Endoscopic thyroid surgery training result discrimination method and resection training model

Abstract

The invention relates to an endoscopic thyroid surgery training result discrimination method and a resection training model. The method comprises the following steps: S1, sending a data acquisition instruction to a sensor; the data acquisition instruction is used for indicating the sensor to acquire operation data in the operation process and transmitting the operation data and the judgment instruction to the server; s2, in response to the judgment instruction, analyzing and judging the operation data according to a preset judgment rule to obtain a judgment result, and obtaining an operation optimization suggestion according to the judgment result; s3, the judgment result, the operation optimization suggestion and the display instruction are transmitted to a display module; the display instruction is used for indicating the display equipment to display the judgment result and the operation optimization suggestion in a visual mode. According to the method, the endoscopic thyroid surgery training result can be effectively distinguished, the distinguishing result and optimization suggestions can be visually presented for trainees, and the technical effects of assisting in improving the training effect are achieved.

Description

Technical Field

[0001] The present invention belongs to the field of medical technology, and particularly relates to a method for discriminating the training results of endoscopic thyroidectomy and an excision training model. Background Art

[0002] With the development of medical technology, endoscopic thyroidectomy has been increasingly widely applied due to its advantages such as minimal invasiveness and rapid recovery. However, the operation is complex and requires extremely high surgical skills of doctors, making the importance of surgical training more prominent. Traditional surgical training mainly relies on the accumulation of experience in actual surgeries, which poses a great risk to patients and is difficult to rapidly improve the operation level of doctors in actual surgical scenarios.

[0003] Currently, although there are some surgical training models, there are many deficiencies in the training for endoscopic thyroidectomy. Most models cannot accurately simulate the true characteristics of thyroid tissue and the surgical environment, and lack effective means for evaluating the accuracy of surgical operations and surgical outcomes.

[0004] Therefore, there is an urgent need for a method that can comprehensively and accurately discriminate the training results of endoscopic thyroidectomy and a supporting excision training model that is highly simulated and has an effective evaluation function to fill the gaps in the existing technology, improve the quality of surgical training, ensure the safety and effectiveness of surgeries, and promote the development and popularization of endoscopic thyroidectomy technology. Summary of the Invention

[0005] Based on this, in view of the above technical problems, it is necessary to provide a method for discriminating the training results of endoscopic thyroidectomy that can comprehensively and accurately discriminate the training results of endoscopic thyroidectomy, a surgical training result discrimination system, an excision training model used in conjunction with this method, a computer device, and a storage medium.

[0006] In a first aspect, the present application provides a method for discriminating the training results of endoscopic thyroidectomy, which is applied to a server in a surgical training result discrimination system. The surgical training result discrimination system further includes an excision training model and a display device; the excision training model simulates the human neck structure and is used to provide endoscopic thyroidectomy training for trainees, and a sensor for collecting surgical data is integrated inside the excision training model; the sensor is connected to the server through a built-in first data transmission module; the display device is connected to the server through a built-in second data transmission module;

[0007] The method for discriminating the training results of endoscopic thyroidectomy includes:

[0008] S1: Send a data acquisition instruction to the sensor; the data acquisition instruction is used to instruct the sensor to acquire surgical data during the surgery and transmit the surgical data and a discrimination instruction to the server;

[0009] S2: In response to the discrimination instruction, analyze and discriminate the surgical data according to the preset discrimination rules to obtain a discrimination result, and obtain surgical optimization suggestions based on the discrimination result;

[0010] S3: Transmit the discrimination result, surgical optimization suggestions, and display instruction to the display module; the display instruction is used to instruct the display device to visually display the discrimination result and surgical optimization suggestions.

[0011] In a second aspect, the present application further provides a surgical training result discrimination system, including: an excision training model, a server, and a display device;

[0012] The excision training model simulates the human neck structure, is used to provide laparoscopic thyroid surgery training for trainees, and a sensor for collecting surgical data is integrated inside the excision training model;

[0013] The sensor is connected to the server through the built-in first data transmission module, and the display device is connected to the server through the built-in second data transmission module;

[0014] The server is used to implement a method for discriminating the results of laparoscopic thyroid surgery training as described in the first aspect.

[0015] In a third aspect, the present application further provides an excision training model, including: a main body part that simulates the human neck structure, a trocar for laparoscopic thyroid surgery training, a cutting tool for laparoscopic thyroid surgery training, a sensor assembly integrated inside the main body part, and a data transmission unit;

[0016] The main body part has a simulated skin, a simulated muscle layer, and a thyroid tissue module. The thyroid tissue module has the same shape, size, texture, and capsule structure as the human thyroid, and the connection characteristics of the capsule structure with the surrounding tissues simulate the adhesion degree in the real human physiological state;

[0017] The sensor assembly includes: a position sensor for detecting the positions of the cutting tool and the trocar, and the position sensors are distributed around and inside the thyroid tissue module; and a pressure sensor for measuring the cutting force exerted by the cutting tool on the thyroid tissue module, and the pressure sensor is installed on the surface and internal layer where the thyroid tissue module contacts the cutting tool; and an impedance sensor system for collecting impedance data at different positions inside the thyroid tissue module, and the impedance sensor system is composed of electrodes arranged around the thyroid tissue module and impedance sensors arranged at different positions inside the thyroid module. By applying an alternating current signal with a specific frequency and specific intensity to the thyroid tissue module through the electrodes, the impedance sensors can collect impedance data at different positions inside the thyroid tissue module;

[0018] The data transmission unit is connected to the sensor component and is used to transmit the data collected by the sensor component to the server, and the server is used to implement a method for discriminating the training result of endoscopic thyroidectomy as described in the first aspect.

[0019] In a fourth aspect, the present application further provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements a method for discriminating the training result of endoscopic thyroidectomy as described in the first aspect.

[0020] In a fifth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements a method for discriminating the training result of endoscopic thyroidectomy as described in the first aspect.

[0021] For the above-mentioned method for discriminating the training result of endoscopic thyroidectomy, the surgical training result discrimination system, the resection training model used in conjunction with this method, the computer device, and the storage medium, by integrating sensors capable of collecting surgical data inside the resection training model that simulates the human neck structure and connecting it to the server, and also connecting the display device to the server; by sending a data acquisition instruction to the sensor and analyzing and discriminating the acquired surgical data according to the preset discrimination rules to obtain the result and surgical optimization suggestions; and transmitting the relevant content to the display device for visual presentation. Thus, the training result of endoscopic thyroidectomy can be effectively discriminated, and the discrimination result and optimization suggestions can be intuitively presented to the training personnel to assist in improving the training effect. Description of the Drawings

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the drawings required for use in the description of the embodiments or related technologies. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0023] Figure 1 It is a schematic flowchart of a method for discriminating the training result of endoscopic thyroidectomy provided by the present invention;

[0024] Figure 2 It is a schematic structural diagram of a surgical training result discrimination system provided by the present invention;

[0025] Figure 3 It is a schematic structural diagram of a resection training model provided by the present invention.

[0026] In the figure:

[0027] 1. Main body; 2. Trocar; 3. Sensor assembly; 4. Data transmission unit; 11. Simulated skin; 12. Simulated muscle layer; 13. Thyroid tissue module. Detailed implementation manners

[0028] In order to make the objectives, technical solutions and advantages of the present application clearer and more understandable, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0029] Refer to Figure 1 , which shows a schematic flow chart of a method for discriminating the training results of endoscopic thyroid surgery provided by the present application. This method is applied to the server in the surgical training result discrimination system, and the surgical training result discrimination system further includes an excision training model and a display device; the excision training model simulates the human neck structure and is used to provide endoscopic thyroid surgery training for trainees, and a sensor for collecting surgical data is integrated inside the excision training model; the sensor is connected to the server through a built-in first data transmission module; the display device is connected to the server through a built-in second data transmission module.

[0030] The method for discriminating the training results of endoscopic thyroid surgery includes the following steps:

[0031] S1: Send a data acquisition instruction to the sensor; the data acquisition instruction is used to instruct the sensor to acquire surgical data during the surgical process and transmit the surgical data and a discrimination instruction to the server.

[0032] Specifically, the server is the core control unit of the surgical training result discrimination system, and step S1 is used to start the data acquisition function. A data acquisition instruction can be sent to the sensor integrated inside the excision training model through a pre-established communication protocol. The sending of this instruction can be triggered by a system-set timing trigger mechanism or manually initiated by the trainee. For example, when the trainee completes a surgical operation session or reaches a system-preset phased training node, the server will send an instruction.

[0033] After receiving the instruction, the sensor immediately starts its data collection function. The sensors are distributed in various key parts of the resection training model and can sense various parameters during the operation, such as the contact force between the surgical instrument and the simulated tissue, the cutting angle, the moving speed, the operation path and other surgical data. These data are collected in real time by the sensor, and through its built-in first data transmission module, a safe, reliable and high-speed transmission method is adopted, such as wireless encrypted transmission or wired optical fiber transmission, to transmit the collected surgical data and the corresponding discrimination instructions to the server. In this process, in order to ensure the integrity and accuracy of the data, the transmission module can verify and correct the data to prevent data loss or errors during transmission.

[0034] S2: In response to the discrimination instruction, the surgical data is analyzed and discriminated according to the preset discrimination rules to obtain the discrimination result, and the surgical optimization suggestion is obtained according to the discrimination result.

[0035] Specifically, after receiving the surgical data and identification instructions from the sensor, the server starts its built-in analysis and identification module, which performs calculations based on pre-set identification rules. These identification rules can be based on a large amount of clinical practice data, expert experience, and medical standards, covering all key aspects of surgical operations.

[0036] For example, for the operation path of surgical instruments, the judgment rules will compare with the standard surgical path library. If the trainee's operation path deviates too much from the standard path and exceeds the allowable error range, it will be recorded as a potential problem point. For cutting angles, the system will determine whether there is a risk of over-cutting or improper cutting angles that may cause damage to important tissues based on the anatomical characteristics of the thyroid tissue. Through detailed analysis of these surgical data, the server can come up with a comprehensive judgment result, clearly pointing out the strengths and weaknesses of the trainee during the surgical operation.

[0037] Based on the obtained judgment results, the server further calls its built-in intelligent optimization suggestion generation algorithm. The algorithm can generate targeted surgical optimization suggestions based on the specific operation conditions of the trainees and combined with medical best practices. If the judgment results show that the trainees are too fast in a certain operation step during the operation, which may affect the accuracy of the operation, then the optimization suggestion may be to appropriately reduce the operation speed and specify the specific numerical range or reference indicators for reducing the speed. If there is a problem with the use of surgical instruments, the optimization suggestions can provide the correct instrument holding method, operation skills, and visual demonstration animations or pictures to help trainees better understand and improve.

[0038] S3: Transmit the discrimination result, surgical optimization suggestions, and display instructions to the display module; the display instructions are used to instruct the display device to visually display the discrimination result and surgical optimization suggestions.

[0039] Specifically, after the server completes the analysis of the discrimination result and the generation of surgical optimization suggestions, it integrates and packages these important information and display instructions. The display instructions include the requirements for visual display of the discrimination result and surgical optimization suggestions, such as in what chart form to display the data comparison in the discrimination result, and in what text layout and animation demonstration methods to present the surgical optimization suggestions, etc.

[0040] The server transmits this data to the display device through the connection with the second data transmission module built into the display device. The encryption and verification mechanisms can also be adopted during the transmission process to ensure the security and integrity of the data. After receiving these data and display instructions, the display device activates its display function and, according to the instructions of the server, presents the discrimination result to the training personnel in a visual manner, such as comparing the differences between the training personnel and the standard surgical operations in various key indicators through bar charts, and at the same time presenting the surgical optimization suggestions in a combination of text descriptions and animation demonstrations, enabling the training personnel to intuitively understand the problems in their operations and how to improve, thereby effectively improving the effect and quality of endoscopic thyroid surgery training and providing strong technical support and guidance for the training personnel in actual surgical operations.

[0041] The above method for discriminating the training result of endoscopic thyroid surgery integrates sensors capable of collecting surgical data inside the resection training model that simulates the human neck structure and connects it to the server, and also connects the display device to the server; by sending data acquisition instructions to the sensors, analyzing and discriminating the acquired surgical data according to the preset discrimination rules to obtain the result and surgical optimization suggestions; transmitting the relevant content to the display device for visual presentation. Thus, it effectively discriminates the training result of endoscopic thyroid surgery and visually presents the discrimination result and optimization suggestions to the training personnel, assisting in improving the training effect.

[0042] In an optional embodiment, the surgical data includes operation data and thyroid status data; the server analyzes and discriminates the surgical data according to the preset discrimination rules to obtain the discrimination result, including the following steps:

[0043] Based on the operation data, obtain the surgical operation accuracy index;

[0044] Based on the thyroid status data, obtain the surgical effect index;

[0045] Based on the surgical operation accuracy index and the surgical effect index, obtain the comprehensive score and evaluation result, and use the comprehensive score and evaluation result as the discrimination result.

[0046] Specifically, during the entire training process of endoscopic thyroidectomy, the surgical data involved specifically includes two major parts: operation data and thyroid status data.

[0047] The operation data focuses on reflecting the relevant situations of the trainer during the surgical operation, covering specific information in multiple dimensions. For example, the operation angle of the surgical instrument records the angle change between the instrument and the simulated tissue when the trainer holds the endoscopic surgical instrument and operates within the resection training model that simulates the human neck structure. Different operation steps have corresponding standard angle ranges, and these angle data play a key role in judging whether the operation is precise. Another example is the moving speed of the surgical instrument, which reflects how fast or slow the trainer operates the instrument to move within the simulated surgical area. Excessive or too slow speed may affect the surgical effect. For example, during delicate tissue cutting or separation operations, too fast a speed may lead to accidental cutting, etc., while too slow a speed may affect the surgical efficiency. Therefore, this data can also be regarded as operation data.

[0048] The thyroid status data mainly focuses on the specific state performance of the simulated thyroid before, during, and after the surgical operation. On the one hand, it can be the integrity data of the thyroid tissue. During the surgical training process, through sensors, it monitors whether the simulated thyroid tissue is overly cut or has any unnecessary damage, etc. The integrity status of the thyroid tissue is directly related to the success of the operation. If there is a large area of unreasonable damage, it is very likely that there are mistakes in the surgical operation. On the other hand, it can also involve data on the degree of influence on important adjacent structures such as blood vessels and nerves around the thyroid. Because in actual endoscopic thyroidectomy, protecting these surrounding important structures is extremely crucial. The sensor will collect relevant information such as whether the blood vessels are accidentally cut off and whether the nerves are pulled or damaged, etc., so as to comprehensively reflect the state of the thyroid and the impact of the surgical operation on its surrounding environment.

[0049] After receiving the operation data, the server analyzes and processes it according to a preset set of discrimination rules, and then obtains the surgical operation accuracy index.

[0050] Taking the angle data of the operating instrument as an example, the server compares the actual angle data generated by the trainer in each operation link with the standard angle range pre-stored in the system, and can calculate the angle deviation value through an algorithm. The weights of these deviation values are different in different operation steps. For example, the weight of the angle deviation in the key tissue cutting step is relatively high. Then, by comprehensively considering the angle deviation situations of all operation steps and performing weighted calculations according to the established mathematical model, the accuracy score regarding the operation angle is obtained.

[0051] For operation data such as the moving speed and acting force of the operating instrument, a similar method can also be adopted to compare and analyze them with their respective corresponding standard ranges respectively, obtain the corresponding scores, and finally integrate the scores corresponding to these operation data in different dimensions according to a certain proportional relationship, so as to obtain an index value that can comprehensively reflect the accuracy of the surgical operation. This value can intuitively reflect the accuracy level of the training personnel during the operation.

[0052] When processing thyroid status data to obtain surgical effect indicators, the server follows another set of discrimination rules to execute.

[0053] For the integrity data of the thyroid tissue, the system can quantitatively evaluate it according to factors such as the degree and scope of tissue damage. For example, a tissue integrity scoring system is set. If there is a small area of damage to the simulated thyroid tissue that does not affect key functions, a certain score will be deducted, and if there is a large area of severe damage, more points will be deducted. In this way, a score regarding the integrity of the thyroid tissue is obtained.

[0054] For the data on the affected degree of important adjacent structures around the thyroid, the server can also grade and score according to the severity of damage to structures such as blood vessels and nerves. For example, a slight scratch on a blood vessel may correspond to a lower deduction of points, while a serious situation such as a complete rupture of a blood vessel will result in a larger deduction of points. Then, by integrating the scores of the affected situations of these surrounding structures and combining the score of the thyroid tissue integrity, calculations are made according to the pre-set weight ratio, and finally, an index value of the surgical effect that can comprehensively reflect the impact of the operation on the thyroid and its surrounding environment is obtained.

[0055] According to the surgical operation accuracy index and the surgical effect index, a comprehensive score and an evaluation result are obtained, and the comprehensive score and the evaluation result are used as the discrimination result

[0056] After obtaining the surgical operation accuracy index and the surgical effect index respectively, the server further calculates the comprehensive score according to the integration rule. Usually, corresponding weights can be assigned to the surgical operation accuracy index and the surgical effect index respectively. The setting of these weights can be determined based on the importance of the two in surgical success in clinical practice. For example, the surgical operation accuracy index can be assigned a weight of 60%, and the surgical effect index can be assigned a weight of 40%.

[0057] Then, according to such a weight relationship, the values of the two indexes are calculated by weighted summation to obtain the comprehensive score.

[0058] In addition to calculating the comprehensive score, the server can also generate corresponding evaluation results according to the different range intervals where the comprehensive score is located and the specific numerical values of the two indicators. For example, when the comprehensive score is 90 points or above and the numerical values of the two indicators are both relatively ideal, the evaluation result can be "Excellent, the surgical operation is standardized and the effect is good"; if the comprehensive score is between 60-89 points, the evaluation result can be "Qualified, some operation details can be further optimized"; and when the comprehensive score is below 60 points, the evaluation result can be "Unqualified, it is necessary to focus on improving the operation accuracy and surgical effect", etc. Finally, this comprehensive score and the corresponding evaluation result are used together as the discrimination result to feedback the surgical training situation to the training personnel for subsequent improvement and enhancement.

[0059] In an alternative embodiment, the resection training model further includes a trocar and a cutting tool for laparoscopic thyroid surgery training, and the operation data includes: the time-series coordinates of the trocar in three-dimensional space during the puncture process, and the time-series coordinates of the cutting tool in three-dimensional space during the resection process;

[0060] Based on the operation data, obtain the surgical operation accuracy indicators, including:

[0061] Based on the time-series coordinates of the trocar, obtain the movement trajectory L1 of the trocar; based on the time-series coordinates of the cutting tool, obtain the movement trajectory L2 of the cutting tool;

[0062] According to the formula Calculate the average deviation distance D of the puncture path; where n is the number of sampling points selected on the movement trajectory L1 for calculation, L standard is the preset standard puncture trajectory, p i is the i-th sampling point on the movement trajectory L1, d(p i , L standard ) is the shortest distance from the point p i to the movement trajectory L1;

[0063] Using computer graphics algorithms, calculate the area A enclosed by the movement trajectory L2 of the cutting tool actual ; According to the formula Calculate the cutting path deviation rate P; where A standard is the preset standard resection range area of the thyroid tissue;

[0064] Take the average deviation distance D of the puncture path and the cutting path deviation rate P as the surgical operation accuracy indicators.

[0065] Specifically, during the training process of endoscopic thyroidectomy, the resection training model is equipped with trocars and cutting tools for simulating surgical operations. The time-series coordinates of the two in three-dimensional space can be used as important operation data to measure the accuracy of surgical operations.

[0066] During the corresponding surgical training operations of the trocar and the cutting tool, their positions in three-dimensional space change continuously with time. The sensor records these position information at a high frequency, thus forming a series of coordinate data with time stamps, that is, time-series coordinates. These coordinate data contain the position information of the tool at each instant in three-dimensional space (in the length, width, and height directions). For example, the three-dimensional coordinates (x1, y1, z1) of the tip of the trocar or the cutting tool at a certain moment, and the coordinates (x2, y2, z2) at the next moment, etc.

[0067] After receiving these time-series coordinates, the server connects these discrete coordinate points in sequence according to the time order through a specific algorithm, and can depict the movement trajectories of the trocar and the cutting tool during the corresponding surgical operations. These two movement trajectories are like the "action roadmaps" left by the trocar and the tool respectively in three-dimensional space. They respectively intuitively show the movement processes of the trocar and the tool during the corresponding surgical procedures, including various movement situations such as the movement paths, turns, and pauses of the trocar and the tool in different directions.

[0068] Based on the obtained movement trajectory L1 of the trocar, the server selects n sampling points p for calculation on the movement trajectory of the trocar i (i = 1, 2,..., n). These sampling points can be selected in a uniformly distributed manner on the trajectory, or selected specifically according to the key operation stages to ensure that the overall characteristics of the puncture path can be accurately reflected.

[0069] For each sampling point p i , the server calculates its shortest distance d(p standard , L i , L standard ) to the preset standard puncture trajectory L. The method for calculating the shortest distance can adopt geometric calculation methods in three-dimensional space. For example, by constructing a perpendicular line segment from a point to a straight line (or curve) and using geometric principles such as the Pythagorean theorem to calculate its length.

[0070] The server adds up the shortest distances of all sampling points and divides by the number of sampling points n to obtain the average deviation distance of the puncture path This index reflects the average deviation degree between the actual movement trajectory of the trocar and the standard puncture trajectory. If the value of D is small, it indicates that the puncture path is relatively close to the standard path, and the puncture accuracy of the training personnel is relatively high; conversely, a larger D value means that the puncture path deviates more from the standard, and there may be problems such as inaccurate puncture position and angular deviation, which will affect the surgical effect.

[0071] Based on the obtained movement trajectory L2 of the cutting tool, the server calls a professional algorithm in the field of computer graphics to calculate the area A enclosed by this trajectory. actual . The computer graphics algorithm can regard the movement trajectory as a closed curve and adopt various mature algorithms such as polygon approximation method and integral method to calculate the area enclosed by this closed curve.

[0072] In the medical professional field, for endoscopic thyroidectomy, through a large number of clinical studies and the accumulation of practical experience, a relatively ideal and safe standard resection range of thyroid tissue has been determined, and the corresponding area is set as A. standard . This standard resection range area is comprehensively determined based on various factors such as the normal physiological structure of the human thyroid gland, the pathological conditions, and the best surgical treatment effect.

[0073] The server substitutes the area A enclosed by the actual movement trajectory calculated previously. actual And this preset standard resection range area A. standard Into the above formula for calculation. The numerator |A actual - A standard | in the formula represents the absolute value of the difference between the actual resection area and the standard resection area, and this difference reflects the deviation degree between the actual operation and the standard operation in the resection range; the denominator A standard then plays a role of normalization, so that the calculated cutting path deviation rate P can intuitively reflect this deviation degree in the form of a relative ratio.

[0074] The cutting path deviation rate P can reflect the degree of closeness between the operation path of the training personnel when using the cutting tool for surgery and the ideal standard path. When the value of P is closer to 0, it indicates that the cutting path of the actual operation is more consistent with the preset standard resection range, indicating that the surgical operation accuracy of the training personnel is higher; conversely, the larger the value of P, the lower the operation accuracy and the more serious the deviation from the standard operation.

[0075] Finally, the average deviation distance D of the puncture path and the deviation rate P of the cutting path are jointly used as the surgical operation accuracy indicators. These two indicators comprehensively evaluate the accuracy of the trainer in laparoscopic thyroid surgery from different aspects. D focuses on the accuracy of the path during the puncture process, while P concerns the scope accuracy of the cutting operation. The combination of the two can accurately reflect the overall skill level of the trainer in the surgical operation.

[0076] In an alternative embodiment, the thyroid status data includes current signal data at different positions inside the thyroid tissue; based on the thyroid status data, obtaining the surgical effect indicators includes the following steps:

[0077] According to the current signal data at different positions inside the thyroid tissue, using an image construction algorithm based on EIT technology, reconstruct the electrical impedance distribution image of the thyroid tissue;

[0078] According to the electrical impedance distribution image, using a volume calculation algorithm based on EIT technology, obtain the resected volume V of the thyroid tissue actual ;

[0079] Using the formula Calculate the resection ratio R; where V standard Is the preset volume of the thyroid tissue to be resected;

[0080] Take the resection ratio R as the surgical effect indicator.

[0081] Specifically, a plurality of sensor nodes capable of detecting current signals can be preset inside the thyroid tissue of the resection training model, and these nodes are distributed at different positions of the thyroid tissue. During the surgical training process, when current passes through the thyroid tissue, each sensor node will collect the current signal data at its location in real time. These data contain information such as current intensity and phase, which reflect the electrical characteristics of different regions inside the thyroid tissue. Among them, the current application method is a specific setting based on EIT technology (Electrical Impedance Tomography), to ensure that current signals reflecting tissue characteristics can be obtained.

[0082] After the server receives the current signal data from different locations, it starts an advanced image construction algorithm based on EIT technology. This algorithm utilizes the variation law generated by the different tissue impedances when the current signal propagates in the tissue. Through mathematical calculations and model reconstruction processes, the collected discrete current signal data is converted into an intuitive impedance distribution image. This image visually shows the impedance distribution within the thyroid tissue. Different impedance values correspond to different tissue states, such as normal tissue, diseased tissue, or tissue change areas affected by surgical operations, etc. In this way, the internal structure and state information of the thyroid tissue can be intuitively "seen".

[0083] Based on the reconstructed impedance distribution image of the thyroid tissue, the server further uses a volume calculation algorithm designed for EIT technology to determine the resected volume V of the thyroid tissue actual . This volume calculation algorithm utilizes the impedance differences in different regions of the impedance distribution image to distinguish the resected tissue from the non-resected tissue. Since the impedance characteristics of the resected tissue region will change significantly, the algorithm calculates the volume size of the resected tissue part in the three-dimensional space by identifying the boundaries and region ranges of these impedance changes and combining the three-dimensional spatial information of the image, that is, V actual . This calculation process involves image processing techniques and mathematical models, such as operations like segmenting different impedance regions, contour extraction, and spatial integration

[0084] Under the guidance of medical expertise and surgical norms, for a specific laparoscopic thyroid surgery training scenario, according to factors such as the type and degree of thyroid lesions and the surgical treatment goals, a standard value V of the thyroid tissue volume that should be resected is preset standard . This standard value is determined through a large amount of clinical experience and medical research and is an important reference basis for measuring whether the surgical resection degree is appropriate

[0085] The server substitutes the actual resected volume V of the thyroid tissue calculated above actual and the preset standard resected volume V standard into the above formula for calculation. The calculation result of the resection ratio R intuitively reflects the proportional relationship between the resected thyroid tissue volume and the ideal standard volume in the actual surgical operation. For example, if R = 0.9, it means that the actual resected volume reaches 90% of the preset standard volume; if R = 1.1, it indicates that the actual resected volume exceeds the preset standard volume by 10%. This ratio value is crucial for evaluating the surgical effect. It can help determine whether the surgical operation accurately resected the tissue part that should be resected and whether there is over-resection or under-resection

[0086] The resection ratio R, as a core quantitative index, can directly and effectively reflect the accuracy and rationality of the resection degree of thyroid tissue by surgical operation. When the value of R is close to 1, it indicates that the actual resected volume is highly consistent with the preset standard volume, meaning that the surgical effect has reached an ideal state in terms of tissue resection amount, and the surgical operation is relatively accurate in grasping the resection range; conversely, if the value of R deviates significantly from 1, whether it is greater than 1 or less than 1, it indicates that there are problems with the surgical operation in terms of resection ratio, which may affect the surgical treatment effect.

[0087] In an alternative embodiment, according to the surgical operation accuracy index and the surgical effect index, a comprehensive score and an evaluation result are obtained, and the comprehensive score and the evaluation result are used as the discrimination result, including the following steps:

[0088] S21: Calculate the surgical operation accuracy score S1 according to the surgical operation accuracy index;

[0089] S22: Calculate the surgical effect score S2 according to the surgical effect index;

[0090] S23: Calculate the comprehensive score according to the formula S = ω1×S1 + ω2×S2;

[0091] where S is the comprehensive score, ω1 is the weight coefficient of the surgical operation accuracy score S1, ω2 is the weight coefficient of the surgical effect score S2, and ω1 + ω2 = 1; the full score of the surgical operation accuracy score S1 is N, and the full score of the surgical effect score S2 is M;

[0092] If the average deviation distance D of the puncture path ≤ ε, the surgical operation accuracy score S1 is not deducted; if the average deviation distance D of the puncture path > ε, the surgical operation accuracy score S1 is deducted points, ε is the average deviation distance threshold, D max is the preset maximum acceptable puncture deviation distance, and k1 is the first deduction coefficient;

[0093] If the cutting path deviation rate P ≤ δ, the surgical operation accuracy score S1 is not deducted; if the cutting path deviation rate P > δ, the surgical operation accuracy score S1 is deducted points, δ is the deviation rate threshold, and k2 is the second deduction coefficient;

[0094] If the resection ratio R ∈ [∈1, ∈2], the surgical effect score S2 is not deducted; if the resection ratio R < ∈1, the surgical effect score S2 is deducted points; if the resection ratio R > ∈2, the surgical effect score S2 is deducted points, ∈1 is the minimum resection ratio threshold, ∈2 is the maximum resection ratio threshold, k3 is the third deduction coefficient, and k4 is the fourth deduction coefficient;

[0095] S24: Generate an analysis table of deduction reasons based on the calculation process of the comprehensive score S in step S23, and evaluate the current training according to the analysis table of deduction reasons to obtain an evaluation result.

[0096] Specifically, the server first determines the magnitude relationship between the average deviation distance D of the puncture path and the average deviation distance threshold ε. The average deviation distance threshold ε can be set according to clinical practice experience and surgical operation specifications, and it defines the acceptable range of the surgical operation in terms of puncture accuracy.

[0097] If D ≤ ε, it indicates that the deviation between the actual puncture path and the preset standard puncture path is within the acceptable range. At this time, the surgical operation accuracy score S1 is not deducted. This means that the trainer has achieved a high accuracy standard in the puncture operation and meets the basic requirements of the surgical operation specifications.

[0098] If D > ε, then the deviation between the actual puncture path and the preset standard puncture path exceeds the acceptable range, and the surgical operation accuracy score S1 needs to be deducted according to the specific deviation degree. The deducted score is points, where k1 is the first deduction coefficient, which determines the proportion of points deducted when exceeding the average deviation distance threshold to a certain extent, and D max is the preset maximum acceptable puncture deviation distance.

[0099] The server then determines the magnitude relationship between the cutting path deviation rate P and the deviation rate threshold δ. The deviation rate threshold δ can be an important reference value set according to clinical practice experience and surgical operation specifications, and it defines the acceptable range of the surgical operation in terms of cutting path accuracy.

[0100] If P ≤ δ, it indicates that the deviation between the actual cutting path and the preset standard resection range is within the acceptable range. At this time, the surgical operation accuracy score S1 is not deducted. This means that the trainer has achieved a high accuracy standard in the cutting path operation and meets the basic requirements of the surgical operation specifications.

[0101] If P > δ, it means that the actual cutting path deviation exceeds the acceptable range, and the surgical operation accuracy score S1 needs to be deducted according to the specific deviation degree. The deducted score is points, where k2 is the second deduction coefficient, which determines the proportion of points deducted when exceeding the deviation rate threshold to a certain extent. The design principle of this formula is that the larger the deviation rate P and the more it exceeds the threshold δ, the more points are deducted and the lower the score S1, thus accurately reflecting the decrease in surgical operation accuracy as the cutting path deviation rate increases.

[0102] The server finally determines the relationship between the resection ratio R and the minimum resection ratio threshold ∈1 and the maximum resection ratio threshold ∈2. The minimum resection ratio threshold ∈1 and the maximum threshold ∈2 are determined based on the treatment objectives of thyroid surgery, the human physiological structure, and clinical experience, and they define the ideal range of thyroid tissue resection.

[0103] If R ∈ [∈1, ∈2], it indicates that the volume of the actually resected thyroid tissue is within the ideal range. At this time, the surgical effect score S2 is not deducted. This means that the surgery has achieved the expected effect in terms of tissue resection volume and meets the basic requirements of surgical treatment.

[0104] If R < ∈1, it means that the resection ratio is insufficient, and there may be risks such as residual diseased tissue. At this time, the surgical effect score S2 is deducted points. Among them, k3 is the third deduction coefficient. This formula reflects that the lower the resection ratio is below the minimum threshold ∈1, the more points are deducted and the lower the score is, to reflect the impact on the surgical effect due to insufficient resection.

[0105] If R > ∈2, it means that the resection ratio is too large, which may cause excessive damage to the normal function of the thyroid. At this time, the surgical effect score S2 is deducted Here, k4 is the fourth deduction coefficient, and its function is to deduct corresponding points according to the degree of exceeding the maximum threshold ∈2, accurately reflecting the poor surgical effect caused by excessive resection.

[0106] After the server obtains the surgical operation accuracy score S1 and the surgical effect score S2 respectively, it calculates the comprehensive score S by weighted summation. Among them, ω1 is the weight coefficient of the surgical operation accuracy score S1, ω2 is the weight coefficient of the surgical effect score S2, and ω1 + ω2 = 1. These weight coefficients are determined according to the relative importance of surgical operation accuracy and surgical effect in the overall surgical quality assessment.

[0107] In the process of calculating the comprehensive score S, the server details the calculation basis of each score S1 and S2, including the average deviation distance D of the puncture path, the deviation rate P of the cutting path, the comparison of the resection ratio R with their respective thresholds, and the corresponding deduction situations. Based on these recorded information, the server generates an analysis table of the reasons for deductions.

[0108] The deduction reason analysis table clearly lists the possible problems in the surgical operation accuracy and surgical effect and their corresponding deduction situations. For example, if the score S1 of the surgical operation accuracy is deducted because the cutting path deviation rate P is too large, the value of the deviation rate P, the deviation rate threshold δ, the second deduction coefficient k2, and the specific deducted score will be clearly shown in the table; for the surgical effect score S2, the relationship between the resection ratio R and the minimum threshold ∈1 and the maximum threshold ∈2 of the resection ratio will also be listed in detail, as well as the third deduction coefficient k3, the fourth deduction coefficient k4, and the corresponding deduction situations.

[0109] According to this deduction reason analysis table, the server comprehensively evaluates this surgical training. If the comprehensive score S is relatively high, and all indicators in the deduction reason analysis table show that they are close to the ideal state, with only a small number of minor deductions (such as the cutting path deviation rate slightly exceeding the threshold or the resection ratio slightly deviating from the ideal range), the evaluation result may be "Good. The overall surgical operation is relatively standardized, and only individual details need to be further improved." If the comprehensive score is relatively low, and there are many serious deduction situations in the deduction reason analysis table (such as the cutting path deviation rate being too large or the resection ratio seriously deviating from the threshold range), the evaluation result may be "Poor. There are obvious problems in multiple aspects of the surgical operation, and it is necessary to focus on improving the operation accuracy and grasping the resection range", etc. In this way, detailed and accurate surgical training feedback can be provided to the training personnel to help them improve their surgical skills targeted.

[0110] In an optional embodiment, the operation data further includes the peak cutting force data {F1, F2, …, F m} of the cutting tool; the surgical operation accuracy index further includes the peak cutting force data; calculating the surgical operation accuracy score S1 according to the surgical operation accuracy index further includes the following operations:

[0111] If there exists F j > F max then confirm F j as the abnormal peak cutting force; F max is the cutting force threshold required when using the cutting tool to cut the preset part to be cut, j = 1, 2, …, m;

[0112] Count the number Q of abnormal peak cutting forces in the peak cutting force data;

[0113] Deduct the score of the surgical operation accuracy score S1 by Q × k5 × N, where k5 is the fifth deduction coefficient.

[0114] Specifically, for a series of peak cutting force data {F1, F2, …, F m} generated by the cutting tool during the surgical operation, the system presets a cutting force threshold F required when using the cutting tool to cut the preset part to be cutmax This threshold is determined based on the research and practical experience of cutting forces under normal surgical operations, and it represents the reasonable maximum cutting force that should be applied to complete the corresponding cutting task under ideal operating conditions.

[0115] The server checks each value F in the cutting force peak data one by one i (j = 1, 2, …, m), and compares it with the cutting force threshold F max If there exists a certain F j > F max , then this F j is identified as an abnormal cutting force peak. The appearance of an abnormal cutting force peak may indicate that the trainer has applied excessive force when operating the cutting tool, which may cause unnecessary damage to the simulated thyroid tissue and surrounding structures, or reflect instability and non-standardization during the operation.

[0116] After determining all the abnormal cutting force peaks, the server counts and statistics these abnormal values to obtain the number Q of abnormal cutting force peaks.

[0117] After determining the number Q of abnormal cutting force peaks, the server will adjust the deduction of the surgical operation accuracy score S1 according to the pre-set rules. The deducted score is Q × k5 × N, where k5 is the fifth deduction coefficient.

[0118] The fifth deduction coefficient k5 determines the proportion of points deducted for each abnormal cutting force peak, and its value is determined according to the severity of the impact of the abnormal cutting force on the surgical operation accuracy. Such a deduction mechanism can encourage the trainer to pay more attention to controlling the cutting force in subsequent surgical training, improve the stability and standardization of the operation, and reduce the potential risks caused by improper cutting force to the surgical effect and tissue.

[0119] The above-mentioned method for discriminating the training results of endoscopic thyroidectomy constructs an endoscopic thyroidectomy training result discrimination system by means of an excision training model, a sensor, a server, and a display device. The sensor collects the time-series coordinates of the trocar and the cutting tool, the peak cutting force data of the cutting tool, and the internal current signal data of the thyroid tissue during the operation. The server analyzes and processes these data according to preset rules, calculates the surgical operation accuracy index based on the average deviation distance of the puncture path, the deviation rate of the cutting path, and the peak cutting force data, calculates the surgical effect index according to the resection ratio, and then obtains the comprehensive score and evaluation result, generates surgical optimization suggestions, and finally visualizes and presents them through the display device. Thus, the accurate quantitative evaluation of endoscopic thyroidectomy training is realized, the problems in the operation of the training personnel can be found in time, targeted optimization suggestions can be provided, the surgical skills of the training personnel can be effectively improved, the quality and effect of surgical training can be improved, a scientific and efficient auxiliary means for the training of endoscopic thyroidectomy is provided, the surgical risk can be reduced, and the success rate of actual surgery can be improved.

[0120] It should be understood that although the steps in the flowcharts involved in the above-described embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise clearly stated in this article, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, at least some of the steps in the flowcharts involved in the above-described embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least some of the steps or stages in other steps or other steps.

[0121] Based on the same inventive concept, the embodiments of the present application also provide a surgical training result discrimination system for implementing the above-mentioned method. The solution provided by this system to solve the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the surgical training result discrimination system provided below can refer to the limitations on a method for discriminating the training results of endoscopic thyroidectomy in the above text, and will not be repeated here.

[0122] In an exemplary embodiment, as Figure 2 shown, a surgical training result discrimination system 200 is provided, including: an excision training model 201, a server 202, and a display device 203;

[0123] The resection training model simulates the human neck structure and is used to provide training personnel with laparoscopic thyroid surgery training. A sensor for collecting surgical data is integrated inside the resection training model;

[0124] The sensor is connected to the server 202 through the built-in first data transmission module, and the display device 203 is connected to the server 202 through the built-in second data transmission module;

[0125] The server 202 is used to implement the steps of the method according to any one of claims 1-6.

[0126] Specifically, (1) the resection training model 201:

[0127] The simulated human neck structure is highly realistic. It is not only similar to the real human neck in appearance, but also as close as possible to the real situation in the texture, layers of internal tissues, and anatomical relationships between organs. This resection training model is mainly used to enable training personnel to train their ability to distinguish muscles during puncture in a real surgical environment of the model, so as to achieve the effect of exposing the thyroid tissue, and then practice the resection of the thyroid tissue. This enables training personnel to obtain a tactile and visual experience close to real surgery during laparoscopic thyroid surgery training, which helps to improve their surgical operation skills and familiarity with anatomical structures.

[0128] The sensors integrated inside the model have multiple functions and can collect detailed surgical data such as the contact force between surgical instruments and tissues, cutting angles, operation paths, the scope and speed of tissue resection, etc.

[0129] (2) The server 202:

[0130] As the data processing and storage center of the entire system, the server has powerful computing capabilities and storage capacity. It receives the surgical data sent by the first data transmission module of the sensor of the resection training model and processes and analyzes this data in real time.

[0131] The server is built with advanced algorithms and models and can quantitatively evaluate the surgical data according to preset standards and indicators, such as judging the performance of surgical operations in terms of accuracy, standardization, stability, etc. At the same time, it can also integrate and compare and analyze the data of multiple trainings to track the skill improvement of training personnel and provide data support for personalized training suggestions.

[0132] The server can also have data management functions, capable of effectively organizing and storing a large amount of surgical training data for subsequent query, statistics, and research use. In addition, it can interact and share data with external medical databases or other relevant systems to obtain more reference information and resources, further enriching and improving the discrimination system for surgical training results.

[0133] (3) Display device 203:

[0134] The display device is connected to the server through the second data transmission module, and displays the surgical training results and relevant information processed by the server in real time. It can be presented to the training personnel and instructors in an intuitive and clear graphical interface. For example, it shows the actual situation of the surgical operation through a 3D model, uses charts and data comparison to show the differences between the training personnel and the standard operation process, as well as the scores and detailed reports of skill assessment, etc.

[0135] The display device can also have an interaction function. The training personnel and instructors can operate on the display interface through a touch screen or other input devices, such as viewing surgical data for a specific period, zooming in or out on the detailed display of the surgical site, and selecting different evaluation indicators for key analysis, etc. This enables them to more deeply understand the problems and advantages in the surgical training process, and thus make targeted improvements and enhancements.

[0136] Reference Figure 3 , this application also provides an excision training model, which is used in conjunction with a method for discriminating laparoscopic thyroid surgery training results provided by the application. The excision training model includes: a main body part 1 simulating the human neck structure, a puncture device 2 for laparoscopic thyroid surgery training, a cutting tool 5 for laparoscopic thyroid surgery training, a sensor component 3 integrated inside the main body part, and a data transmission unit 4.

[0137] The main part 1 simulating the human neck structure is the basis of the entire model. It includes simulated skin 11, simulated muscle layer 12 and thyroid tissue module 13. The simulated skin 11 is not only similar to real skin in appearance, but also highly simulated in its physical properties such as touch and elasticity, so that the user can feel the resistance and feedback similar to the actual operation when operating the cutting tool to cut the skin. The layout, layering and texture of the simulated muscle layer 12 are all based on the real human neck muscle conditions, and the connection relationship between different muscle groups is also accurately restored, so that when separating or bypassing the muscle operation in surgical training, the operator can experience the feel of the real operation, so as to accurately grasp the operation force and angle. The thyroid tissue module 13 has achieved a high degree of simulation in many aspects. Its shape and size are exactly the same as those of the human thyroid gland. From the overall outline to the details of each lobe and isthmus, it is accurately reproduced, providing an accurate target structure for surgical operation. In terms of texture, it simulates the softness and toughness of real thyroid tissue, and its performance during cutting and pulling is similar to the real surgical situation, which helps to train the operator's ability to accurately control the tissue. The integrity of the capsule structure and its connection characteristics with the surrounding tissues simulate the degree of adhesion under real human physiological conditions. This means that when surgically separating the capsule and dealing with related parts of the surrounding tissues, the operator will face difficulties similar to those in actual surgery, effectively improving their ability to deal with complex situations.

[0138] The puncture device 2 is a device specially designed for laparoscopic thyroid surgery training. Its appearance and function are highly similar to the puncture devices actually used in clinical practice. Its material has good rigidity and durability, which can ensure that its structural integrity and performance stability can be maintained after multiple puncture operations. The needle core of the puncture device 2 is sharp and has a suitable length and thickness, which can smoothly perform the puncture operation on the main part 1 simulating the human neck structure, simulating the process of establishing a laparoscopic channel in actual surgery. The established laparoscopic channel can be passed through by the laparoscope and the cutting tool 5. The surface of the needle core of the puncture device 2 is specially treated to reduce the friction during puncture, and at the same time, it can provide a certain hand feel feedback during the puncture process, so that the trainee can sense the depth and direction of the puncture, avoid puncturing too deep or deviating from the predetermined track to cause damage to the surrounding tissue, thereby improving the accuracy and safety of the puncture operation. The outer sleeve part of the puncture device 2 is tightly matched with the needle core, has good sealing, and can effectively maintain the stability of the laparoscopic channel after the puncture is successful. At the same time, the material of the outer sleeve has a certain flexibility, which can adapt to the slight bending and twisting that may occur during the simulated surgical operation, ensuring the smooth progress of the surgical operation.

[0139] The cutting tool 5 (not shown in the figure) for laparoscopic thyroid surgery training is optimized based on actual surgical instruments. Its size, shape, and operating feel are similar to those of the instruments used in clinical practice, but appropriate adjustments have been made in terms of materials, etc., to meet the requirements of repeated training and ensure good cooperation with the sensor component, accurately feedback various data during the operation process, enabling the operator to perform precise operations as if using real surgical instruments during training, thereby cultivating correct operating habits and feel.

[0140] The sensor component 3 integrated inside the main body part is the core part of the entire resection training model. The position sensors 31 are distributed around and inside the thyroid tissue module 13, capable of monitoring the position changes of the cutting tool 5 in the thyroid tissue module 13 and its surrounding areas in all directions and in real time, accurately capturing the movement trajectory of the tool. Whether the tool approaches the thyroid tissue module 13 from the outside or operates deep inside the tissue, every position movement can be accurately recorded, which is crucial for subsequent evaluation of whether the operator's operation path is reasonable and whether the target position is accurately reached, etc., and helps the trainer to promptly discover and correct deviations in the operation. The pressure sensors 32 are installed on the surface and internal layers where the thyroid tissue module 13 contacts the cutting tool 5. Based on the principle of mechanical induction, when the tool applies pressure to the tissue for cutting, the sensors will generate corresponding electrical signal changes according to the magnitude of the force, thereby accurately quantifying the cutting force value, enabling the trainer to intuitively understand the magnitude of the force applied during the operation, avoiding problems such as excessive tissue damage and bleeding caused by inappropriate cutting force during actual surgery, and helping them gradually cultivate an appropriate and stable operating force control ability. The impedance sensor system 33 consists of electrodes 331 arranged around the thyroid tissue module 13 and impedance sensors 332 distributed at different positions inside the thyroid module 13. By applying an alternating current signal with a specific frequency and intensity to the thyroid tissue module 13 through the electrodes 331, impedance data at different positions inside the thyroid tissue module 13 is collected using the differences in the influence of different components and structures inside the tissue on current conduction.

[0141] The data transmission unit 4 is connected to the sensor component 3. It has efficient and stable transmission capabilities and can accurately transmit various data such as the position information, cutting force data, and impedance data collected by the sensor component 3 to the server. The server can then process, analyze, and store these data according to a method for discriminating the results of laparoscopic thyroid surgery training provided in this application, thereby comprehensively improving the professional skill level of the surgical operator and making this resection training model a powerful tool for laparoscopic thyroid surgery training.

[0142] Embodiments of the present application also provide a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps in the foregoing method embodiments are implemented.

[0143] Embodiments of the present application also provide a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps in the foregoing method embodiments are implemented.

[0144] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to the partial descriptions of the method embodiments. The device embodiments described above are merely illustrative. The components described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the present disclosure solution. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0145] The above embodiments only represent several implementation manners of the embodiments of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of the application embodiments. It should be noted that for those of ordinary skill in the art, without departing from the concept of the embodiments of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the embodiments of the present application.

Claims

1. A method for determining the results of laparoscopic thyroid surgery training, applied to a server in a surgery training result determination system, characterized in that: The surgical training result determination system further includes a resection training model and a display device; the resection training model simulates the human neck structure and is used to provide training personnel with laparoscopic thyroid surgery training, and a sensor for collecting surgical data is integrated inside the resection training model; the sensor is connected to the server via a built-in first data transmission module; The display device is connected to the server via a built-in second data transmission module; The method for determining the results of laparoscopic thyroid surgery training comprises: S1: Sending a data acquisition instruction to the sensor; the data acquisition instruction is used to instruct the sensor to acquire the surgical data during the surgical process, and transmit the surgical data and the determination instruction to the server; S2: In response to the discrimination instruction, the surgical data is analyzed and discriminated according to a preset discrimination rule to obtain a discrimination result, and surgical optimization suggestions are obtained according to the discrimination result; S3: Transmitting the identification result, the surgical optimization suggestion and the display instruction to the display module; the display instruction is used to instruct the display device to display the identification result and the surgical optimization suggestion in a visual manner.

2. The method according to claim 1, characterized in that The surgical data include: operation data and thyroid status data; The server analyzes and judges the surgical data according to a preset judgment rule to obtain a judgment result, including: Obtaining a surgical operation accuracy index according to the operation data; Obtaining a surgical effect indicator according to the thyroid status data; According to the surgical operation accuracy index and the surgical effect index, a comprehensive score and an evaluation result are obtained, and the comprehensive score and the evaluation result are used as the discrimination result.

3. The method according to claim 2, characterized in that The resection training model also includes a puncture device and a cutting tool for laparoscopic thyroid surgery training, and the operation data includes: time series coordinates of the puncture device in three-dimensional space during the puncture process, and time series coordinates of the cutting tool in three-dimensional space during the resection process; The step of obtaining a surgical operation accuracy index based on the operation data includes: According to the time series coordinates of the puncture device, the motion trajectory L1 of the puncture device is obtained; according to the time series coordinates of the cutting tool, the motion trajectory L2 of the cutting tool is obtained; According to the formula Calculate the average deviation distance D of the puncture path; where n is the number of sampling points selected for calculation on the motion trajectory L1, L standard is the preset standard puncture trajectory, p i is the i-th sampling point on the motion trajectory L1, d(p i ,L standard ) is point p i The shortest distance to the motion trajectory L1; Using computer graphics algorithms, calculate the area A enclosed by the motion trajectory L2 of the cutting tool actual According to the formula Calculate the cutting path deviation rate P; where A standard The preset standard resection area of ​​thyroid tissue; The average deviation distance D of the puncture path and the deviation rate P of the cutting path are used as indicators of the accuracy of the surgical operation.

4. The method according to claim 3, characterized in that The thyroid status data includes current signal data at different locations inside the thyroid tissue; The step of obtaining surgical effect indicators based on the thyroid status data includes: Reconstructing an electrical impedance distribution image of the thyroid tissue using an image construction algorithm based on EIT technology according to the current signal data at different positions inside the thyroid tissue; According to the electrical impedance distribution image, the volume calculation algorithm based on EIT technology is used to obtain the thyroid tissue resection volume V actual ; Using the formula Calculate the resection ratio R; where V standard The preset volume of thyroid tissue to be removed; The resection ratio R is used as the surgical effect indicator.

5. The method according to claim 4, characterized in that The step of obtaining a comprehensive score and an evaluation result based on the surgical operation accuracy index and the surgical effect index, and using the comprehensive score and the evaluation result as the discrimination result, includes: S21: Calculating a surgical operation accuracy score S1 according to the surgical operation accuracy index; S22: Calculating a surgical effect score S2 according to the surgical effect index; S23: Calculate the comprehensive score according to the formula S=ω1×S1+ω2×S2; Wherein, S is the comprehensive score, ω1 is the weight coefficient of the surgical operation accuracy score S1, ω2 is the weight coefficient of the surgical effect score S2, and ω1+ω2=1; the full score of the surgical operation accuracy score S1 is N, and the full score of the surgical effect score S2 is M; If the average deviation distance of the puncture path D≤ε, the surgical operation accuracy score S1 will not be deducted; if the average deviation distance of the puncture path D>ε, the surgical operation accuracy score S1 will be deducted by N× points, ε is the average deviation distance threshold, D max is the preset maximum acceptable puncture deviation distance, k1 is the first deduction coefficient; If the cutting path deviation rate P≤δ, the surgical operation accuracy score S1 will not be deducted; if the cutting path deviation rate P>δ, the surgical operation accuracy score S1 will be deducted points, δ is the deviation rate threshold, and k2 is the second deduction coefficient; If the resection ratio R∈[∈1,∈2], the surgical effect score S2 will not be deducted; if the resection ratio R<∈1, the surgical effect score S2 will be deducted If the resection ratio R>∈2, the surgical effect score S2 is deducted points, ∈1 is the minimum threshold of the resection ratio, ∈2 is the maximum threshold of the resection ratio, k3 is the third deduction coefficient, and k4 is the fourth deduction coefficient; S24: Generate a deduction reason analysis table according to the calculation process of the comprehensive score S in step S23, and evaluate the training according to the deduction reason analysis table to obtain the evaluation result.

6. The method according to claim 5, characterized in that The operation data also includes the cutting force peak data {F1, F2, ..., F m }; The surgical operation accuracy index also includes the cutting force peak data; The step of calculating the surgical operation accuracy score S1 according to the surgical operation accuracy index further includes: If there is F j >F max , then F j Confirmed as abnormal cutting force peak; F max is the cutting force threshold required when using the cutting tool to cut the preset part to be cut, j=1, 2, ..., m; Counting the number Q of the abnormal cutting force peaks in the cutting force peak data; The surgical operation accuracy score S1 is deducted by Q×k5×N, where k5 is the fifth deduction coefficient.

7. A surgical training result determination system, characterized in that: The system comprises: a resection training model, a server and a display device; The resection training model simulates the human neck structure and is used to provide training personnel with laparoscopic thyroid surgery training, and the resection training model is internally integrated with a sensor for collecting surgical data; The sensor is connected to the server via a built-in first data transmission module, and the display device is connected to the server via a built-in second data transmission module; The server is used to implement the steps of the method according to any one of claims 1-6.

8. A resection training model, characterized in that: include: A main body (1) simulating a human neck structure, a puncture device (2) for laparoscopic thyroid surgery training, a cutting tool (5) for laparoscopic thyroid surgery training, a sensor component (3) integrated inside the main body, and a data transmission unit (4); The main body portion comprises simulated skin (11), a simulated muscle layer (12) and a thyroid tissue module (13); the thyroid tissue module (13) has the same shape, size, texture and capsule structure as the human thyroid gland, and the connection characteristics between the capsule structure and the surrounding tissue simulate the degree of adhesion under the physiological state of the real human body; The sensor assembly (3) comprises: a position sensor (31) for detecting the positions of the cutting tool (5) and the puncturing device (2), the position sensor (31) being distributed around and inside the thyroid tissue module (13); and a pressure sensor (32) for measuring the cutting force applied by the cutting tool on the thyroid tissue module (13), the pressure sensor (32) being installed on the surface and internal layer of the thyroid tissue module (13) in contact with the cutting tool (5); and an electrical impedance sensor system (33) for collecting electrical impedance data at different positions inside the thyroid tissue module (13), the electrical impedance sensor system (33) being composed of electrodes (331) arranged around the thyroid tissue module (13) and electrical impedance sensors (332) arranged at different positions inside the thyroid module (13), and applying an alternating current signal of a specific frequency and a specific strength to the thyroid tissue module (13) through the electrodes (331), so that the electrical impedance sensor (332) can collect electrical impedance data at different positions inside the thyroid tissue module (13); The data transmission unit (4) is connected to the sensor component (3) and is used to transmit the data collected by the sensor component to a server, and the server is used to implement the steps of the method according to any one of claims 1 to 6.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

Images