive TI electrical stimulation regulation method.

[0007] To solve the above technical problems, the technical scheme of the present application is:

[0008] A target area adaptive TI electrical stimulation regulation method,

[0009] Step S1, acquiring user image information and constructing a cranial nerve three-dimensional model according to the image information;

[0010] Step S2, adding a simulation electrode in the cranial nerve three-dimensional model and configuring the stimulation attributes of the simulation electrode;

[0011] Step S3, target region position information is acquired, and the target region is mapped into the cranial nerve three-dimensional model through a pre-constructed mapping matrix;

[0012] Step S4, the target region volume is calculated according to a preset volume calculation algorithm, and the corresponding electrode layout instruction is acquired from the pre-constructed layout mapping library according to the target region volume, and the simulation electrode is configured in the corresponding cranial nerve three-dimensional model according to the electrode layout instruction;

[0013] Step S5, the corresponding optimal stimulation parameter is configured through a preset parameter adaptive sub-strategy to make the envelope modulation electric field in the cranial nerve three-dimensional model match the target region.

[0014] Further, the user image information includes a cranial CT image and an MRI image.

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

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

[0017]

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

[0019] Further, the parameter adaptive sub-strategy includes

[0020] Step S5-1, a new stimulation frequency value and a stimulation intensity value are acquired and output in the simulation electrode;

[0021] Step S5-2, the corresponding envelope total volume is calculated through a preset envelope volume calculation algorithm, and the corresponding envelope center coordinate is calculated through a preset envelope center coordinate calculation algorithm;

[0022] Step S5-3, the volume deviation of the envelope total volume and the target region volume and the center coordinate deviation of the envelope center coordinate and the target region center coordinate are calculated, 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 step S5-4 is entered, otherwise step S5-1 is returned;

[0023] Step S5-4, the current stimulation frequency value and stimulation intensity value are output as the optimal stimulation parameter.

[0024] Further, the envelope volume calculation algorithm comprises

[0025] The modulation envelope amplitude of the cranial nerve three-dimensional model under the current simulation electrode is calculated, the corresponding space of the cranial nerve three-dimensional model is discretized to obtain a plurality of voxels, the voxel signal value of each voxel is calculated according to the modulation envelope amplitude, the voxels with voxel signal values higher than a preset reference voxel threshold are screened, and the total volume of the screened voxels is calculated to obtain the envelope total volume.

[0026] Further, the modulation envelope amplitude calculation method is

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

[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] Further, the envelope center coordinate calculation algorithm is:

[0031]

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

[0033] The application also provides a device using the target region adaptive time-coherent electrical stimulation regulation method, comprising a simulation electrode, a coherent electric generator and a calculation component, wherein,

[0034] The simulation electrode is connected to the coherent electric generator through a lead;

[0035] The calculation component is used to obtain the optimal stimulation parameter according to the target region adaptive time-coherent electrical stimulation regulation method.

[0036] A coherent electrical generator generates coherent electricity applied to the simulation electrode based on the determined optimal electrical stimulation parameters.

[0037] The technical effects of the present application mainly embody in the following aspects: a target region self-adaptive time-coherent electrical stimulation regulation method is provided, by confirming the target region spatial coordinate information and the envelope electric field characteristics of the TI electrical stimulation, the TI electrical stimulation stimulation parameters can be self-adaptively adjusted, and the problem of difficult setting of the existing TI electrical stimulation stimulation parameters is solved. BRIEF DESCRIPTION OF DRAWINGS

[0038] Figure 1 The whole scheme schematic diagram of the target region self-adaptive time-coherent electrical stimulation regulation method

[0039] Figure 2 The TI electrical stimulation parameter self-adaptive adjustment algorithm flowchart

[0040] Figure 3 The neural tissue TI electrical stimulation three-dimensional geometric stimulation model configuration schematic diagram

[0041] Figure 4 The TI electrical stimulation parameter schematic diagram of different volume target regions. DETAILED DESCRIPTION

[0042] The specific embodiments of the present application are further described in detail below in combination with the drawings, so that the technical scheme of the present application is easier to understand and master.

[0043] A target region self-adaptive time-coherent electrical stimulation regulation method,

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

[0045] By imageomics data, the basic three-dimensional spatial coordinate information of the target region is determined, and the mapping spatial coordinate information of the target region in the simulation software three-dimensional geometric model is obtained by using a formula.

[0046]

[0047] Wherein, XMRI, YMRI and ZMRI are the three-dimensional spatial coordinate information of the target region in the imageomics data, Xsimulation, Ysimulation and Zsimulation are the three-dimensional spatial coordinate information mapped into the three-dimensional geometric model, and A is the affine transformation matrix of the imageomics coordinate system to the three-dimensional geometric model coordinate system.

[0048] Based on the brain CT and MRI data, the three-dimensional geometric model of the brain neural tissue is constructed by the GUI geometric modeling module of the simulation software. And the electrodes are added on the scalp surface, the anode and cathode are set, and the tissue conductivity is set to construct the three-dimensional geometric model of the brain neural tissue TI electric stimulation, Figure 3 for the corresponding model.

[0049] Step S2, add simulation electrodes in the brain neural three-dimensional model, and configure the stimulation attributes of the simulation electrodes; the stimulation attributes of the simulation electrodes include model response conductivity, and a conductive effect engine corresponding to the brain neural three-dimensional model is generated according to the model response conductivity, and the model response conductivity is generated according to the electrical properties of the neural tissue and the electrical properties of the electrodes. The specific means is to input the literature data into the database to generate a deduction model. For example, bone, muscle, nerve, skin, etc. Then output the conductivity according to the input attribute value, for example, the skin conductivity is 0.0025, the fat conductivity is 0.04, the chest 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 result, the conductivity distribution can be obtained.

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

[0051] Step S4, calculate the target area volume according to the preset volume calculation algorithm, obtain the corresponding electrode layout instruction from the pre-constructed layout mapping library according to the target area volume, and configure the simulation electrodes in the corresponding brain neural three-dimensional model according to the electrode layout instruction; the volume calculation algorithm is configured as

[0052]

[0053] Wherein, V is the target area volume, (x1, y1, z1) is the first boundary point coordinate of the target area, (x2, y2, z2) is the second boundary point coordinate of the target area, (x3, y3, z3) is the third boundary point coordinate of the target area, and (x4, y4, z4) is the fourth boundary point coordinate 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, the target area volume information V is obtained according to the equation, the TI electric stimulation electrode space layout is obtained through the TI electric stimulation parameter self-adaptive adjustment algorithm, including the number of electrodes and the space layout.

[0054] On the basis of the TI electric stimulation electrode space layout constructed above, the TI electric stimulation parameters are adaptively adjusted, the envelope modulation electric field space volume size is calculated, the envelope modulation electric field three-dimensional geometric center coordinate information is obtained, and the matching is performed, so that the envelope modulation electric field is consistent with the simulation geometric region where the target area is located, and the best TI electric stimulation parameters are obtained.

[0055] Step S5, configure the corresponding optimal stimulation parameters by the preset parameter adaptive sub-strategy configuration to make the envelope modulation electric field in the cranial nerve three-dimensional model match the target area region. The obtained envelope modulation amplitude electric field center coordinate point and the reticular tissue center coordinate point are introduced into the TI electric stimulation parameter adaptive adjustment algorithm, the electric stimulation parameters including the electric stimulation frequency and the electric stimulation intensity are adaptively adjusted, so that the envelope modulation electric field matches the simulation geometric region where the reticular tissue is located, and the best TI electric stimulation parameters are obtained.

[0056] The parameter adaptive sub-strategy includes

[0057] Step S5-1, obtain a new stimulation frequency value and a stimulation intensity value and output in the simulation electrode;

[0058] Step S5-2, calculate the corresponding envelope total volume by a preset envelope volume calculation algorithm, and calculate the corresponding envelope center coordinate by a preset envelope center coordinate calculation algorithm;

[0059] The envelope volume calculation algorithm includes

[0060] The envelope volume calculation algorithm includes

[0061] The envelope volume calculation algorithm includes

[0062] The envelope volume calculation algorithm includes

[0063] R=sqrt(X 2 +Y 2 +Z 2 ), has,

[0064]

[0065] wherein, and It is the electric field generated by the first electrode pair and the second electrode pair in the x-direction. and It is the electric field generated in the y direction by the first electrode pair and the second electrode pair. and R is the electric field generated in the z-direction by the first and second electrode pairs. R is the modulation envelope amplitude of the unit vector r(x,y,z).

[0066] After obtaining the modulation envelope amplitude R using the above equation, the volume of its spatial distribution is estimated based on voxel units. 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 location, and its volume V. voxel This is the product of the grid resolutions in the three directions.

[0067] V voxel =Δx·Δy·Δz

[0068] Here, Δx, Δy, and Δz represent the resolution in the three directions. The total volume V is obtained by multiplying the number n of voxels with signal values ​​greater than a threshold by the volume of a single voxel.

[0069] V = n·V voxel

[0070] Generally, higher resolution improves computational accuracy but significantly increases computational load, leading to increased computation time and memory requirements. Therefore, in practical applications, the resolution setting needs to be reasonably optimized based on the model's accuracy requirements to achieve a balance between computational accuracy and computational resource consumption. To accurately capture the spatial distribution characteristics of the electric field, the resolution should be significantly smaller than the geometric size of the target region. Taking the hippocampus as an example, its typical size is approximately 3×1×1 cm³, and the resolution should be at least at the 1 mm³ level to ensure accurate description of the electric field distribution within the target region.

[0071] The algorithm for calculating the envelope center coordinates is as follows:

[0072] That In the middle, X i Y i Z i W represents the coordinates of points in voxels whose voxel signal values ​​are higher than a preset reference voxel threshold. i It represents the normalized amplitude of the modulation envelope, where (X, Y, Z) are the coordinates of the envelope center.

[0073] Determine the stimulation frequency:

[0074] The TI electric stimulation three-dimensional geometric model of the nerve tissue at different stimulation frequencies is sequentially constructed. The spatial volume size and three-dimensional geometric coordinate information of the envelope modulation electric field at the stimulation frequency are calculated by solving the equation. According to the optimization principle, the stimulation frequency with the minimum volume phase difference is selected as the optimal stimulation frequency by comparing the results of different stimulation frequencies.

[0075] Determination of stimulation intensity:

[0076] The TI electric stimulation three-dimensional geometric model of the nerve tissue at different stimulation intensities is sequentially constructed. The spatial volume size and three-dimensional geometric coordinate information of the envelope modulation electric field at the stimulation intensity are calculated by solving the equation. According to the optimization principle, the stimulation intensity with the minimum volume phase difference is selected as the optimal stimulation intensity by comparing the results of different stimulation intensities.

[0077] Step S5-3, calculate the volume deviation of the envelope total volume and the target volume, and the center coordinate deviation of the envelope center coordinate and the target center coordinate. 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, go to step S5-4, otherwise return to step S5-1.

[0078] Step S5-4, output the current stimulation frequency value and stimulation intensity value as the optimal stimulation parameters.

[0079] The specific experimental data are as follows: Example 1: The target nerve tissue is determined to be a reticular tissue, and its MRI coordinates are: (-28, -7, 22), (-30, -9, 10), (-36, -13, 11), (-29, -4, 22), (-32, -11, 8), and (-27, -15, 14). The six point coordinates are imported into the TI electric stimulation parameter adaptive adjustment algorithm, and the affine transformation matrix algorithm therein is used to obtain the spatial coordinates in the simulation software as approximately: (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), and (0.2075, 0.2569, -0.1984). The TI electric stimulation parameter adaptive adjustment algorithm is run to obtain a volume size of 2.20 cm3. The volume size of 2.20 cm3 obtained in step 3 is automatically input into the TI electric stimulation parameter adaptive adjustment algorithm to obtain the TI electric stimulation electrode spatial layout. Among them, the number of electrodes is 4, the electric stimulation frequency is 1000 Hz and 1030 Hz, and the electric stimulation intensity of the two pairs of electrodes is 4 mA and 4 mA respectively. The selected electrode layout is as shown in FIG. 1. Figure 4The obtained envelope volume is 2.25 cm3, and the center coordinates are X = 0.1976, Y = 0.2458, and Z = -0.1901. The stimulation intensity and the stimulation frequency are adjusted by using the TI electric stimulation parameter adaptive adjustment algorithm to optimize the stimulation efficiency, and the results are that the electric stimulation frequency is 1000 Hz and 1042 Hz, the electric stimulation intensity of the two groups of electrodes is 5.3 mA and 2.7 mA respectively, and the center coordinates are X = 0.1986, Y = 0.2724, and Z = -0.2002, as shown in FIG. 2b of the drawings. Figure 4

[0080] In Example 2, the target region is stimulated, and the target neural tissue MRI coordinates are determined as: (-42, 1, -27), (-36, -7, -37), (-31, -9, -24), (-40, -3, -28), (-34, -5, -30), and (-38, -7, -27). The six point coordinates are input into the TI electric stimulation parameter adaptive adjustment algorithm, the affine transformation matrix algorithm therein is used, 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), and (0.1800, 0.2755, -0.2850), and the convex hull algorithm in the TI electric stimulation parameter adaptive adjustment algorithm is run to obtain a volume size of 1.73 cm3. The volume size obtained in step 3 is automatically input into the TI electric stimulation parameter adaptive adjustment algorithm to obtain the TI electric stimulation electrode spatial layout. The number of electrodes is 8, the stimulation frequency is 1000 Hz, 1020 Hz, 1000 Hz, 1020 Hz, the electric stimulation intensity of the electrodes is 4 mA, 4 mA, 4 mA, and 4 mA respectively, and the electrode layout is shown in FIG. 2c of the drawings. Figure 4 The obtained envelope volume is 1.79 cm3, and the center coordinates are X = 0.2008, Y = 0.2570, and Z = -0.2596. The stimulation intensity and the stimulation frequency are adjusted by using the TI electric stimulation parameter adaptive adjustment algorithm to optimize the stimulation efficiency, and the results are that the electric stimulation frequency is 1000 Hz, 1010 Hz, and 1000 Hz, 1030 Hz, the electric stimulation intensity of the two groups of electrodes is 5.3 mA, 2.7 mA, and 6 mA, 2 mA respectively, and the center coordinates are X = 0.1841, Y = 0.2825, and Z = -0.2914, as shown in FIG. 2d of the drawings. Figure 4

[0081] ​​The application also provides a target region self-adaptive time-coherent electric stimulation regulation device. The device comprises an analog electrode, a coherent electric generating device and a computing component. In use, the analog electrode is fixed at a suitable position on the back of a human body, and the coherent electric generating device is connected to the analog electrode through a lead. The computing component is used to obtain optimal stimulation parameters according to the target region self-adaptive time-coherent electric stimulation regulation method. The coherent electric generating device generates coherent electric stimulation applied to the analog electrode based on the determined optimal stimulation parameters.

[0082] Of course, the above is only a typical example of the application, and in addition to this, the application can have other various specific embodiments, and any technical solution formed by equivalent replacement or equivalent transformation falls within the scope of the application.

Claims

1. A target region adaptive based time-coherent electrical stimulation regulation method, characterized in that: Step S1, obtaining user image information, and constructing a cranial nerve three-dimensional model according to the image information; Step S2, adding a simulation electrode in the cranial nerve three-dimensional model, and configuring the stimulation attribute of the simulation electrode; Step S3, obtaining target region position information, and mapping the target region to the cranial nerve three-dimensional model through a pre-constructed mapping matrix; Step S4, calculating the target region volume according to a pre-set volume calculation algorithm, and obtaining the corresponding electrode layout instruction from the pre-constructed layout mapping library according to the target region volume, and configuring the simulation electrode in the corresponding cranial nerve three-dimensional model according to the electrode layout instruction; Step S5, configuring the optimal stimulation parameters through a pre-set parameter adaptive sub-strategy to make the envelope modulation electric field in the cranial nerve three-dimensional model match the target region area, the parameter adaptive sub-strategy comprising: Step S5-1, obtaining new stimulation frequency value and stimulation intensity value in the simulation electrode; Step S5-2, calculating the corresponding envelope total volume through a pre-set envelope volume calculation algorithm, and calculating the corresponding envelope center coordinates through a pre-set envelope center coordinate calculation algorithm; wherein the envelope volume calculation algorithm comprises: calculating the modulation envelope amplitude of the cranial nerve three-dimensional model under the action of the current simulation electrode, discretizing the cranial nerve three-dimensional model corresponding space to obtain a plurality of voxels, calculating the voxel signal value of each voxel according to the modulation envelope amplitude, and screening the voxels with voxel signal value higher than the pre-set reference voxel threshold value and calculating the total volume of the screened voxels to obtain the envelope total volume; Step S5-3, calculating the volume deviation of the envelope total volume and the target region volume and the center coordinate deviation of the envelope center coordinates and the target region center coordinates, if the volume deviation is less than the pre-set reference volume value and the center coordinate deviation is less than the pre-set reference center coordinate deviation value, then entering step S5-4, otherwise returning to step S5-1; Step S5-4, outputting the current stimulation frequency value and stimulation intensity value as the optimal stimulation parameters.

2. The method of claim 1, wherein the method is based on target region adaptation. The user image information includes cranial CT image and MRI image.

3. The method of claim 2, wherein the target region is determined by a target region adaptive time-coherent electrical stimulation method, comprising: determining a target region of the brain based on a brain activity of the subject; and stimulating the target region of the brain with the time-coherent electrical stimulation. The stimulation attribute of the simulation electrode includes model response conductivity, and a cranial nerve three-dimensional model corresponding conductive effect engine is generated according to the model response conductivity, and the model response conductivity is generated according to the electrical properties of the neural tissue and the electrical properties of the electrode.

4. The method of claim 1, wherein the method is based on target region adaptation. The volume calculation algorithm is configured as Wherein, V is the target region volume, (x1, y1, z1) is the first boundary point coordinate of the target region, (x2, y2, z2) is the second boundary point coordinate of the target region, (x3, y3, z3) is the third boundary point coordinate of the target region, and (x4, y4, z4) is the fourth boundary point coordinate of the target region.

5. The method of claim 1, wherein the method is based on target region adaptation. The modulation envelope amplitude calculation method is R = sqrt(X 2 + Y 2 + Z 2 ), has, wherein and are the electric fields generated by the first and second electrode pairs in the x-direction, and are the electric fields generated by the first and second electrode pairs in the y-direction, and are the electric fields generated by the first and second electrode pairs in the z-direction, R is the modulation envelope amplitude of the unit vector r(x,y,z).

6. The method of claim 5, wherein the method is based on target region adaptation. The envelope center coordinate calculation algorithm is: wherein X i , Y i , Z i are the coordinates of each point in the voxels whose voxel signal values are higher than a preset reference voxel threshold, W i is the corresponding normalized modulation envelope amplitude, and (X, Y, Z) is the envelope center coordinate.

7. Apparatus for target region adaptive time-coherent electrical stimulation modulation according to any one of claims 1 to 6, characterized in that, It comprises a simulation electrode, a coherent electric generator and a calculation component, wherein, The simulation electrode is connected to the lead coherent electric generator. a computing component for obtaining optimal stimulation parameters according to the target region-adaptive time-coherent electrical stimulation regulation method; a coherent electrical generator device for generating coherent electricity applied to the simulation electrode based on the determined optimal electrical stimulation parameters.

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