A virtual simulation operation training and analysis system for anesthesia puncture

Abstract

The present invention relates to the field of medical simulation training technology, and specifically to an anesthesia puncture virtual simulation operation training and analysis system, which includes a force feedback calibration unit, a force feedback adjustment unit and a force feedback output unit. The present invention uses multiple sensors to collect movement and force data of a puncture needle in a virtual tissue, and calculates a theoretical force feedback value based on a human tissue mechanics model library, accurately considering tissue levels and characteristics, and in the deviation correction link, by periodically recalculating force perception deviation values, and using a sliding window averaging method to process data, distinguishing overall and local deviations and making corresponding adjustments, wherein the overall deviation is uniformly corrected, and local functions are set for fine-tuning according to the puncture depth in sections, and considering the time-dependent force feedback of tissue viscoelasticity, the convolution integral is used to calculate components and synthesize the final value with elastic and inertial components, thereby comprehensively improving the accuracy of force feedback, fitting the individual differences and operation details of trainees, and efficiently improving the quality and effect of anesthesia puncture training.

Description

Technical Field

[0001] The invention relates to the technical field of medical simulation training, in particular to an anesthesia puncture virtual simulation operation training and analysis system. Background Art

[0002] Medical simulation training is an important technology. In medical anesthesia, accurate mastery of anesthesia puncture technology is crucial to surgical success and patient safety. Traditional anesthesia puncture training mainly relies on actual operation guidance in clinical practice, but this method has many limitations.

[0003] Among them, there are significant individual differences among patients. The differences in their tissue characteristics and anatomical structures make the difficulty and feel of the puncture operation complex. It is difficult for beginners to fully experience and skillfully deal with various situations in limited clinical practice, which increases the risk of harming patients due to operational errors. In addition, it is difficult for teachers to accurately quantify the operational deviations and force feedback perception differences of trainees during on-site guidance, making it difficult to effectively implement personalized teaching, resulting in low teaching efficiency. In order to solve this technical problem, we provide an anesthesia puncture virtual simulation operation training and analysis system. Summary of the invention

[0004] The purpose of the present invention is to provide an anesthesia puncture virtual simulation operation training and analysis system to solve the problems raised in the above background technology.

[0005] To achieve the above purpose, a virtual simulation operation training and analysis system for anesthesia puncture is provided, comprising a force feedback calibration unit, a force feedback adjustment unit and a force feedback output unit;

[0006] The force feedback calibration unit is used to collect force feedback data of the trainee performing a puncture action in a simulated human tissue, and calculate the force perception deviation value of the trainee according to a preset standard force feedback curve, and the force perception deviation value is used to adjust the force feedback output compensation parameter in subsequent simulation operations;

[0007] The force feedback adjustment unit uses a multi-sensor sequence to obtain the motion state information of the puncture needle in three-dimensional space and the distribution of the force generated when interacting with the virtual tissue, and calculates the theoretical force feedback value of the puncture needle at different tissue levels and operating states based on the human tissue mechanics model library and the real-time data obtained by the multi-sensor sequence, and then corrects the theoretical force feedback value according to the force perception deviation value of the trainee, while considering the time-dependent force feedback of tissue viscoelasticity, and compensates the theoretical force feedback value to obtain the final force feedback value;

[0008] The force feedback output unit converts the corrected and compensated force feedback value into an instruction that can drive the force feedback device, and transmits the instruction to the force feedback mechanical simulator.

[0009] As a further improvement of the technical solution, the force feedback calibration unit calculates the force perception deviation value of the trainee according to a preset standard force feedback curve, as follows:

[0010] The collected force feedback data set is compared with the preset standard force feedback curve, and for each corresponding puncture depth, the difference between the trainee's actual collected force and the standard force is calculated;

[0011] Then, the mean square error calculation formula is used to quantify the overall force perception deviation, and the obtained mean square error value is the student's force perception deviation value.

[0012] As a further improvement of the technical solution, the force feedback adjustment unit includes a fusion monitoring module, and the multi-sensor sequence in the fusion monitoring module includes a position sensor, a pressure sensor and an acceleration sensor. The steps of obtaining the motion state information and force distribution of the puncture needle are as follows:

[0013] The position sensor uses optical positioning to record the coordinate position of the puncture needle tip in three-dimensional space, and calculates the displacement vector of the puncture needle by the coordinate difference of adjacent sampling points to determine the movement direction and speed of the puncture needle;

[0014] The pressure sensors are distributed at the contacting parts between the simulated tissue and the puncture needle, and the pressure value when the puncture needle interacts with the virtual tissue is collected in real time, and the distribution of the force on the surface of the puncture needle can be obtained through the pressure sensor array data;

[0015] The acceleration sensor is installed on the puncture needle to measure the acceleration change of the puncture needle during operation, and calculates the change of the resultant force applied to the puncture needle in combination with the mass information.

[0016] As a further improvement of the technical solution, the force feedback adjustment unit includes a model calculation module, and the method for calculating the theoretical force feedback value based on the human tissue mechanics model library is as follows:

[0017] The virtual tissue level where the puncture needle is located is determined according to its position information, and the finite element analysis method is used to calculate the theoretical force feedback value received by the puncture needle in the current tissue level and motion state based on the mechanical parameters of the corresponding tissue type in the human tissue mechanics model library and the motion state of the puncture needle.

[0018] As a further improvement of the technical solution, the model calculation module, when calculating the theoretical force feedback value, processes tissue heterogeneity as follows:

[0019] When the virtual tissue has different density regions, the tissue is divided into multiple sub-regions, and a local mechanical model is constructed for each sub-region to determine its corresponding elastic modulus, Poisson's ratio and viscosity coefficient;

[0020] Based on the intersection between the puncture needle and each sub-area, the total theoretical force feedback value is calculated by weighted summation, where the weight is determined according to the intersection volume ratio.

[0021] As a further improvement of the technical solution, the force feedback adjustment unit includes a feedback correction module. The feedback correction module dynamically updates the force perception deviation value in the process of correcting the theoretical force feedback value, as follows:

[0022] As the number of student operations increases, the force perception deviation value is recalculated regularly, and the sliding window average method is used to take the most recent The force feedback data of the operation is compared with the standard force feedback curve to calculate the deviation value, and the correction coefficient is gradually adjusted according to the new deviation value.

[0023] As a further improvement of the technical solution, the feedback correction module, when correcting the theoretical force feedback value according to the trainee's force perception deviation value, distinguishes and processes different types of force perception deviations, as follows:

[0024] The force perception deviation is divided into overall deviation and local deviation. The overall deviation is obtained by calculating the difference between the mean of the force feedback data and the mean of the standard force feedback curve.

[0025] The local deviation is analyzed segmentally according to the puncture depth, and the deviation in each segment is calculated. A unified correction coefficient is used to adjust the overall deviation, and different correction functions are used for local deviations according to the deviation of different segments.

[0026] As a further improvement of the technical solution, the feedback correction module considers the time-dependent force feedback calculation method of tissue viscoelasticity when calculating the final force feedback value, as follows:

[0027] A preset fractional derivative model is used to describe the viscoelastic properties of tissues, and the model parameters are determined based on experimental data on human tissue mechanics;

[0028] Combined with the movement speed and historical force conditions of the puncture needle, the force feedback component generated by the tissue viscoelasticity at the current moment is calculated by convolution integral, and this component is added to the elastic force feedback component and the inertial force feedback component to obtain the final force feedback value considering the tissue viscoelasticity.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] In a virtual simulation operation training and analysis system for anesthesia puncture, a force feedback adjustment unit calculates theoretical force feedback values ​​based on a human tissue mechanics model library, fully considers tissue characteristics and puncture needle states, and accurately calculates force feedback in each layer and state through processes such as tissue stratification, unit discretization, stiffness matrix construction, and load solution, thereby improving the adaptability of training to different tissue puncture scenarios. In terms of deviation correction, the force perception deviation value is dynamically updated, and overall and local deviations are distinguished and processed. The force feedback adjustment strategy is optimized using a sliding window averaging method and an appropriate correction function, which is in line with the individual characteristics of trainees and the characteristics of the operation stage, accelerates trainees' skill improvement, and improves the effect and quality of virtual simulation training. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is an overall block diagram of the present invention.

[0032] The meaning of each number in the figure is:

[0033] 1. Force feedback calibration unit; 2. Force feedback adjustment unit; 21. Fusion monitoring module; 22. Model calculation module; 23. Feedback correction module; 3. Force feedback output unit. DETAILED DESCRIPTION

[0034] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] The present invention provides a virtual simulation operation training and analysis system for anesthesia puncture. Figure 1 As shown, it includes a force feedback calibration unit 1, a force feedback adjustment unit 2 and a force feedback output unit 3;

[0036] The force feedback calibration unit 1 is used to collect force feedback data of the trainee performing puncture action in simulated human tissue, and calculate the trainee's force perception deviation value according to a preset standard force feedback curve. The force perception deviation value is used to adjust the force feedback output compensation parameters in subsequent simulation operations.

[0037] First, ensure the consistency of the collected force feedback data set with the preset standard force feedback curve in terms of time axis and puncture depth scale. For the puncture depth, accurately associate the puncture depth information recorded by the displacement sensor with the force feedback data, and compare the force values ​​in the force feedback data set with the standard force values ​​of the standard force feedback curve at the same puncture depth in order from small to large. In this process, the accuracy of depth measurement and the resolution of the standard curve need to be considered to ensure the accuracy of the difference calculation. This step can intuitively reflect the degree of deviation of the trainees' force perception at each puncture depth from the professional standard, and provide detailed data points for the subsequent overall deviation evaluation.

[0038] Determine the depth interval based on the characteristics and requirements of the anesthesia puncture operation. For the depth interval division, different interval ranges can be set according to the different layers of human tissue, which helps to more specifically analyze the force perception deviation of trainees in different operation scenarios.

[0039] For each depth interval or operation stage, count the difference data points within the range , Represents the data point number within the interval or stage, and then, according to the mean square error calculation formula ; Calculate the mean square error value of the interval. The mean square error value can comprehensively reflect the overall degree of the trainees' force perception deviation in the interval or stage. By comparing the mean square error values ​​of different intervals or stages, it can be analyzed in which specific puncture depths or operation links the trainees have a large force perception deviation, providing a strong basis for subsequent targeted training and force feedback adjustment.

[0040] The force feedback adjustment unit 2 uses a multi-sensor sequence to obtain the motion state information of the puncture needle in three-dimensional space and the distribution of the force generated when interacting with the virtual tissue, and based on the human tissue mechanics model library and combined with the real-time data obtained by the multi-sensor sequence, calculates the theoretical force feedback value received by the puncture needle at different tissue levels and operating states, and then corrects the theoretical force feedback value based on the force perception deviation value of the trainee. At the same time, the time-dependent force feedback of the tissue viscoelasticity is considered, and the theoretical force feedback value is compensated to obtain the final force feedback value.

[0041] The force feedback adjustment unit 2 includes a fusion monitoring module 21. The multi-sensor sequence in the fusion monitoring module 21 includes a position sensor, a pressure sensor, and an acceleration sensor. The steps of obtaining the motion state information and force distribution of the puncture needle are as follows:

[0042] Multiple high-precision optical cameras are arranged around the simulated operating environment to form an optical monitoring space that can cover the puncture operation area. Specific optical markers are fixed on the tip of the puncture needle. The optical camera captures the reflected light of these markers and uses the principle of triangulation to calculate the coordinate position of the markers in three-dimensional space to form a position data sequence of the puncture needle tip.

[0043] An array of pressure sensors is evenly distributed around the puncture entrance where the simulated tissue contacts the puncture needle. When the puncture needle contacts or passes through the simulated tissue, the pressure sensor converts the pressure signal into an electrical signal output. The pressure data is collected through a data acquisition circuit to form a pressure data matrix.

[0044] For each sampling moment, the force distribution on the surface of the puncture needle is calculated based on the data matrix of the pressure sensor array. By integrating and analyzing the forces of all sensors, a distribution graph or data description of the force on the surface of the puncture needle can be obtained. This is of great significance for analyzing the contact state and mechanical interaction between the puncture needle and the virtual tissue, and provides detailed information about the force distribution for subsequent force feedback calculations.

[0045] The acceleration sensor is firmly installed on the puncture needle or its connecting parts, ensuring that the measuring axis of the sensor is aligned with the main movement direction of the puncture needle. The acceleration sensor collects the acceleration values ​​of the puncture needle in the directions of the three coordinate axes, and calculates the components of the resultant force acting on the puncture needle in the directions of the three coordinate axes based on the mass of the puncture needle. These components are then synthesized to obtain the magnitude and direction information of the resultant force acting on the puncture needle. These resultant force information is combined with the data collected by the position sensor and the pressure sensor to form a complete information sequence describing the movement and force of the puncture needle in three-dimensional space, providing comprehensive and accurate basic data for subsequent force feedback calculations based on the human tissue mechanics model library, so that the force feedback can truly reflect the actual mechanical state of the puncture needle in the virtual simulation environment.

[0046] The force feedback adjustment unit 2 includes a model calculation module 22. The model calculation module 22 calculates the theoretical force feedback value based on the human tissue mechanics model library, which is specifically as follows:

[0047] When the position information of the puncture needle is transmitted to the system, these coordinates are first matched with the geometric structure information of the pre-built virtual human tissue model. The virtual human tissue model adopts hierarchical modeling technology to accurately describe the spatial position and shape information of each tissue layer such as skin, subcutaneous tissue, muscle, and bone. By judging whether the puncture needle coordinates are within the geometric range of each tissue layer, the virtual tissue layer where the puncture needle is located is determined, and the tissue environment where the puncture needle is located is accurately located, providing accurate tissue characteristic basis for subsequent force feedback calculations, so that force feedback can truly reflect the mechanical differences of different tissues.

[0048] The virtual tissue area corresponding to the determined virtual tissue level is discretized into a finite number of units. For each unit, the corresponding material mechanical parameters are obtained from the human tissue mechanics model library according to the tissue type to which it belongs. The mechanical parameters include elastic modulus, Poisson's ratio and viscosity coefficient. The complex tissue is simplified into computable units, which is convenient for analysis using mechanical models and can efficiently handle tissue mechanics calculations.

[0049] Construct the element stiffness matrix based on the mechanical properties of the element and the node connection relationship , ; where B is the strain-displacement matrix, D is the elastic matrix, is the unit volume, the elastic matrix is ​​related to the elastic modulus and Poisson's ratio, and the stiffness matrices of all units are assembled into the overall stiffness matrix , constructing a mathematical expression of tissue mechanics relationships, providing a basis for solving node displacements and accurately describing the stress-deformation characteristics of tissues.

[0050] Determine the applied load based on the velocity and acceleration of the puncture needle and the mechanical properties of the tissue in which it is located When the puncture needle moves at a certain speed With a viscosity coefficient When the tissue moves, the viscous resistance load ; At the same time, consider the inertia force of the puncture needle ; is the mass of the puncture needle, and the acting load is obtained comprehensively , then, according to the overall stiffness matrix and applied load , solve the node displacement equation ;in The node displacement vector is taken into account comprehensively, the factors affecting the force of the puncture needle are calculated accurately, and the node displacement that conforms to the actual movement is obtained.

[0051] The reaction force on the puncture needle is calculated based on the node displacement. Since the interaction between the puncture needle and the virtual tissue is transmitted through the node force, the node force can be calculated based on the node displacement and the unit stiffness matrix, and then the reaction force on the puncture needle is obtained as the theoretical force feedback value, as follows:

[0052] For nodes in contact with the puncture needle , its node force ; For the node The associated local stiffness matrix, For Node The displacement vector of the puncture needle is synthesized by combining all the node forces in contact with the puncture needle to obtain the reaction force on the puncture needle. This force is the theoretical force feedback value of the puncture needle at the current tissue level and motion state, reflecting the magnitude and direction of the force that the puncture needle should be subjected to under the ideal model, providing basic reference data for subsequent force feedback adjustment, obtaining the force on the puncture needle through node force synthesis, accurately quantifying the theoretical force feedback, and ensuring the integrity and accuracy of the force feedback calculation.

[0053] The model calculation module 22 processes tissue heterogeneity when calculating the theoretical force feedback value, as follows:

[0054] First, geometric information and material property information are extracted from the three-dimensional model data of the virtual tissue, and the image segmentation algorithm is used to divide the different density areas. By setting the density threshold, the voxel sets above or below the specific threshold are determined as different areas. The specific position and range of the heterogeneity in the tissue can be accurately located, providing accurate regional information for subsequent targeted mechanical modeling, so that the entire force feedback calculation can carefully consider the complex characteristics of the tissue and improve the realism of the simulation.

[0055] For each sub-region, the mechanical parameters are determined based on the human tissue mechanics database and the specific tissue type of the sub-region. If the elastic modulus of normal muscle tissue is , the density increases , then the expression of the adjusted elastic modulus is ;in Poisson’s ratio and viscosity coefficient are also adjusted in the same way according to the experimentally determined coefficients. Such determination of parameters can more accurately reflect the actual mechanical behavior of the sub-region, making the constructed local mechanical model more consistent with the actual tissue situation and laying the foundation for the accurate calculation of force feedback values.

[0056] The local mechanical model is constructed by using the finite element method. Each sub-region is discretized into tetrahedral or hexahedral units. The corresponding material properties are assigned to each unit according to the determined mechanical parameters. , Poisson's ratio is The viscosity coefficient is In the sub-region, the material constitutive relation of the unit in the finite element model is set as a mechanical equation containing elastic and viscous terms, and the expression is ;in is the stress tensor, is the strain tensor, It is the strain rate tensor. At the same time, the connection relationship and constraint conditions between the units are determined according to the geometric shape and boundary conditions of the sub-area, and a complete local finite element mechanical model is constructed. The advantage of building the model by the finite element method is that it can handle complex geometric shapes and material nonlinear problems, and can accurately simulate the mechanical response of the sub-area during the puncture process, and provide an accurate model framework for calculating the force of the interaction between the puncture needle and the sub-area, so as to obtain a reliable theoretical force feedback value.

[0057] As the puncture needle moves in the virtual tissue, the intersection volume between the puncture needle and each sub-region is calculated in real time. The intersection between the puncture needle body and the units in the sub-region is determined based on the algorithm of ray and triangle intersection, and then the intersection volume is calculated as follows:

[0058] For a puncture needle that is cylindrical and has an axis direction of , the radius is , the center coordinates are , the triangle vertex of a unit in the sub-region is , by judging the ray ; Whether it intersects with the triangle face and the length of the intersecting line segment, combined with the radius of the cylinder to calculate the intersection volume , set the puncture needle and sub-area The intersection volume is , then the weight of the sub-region ;in This method of determining weights based on the intersection volume by traversing all sub-areas that intersect with the puncture needle can accurately reflect the force contribution ratio of the puncture needle in different sub-areas, because the larger the intersection volume, the larger the interaction area and degree of action between the puncture needle and the sub-area, and thus it should account for a larger weight in the force feedback calculation, making the calculation of the total theoretical force feedback value more consistent with the actual physical situation, thereby improving the authenticity and accuracy of the force feedback simulation.

[0059] In the finite element model, according to the movement speed of the puncture needle , acceleration As well as the mechanical parameters and geometric shapes of the sub-regions, the finite element equations are solved by applying the corresponding boundary conditions and loads to obtain the reaction force on the puncture needle. , then, according to the calculated weight Perform weighted summation to calculate the total theoretical force feedback value Such weighted summation calculation can comprehensively consider the stress conditions of the puncture needle in different mechanical characteristic sub-areas. The total theoretical force feedback value obtained can accurately reflect the overall stress state of the puncture needle in non-uniform tissue, providing a reliable basis for subsequent force feedback adjustment and output, making the force feedback of the virtual simulation system closer to the mechanical environment in the real puncture operation, and helping trainees to better master anesthesia puncture skills and the ability to cope with complex tissue conditions.

[0060] The force feedback adjustment unit 2 includes a feedback correction module 23. The feedback correction module 23 dynamically updates the force perception deviation value in the process of correcting the theoretical force feedback value. Specifically, the method is as follows:

[0061] During the students' virtual simulation operation of anesthesia puncture, the system continuously records the detailed force feedback data of each operation and the corresponding operation step information. The comprehensive operation data can reflect the students' force perception performance in different operation scenarios. The advantage is that it is conducive to in-depth analysis of the students' operation habits and force perception characteristics, and the effect is to make the subsequent deviation value calculation more representative and reliable.

[0062] Set the deviation value update calculation to be performed every 10 operations to avoid updating the deviation value too frequently or too infrequently and improve the training effect. When the deviation value calculation is triggered, the sliding window averaging method is used to select the most recent The data of the operation, The value of is determined according to the stability of the operation and the amount of data required, and this value is extracted from the database. The force feedback data sequence of the first operation is compared with the preset standard force feedback curve under the same operation steps. For each corresponding data point, the difference is calculated. Operation at a certain puncture depth The force feedback value at The force value of the standard force feedback curve at this depth is , then the deviation value of this point The sliding window averaging method can balance the importance of recent data and the reference of historical data, and can effectively reduce the impact of abnormal data of a single operation on the calculation of the deviation value, so that the calculated deviation value can better reflect the student's actual force perception state, and provide a reliable basis for the subsequent adjustment of the correction coefficient.

[0063] According to the calculated new force perception deviation value, the correction coefficient is gradually adjusted. The current correction coefficient is set to The new deviation value is , using the proportional adjustment strategy, that is ;in It is a coefficient determined according to the system sensitivity and adjustment range requirements. If the deviation value is positive, it means that the force perceived by the trainee is greater than the standard. The correction coefficient should be appropriately reduced to reduce the subsequent force feedback value accordingly. Conversely, if the deviation value is negative, the correction coefficient should be increased. During the adjustment process, the upper and lower limits of the correction coefficient are set, where the lower limit of the correction coefficient is , the upper limit is , when the calculation Less than When ,when Greater than When Adjusting the correction coefficient in this way can accurately adjust the force feedback according to the force perception deviation of the students, so that the force feedback system can dynamically adapt to the individual differences of the students, provide force feedback that is more in line with the students' actual perception, and improve the quality and effect of virtual simulation training.

[0064] Among them, the feedback correction module 23, when correcting the theoretical force feedback value according to the student's force perception deviation value, distinguishes and processes different types of force perception deviations, as follows:

[0065] First, the system collects all force feedback data points of the trainees during a complete anesthesia puncture operation. These data cover the entire process from the puncture needle contacting the simulated tissue to the completion of the puncture action. These data are integrated to form a force feedback data sequence. , and then calculate the mean of the series At the same time, obtain the force value sequence of the preset standard force feedback curve in the corresponding complete operation process , and calculate its mean ; Calculate the overall deviation value The overall deviation reflects the average deviation of the trainees’ force perception during the entire operation process. It can quickly grasp the difference between the trainees’ overall force perception characteristics and the standard, and provide a macro correction direction for the subsequent overall force feedback adjustment, so that the force feedback system can adapt to the trainees’ force perception habits as a whole, and avoid the force feedback being too different from the trainees’ expectations at the overall level.

[0066] The overall deviation value calculated based on Determining uniform correction factors , using a simple linear relationship such as ,in is a coefficient determined empirically based on the overall sensitivity of the system and the adjustment range. When the students' overall perception is relatively large, <1, the theoretical force feedback value is adjusted to be smaller overall; when <0, the overall perception of the students is relatively small, >1, the theoretical force feedback value is adjusted as a whole. During the entire operation, all theoretical force feedback values ​​are multiplied by this unified correction coefficient. The overall deviation has a consistent impact on the entire operation. The use of a unified coefficient adjustment is simple and efficient, and can quickly and effectively correct the overall force feedback, so that students can feel that the overall force feedback is changing in a direction that is more in line with their own perception in subsequent operations, thereby improving students' adaptability to overall force feedback and reducing operational discomfort caused by overall force perception deviation.

[0067] The force feedback data is segmented according to the puncture depth, and the puncture depth is divided into shallow , middle level and deep , is the maximum penetration depth, for each depth segment , extract the force feedback data subsequence within this segment , and calculate its mean At the same time, obtain the force value sequence of the standard force feedback curve in the same depth segment , calculate its mean , calculate the local deviation value of the depth segment Different puncture depths correspond to different tissue characteristics, and students may have different force perception deviations at different depths. Segmented calculation can accurately locate these differences, and can provide a more detailed understanding of students' force perception at each key operating depth, providing a basis for targeted local force feedback adjustments.

[0068] According to the local deviation value of each depth segment , design different correction functions , for the shallow penetration depth segment, if the local deviation value , indicating that the students have a relatively large shallow perception, and an exponential decay function can be used The theoretical force feedback value within this section Correction is made. For the middle and deep puncture depth segments, different correction functions are designed according to their tissue characteristics and operation requirements. During the operation, when the puncture needle is in the corresponding depth segment, the corresponding correction function is applied to correct the theoretical force feedback value. The tissue mechanical properties and operation requirements of different depth segments are different, and different correction strategies are needed to accurately adjust the force feedback. It can perform personalized and precise force feedback correction according to the force perception deviation of the trainees at different depths, so that the trainees can feel accurate force feedback that conforms to their own force perception at different depths during the entire puncture operation, effectively improving the trainees' adaptability to local force feedback changes and the training effect of operation skills.

[0069] The feedback correction module 23 takes into account the time-dependent force feedback calculation method of tissue viscoelasticity when calculating the final force feedback value, as follows:

[0070] The preset fractional derivative model is used to describe the viscoelastic properties of tissues. This model can better reflect the viscoelastic behavior of tissues at different strain rates. Its stress-strain relationship can be expressed as ;in is stress, It's strain. is the elastic modulus, is the viscosity coefficient, is the fractional derivative operator, It is a fractional order. The fractional-order derivative model can simulate the time-dependent characteristics of tissue viscoelasticity more accurately, which is superior to the traditional integer-order model. It can improve the accuracy of force feedback calculation and make the simulated force feedback closer to the actual tissue force condition, allowing trainees to feel more realistic tissue viscoelastic resistance in virtual puncture operations, thereby enhancing the authenticity and effectiveness of training.

[0071] During the virtual simulation process, the movement speed information of the puncture needle is obtained in real time The position sensor can continuously monitor the position of the puncture needle and calculate the displacement difference of adjacent time points to obtain the velocity sequence. At the same time, the historical force of the puncture needle can be recorded. , that is, all the force data from the start of the puncture operation to the current moment. The viscoelastic response of the tissue has memory. The current force feedback depends not only on the current state of motion, but also on the previous force history, so as to accurately calculate the viscoelastic force feedback component that conforms to the actual physical process.

[0072] According to the fractional derivative model and the acquired motion speed and historical force data, the force feedback component generated by tissue viscoelasticity at the current moment is calculated by convolution integral. , let the memory function Related to the fractional derivative model, for the fractional order model, ;in is a gamma function, then the calculation formula for the viscoelastic force feedback component is: ;

[0073] The convolution integral can accurately describe the cumulative effect of tissue viscoelasticity over time and precisely calculate the viscoelastic force feedback component, so that the force feedback can truly reflect the changing characteristics of tissue viscoelasticity over time, providing students with a more realistic operating feel.

[0074] Calculation of elastic force feedback components , according to the current displacement of the puncture needle and the elastic modulus of the tissue , according to Hooke's law, ; Calculate the inertial force feedback component , the mass of the puncture needle is known and acceleration , according to Newton's second law ; These calculations are based on the principles of classical mechanics and can accurately reflect the contribution of tissue elasticity and the inertia of the puncture needle to force feedback.

[0075] The calculated viscoelastic force feedback component , elastic force feedback component and inertial force feedback component Add together to get the theoretical force feedback value considering tissue viscoelasticity This synthesis method can comprehensively consider the influence of the mechanical properties of the tissue and the motion state of the puncture needle on the force feedback. The final force feedback value obtained accurately simulates the force condition of the puncture needle in the viscoelastic tissue, providing trainees with a highly realistic force feedback experience, which helps to improve the quality and effectiveness of anesthesia puncture virtual simulation operation training.

[0076] The force feedback output unit 3 converts the corrected and compensated force feedback value into an instruction that can drive the force feedback device, and transmits it to the force feedback mechanical simulator.

[0077] In the present invention, the movement and force data of the puncture needle in the virtual tissue are collected with the help of multiple sensors, and the theoretical force feedback value is calculated based on the human tissue mechanics model library, the tissue hierarchy and characteristics are accurately considered, and in the deviation correction link, the force perception deviation value is periodically recalculated, and the sliding window averaging method is used to process the data, distinguishing between overall and local deviations and making corresponding adjustments, wherein the overall deviation is corrected uniformly, and the local deviation is fine-tuned by setting functions in segments according to the puncture depth, and the time-dependent force feedback of the tissue viscoelasticity is considered, the components are calculated by convolution and synthesized with the elastic and inertial components to form the final value, thereby comprehensively improving the accuracy of force feedback, adapting to the individual differences and operation details of the trainees, and efficiently improving the quality and effect of anesthesia puncture training.

[0078] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A virtual simulation operation training and analysis system for anesthesia puncture, characterized in that: It comprises a force feedback calibration unit (1), a force feedback adjustment unit (2) and a force feedback output unit (3); The force feedback calibration unit (1) is used to collect force feedback data of a trainee performing a puncture action in a simulated human tissue, and calculate the trainee's force perception deviation value according to a preset standard force feedback curve, wherein the force perception deviation value is used to adjust a force feedback output compensation parameter in a subsequent simulated operation; The force feedback adjustment unit (2) uses a multi-sensor sequence to obtain the motion state information of the puncture needle in the three-dimensional space and the distribution of the force generated when interacting with the virtual tissue, and calculates the theoretical force feedback value received by the puncture needle at different tissue levels and operating states based on the human tissue mechanics model library and the real-time data obtained by the multi-sensor sequence, and then corrects the theoretical force feedback value based on the force perception deviation value of the trainee, while considering the time-dependent force feedback of the tissue viscoelasticity, and compensating the theoretical force feedback value to obtain the final force feedback value; The force feedback output unit (3) converts the corrected and compensated force feedback value into an instruction that can drive the force feedback device, and transmits the instruction to the force feedback mechanical simulator.

2. The anesthesia puncture virtual simulation operation training and analysis system according to claim 1 is characterized in that: The force feedback calibration unit (1) calculates the force perception deviation value of the trainee according to a preset standard force feedback curve, as follows: The collected force feedback data set is compared with the preset standard force feedback curve, and for each corresponding puncture depth, the difference between the trainee's actual collected force and the standard force is calculated; Then, the mean square error calculation formula is used to quantify the overall force perception deviation, and the obtained mean square error value is the student's force perception deviation value.

3. The anesthesia puncture virtual simulation operation training and analysis system according to claim 1 is characterized in that: The force feedback adjustment unit (2) comprises a fusion monitoring module (21), wherein the multi-sensor sequence in the fusion monitoring module (21) comprises a position sensor, a pressure sensor and an acceleration sensor, and the steps of obtaining the motion state information and force distribution of the puncture needle are specifically as follows: The position sensor uses optical positioning to record the coordinate position of the puncture needle tip in three-dimensional space, and calculates the displacement vector of the puncture needle by the coordinate difference of adjacent sampling points to determine the movement direction and speed of the puncture needle; The pressure sensors are distributed at the contacting parts between the simulated tissue and the puncture needle, and the pressure value when the puncture needle interacts with the virtual tissue is collected in real time, and the distribution of the force on the surface of the puncture needle can be obtained through the pressure sensor array data; The acceleration sensor is installed on the puncture needle to measure the acceleration change of the puncture needle during operation, and calculates the change of the resultant force applied to the puncture needle in combination with the mass information.

4. The anesthesia puncture virtual simulation operation training and analysis system according to claim 3 is characterized by: The force feedback adjustment unit (2) comprises a model calculation module (22), wherein the model calculation module (22) calculates a theoretical force feedback value based on a human tissue mechanics model library, specifically as follows: The virtual tissue level where the puncture needle is located is determined according to its position information, and the finite element analysis method is used to calculate the theoretical force feedback value received by the puncture needle in the current tissue level and motion state based on the mechanical parameters of the corresponding tissue type in the human tissue mechanics model library and the motion state of the puncture needle.

5. The anesthesia puncture virtual simulation operation training and analysis system according to claim 4 is characterized in that: When the model calculation module (22) calculates the theoretical force feedback value, the method for processing tissue heterogeneity is specifically as follows: When the virtual tissue has different density regions, the tissue is divided into multiple sub-regions, and a local mechanical model is constructed for each sub-region to determine its corresponding elastic modulus, Poisson's ratio and viscosity coefficient; Based on the intersection between the puncture needle and each sub-area, the total theoretical force feedback value is calculated by weighted summation, where the weight is determined according to the intersection volume ratio.

6. The anesthesia puncture virtual simulation operation training and analysis system according to claim 5 is characterized in that: The force feedback adjustment unit (2) comprises a feedback correction module (23). The feedback correction module (23) dynamically updates the force perception deviation value in the process of correcting the theoretical force feedback value, which is specifically as follows: As the number of student operations increases, the force perception deviation value is recalculated regularly, and the sliding window average method is used to take the most recent The force feedback data of the operation is compared with the standard force feedback curve to calculate the deviation value, and the correction coefficient is gradually adjusted according to the new deviation value.

7. The anesthesia puncture virtual simulation operation training and analysis system according to claim 6 is characterized by: The feedback correction module (23), when correcting the theoretical force feedback value according to the trainee's force perception deviation value, distinguishes and processes different types of force perception deviations, specifically as follows: The force perception deviation is divided into overall deviation and local deviation. The overall deviation is obtained by calculating the difference between the mean of the force feedback data and the mean of the standard force feedback curve. The local deviation is analyzed segmentally according to the puncture depth, and the deviation in each segment is calculated. A unified correction coefficient is used to adjust the overall deviation, and different correction functions are used for local deviations according to the deviation of different segments.

8. The anesthesia puncture virtual simulation operation training and analysis system according to claim 7 is characterized by: The feedback correction module (23) takes into account the time-dependent force feedback calculation method of tissue viscoelasticity when calculating the final force feedback value, as follows: A preset fractional derivative model is used to describe the viscoelastic properties of tissues, and the model parameters are determined based on experimental data on human tissue mechanics; Combined with the movement speed and historical force conditions of the puncture needle, the force feedback component generated by the tissue viscoelasticity at the current moment is calculated by convolution integral, and this component is added to the elastic force feedback component and the inertial force feedback component to obtain the final force feedback value considering the tissue viscoelasticity.

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