A force feedback simulation method and system for virtual surgery

Abstract

The present invention relates to the technical field of virtual surgery, and specifically discloses a force feedback simulation method and system for virtual surgery, comprising: obtaining virtual simulation surgery information, and obtaining virtual biological soft tissue model information and virtual surgical tool model information according to the virtual simulation surgery information; obtaining particle information of multiple tissue positioning particles according to the virtual biological soft tissue model information, wherein the particle information includes tissue damping value and tissue bending elasticity value; and obtaining virtual biological soft tissue model information and virtual surgical tool model information according to the virtual simulation surgery information; obtaining virtual surgical tool information corresponding to each tissue positioning particle according to the virtual surgical tool model information; the present invention introduces particle information of multiple tissue positioning particles, including tissue damping value and tissue bending elasticity value, and calculates a virtual tissue elasticity index based on this information, so that the elastic response of the virtual soft tissue model after being subjected to force is closer to reality.

Description

Technical Field

[0001] The present invention relates to the technical field of virtual surgery, and in particular to a force feedback simulation method and system for virtual surgery. Background Art

[0002] Virtual surgery systems have broad application prospects in the medical field. They can not only be used for pre-operative planning and training of doctors to improve the success rate and safety of surgery, but can also be used for medical education and training to provide medical students with richer and more realistic surgical practice opportunities. In addition, with the continuous development and improvement of virtual reality technology, virtual surgery systems will further expand their scope of application.

[0003] Although the appearance and shape of the soft tissue model created by existing virtual surgery are close to the real thing, when the soft tissue model is cut by virtual instruments, the density of the virtual tissue point cloud of the model is uneven, which causes the feedback force of the cutting mouth of the virtual tissue to change, affecting the training effect of the virtual surgery simulation. Summary of the invention

[0004] The purpose of the present invention is to provide a force feedback simulation method and system for virtual surgery to solve the technical problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A force feedback simulation method for virtual surgery, comprising:

[0007] Acquire virtual simulation surgery information, and acquire virtual biological soft tissue model information and virtual surgical tool model information according to the virtual simulation surgery information;

[0008] Acquiring particle information of a plurality of tissue positioning particles according to the virtual biological soft tissue model information, wherein the particle information includes a tissue damping value and a tissue bending elasticity value;

[0009] Obtaining virtual tissue elasticity indexes of multiple tissue positioning points according to tissue damping values ​​and tissue bending elasticity values;

[0010] Acquiring virtual surgical tool information according to the virtual surgical tool model information, wherein the virtual surgical tool information includes virtual tool shape information and real-time tool operation information;

[0011] Acquire a real-time virtual surgical tool pressure value according to virtual tool shape information and real-time tool operation information;

[0012] Acquire at least one virtual tool force feedback value when the virtual surgical tool contacts at least one tissue positioning particle according to the real-time virtual surgical tool pressure value and the virtual tissue elasticity index of the plurality of tissue positioning particles;

[0013] Acquire a virtual biological tissue deformation simulation value according to at least one virtual tool force feedback value, acquire a biological soft tissue model deformation image based on the virtual biological tissue deformation simulation value, and play the biological soft tissue model deformation image through a visualization device;

[0014] The force feedback value of the virtual tool is used as virtual tool simulation feedback for the force feedback interaction device.

[0015] Preferably, the step of acquiring the particle information of a plurality of tissue positioning particles according to the virtual biological soft tissue model information comprises:

[0016] Acquire shape information and multiple virtual biological soft tissue texture layers according to virtual biological soft tissue model information;

[0017] Determine a plurality of tissue positioning particles corresponding to each virtual biological soft tissue texture layer according to the shape information and the virtual biological soft tissue texture layer, wherein the tissue positioning particles are preset points where the virtual tool contacts the virtual biological soft tissue texture layer;

[0018] Constructing a coordinate system and obtaining the three-dimensional coordinates of multiple tissue positioning particles corresponding to each virtual biological soft tissue texture layer and the preset center coordinates;

[0019] Obtaining the centroid distance value from each tissue positioning mass point to the preset center coordinates;

[0020] Obtaining the total number of particle values ​​of multiple tissue positioning particles;

[0021] Obtain the particle density value according to the total number of particles and the centroid distance value;

[0022] Obtain tissue damping value according to particle density value;

[0023] Taking any tissue positioning particle as a target particle, and obtaining the adjacent particle distance values ​​of multiple tissue positioning particles adjacent to the target particle according to preset conditions;

[0024] Obtaining the particle elastic connection value between the tissue positioning particles corresponding to each virtual biological soft tissue texture layer;

[0025] The elasticity value of each virtual biological soft tissue texture layer is obtained according to the adjacent particle distance value and the particle elastic connection value, and the elasticity values ​​of multiple layers are summed to obtain the tissue bending elasticity value.

[0026] Preferably, the step of acquiring virtual biological soft tissue model information and virtual surgical tool model information according to virtual simulation surgery information includes:

[0027] Obtaining the tissue damping value corresponding to each tissue positioning particle;

[0028] Obtaining the particle displacement change rate corresponding to each tissue positioning particle;

[0029] Obtaining tissue bending elasticity value;

[0030] Obtain the elastic coefficient of each tissue positioning mass point;

[0031] The virtual tissue elasticity index corresponding to each tissue positioning particle is obtained according to the tissue damping value, the particle displacement change rate, the tissue bending elasticity value and the elastic coefficient.

[0032] Preferably, the step of obtaining the real-time virtual surgical tool pressure value according to the virtual tool shape information and the real-time tool operation information includes:

[0033] Acquiring virtual surgical tool geometric shape information according to the virtual surgical tool model information;

[0034] Acquiring tool contact point position information for contacting with tissue positioning particles according to the virtual surgical tool geometric shape information;

[0035] Acquire virtual handle position information of the virtual operating handle according to the geometric shape information of the virtual surgical tool;

[0036] Obtaining a tool operation pressure value of a virtual surgical tool;

[0037] Obtaining a tool resistance value according to tool contact point position information and virtual handle position information;

[0038] The real-time virtual surgical tool pressure value exerted on each tissue positioning particle is obtained according to the tool resistance value and the tool operation pressure value.

[0039] Preferably, the step of obtaining at least one virtual tool force feedback value when the virtual surgical tool contacts at least one tissue positioning particle according to the real-time virtual surgical tool pressure value and the virtual tissue elasticity index of multiple tissue positioning particles comprises:

[0040] Acquiring the number of the virtual biological soft tissue texture layer where the target tissue positioning particle is located when the virtual surgical tool contacts at least one target tissue positioning particle;

[0041] Obtaining a thickness value of a virtual biological soft tissue texture layer corresponding to the number of layers;

[0042] Obtaining a virtual tissue elasticity index corresponding to a target tissue positioning particle;

[0043] The target resistance value of the virtual surgical tool is calculated according to the number of layers, thickness value and virtual tissue elasticity index of the virtual biological soft tissue texture layer where the target tissue positioning particle is located, wherein the calculation formula is:

[0044] ;

[0045] Among them, R is the target resistance value of the virtual surgical tool, N is the number of virtual biological soft tissue texture layers where the target tissue positioning particle is located, C is the proportional constant used to adjust the resistance, and d i is the thickness of the i-th virtual biological soft tissue texture layer, F i is the virtual tissue elasticity index corresponding to at least one target tissue positioning mass point in the i-th layer, where i represents the number of virtual biological soft tissue texture layers;

[0046] Get the preset drag coefficient;

[0047] The virtual tool force feedback value is calculated according to the target resistance value of the virtual surgical tool and the real-time virtual surgical tool pressure value, wherein the calculation formula is:

[0048] ;

[0049] Among them, E is the force feedback value of the virtual tool, I is the preset resistance coefficient, R is the target resistance value of the virtual surgical tool, and S is the real-time virtual surgical tool pressure value.

[0050] Preferably, the step of obtaining a virtual biological tissue deformation simulation value according to a plurality of virtual tool force feedback values ​​comprises:

[0051] Obtaining the three-dimensional coordinates of at least one tissue positioning particle and using it as the first node coordinates;

[0052] Acquire the three-dimensional coordinates of the virtual tool after the virtual tool contacts the at least one first node coordinate, and use the three-dimensional coordinates as the second node coordinates;

[0053] Obtain at least one direction vector value from a first node coordinate to a second node coordinate;

[0054] Obtaining a virtual tissue elasticity index corresponding to at least one first node coordinate;

[0055] Obtaining a target resistance value corresponding to at least one first node coordinate;

[0056] The virtual biological tissue deformation simulation value is calculated according to the virtual tool force feedback value, at least one first node coordinate, the second node coordinate, the direction vector value, the virtual tissue elasticity index corresponding to at least one first node coordinate, and the target resistance value corresponding to at least one first node coordinate, wherein the calculation formula is:

[0057] ;

[0058] Among them, G is the simulated value of virtual biological tissue deformation, F Z is the virtual tissue elasticity index corresponding to at least one first node coordinate, (x1 ,y 1 , z 1 ) is at least one first node coordinate, (x 2 ,y 2 , z 2 ) is the second node coordinate, E is the virtual tool force feedback value, α is the direction vector value, and B is the target resistance value corresponding to at least one first node coordinate.

[0059] The present application also discloses a force feedback simulation system for virtual surgery, comprising:

[0060] A first acquisition module is used to acquire virtual simulation surgery information, and acquire virtual biological soft tissue model information and virtual surgical tool model information according to the virtual simulation surgery information;

[0061] A second acquisition module is used to acquire the particle information of a plurality of tissue positioning particles according to the virtual biological soft tissue model information, wherein the particle information includes a tissue damping value and a tissue bending elasticity value;

[0062] A third acquisition module is used to acquire virtual tissue elasticity indexes of multiple tissue positioning points according to the tissue damping value and the tissue bending elasticity value;

[0063] A fourth acquisition module, used for acquiring virtual surgical tool information according to the virtual surgical tool model information, wherein the virtual surgical tool information includes virtual tool shape information and real-time tool operation information;

[0064] A fifth acquisition module, used for acquiring a real-time virtual surgical tool pressure value according to the virtual tool shape information and the real-time tool operation information;

[0065] A sixth acquisition module, configured to acquire at least one virtual tool force feedback value when the virtual surgical tool contacts at least one tissue positioning particle according to the real-time virtual surgical tool pressure value and the virtual tissue elasticity index of the plurality of tissue positioning particles;

[0066] A first interactive module is used to obtain a virtual biological tissue deformation simulation value according to at least one virtual tool force feedback value, obtain a biological soft tissue model deformation image based on the virtual biological tissue deformation simulation value, and play the biological soft tissue model deformation image through a visualization device;

[0067] The second interaction module is used to use the virtual tool force feedback value as virtual tool simulation feedback for the force feedback interaction device.

[0068] Preferably, the second acquisition module includes:

[0069] A first acquisition unit, used for acquiring shape information and multiple virtual biological soft tissue texture layers according to the virtual biological soft tissue model information;

[0070] A second acquisition unit is used to determine a plurality of tissue positioning particles corresponding to each virtual biological soft tissue texture layer according to the shape information and the virtual biological soft tissue texture layer, wherein the tissue positioning particles are preset points where the virtual tool contacts the virtual biological soft tissue texture layer;

[0071] A third acquisition unit is used to construct a coordinate system and acquire the three-dimensional coordinates of a plurality of tissue positioning particles corresponding to each virtual biological soft tissue texture layer and the preset center coordinates;

[0072] A fourth acquisition unit, used to acquire a centroid distance value from each tissue positioning particle to a preset center coordinate;

[0073] A fifth acquisition unit, used for acquiring a total number of particle values ​​of a plurality of tissue positioning particles;

[0074] A sixth acquisition unit, used for acquiring a particle density value according to a total number of particles and a centroid distance value;

[0075] A seventh acquisition unit, used for acquiring a tissue damping value according to a particle density value;

[0076] an eighth acquisition unit, configured to take any tissue positioning particle as a target particle, and acquire adjacent particle distance values ​​of a plurality of tissue positioning particles adjacent to the target particle according to a preset condition;

[0077] A ninth acquisition unit, used for acquiring the particle elastic connection value between the tissue positioning particles corresponding to each virtual biological soft tissue texture layer;

[0078] The tenth acquisition unit is used to acquire the elasticity value of each virtual biological soft tissue texture layer according to the adjacent particle distance value and the particle elastic connection value and sum the multiple elastic values ​​to obtain the tissue bending elasticity value.

[0079] Preferably, the third acquisition module includes:

[0080] an eleventh acquisition unit, used for acquiring a tissue damping value corresponding to each tissue positioning particle;

[0081] A twelfth acquisition unit is used to acquire the particle displacement change rate corresponding to each tissue positioning particle;

[0082] a thirteenth obtaining unit, used for obtaining a tissue bending elasticity value;

[0083] A fourteenth acquisition unit, used to acquire the elastic coefficient of each tissue positioning mass point;

[0084] The fifteenth acquisition unit is used to acquire the virtual tissue elasticity index corresponding to each tissue positioning particle according to the tissue damping value, the particle displacement change rate, the tissue bending elasticity value and the elastic coefficient.

[0085] Preferably, the first interaction module includes:

[0086] A sixteenth acquisition unit, used to acquire the three-dimensional coordinates of at least one tissue positioning particle and use it as the first node coordinates;

[0087] A seventeenth obtaining unit, configured to obtain the three-dimensional coordinates of the virtual tool after the virtual tool contacts the at least one first node coordinate, and use the three-dimensional coordinates as the second node coordinates;

[0088] An eighteenth obtaining unit, used to obtain a direction vector value from at least one first node coordinate to a second node coordinate;

[0089] A nineteenth obtaining unit, configured to obtain a virtual tissue elasticity index corresponding to at least one first node coordinate;

[0090] A twentieth acquisition unit, used to acquire a target resistance value corresponding to at least one first node coordinate;

[0091] The first calculation unit is used to calculate the virtual biological tissue deformation simulation value according to the virtual tool force feedback value, at least one first node coordinate, the second node coordinate, the direction vector value, the virtual tissue elasticity index corresponding to at least one first node coordinate, and the target resistance value corresponding to at least one first node coordinate, wherein the calculation formula is:

[0092] ;

[0093] Among them, G is the simulated value of virtual biological tissue deformation, F Z is the virtual tissue elasticity index corresponding to at least one first node coordinate, (x 1 ,y 1 , z 1 ) is at least one first node coordinate, (x 2 ,y 2 , z 2 ) is the second node coordinate, E is the virtual tool force feedback value, α is the direction vector value, and B is the target resistance value corresponding to at least one first node coordinate.

[0094] The beneficial effects of the present application are as follows: the present invention introduces the particle information of multiple tissue positioning particles, including tissue damping value and tissue bending elasticity value, and calculates the virtual tissue elasticity index based on this information, so that the elastic response of the virtual soft tissue model after being subjected to force is closer to reality. In addition, by obtaining the pressure value of the virtual surgical tool in real time, and calculating the virtual tool force feedback value in combination with the virtual tissue elasticity index, the user's immersion in the virtual environment is further enhanced, not only considering the position change when the tool contacts the soft tissue, but also determining the cutting direction by calculating the direction vector value from the first node coordinate to the second node coordinate, so that the user can perceive tactile feedback that is closer to the actual surgery. At the same time, the virtual biological tissue deformation simulation value calculated according to the virtual tool force feedback value and the target resistance value can accurately reflect the deformation of the soft tissue under the action of the virtual tool, so that the user can obtain tactile feedback that is closer to reality when performing surgery in the virtual environment. By accurately simulating the characteristics of different tissue layers, the system can provide more accurate force feedback to help users better understand and master the force control skills in surgical operations. This will not only help improve the learning outcomes of medical students or surgeons in virtual surgical training, but also allow them to practice their skills in an environment that is closer to actual surgical conditions, thereby improving the effectiveness of surgical training. BRIEF DESCRIPTION OF THE DRAWINGS

[0095] Figure 1 The figure is a schematic diagram of a method flow of an embodiment of the present application.

[0096] Figure 2 A schematic diagram of the system structure of an embodiment of the present application.

[0097] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0098] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0099] like Figure 1 As shown, the present application provides a force feedback simulation method for virtual surgery, comprising:

[0100] S1, obtaining virtual simulation surgery information, and obtaining virtual biological soft tissue model information and virtual surgical tool model information according to the virtual simulation surgery information;

[0101] S2. acquiring particle information of a plurality of tissue positioning particles according to the virtual biological soft tissue model information, wherein the particle information includes a tissue damping value and a tissue bending elasticity value;

[0102] S3, obtaining virtual tissue elasticity indexes of multiple tissue positioning points according to tissue damping values ​​and tissue bending elasticity values;

[0103] S4, acquiring virtual surgical tool information according to the virtual surgical tool model information, wherein the virtual surgical tool information includes virtual tool shape information and real-time tool operation information;

[0104] S5, obtaining a real-time virtual surgical tool pressure value according to the virtual tool shape information and the real-time tool operation information;

[0105] S6, obtaining at least one virtual tool force feedback value when the virtual surgical tool contacts at least one tissue positioning particle according to the real-time virtual surgical tool pressure value and the virtual tissue elasticity index of the plurality of tissue positioning particles;

[0106] S7, obtaining a virtual biological tissue deformation simulation value according to at least one virtual tool force feedback value, obtaining a biological soft tissue model deformation image based on the virtual biological tissue deformation simulation value, and playing the biological soft tissue model deformation image through a visualization device;

[0107] S8. Using the virtual tool force feedback value as virtual tool simulation feedback for the force feedback interaction device.

[0108] As described in the above steps S1-S8, the existing force feedback simulation method of virtual surgery has broad application prospects in the medical field. It can not only be used for doctors' pre-operative planning and training to improve the success rate and safety of surgery, but also can be used for medical education and training to provide medical students with rich and realistic surgical practice opportunities. The existing soft tissue model established by medical imaging data, although the appearance shape is close to the real one, the point cloud distribution inside the model may not be uniform enough. This unevenness will cause the force feedback during the cutting operation to change, affecting the effect of the virtual surgery simulation training, and the model lacks real soft tissue texture, which to a certain extent weakens the user's immersion during training; the present invention obtains information of the virtual biological soft tissue model, including particle information of multiple tissue positioning particles, such as tissue damping value and tissue bending elasticity value, and then calculates the virtual tissue elasticity index based on the particle information. This index is used to reflect the elastic response characteristics of the tissue after being subjected to force, and then obtains information of the virtual surgical tool, including the geometry of the tool. The shape information and the operator's real-time operation information of the tool in the virtual environment are used to determine the real-time pressure value of the virtual surgical tool. Then, the feedback force exerted on the virtual tool is calculated according to the pressure value of the virtual tool and the elastic index of the tissue. The calculation of this feedback force takes into account the multi-layer structure and thickness of the tissue, and is adjusted by a preset resistance coefficient to ensure the authenticity of the feedback force. Based on this feedback force, the deformation simulation value of the virtual biological tissue is calculated, and a deformation image is generated and displayed to the user through a visualization device. In addition, the feedback force is also transmitted to the interactive device as a force feedback signal, so that the user can feel tactile feedback similar to real surgery during the virtual surgery. In order to achieve a realistic effect, the method also takes into account factors such as the coordinate change and direction vector value after the virtual surgical tool collides with the tissue positioning particle, and uses these parameters to calculate the deformation of the virtual biological tissue. This method improves the realism of tissue cutting during virtual surgery, enhances the user's immersion, and can better simulate the force feedback in surgical operations.

[0109] In one embodiment, the step of acquiring the particle information of a plurality of tissue positioning particles according to the virtual biological soft tissue model information comprises:

[0110] S201, acquiring shape information and multiple virtual biological soft tissue texture layers according to virtual biological soft tissue model information;

[0111] S202, determining a plurality of tissue positioning particles corresponding to each virtual biological soft tissue texture layer according to the shape information and the virtual biological soft tissue texture layer, wherein the tissue positioning particles are preset points where the virtual tool contacts the virtual biological soft tissue texture layer;

[0112] S203, constructing a coordinate system and obtaining the three-dimensional coordinates of a plurality of tissue positioning particles corresponding to each virtual biological soft tissue texture layer and the preset center coordinates;

[0113] S204, obtaining the centroid distance value from each tissue positioning particle to the preset center coordinate;

[0114] S205, obtaining the total number of particle values ​​of multiple tissue positioning particles;

[0115] S206, obtaining a particle density value according to the total number of particles and the centroid distance value;

[0116] S207, obtaining a tissue damping value according to the particle density value;

[0117] S208, taking any tissue positioning particle as a target particle, and obtaining the adjacent particle distance values ​​of multiple tissue positioning particles adjacent to the target particle according to preset conditions;

[0118] S209, obtaining the particle elastic connection value between the tissue positioning particles corresponding to each virtual biological soft tissue texture layer;

[0119] S210, obtaining the elasticity value of each virtual biological soft tissue texture layer according to the adjacent particle distance value and the particle elastic connection value, and summing the elasticity values ​​of multiple layers to obtain a tissue bending elasticity value.

[0120] As described in the above steps S201-S210, the present invention can more accurately define the geometric properties of soft tissues by acquiring the texture information and shape information of virtual biological soft tissues, and acquire the three-dimensional coordinates of multiple tissue positioning particles, so as to establish the spatial framework of the soft tissue model, which is convenient for subsequent physical simulation. Then, the distance value of the center of mass from each particle to the center of the model is calculated. First, the distance from each particle to the center of the model needs to be acquired, and then the total number of particles positioned on the tissue surface is counted, and finally the spatial volume occupied by the particles is estimated. For example, assuming that the particles are evenly distributed in a simulated sphere, the sphere volume formula can be used:

[0121] ;

[0122] Among them, V represents the volume of the simulated sphere, r represents the distance from the particle to the center of the model, π is a mathematical constant (pi), and finally the total number of particles is divided by the estimated total volume to get the particle density value. Through the above steps, we can understand the differences in the characteristics of soft tissues in different parts, and then obtain the particle density value through the total number of particles and the center of mass distance value, which can quantify the density of soft tissues and simulate the influence of soft tissues under force. The particle density value is used to obtain the tissue damping value, that is, the blocking effect of soft tissues during movement, which directly affects the dynamic behavior of soft tissues during surgery. The particle density value reflects the density of particles inside the virtual biological soft tissue, while the tissue damping value describes the soft tissue. The ability to absorb energy when subjected to force, that is, the blocking effect of tissue during movement. Areas with higher particle density values ​​usually mean stronger interactions between particles in this area, resulting in higher damping effects. For example, higher particle density values ​​mean more particles per unit volume, and stronger interactions between these particles. When external force is applied to soft tissue, particles in high-density areas are more likely to interact with each other, thereby consuming more energy to overcome these interaction forces, which manifests as a greater damping effect. On the contrary, low-density areas have fewer particles and weaker interaction forces, so they exhibit lower damping effects. Higher particle density values ​​may lead to higher tissue damping values ​​because in high-density areas, The interaction force between particles is large, and the tissue needs to overcome more internal resistance when subjected to force, thus showing a higher damping effect. This association helps to more realistically simulate the dynamic behavior of soft tissue under force in the virtual environment, especially during surgery, which helps to improve the accuracy and reliability of virtual surgery training. The distance value of adjacent particles and the elastic connection value of particles are obtained (when any tissue positioning particle is used as the target particle, the definition of "adjacent" is based on a certain spatial distance or connection relationship. Specifically, "adjacent" under the preset conditions refers to a group of particles that are closest to the target particle in three-dimensional space. These particles are usually directly connected to the target particle in the virtual soft tissue model or Particles within a certain range, for example, the nearest few particles), help calculate the tissue bending elasticity value, which reflects the recovery ability of soft tissue when deformed by force, thereby improving the realism of the virtual biological soft tissue model, making it closer to the real biological tissue in appearance and physical properties, and solving the problem of changes in cutting mouth feedback force caused by uneven point cloud density in traditional models, making virtual surgical simulation training more reliable, and improving the accuracy of tissue elasticity simulation, making the deformation of soft tissue in virtual surgery more in line with actual conditions, optimizing the simulation of force feedback in virtual surgery, so that doctors can obtain more accurate tactile feedback when performing virtual surgery training, which helps to improve surgical skills.

[0123] In one embodiment, the step of acquiring virtual biological soft tissue model information and virtual surgical tool model information according to virtual simulation surgery information includes:

[0124] S301, obtaining a tissue damping value corresponding to each tissue positioning particle;

[0125] S302, obtaining the displacement change rate of each tissue positioning particle corresponding to the particle;

[0126] S303, obtaining the tissue bending elasticity value;

[0127] S304, obtaining the elastic coefficient of each tissue positioning particle;

[0128] S305 , obtaining a virtual tissue elasticity index corresponding to each tissue positioning particle according to the tissue damping value, the particle displacement change rate, the tissue bending elasticity value and the elastic coefficient.

[0129] As described in the above steps S301-S305, the present invention obtains the tissue damping value corresponding to the tissue positioning particle, and the system can better simulate the energy absorption capacity of the tissue when it is subjected to force. The damping value reflects the energy loss of the tissue after the force is applied. By more accurately calculating the virtual tissue elasticity index, the problem of inconsistent feedback force in the traditional virtual surgery system is solved, so that the user can experience a surgical feel closer to the real thing. Then, by obtaining the rate of change of the particle displacement, the system can accurately reflect the deformation speed of the tissue under the action of force, and can more realistically simulate the response of the tissue under different forces, such as the rapid deformation of the tissue during the scalpel cutting process. The elastic coefficient reflects the rigidity of the tissue, that is, the ability of the tissue to resist deformation. By obtaining this coefficient, the rigid response of the tissue when it is subjected to force can be more accurately simulated. By considering the bending elasticity value and elasticity coefficient of the tissue, the deficiencies of the traditional model in deformation simulation are solved, so that the deformation of the soft tissue in the virtual surgery is more in line with the actual situation. The virtual tissue elasticity index can be calculated according to the tissue damping value, the rate of change of the particle displacement, the bending elasticity value of the tissue and the elasticity coefficient. This index comprehensively reflects the physical properties of tissues in a virtual environment, allowing the system to more realistically simulate the behavior of tissues during surgery. The virtual tissue elasticity index is calculated based on the tissue damping value, the rate of change of particle displacement, the tissue bending elasticity value, and the elastic coefficient. The calculation formula is:

[0130] ;

[0131] Among them, F is the virtual tissue elasticity index, K is the tissue damping value, x is the rate of change of particle displacement, D is the tissue bending elasticity value, and y is the elastic coefficient. Suppose we have a virtual biological tissue sample, some key parameters of the sample are as follows:

[0132] The tissue damping value D=0.3, which means that the tissue can absorb part of the energy after being stressed, reducing vibration or movement;

[0133] The rate of change of particle displacement V = 0.05 indicates the change in the position of the particle in a certain period of time, which reflects the response speed of the tissue under the action of external force;

[0134] The tissue bending elasticity value E=1000, which indicates the ability of the tissue to resist bending deformation;

[0135] The elastic coefficient K=200 reflects the degree of reaction force generated by the tissue when it is subjected to force; in this example, the virtual tissue elasticity index F=30, and the elastic response strength of the virtual tissue is 30. The larger this value is, the stronger the elastic response of the tissue simulated in the virtual environment, and vice versa. Through such calculations, we can set corresponding parameters according to the physical properties of different types of tissues, thereby simulating more realistic soft tissue behavior in the virtual surgical environment.

[0136] In one embodiment, the step of obtaining the real-time virtual surgical tool pressure value according to the virtual tool shape information and the real-time tool operation information includes:

[0137] S401, obtaining virtual surgical tool geometric shape information according to virtual surgical tool model information;

[0138] S402, acquiring the tool contact point position information for contacting with the tissue positioning particle according to the virtual surgical tool geometric shape information;

[0139] S403, acquiring virtual handle position information of the virtual operating handle according to the geometric shape information of the virtual surgical tool;

[0140] S404, obtaining a tool operation pressure value of a virtual surgical tool;

[0141] S405, obtaining a tool resistance value according to the tool contact point position information and the virtual handle position information;

[0142] S406 , obtaining a real-time virtual surgical tool pressure value exerted on each tissue positioning particle according to the tool resistance value and the tool operation pressure value.

[0143] As described in the above steps S401-S406, the present invention provides basic data for subsequent simulation by extracting the geometric shape information of the virtual surgical tool, such as the shape and size of the blade. This ensures that the virtual surgical tool has correct physical properties in the simulation, such as weight, balance point, etc., and determines the point where the tool contacts the virtual soft tissue model, i.e., the tool contact position, based on the geometric shape information of the virtual surgical tool. This step ensures that the interactive position of the tool and the soft tissue is accurate when simulating the surgical operation. Similarly, based on the geometric shape information of the tool, the position where the user holds the tool in the virtual environment, i.e., the virtual handle position, is determined. This helps to simulate the actual feeling of the user holding the tool, thereby improving the authenticity of the surgical simulation, and the actual operating force applied by the user to the surgical tool in the virtual environment, including the pressure during cutting. It is used to simulate the interaction between the tool and soft tissue during surgery. According to the tool contact position information and the virtual handle position information, the resistance encountered by the tool when moving in the virtual soft tissue is calculated. The tool contact position information is used to determine the point where the tool contacts the soft tissue. The point of contact with the soft tissue directly affects the resistance encountered by the tool when cutting. Different contact positions mean different angles and directions of the tool cutting, which in turn affects the resistance. The virtual handle position information is the position where the user holds the tool. The position where the user holds the tool affects the direction and magnitude of the force applied by the user to the tool, thereby indirectly affecting the resistance of the tool when advancing in the soft tissue. This resistance value is achieved by considering the tool contact position information and the virtual handle position information. In the virtual surgery simulation, these information jointly determine the interaction between the tool and the soft tissue, which in turn affects the resistance value. It is used to simulate the different resistance situations encountered by the surgical tool when advancing in the soft tissue during real surgery. Finally, the real-time pressure value of the positioning particle on the surface of the virtual soft tissue is calculated by combining the tool resistance value and the tool operation pressure value. It ensures that the reaction of soft tissue during virtual surgery is more consistent with actual physical phenomena. Through the above steps, the interaction between surgical tools and soft tissue can be simulated more accurately, making the virtual surgery process closer to the real situation, solving the problem of lack of real feel in previous simulation processes. Users can feel a more real surgical experience in the virtual environment, including the force applied to the tool and the resistance feedback encountered by the tool in the soft tissue, thereby improving the effectiveness of training. By accurately calculating the tool resistance value and real-time pressure value, the force feedback mechanism of the virtual surgery system is more perfect, helping users to better understand and master the force control skills in surgical operations.

[0144] In one embodiment, the step of obtaining at least one virtual tool force feedback value when the virtual surgical tool contacts at least one tissue positioning particle according to the real-time virtual surgical tool pressure value and the virtual tissue elasticity index of multiple tissue positioning particles includes:

[0145] S501, obtaining the number of the virtual biological soft tissue texture layer where the target tissue positioning particle is located when the virtual surgical tool contacts at least one target tissue positioning particle;

[0146] S502, obtaining a thickness value of a virtual biological soft tissue texture layer corresponding to the number of layers;

[0147] S503, obtaining a virtual tissue elasticity index corresponding to the target tissue positioning particle;

[0148] S504, calculating the target resistance value of the virtual surgical tool according to the number of layers, thickness value and virtual tissue elasticity index of the virtual biological soft tissue texture layer where the target tissue positioning particle is located, wherein the calculation formula is:

[0149] ;

[0150] Among them, R is the target resistance value of the virtual surgical tool, N is the number of virtual biological soft tissue texture layers where the target tissue positioning particle is located, C is the proportional constant used to adjust the resistance, and d i is the thickness of the i-th virtual biological soft tissue texture layer, F i is the virtual tissue elasticity index corresponding to at least one target tissue positioning mass point in the i-th layer, where i represents the number of virtual biological soft tissue texture layers;

[0151] S505, obtaining a preset resistance coefficient;

[0152] S506, calculating the virtual tool force feedback value according to the target resistance value of the virtual surgical tool and the real-time virtual surgical tool pressure value, wherein the calculation formula is:

[0153] ;

[0154] Among them, E is the force feedback value of the virtual tool, I is the preset resistance coefficient, R is the target resistance value of the virtual surgical tool, and S is the real-time virtual surgical tool pressure value.

[0155] As described in the above steps S501-S506, the present invention can better simulate the performance of tissues at different levels when subjected to force by obtaining the number of tissue texture layers of tissue positioning particles and tool contact position information. It is used to distinguish the characteristics of tissues at different depths, so as to more accurately simulate the cutting and resistance changes during the operation. The thickness information of each layer of tissue is crucial for simulating the reaction of tissues at different levels when cut by surgical tools. By obtaining these values, the resistance of each layer of tissue during cutting can be calculated, making the simulation more precise and realistic. After that, by obtaining the virtual tissue elasticity index, the deformation of the virtual soft tissue model after being subjected to force can be simulated according to the physical characteristics of the virtual soft tissue model, thereby improving the authenticity of the soft tissue behavior during the simulation. By calculating the resistance value of each layer of tissue according to the preset number of tissue layers, the thickness value of each layer of tissue and the virtual tissue elasticity index, the resistance value of each layer of tissue can be calculated. By calculating the resistance value of different tissue layers and adjusting the force feedback of the tool accordingly, the problem of lack of real resistance feedback during the cutting process in the traditional virtual surgery system is solved, ensuring that during the simulation process, tissues at different depths can show resistance consistent with their physical characteristics, further enhancing the authenticity of the simulation. Assuming the following values:

[0156] The number of tissue texture layers N=3, that is, the tissue is divided into three layers.

[0157] The thickness of the first layer of tissue d 1 =2mm,

[0158] The thickness of the second layer of tissue d 2 =3mm,

[0159] The thickness of the third layer of tissue d 3 =1mm,

[0160] The constants used to adjust the resistance ratio are C1=0.5, C2=0.7, C3=0.3,

[0161] Virtual Organizational Resilience Index F 1 、F 2 、F 3 Both are 100;

[0162] Substitute the above data into the target resistance value calculation formula of the virtual surgical tool: R Z =340; if the tool passes through three layers of tissue, the total resistance it encounters will be R Z= 340 units. This value is determined by the thickness of each layer of tissue, the constant for adjusting the resistance ratio, and the virtual tissue elasticity index. Through such calculations, the virtual surgery system can more accurately simulate the resistance changes encountered by the tool when cutting different tissue layers, thereby improving the authenticity and accuracy of the surgical simulation. By combining the target resistance value of the virtual surgical tool and the real-time virtual surgical tool pressure value, the virtual tool force feedback value is calculated. Suppose we use a virtual tool to cut tissue in virtual surgery, and the following parameters are known:

[0163] The default resistance coefficient is l=0.5.

[0164] The target resistance value of the virtual surgical knife for the first layer of tissue is R1=10,

[0165] The target resistance value of the virtual surgical knife for the second layer of tissue is R2=15,

[0166] The target resistance value of the virtual surgical knife for the third layer of tissue is R3=20.

[0167] Real-time virtual surgical tool pressure value S=10.

[0168] Calculate the virtual tool force feedback value according to the formula: E=17.5;

[0169] When the virtual tool cuts the tissue, the virtual tool force feedback value calculated is 17.5 based on the current tool pressure value and the target resistance value of the virtual surgical tool in the tissue layer. This value represents the total resistance felt by the virtual tool during the cutting process, and will be used as an indicator for feedback to the user, allowing the user to perceive the resistance change during the cutting operation, thereby simulating a more realistic surgical experience. This value reflects the resistance encountered by the virtual tool during the cutting process, allowing the user to feel tactile feedback similar to that in real surgery, thereby improving the realism of virtual surgery. By introducing parameters such as the number of tissue texture layers, thickness values, and virtual tissue elasticity index through the above steps, the physical behavior of soft tissue during surgery can be more accurately simulated, allowing users to obtain more realistic tactile feedback in the virtual environment, enhancing the sense of immersion, and by considering the characteristics of different tissue layers, more accurate force feedback can be provided to help users better understand and master the force control skills in surgical operations, thereby improving the effectiveness of virtual surgery training.

[0170] In one embodiment, the step of obtaining a virtual biological tissue deformation simulation value according to a plurality of virtual tool force feedback values ​​comprises:

[0171] S601, obtaining the three-dimensional coordinates of at least one tissue positioning particle, and using it as the first node coordinates;

[0172] S602, obtaining the three-dimensional coordinates of the virtual tool after the virtual tool contacts at least one first node coordinate, and using the three-dimensional coordinates as the second node coordinates;

[0173] S603, obtaining a direction vector value from at least one first node coordinate to a second node coordinate;

[0174] S604, obtaining a virtual tissue elasticity index corresponding to at least one first node coordinate;

[0175] S605, obtaining a target resistance value corresponding to at least one first node coordinate;

[0176] S606, calculating a virtual biological tissue deformation simulation value according to the virtual tool force feedback value, at least one first node coordinate, a second node coordinate, a direction vector value, a virtual tissue elasticity index corresponding to at least one first node coordinate, and a target resistance value corresponding to at least one first node coordinate, wherein the calculation formula is:

[0177] ;

[0178] Among them, G is the simulated value of virtual biological tissue deformation, F Z is the virtual tissue elasticity index corresponding to at least one first node coordinate, (x 1 ,y 1 , z 1 ) is at least one first node coordinate, (x 2 ,y 2 , z 2 ) is the second node coordinate, E is the virtual tool force feedback value, α is the direction vector value, and B is the target resistance value corresponding to at least one first node coordinate.

[0179] As described in the above steps S601-S606, the present invention can reflect the force generated by the interaction between the virtual tool and the soft tissue during the cutting process by obtaining the virtual tool force feedback values ​​corresponding to multiple tissue positioning particles, ensuring that the cutting force of the virtual tool can be accurately perceived during the simulated surgery, and then obtain the three-dimensional coordinates of the tissue positioning particles and use them as the first node coordinates. This is to determine the position of the tool before contact with the soft tissue, so as to subsequently calculate the movement path of the tool, and then obtain the three-dimensional coordinates of the virtual tool after the collision with the first node coordinate, and use them as the second node coordinates. This step records the position change of the tool after cutting the soft tissue, and provides basic data for calculating the cutting trajectory. By calculating the direction vector value from the first node coordinate to the second node coordinate, the direction of the tool cutting can be determined, and then the virtual tissue elasticity index of the tissue positioning particle is obtained. The index reflects the elastic characteristics of the soft tissue after being subjected to force, and the target resistance value of the tissue positioning particle is obtained. The target resistance value represents the resistance of the tissue under a specific force condition. According to the data obtained in the above steps, the virtual biological tissue deformation simulation value is calculated by the formula, assuming that we have the following parameter values:

[0180] Virtual tissue elasticity index F = 100;

[0181] The virtual tool force feedback value F=(10,5,0) (indicates that there is 10 units of force on the x-axis, 5 units of force on the y-axis, and no force on the z-axis);

[0182] The coordinates of the first node are (1,1,0)(1,1,0), and the coordinates of the second node are (2,2,0)(2,2,0), then the direction vector value α=(2−1,2−1,0−0)=(1,1,0);

[0183] Target resistance value B=20, substitute the above data into the formula The calculated value is G=75, and the deformation of the virtual biological tissue under the action of the virtual surgical knife is 75 units. The larger the value, the more obvious the degree of tissue deformation, and vice versa. In this way, the virtual surgery system can simulate the deformation of soft tissues under different conditions, and can accurately simulate the deformation of soft tissues under the action of virtual tools, including the shape and size of the incision. Through the above steps, detailed steps and precise calculation formulas, the problem of soft tissue deformation simulation in traditional virtual surgery systems is solved. The virtual surgery system can better simulate the behavior of soft tissues in actual surgery. By obtaining data such as tool force feedback values ​​and deformation simulation values, users can obtain tactile feedback closer to reality when performing surgery in a virtual environment, which enhances the sense of immersion. More accurate deformation simulation and feedback help improve the learning effect of medical students or surgeons in virtual surgery training, because they can practice skills in an environment closer to actual surgical conditions. At the same time, when multiple first node coordinates are involved, the calculation of the virtual biological tissue deformation simulation value G can be completed by summing the deformation simulation values ​​corresponding to each node. Assume that we have two first node coordinates (1, 1, 0) and (2, 2, 0), and the positions of the virtual tool after collision with these two nodes are (2, 2, 0) and (3, 3, 0), the virtual tissue elasticity index F is 100, the direction vector values ​​are (1, 1, 0) and (1, 1, 0), the target resistance values ​​B are 20 and 25, and the virtual tool force feedback value F is the same at the two nodes, which is (10, 5, 0);

[0184] For the first node:

[0185] The first node coordinate P1=(1,1,0);

[0186] The second node coordinate P2=(2,2,0);

[0187] Direction vector value V=(2-1,2-1,0-0)=(1,1,0);

[0188] Virtual tissue elasticity index F1 = 100;

[0189] Target resistance value B1=20;

[0190] For the second node:

[0191] The first node coordinate P3 = (2, 2, 0);

[0192] The second node coordinate P4=(3,3,0);

[0193] Direction vector value V=(3-2,3-2,0-0)=(1,1,0);

[0194] Virtual tissue elasticity index F2 = 100;

[0195] Target resistance value B2=25;

[0196] The virtual biological tissue deformation simulation value G is the sum of G1 and G2:

[0197] G = G1 + G2 = 0.75 + 0.6 = 1.35;

[0198] For the two first node coordinates, the virtual biological tissue deformation simulation value G is 1.35 units. This calculation method ensures that the virtual surgery can comprehensively consider the deformation of multiple contact points, thereby more accurately simulating the response of soft tissue.

[0199] like Figure 2 As shown, the present invention also provides a force feedback simulation system for virtual surgery, comprising:

[0200] The first acquisition module 1 is used to acquire virtual simulation surgery information, and acquire virtual biological soft tissue model information and virtual surgical tool model information according to the virtual simulation surgery information;

[0201] A second acquisition module 2, used for acquiring the particle information of a plurality of tissue positioning particles according to the virtual biological soft tissue model information, wherein the particle information includes a tissue damping value and a tissue bending elasticity value;

[0202] A third acquisition module 3 is used to acquire virtual tissue elasticity indexes of multiple tissue positioning particles according to tissue damping values ​​and tissue bending elasticity values;

[0203] A fourth acquisition module 4 is used to acquire virtual surgical tool information according to the virtual surgical tool model information, wherein the virtual surgical tool information includes virtual tool shape information and real-time tool operation information;

[0204] A fifth acquisition module 5, used for acquiring a real-time virtual surgical tool pressure value according to the virtual tool shape information and the real-time tool operation information;

[0205] A sixth acquisition module 6, for acquiring at least one virtual tool force feedback value when the virtual surgical tool contacts at least one tissue positioning particle according to the real-time virtual surgical tool pressure value and the virtual tissue elasticity index of the plurality of tissue positioning particles;

[0206] A first interactive module 7 is used to obtain a virtual biological tissue deformation simulation value according to at least one virtual tool force feedback value, obtain a biological soft tissue model deformation image based on the virtual biological tissue deformation simulation value, and play the biological soft tissue model deformation image through a visualization device;

[0207] The second interaction module 8 is used to use the virtual tool force feedback value as virtual tool simulation feedback for the force feedback interaction device.

[0208] In one embodiment, the second acquisition module 2 includes:

[0209] A first acquisition unit, used for acquiring shape information and multiple virtual biological soft tissue texture layers according to the virtual biological soft tissue model information;

[0210] A second acquisition unit is used to determine a plurality of tissue positioning particles corresponding to each virtual biological soft tissue texture layer according to the shape information and the virtual biological soft tissue texture layer, wherein the tissue positioning particles are preset points where the virtual tool contacts the virtual biological soft tissue texture layer;

[0211] A third acquisition unit is used to construct a coordinate system and acquire the three-dimensional coordinates of a plurality of tissue positioning particles corresponding to each virtual biological soft tissue texture layer and the preset center coordinates;

[0212] A fourth acquisition unit, used to acquire a centroid distance value from each tissue positioning particle to a preset center coordinate;

[0213] A fifth acquisition unit, used for acquiring a total number of particle values ​​of a plurality of tissue positioning particles;

[0214] A sixth acquisition unit, used for acquiring a particle density value according to a total number of particles and a centroid distance value;

[0215] A seventh acquisition unit, used for acquiring a tissue damping value according to a particle density value;

[0216] an eighth acquisition unit, configured to take any tissue positioning particle as a target particle, and acquire adjacent particle distance values ​​of a plurality of tissue positioning particles adjacent to the target particle according to a preset condition;

[0217] A ninth acquisition unit, used for acquiring the particle elastic connection value between the tissue positioning particles corresponding to each virtual biological soft tissue texture layer;

[0218] The tenth acquisition unit is used to acquire the elasticity value of each virtual biological soft tissue texture layer according to the adjacent particle distance value and the particle elastic connection value and sum the multiple elastic values ​​to obtain the tissue bending elasticity value.

[0219] In one embodiment, the third acquisition module 3 includes:

[0220] an eleventh acquisition unit, used for acquiring a tissue damping value corresponding to each tissue positioning particle;

[0221] A twelfth acquisition unit is used to acquire the particle displacement change rate corresponding to each tissue positioning particle;

[0222] a thirteenth obtaining unit, used for obtaining a tissue bending elasticity value;

[0223] A fourteenth acquisition unit, used to acquire the elastic coefficient of each tissue positioning mass point;

[0224] The fifteenth acquisition unit is used to acquire the virtual tissue elasticity index corresponding to each tissue positioning particle according to the tissue damping value, the particle displacement change rate, the tissue bending elasticity value and the elastic coefficient.

[0225] Preferably, the first interaction module includes:

[0226] A sixteenth acquisition unit, used to acquire the three-dimensional coordinates of at least one tissue positioning particle and use it as the first node coordinates;

[0227] A seventeenth obtaining unit, configured to obtain the three-dimensional coordinates of the virtual tool after the virtual tool contacts the at least one first node coordinate, and use the three-dimensional coordinates as the second node coordinates;

[0228] An eighteenth obtaining unit, used to obtain a direction vector value from at least one first node coordinate to a second node coordinate;

[0229] A nineteenth obtaining unit, configured to obtain a virtual tissue elasticity index corresponding to at least one first node coordinate;

[0230] A twentieth acquisition unit, used to acquire a target resistance value corresponding to at least one first node coordinate;

[0231] The first calculation unit is used to calculate the virtual biological tissue deformation simulation value according to the virtual tool force feedback value, at least one first node coordinate, the second node coordinate, the direction vector value, the virtual tissue elasticity index corresponding to at least one first node coordinate, and the target resistance value corresponding to at least one first node coordinate, wherein the calculation formula is:

[0232] ;

[0233] Among them, G is the simulated value of virtual biological tissue deformation, F Z is the virtual tissue elasticity index corresponding to at least one first node coordinate, (x 1 ,y 1 , z 1 ) is at least one first node coordinate, (x 2 ,y 2 , z 2 ) is the second node coordinate, E is the virtual tool force feedback value, α is the direction vector value, and B is the target resistance value corresponding to at least one first node coordinate.

[0234] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, value library or other media provided in this application and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0235] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0236] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent results or equivalent process changes made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A force feedback simulation method for virtual surgery, characterized in that: include: Acquire virtual simulation surgery information, and acquire virtual biological soft tissue model information and virtual surgical tool model information according to the virtual simulation surgery information; Acquiring particle information of a plurality of tissue positioning particles according to the virtual biological soft tissue model information, wherein the particle information includes a tissue damping value and a tissue bending elasticity value; Obtaining virtual tissue elasticity indexes of multiple tissue positioning points according to tissue damping values ​​and tissue bending elasticity values; Acquiring virtual surgical tool information according to the virtual surgical tool model information, wherein the virtual surgical tool information includes virtual tool shape information and real-time tool operation information; Acquire a real-time virtual surgical tool pressure value according to virtual tool shape information and real-time tool operation information; Acquire at least one virtual tool force feedback value when the virtual surgical tool contacts at least one tissue positioning particle according to the real-time virtual surgical tool pressure value and the virtual tissue elasticity index of the plurality of tissue positioning particles; Acquire a virtual biological tissue deformation simulation value according to at least one virtual tool force feedback value, acquire a biological soft tissue model deformation image based on the virtual biological tissue deformation simulation value, and play the biological soft tissue model deformation image through a visualization device; Using the force feedback value of the virtual tool as virtual tool simulation feedback for the force feedback interactive device; Wherein, the step of acquiring the particle information of a plurality of tissue positioning particles according to the virtual biological soft tissue model information comprises: Acquire shape information and multiple virtual biological soft tissue texture layers according to virtual biological soft tissue model information; Determine a plurality of tissue positioning particles corresponding to each virtual biological soft tissue texture layer according to the shape information and the virtual biological soft tissue texture layer, wherein the tissue positioning particles are preset points where the virtual tool contacts the virtual biological soft tissue texture layer; Constructing a coordinate system and obtaining the three-dimensional coordinates of multiple tissue positioning particles corresponding to each virtual biological soft tissue texture layer and the preset center coordinates; Obtaining the centroid distance value from each tissue positioning mass point to the preset center coordinates; Obtaining the total number of particle values ​​of multiple tissue positioning particles; Obtain the particle density value according to the total number of particles and the centroid distance value; Obtain tissue damping value according to particle density value; Taking any tissue positioning particle as a target particle, and obtaining the adjacent particle distance values ​​of multiple tissue positioning particles adjacent to the target particle according to preset conditions; Obtaining the particle elastic connection value between the tissue positioning particles corresponding to each virtual biological soft tissue texture layer; The elasticity value of each virtual biological soft tissue texture layer is obtained according to the adjacent particle distance value and the particle elastic connection value, and the elasticity values ​​of multiple layers are summed to obtain the tissue bending elasticity value.

2. The force feedback simulation method for virtual surgery according to claim 1, characterized in that: The step of acquiring virtual biological soft tissue model information and virtual surgical tool model information according to virtual simulation surgery information includes: Obtaining the tissue damping value corresponding to each tissue positioning particle; Obtaining the particle displacement change rate corresponding to each tissue positioning particle; Obtaining tissue bending elasticity value; Obtain the elastic coefficient of each tissue positioning mass point; The virtual tissue elasticity index corresponding to each tissue positioning particle is obtained according to the tissue damping value, the particle displacement change rate, the tissue bending elasticity value and the elastic coefficient.

3. The force feedback simulation method for virtual surgery according to claim 1, characterized in that: The step of obtaining the real-time virtual surgical tool pressure value according to the virtual tool shape information and the real-time tool operation information includes: Acquiring virtual surgical tool geometric shape information according to the virtual surgical tool model information; Acquiring tool contact point position information for contacting with tissue positioning particles according to the virtual surgical tool geometric shape information; Acquire virtual handle position information of the virtual operating handle according to the geometric shape information of the virtual surgical tool; Obtaining a tool operation pressure value of a virtual surgical tool; Obtaining a tool resistance value according to tool contact point position information and virtual handle position information; The real-time virtual surgical tool pressure value exerted on each tissue positioning particle is obtained according to the tool resistance value and the tool operation pressure value.

4. The force feedback simulation method for virtual surgery according to claim 1, characterized in that: The step of obtaining at least one virtual tool force feedback value when the virtual surgical tool contacts at least one tissue positioning particle according to the real-time virtual surgical tool pressure value and the virtual tissue elasticity index of multiple tissue positioning particles comprises: Acquiring the number of the virtual biological soft tissue texture layer where the target tissue positioning particle is located when the virtual surgical tool contacts at least one target tissue positioning particle; Obtaining a thickness value of a virtual biological soft tissue texture layer corresponding to the number of layers; Obtaining a virtual tissue elasticity index corresponding to a target tissue positioning particle; The target resistance value of the virtual surgical tool is calculated according to the number of layers, thickness value and virtual tissue elasticity index of the virtual biological soft tissue texture layer where the target tissue positioning particle is located, wherein the calculation formula is: ； Among them, R is the target resistance value of the virtual surgical tool, N is the number of virtual biological soft tissue texture layers where the target tissue positioning particle is located, C is the proportional constant used to adjust the resistance, and d i is the thickness of the i-th virtual biological soft tissue texture layer, F i is the virtual tissue elasticity index corresponding to at least one target tissue positioning mass point in the i-th layer, where i represents the number of virtual biological soft tissue texture layers; Get the preset drag coefficient; The virtual tool force feedback value is calculated according to the target resistance value of the virtual surgical tool and the real-time virtual surgical tool pressure value, wherein the calculation formula is: ； Among them, E is the force feedback value of the virtual tool, I is the preset resistance coefficient, R is the target resistance value of the virtual surgical tool, and S is the real-time virtual surgical tool pressure value.

5. The force feedback simulation method for virtual surgery according to claim 1, characterized in that: The step of obtaining a virtual biological tissue deformation simulation value according to a plurality of virtual tool force feedback values ​​comprises: Obtaining the three-dimensional coordinates of at least one tissue positioning particle and using it as the first node coordinates; Acquire the three-dimensional coordinates of the virtual tool after the virtual tool contacts the at least one first node coordinate, and use the three-dimensional coordinates as the second node coordinates; Obtain at least one direction vector value from a first node coordinate to a second node coordinate; Obtaining a virtual tissue elasticity index corresponding to at least one first node coordinate; Obtaining a target resistance value corresponding to at least one first node coordinate; The virtual biological tissue deformation simulation value is calculated according to the virtual tool force feedback value, at least one first node coordinate, the second node coordinate, the direction vector value, the virtual tissue elasticity index corresponding to at least one first node coordinate, and the target resistance value corresponding to at least one first node coordinate, wherein the calculation formula is: ; Among them, G is the simulated value of virtual biological tissue deformation, F Z is the virtual tissue elasticity index corresponding to at least one first node coordinate, (x1, y1, z1) is at least one first node coordinate, (x2, y2, z2) is the second node coordinate, E is the virtual tool force feedback value, α is the direction vector value, and B is the target resistance value corresponding to at least one first node coordinate.

6. A force feedback simulation system for virtual surgery, characterized in that: include: A first acquisition module is used to acquire virtual simulation surgery information, and acquire virtual biological soft tissue model information and virtual surgical tool model information according to the virtual simulation surgery information; A second acquisition module is used to acquire the particle information of a plurality of tissue positioning particles according to the virtual biological soft tissue model information, wherein the particle information includes a tissue damping value and a tissue bending elasticity value; A third acquisition module is used to acquire virtual tissue elasticity indexes of multiple tissue positioning points according to the tissue damping value and the tissue bending elasticity value; A fourth acquisition module, used for acquiring virtual surgical tool information according to the virtual surgical tool model information, wherein the virtual surgical tool information includes virtual tool shape information and real-time tool operation information; A fifth acquisition module, used for acquiring a real-time virtual surgical tool pressure value according to the virtual tool shape information and the real-time tool operation information; A sixth acquisition module, configured to acquire at least one virtual tool force feedback value when the virtual surgical tool contacts at least one tissue positioning particle according to the real-time virtual surgical tool pressure value and the virtual tissue elasticity index of the plurality of tissue positioning particles; A first interactive module is used to obtain a virtual biological tissue deformation simulation value according to at least one virtual tool force feedback value, obtain a biological soft tissue model deformation image based on the virtual biological tissue deformation simulation value, and play the biological soft tissue model deformation image through a visualization device; The second interaction module is used to use the virtual tool force feedback value as virtual tool simulation feedback for the force feedback interaction device; Wherein, the second acquisition module includes: A first acquisition unit is used to acquire the number of virtual biological soft tissue texture layers and virtual biological soft tissue appearance information according to the virtual biological soft tissue model information; A first acquisition unit, used for acquiring shape information and multiple virtual biological soft tissue texture layers according to the virtual biological soft tissue model information; A second acquisition unit is used to determine a plurality of tissue positioning particles corresponding to each virtual biological soft tissue texture layer according to the shape information and the virtual biological soft tissue texture layer, wherein the tissue positioning particles are preset points where the virtual tool contacts the virtual biological soft tissue texture layer; A third acquisition unit is used to construct a coordinate system and acquire the three-dimensional coordinates of a plurality of tissue positioning particles corresponding to each virtual biological soft tissue texture layer and the preset center coordinates; A fourth acquisition unit, used to acquire a centroid distance value from each tissue positioning particle to a preset center coordinate; A fifth acquisition unit, used for acquiring a total number of particle values ​​of a plurality of tissue positioning particles; A sixth acquisition unit, used for acquiring a particle density value according to a total number of particles and a centroid distance value; a seventh acquisition unit, configured to acquire a tissue damping value according to a particle density value; an eighth acquisition unit, configured to take any tissue positioning particle as a target particle, and acquire adjacent particle distance values ​​of a plurality of tissue positioning particles adjacent to the target particle according to a preset condition; A ninth acquisition unit, used for acquiring the particle elastic connection value between the tissue positioning particles corresponding to each virtual biological soft tissue texture layer; The tenth acquisition unit is used to acquire the elasticity value of each virtual biological soft tissue texture layer according to the adjacent particle distance value and the particle elastic connection value and sum the multiple elastic values ​​to obtain the tissue bending elasticity value.

7. A force feedback simulation system for virtual surgery according to claim 6, characterized in that: The third acquisition module includes: an eleventh acquisition unit, used for acquiring a tissue damping value corresponding to each tissue positioning particle; A twelfth acquisition unit is used to acquire the particle displacement change rate corresponding to each tissue positioning particle; a thirteenth obtaining unit, used for obtaining the bending elasticity value of the tissue; A fourteenth acquisition unit, used to acquire the elastic coefficient of each tissue positioning mass point; The fifteenth acquisition unit is used to acquire the virtual tissue elasticity index corresponding to each tissue positioning particle according to the tissue damping value, the particle displacement change rate, the tissue bending elasticity value and the elastic coefficient.

8. The force feedback simulation system for virtual surgery according to claim 6, characterized in that: The first interaction module includes: A sixteenth acquisition unit, used to acquire the three-dimensional coordinates of at least one tissue positioning particle and use it as the first node coordinates; A seventeenth obtaining unit, configured to obtain the three-dimensional coordinates of the virtual tool after the virtual tool contacts the at least one first node coordinate, and use the three-dimensional coordinates as the second node coordinates; An eighteenth obtaining unit, used to obtain a direction vector value from at least one first node coordinate to a second node coordinate; A nineteenth obtaining unit, configured to obtain a virtual tissue elasticity index corresponding to at least one first node coordinate; A twentieth acquisition unit, used to acquire a target resistance value corresponding to at least one first node coordinate; The first calculation unit is used to calculate the virtual biological tissue deformation simulation value according to the virtual tool force feedback value, at least one first node coordinate, the second node coordinate, the direction vector value, the virtual tissue elasticity index corresponding to at least one first node coordinate, and the target resistance value corresponding to at least one first node coordinate, wherein the calculation formula is: ; Among them, G is the simulated value of virtual biological tissue deformation, F Z is the virtual tissue elasticity index corresponding to at least one first node coordinate, (x1, y1, z1) is at least one first node coordinate, (x2, y2, z2) is the second node coordinate, E is the virtual tool force feedback value, α is the direction vector value, and B is the target resistance value corresponding to at least one first node coordinate.

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