In the simulation of acupuncture manipulation, it is necessary to accurately capture the information of acupuncture points and particles around them. Therefore, a soft tissue modeling method that can accurately track model particles is needed. In this paper, a soft tissue acupuncture model based on the mass-spring force net is designed. MSM is used as the auxiliary model and the SHF model is combined. SHF is used to establish a three-layer soft tissue model of skin, fat, and muscle, and a layer of the MSM based force network is covered on the surface of soft tissue to realize the complementary advantages and disadvantages of spherical harmonic function and MSM. In addition, a springback algorithm is designed to simulate the springback phenomenon of soft tissue skin during acupuncture. The evaluation results show that the soft tissue acupuncture modeling method based on mass-spring force net can effectively simulate the springback phenomenon of soft tissue surface during acupuncture surgery, and has good comprehensive performance in the application of virtual acupuncture surgery simulation.
With the development of society, the demand for the quantity and quality of medical staff is higher than before. Surgeons need years of practice to become experts, and their growth needs long-term continuous practice. Also, the traditional training methods need a long cycle, lack of resources, and have high training costs. Therefore, it is urgent to shorten the training cycle of surgeons through advanced technical equipment and training methods. In recent years, the research and application of virtual reality technology have opened up a new way for surgical training. As a new cross research field, virtual surgery [
Soft tissue model construction is the key technology of virtual surgery simulation. The quality of the model directly determines the quality of the virtual surgery simulation. Several commonly used soft tissue models are introduced below.
The mass-spring model (MSM) is a common soft-tissue model in virtual surgery [
The finite element model (FEM) [
The boundary element model (BEM) [
Spherical harmonic function (SHF) is a three-dimensional expansion of the Fourier series [
The present study focuses on improving the existing MSM method and the stability and accuracy without affecting the computational efficiency to expand the ability and application scope of MSM. Thus, it can better simulate the soft tissue and improve the overall quality of soft tissue model and virtual surgery simulation. The study is based on soft tissue acupuncture modeling based on the mass-spring force net and its application in acupuncture simulation. The main contributions of this work are summarized as follows:
1) In the simulation of acupuncture manipulation, it is necessary to accurately capture the information of the punctured point and its surrounding particles. Therefore, a soft tissue modeling method that can accurately track the model particle is needed. The spherical harmonic function (SHF) model can accurately track the acupuncture point. However, the calculation of the force is more complex, and MSM can make up for this deficiency. Therefore, a soft tissue acupuncture modeling method based on the mass-spring force net is designed. MSM is used as an auxiliary model and the SHF model is combined. SHF is used to build a three-layer soft tissue model of skin, fat, and muscle, and a layer of the MSM based force network is covered on the surface of soft tissue to realize the complementary advantages and disadvantages of spherical harmonic function and MSM.
2) In addition, a rebound algorithm [
3) Through the construction of the virtual acupuncture system, the soft tissue acupuncture modeling method based on the mass-spring force network is applied to the virtual acupuncture simulation, and the evaluation experiment is designed to study its application effect.
The remainder of this paper is organized as follows. Section 2 illustrates the related works about the mass-spring model. Section 3 introduces the soft tissue acupuncture modeling method based on the mass-spring force net. Section 4 validates the performance of the proposed model. In the last section, a summary of present research is concluded and future research scopes are discussed.
In virtual surgery simulation, different surgical simulation scenes are often involved, such as simulating specific surgical operations: suture, cutting, acupuncture, etc. or simulating specific tissue structure: tumor, organ, membrane, etc. In order to achieve the simulation requirements, many related types of research have improved the basic performance of the MSM, such as improving the accuracy of the model, improving the stability of the model, and improving the interaction of the model. In addition to improving the basic performance of MSM, we can also expand the application of MSM according to specific requirements, or combine MSM as an auxiliary means with other models to seek new breakthroughs. The improvement of MSM is as follows.
In order to improve the accuracy of MSM, Wang et al. [
In order to improve the stability of MSM, Wang et al. [
In addition to improving the basic performance of MSM, it is often necessary to improve its structure in practical application, so as to expand its application in virtual surgery. Farhang et al. [
With the development of virtual reality soft-tissue modeling technology, more and more soft-tissue models are emerging. In recent years, many researchers combine MSM as an auxiliary model with other models or algorithms to establish a virtual surgery system, so as to seek a new breakthrough in soft tissue modeling technology. Tang et al. [
Acupuncture is a common operation in surgery, involving a variety of soft tissues, such as skin, fat, and muscle. During acupuncture operation, when the needle tip pierces the surface of soft tissue, the deformation of the surface of soft tissue will more or less rebound to the original position. This phenomenon is called the springback phenomenon of soft tissue surface in acupuncture operation. To simulate this phenomenon, we need to accurately capture the puncturing time point and the position information of the puncture point and its surrounding particles before and after being punctured Soft tissue modeling method.
Among the current mainstream soft tissue models, the SHF modeling method can meet this requirement. Because of the multi-scale of SHF, the collision detection between surgical tools and soft tissue can be completed quickly, and the deformation of any point on the soft tissue surface before and after the collision can be quickly obtained by the surface radius of SHF. Therefore, SHF is a modeling method that can accurately track the acupuncture points and surrounding particles before and after the soft tissue surface puncture.
However, the calculation process of forces in SHF model [
The soft tissue model was constructed by SHF and consisted of three layers: skin, fat, and muscle. The three layers of tissue are combined in the following order: the top layer of skin, the middle layer of fat, and the bottom layer of muscle. SHF can be defined by
where
SHF is used to construct a soft tissue model, that is, the surface
where
where
After the establishment of a soft tissue model based on SHF, the force net constructed by MSM is attached to the surface of the soft tissue layer to make up for the shortcomings of SHF in force calculation. There are two kinds of forces in acupuncture simulation. The first force acts before acupuncture breaks the surface of soft tissue. Through force network simulation based on MSM, it is defined as “surface spring force”. When the surface of the tissue is punctured, the surface force disappears, and the second force begins to act, the damping force. The damping force is related to soft tissue characteristics, acupuncture speed, and acupuncture depth. The force tactile models of the three soft tissue materials are shown in
Tissue type | State | Force tactile model |
---|---|---|
Skin | Before puncturing | |
After puncturing | ||
Fat | Before puncturing | |
After puncturing | ||
Muscle | Before puncturing | |
After puncturing |
In
The surface spring force
As shown in Force net structure (see
As shown in Cross section of virtual spring and force net (see
where
In order to show the springback phenomenon when the soft tissue surface is punctured, a springback algorithm based on the improved shape matching algorithm [
As shown in Schematic diagram of rebound algorithm (see
where
where
According to
Through the construction of the virtual acupuncture system, the proposed modeling method is applied to the virtual acupuncture simulation, and the evaluation experiment is designed to study its application effect. After designing the soft tissue model, collision detection, and cutting algorithm in the virtual cutting system, the function of cutting simulation can be realized. Our system consists primarily of a mainframe computer and a haptic interaction facility called PHANTOM OMNI. The computer is based on Windows 10 and comes with an Intel(R) Xeon(R) CPU, E5-1650 v3 @ 3.5 GHz processor and NVIDIA GeForce GT 720 M graphics. The simulation is carried out on VC++ 2019 and 3DS MAX 2019 with OpenGL graphics libraries. The PHANTOM OMNI is a force feedback device that allows the operators to touch and operate on the virtual object simulated by our method. The experimental environment is shown in Experiment environment (see
The construction process of the system is also divided into three parts: virtual scene initialization, real-time calculation, and human-computer interaction, as shown in
First, the virtual scene is initialized. In 3DS MAX 2019, the surface of soft tissue was constructed according to SHF and 3D data, and then the force network was established by MSM, and the model data was exported as a file in obj format. Then, the model data file is imported into VC ++ 2019 and the model parameters are determined. According to the relevant research [
As shown in
According to the above process, the virtual acupuncture system is constructed, and the soft tissue acupuncture modeling method based on the mass-spring force network is applied to the acupuncture simulation. Acupuncture effect of three kinds of soft tissue (see
Types of soft tissue | Thickness (mm) | ||||
---|---|---|---|---|---|
Skin | 0.8 | 0.16 | 3 | 8 | 2 |
Fat | 8.4 | 0.08 | 1 | 4 | 1 |
Muscle | 39.0 | 0.23 | 3 | 10 | 2.5 |
As shown in acupuncture effect of three kinds of soft tissue (see
Design and evaluate the application effect of the model in virtual acupuncture simulation. In the soft tissue acupuncture modeling method based on mass-spring force net, MSM belongs to the auxiliary model, and the accuracy of soft tissue model is mainly controlled by SHF, and the accuracy of SHF itself is better, and the research focus of this paper is not on the improvement and improvement of deformation accuracy of SHF. The key point of soft tissue acupuncture modeling method based on the mass-spring force net is to use MSM to make up for the deficiency of SHF force calculation and to simulate the rebound phenomenon in virtual acupuncture operation. The above-mentioned improvement effect is more intuitive through user experience feedback. Therefore, experts are invited to try out the virtual acupuncture system and comprehensively evaluate the system from seven indicators. In order to improve the objectivity of the scoring system, a comprehensive weighted scoring method was used to deal with the scores of the acupuncture system.
In order to evaluate the comprehensive performance of the soft tissue acupuncture model based on the mass-spring force net, a multi-index comprehensive evaluation experiment method was adopted, and 20 doctors from the First Affiliated Hospital of Nanjing Medical University were invited. Doctors were required to perform acupuncture operation experience and score on the virtual acupuncture system constructed from this model and other models. The acupuncture system constructed by other models, includes MSM [
The comprehensive weighted scoring method was used to deal with the scores of different acupuncture systems. This comprehensive weighted scoring method has been widely used in multi-index evaluation problems [
(1) Suppose that there are
(2) Delphi method is a method based on expert knowledge and experience to determine the subjective weight. The standard steps are as follows:
Step 1: Select 10 to 30 experts with profound theoretical knowledge and rich working experience in the field. (We invited 20 experts.)
Step 2: Provide the experts with a list of indicators to be determined, and attach the relevant information on the indicators and the first round of weighting rules. Experts are required to give the weight
Step 3: Retrieve the results, calculate the average value and standard deviation of each index weight in the round.
Step 4: If the standard deviation of the indicator exceeds the preset value, the average value and standard deviation of the indicators exceeding the preset value of the standard deviation are provided to the experts as reference materials. Therefore, all experts will modify the weight according to the new reference material, and give the weight of each index again.
Step 5: Repeat steps 3 and 4 until the standard deviation of each index weight given by the expert does not exceed the predetermined value. At this time, the expert opinion basically reached an agreement.
After completing step 5, the average value of each index weight is taken as the subjective weight of the index. The standard deviation of the index is 0.1. Each model has the same subjective weight. According to the Delphi method, the subjective weight of indicators is shown in
Experimental indicators | Soft tissue material | Force feedback | Acupuncture effect | Training environment | Real time | Training effect | System stability |
---|---|---|---|---|---|---|---|
Subjective weight | 0.09 | 0.17 | 0.24 | 0.13 | 0.10 | 0.21 | 0.06 |
(3) The objective weight is determined according to the mean square deviation method, which is an objective weighting method based on data determination, and the evaluation data need to have the same unit. The steps are as follows:
Step 1: Calculate the average value of the score
Step 2: Calculate the mean square error of
Step 3: Calculate the objective weight
Different doctors have different scores of the systems constructed by different models. Because the mean square deviation method is an objective weight assignment method based on the scores, the systems constructed by different models have different objective weights, which can balance the subjective preferences of raters. According to the mean square deviation method, the objective weight of each index is shown in
Experimental indicators | MSM | FEM | BEM | SHF | Ours |
---|---|---|---|---|---|
Soft tissue material | 0.097 | 0.116 | 0.124 | 0.097 | 0.159 |
Force feedback | 0.041 | 0.163 | 0.186 | 0.287 | 0.096 |
Acupuncture effect | 0.210 | 0.211 | 0.200 | 0.107 | 0.195 |
Training environment | 0.204 | 0.023 | 0.058 | 0.148 | 0.116 |
Real time | 0.083 | 0.120 | 0.142 | 0.067 | 0.200 |
Training effect | 0.282 | 0.281 | 0.216 | 0.163 | 0.102 |
System stability | 0.084 | 0.087 | 0.073 | 0.132 | 0.133 |
(4) According to the subjective weight and objective weight, the comprehensive weight
where
The comprehensive score
The average scores of MSM, FEM, BEM, SHF, and our model are 7.83, 7.90, 7.93, 7.88, and 8.94 respectively. As shown in
In this paper, a soft tissue acupuncture modeling method [