CN118969235B

CN118969235B - Pressure self-adaptive control communication system and communication device of electric anastomat

Info

Publication number: CN118969235B
Application number: CN202411354983.9A
Authority: CN
Inventors: 沈彬; 赵虎成
Original assignee: Changzhou Yilong Information Technology Co ltd
Current assignee: Changzhou Yilong Information Technology Co ltd
Priority date: 2024-09-27
Filing date: 2024-09-27
Publication date: 2024-12-17
Anticipated expiration: 2044-09-27
Also published as: CN118969235A

Abstract

The invention relates to the technical field of pressure control of an electric anastomat, in particular to a pressure self-adaptive control communication system and a communication device of the electric anastomat, which CAN improve the operation effect, reduce the complication risk, improve the working efficiency and the patient satisfaction, and comprise an operating room control terminal, a central processing unit, an electric anastomat controller and a pressure self-adaptive control module, wherein the operating room control terminal sends wound size characteristics and wound tissue position characteristics to the central processing unit, the central processing unit converts the data format of the wound size characteristics and the wound tissue position characteristics, inputs the converted data information into a pre-built anastomat pressure matching model, obtains an initial pressure set value, sends the initial pressure set value to the electric anastomat controller through a CAN bus, and acquires the hardness and thickness characteristics of the wound tissue in real time based on a sensor integrated on the electric anastomat controller and sends the wound tissue hardness and thickness characteristics to the central processing unit.

Description

Pressure self-adaptive control communication system and communication device of electric anastomat

Technical Field

The invention relates to the technical field of pressure control of an electric anastomat, in particular to a pressure self-adaptive control communication system and a communication device of the electric anastomat.

Background

In modern surgery, an electric anastomat is widely used as a key surgical instrument in gastrointestinal, pulmonary, cardiac and other various open or minimally invasive operations, the main function of the anastomat is to accurately suture the rest healthy tissues together after the pathological tissues are resected so as to promote healing and maintain normal functions of organs, however, the quality and effect of the anastomosis process are greatly affected by the changes of the type, thickness and hardness of the tissues, and improper pressure setting can cause tissue damage, anastomotic line leakage or other complications, thereby affecting the success rate of the operation and the recovery of patients.

The traditional electric anastomat pressure control communication system often adopts fixed pressure setting, and for softer intestinal tissues, the tissue damage and even perforation can be caused by the excessive pressure, while for harder lung or heart tissues, good sealing performance and stability can not be ensured by the lower pressure, so that the traditional anastomat pressure control communication system has obvious limitation in treating tissues with different parts and different properties.

Disclosure of Invention

In order to solve the technical problems, the invention provides a pressure self-adaptive control communication system and a communication device of an electric anastomat, which can improve the operation effect, reduce the complication risk and improve the working efficiency and the satisfaction degree of patients.

In a first aspect, the invention provides a pressure self-adaptive control communication system of an electric anastomat, which comprises an operating room control terminal, a central processing unit, an electric anastomat controller and a pressure self-adaptive control module;

the operating room control terminal sends the wound size characteristics and the wound tissue position characteristics to the central processing unit;

The central processing unit performs data format conversion on the wound size characteristics and the wound tissue part characteristics, inputs the converted data information into a pre-constructed anastomat pressure matching model, obtains an initial pressure set value, and sends the initial pressure set value to the electric anastomat controller through the CAN bus;

Based on the sensor integrated on the electric anastomat controller, the hardness and thickness characteristics of the wound tissue are collected in real time and transmitted to the central processing unit;

The central processing unit fuses the hardness and thickness characteristics of the wound tissue acquired in real time into characteristic vectors, and inputs the characteristic vectors into an anastomotic pressure influence assessment model to obtain an anastomotic pressure regulating factor;

the central processing unit calculates actual pressure parameters according to the anastomosis pressure regulating factor and the initial pressure set value, and sends the actual pressure parameters to the pressure self-adaptive control module through the CAN bus;

the pressure self-adaptive control module is integrated with a communication request monitoring unit and a communication synchronous unlocking unit;

in the communication process, the pressure self-adaptive control module sends a communication request signal to the electric anastomat controller through the communication request monitoring unit;

After receiving the confirmation receipt signal, the communication request monitoring unit sends a synchronous unlocking signal to be used for carrying out communication synchronous confirmation with the communication synchronous unit;

If the communication synchronous unlocking unit successfully receives the synchronous acknowledgement signal from the communication synchronous unit after sending the synchronous unlocking signal, the communication link between the electric anastomat controller and the pressure self-adaptive control module is successfully established;

After the communication link is successfully established, the pressure self-adaptive control module transmits the calculated actual pressure parameters to the electric anastomat controller through the CAN bus to realize pressure adjustment.

Further, the central processing unit calculates an actual pressure parameter, including:

acquiring a wound size feature and a wound tissue site feature based on the surgical plan;

inputting the wound size characteristics and the wound tissue position characteristics into a pre-constructed anastomat pressure matching model to obtain initial pressure on anastomat forceps;

acquiring the hardness characteristics and the thickness characteristics of the wound tissues in real time, and carrying out data fusion on the hardness characteristics and the thickness characteristics of the wound tissues to obtain a characteristic vector of the anastomosis influence of the wound;

Inputting the wound anastomosis influence characteristic vector into a pre-constructed anastomosis pressure influence evaluation model to obtain an anastomosis pressure regulating factor;

according to the anastomosis pressure regulating factor and the initial pressure on the anastomat forceps, calculating to obtain the actual pressure parameter of the electric anastomat aiming at the operation;

and controlling the electric anastomat to press the wound according to the actual pressure parameters of the electric anastomat.

Further, the calculation formula of the actual pressure parameter of the electric anastomat is as follows:

P_actual=P_initial+F_adjust×P_initial

Where P _initial represents the initial pressure on the stapler jaw, F _adjust represents the stapling pressure adjustment factor, and P _actual represents the actual pressure parameter of the electric stapler.

Further, the method for acquiring the wound size characteristics comprises the following steps:

Three-dimensionally reconstructing an operation area through CT scanning, magnetic resonance imaging and ultrasonic examination before operation, and measuring the size of a wound;

Based on preoperative image data, performing operation simulation, planning the size, position and operation path of the wound in advance, and obtaining accurate size characteristics.

Further, the method for identifying the characteristics of the wound tissue site comprises the following steps:

Identifying a tissue type based on anatomical knowledge of the surgical site;

Assessing the tissue state of the surgical area in combination with the specific condition of the patient, and predicting the tissue change;

Performing pathological analysis to confirm the tissue type and characteristics;

by analyzing preoperative image data, the tissue type and position are automatically identified, and the characteristics of the wound tissue part are obtained.

Further, the construction method of the anastomosis pressure influence evaluation model comprises the following steps:

collecting data from historical surgical cases including tissue stiffness, tissue thickness, surgical site, wound size, pressure settings used, and surgical outcome;

Cleaning the collected data, removing abnormal values, filling and deleting the missing data;

selecting a machine learning model as a model infrastructure, wherein the machine learning model comprises linear regression, a support vector machine, a random forest and a neural network;

dividing the data set into a training set, a verification set and a test set;

training a model by using training set data, and learning a mapping relation between the features and the pressure regulating factors by iteratively optimizing a loss function;

evaluating the performance of the model on the verification set, and adjusting the parameters and the structure of the model according to the verification result;

evaluating the model on an independent test set to obtain the performance of the model on unknown data;

and embedding the trained model into an electric anastomat control communication system.

Further, the method for controlling the electric anastomat to press the wound comprises the following steps:

checking the actual pressure parameter;

The actual pressure parameter passes the verification, the electric anastomat is activated, otherwise, an alarm is sent out and the operation is paused;

In the pressing process, the electric anastomat precisely controls the closing force of the jaws according to the actual pressure parameters;

performing a suturing process while the jaws are closed and a suitable pressure is applied;

in the whole pressing and stitching process, the electric anastomat continuously monitors the condition of the wound and collects related data through a sensor;

When the suturing operation is completed, the electric anastomat automatically releases the jaws and sends out a completion signal, and an operator checks the suturing effect.

On the other hand, the application also provides a pressure self-adaptive control communication device of the electric anastomat, which adopts a pressure self-adaptive control communication system of the electric anastomat, and comprises:

A wound feature acquisition module that acquires a wound size feature and a wound tissue site feature based on a surgical plan;

The pressure matching module is used for inputting the wound size characteristics and the wound tissue position characteristics into a pre-constructed anastomat pressure matching model to obtain initial pressure on the anastomat forceps;

the real-time tissue characteristic monitoring module is used for acquiring hardness characteristics of the wound tissue and thickness characteristics of the wound tissue in real time;

the feature fusion and vector generation module is used for carrying out data fusion on the hardness features of the wound tissues and the thickness features of the wound tissues to obtain a feature vector of the anastomosis influence of the wound;

The pressure influence evaluation module is used for inputting the wound anastomosis influence feature vector into a pre-constructed anastomosis pressure influence evaluation model to obtain an anastomosis pressure adjustment factor;

The actual pressure calculation module calculates and obtains the actual pressure parameter of the electric anastomat aiming at the operation according to the anastomat pressure adjustment factor and the initial pressure on the anastomat clamp;

The control module of the electric anastomat controls the electric anastomat to press the wound according to the actual pressure parameter of the electric anastomat.

The application also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of any of the above communication systems.

Compared with the prior art, the pressure setting device has the beneficial effects that the pressure setting device can dynamically adjust pressure setting according to wound size characteristics, tissue part characteristics and tissue hardness and thickness characteristics acquired in real time, can carry out personalized pressure adjustment aiming at different conditions of each patient, improves the success rate of operation, integrates a sensor to monitor the state of wound tissues in real time, carries out data analysis through a central processing unit, timely adjusts pressure parameters, is beneficial to avoiding tissue damage or anastomosis failure caused by improper pressure, can effectively reduce the occurrence of complications such as tissue damage, suture line leakage and the like by applying proper pressure to different types of tissues, improves the safety of operation and the postoperative recovery quality of patients, reduces the dependence on experience of operators through automatic and intelligent pressure control, enables the operation process to be smoother, shortens the operation time, simultaneously reduces the working strength of doctors, ensures the reliability of communication links between an electric anastomat controller and a pressure self-adaptive control module through interaction among a communication request monitoring unit, a communication confirmation unit, a communication synchronous unlocking unit and a communication synchronous unit, can make a more stable decision-making and a more scientific decision-making system according to the best setting and a pressure setting operation model of the pressure setting system.

Drawings

FIG. 1 is a schematic diagram of the structure of a pressure adaptive control communication system of an electric stapler according to the present invention;

FIG. 2 is a flow chart of the actual pressure parameter calculated by the CPU;

fig. 3 is a block diagram of an electric stapler pressure adaptive control communication device.

Detailed Description

The present application will be described below with reference to the drawings in the present application.

The first embodiment is as shown in fig. 1, the pressure self-adaptive control communication system of the electric anastomat comprises an operating room control terminal, a central processing unit, an electric anastomat controller and a pressure self-adaptive control module, and the implementation process is as follows:

The method comprises the steps of inputting wound size and tissue position information through an operating room control terminal by an operator, calculating a preliminary pressure set value through a pre-training model based on the input information by a central processing unit, monitoring the hardness and thickness of tissues in real time by a sensor on an electric anastomat controller, combining real-time data with the preliminary setting to generate a feature vector by the central processing unit, calculating an adjusting factor through a pressure influence evaluation model, updating actual pressure parameters, ensuring that the pressure self-adaptive control module correctly receives the updated pressure parameters through a communication confirmation step, adjusting the pressure of the electric anastomat according to the latest parameters by the pressure self-adaptive control module to adapt to the current tissue state, and realizing self-adaptive control of the pressure of the electric anastomat through an integrated sensor, real-time data processing and an advanced communication mechanism, thereby remarkably improving the accuracy and safety of an operation.

More specifically, as shown in fig. 2, the method for calculating the actual pressure parameter by the central processing unit specifically includes the following steps:

S1, acquiring a wound size characteristic and a wound tissue part characteristic based on an operation scheme;

the method for acquiring the wound size characteristics comprises the following steps:

three-dimensionally reconstructing the operation area by means of preoperative CT scanning, magnetic resonance imaging and ultrasonic examination, and accurately measuring the size of a wound, including the length, the width, the depth and the shape;

In the operation process, the actual size of the wound surface is directly observed and measured by using a high-definition endoscope, and the real-time image data can assist doctors to more accurately adjust the use strategy of the anastomat;

Based on preoperative image data, performing operation simulation by using computer aided design software, and planning the size, position and operation path of a wound in advance so as to obtain accurate size characteristics;

the method for identifying the characteristics of the wound tissue part comprises the following steps:

the surgeon identifies the tissue type according to the anatomical knowledge of the surgical site and knows the general characteristics and mechanical behavior of the tissue at the site;

in the case discussion before surgery, the tissue state of the surgery area is evaluated in combination with the specific condition of the patient, and the possible tissue change is predicted;

performing a tissue biopsy and performing a rapid pathology analysis to confirm tissue type and characteristics;

by using the AI technology, the tissue type and the position are automatically identified by analyzing preoperative image data, and instant and accurate information is provided for an operation team.

In the step, through preoperative high-precision imaging examination and intra-operative real-time image guidance, the acquired wound size data can be ensured to be highly accurate, the pressure setting of the anastomat is more personalized and accurate, complications such as tissue damage and anastomosis failure caused by improper pressure are reduced, preoperative detailed operation planning, case discussion and AI auxiliary diagnosis are combined, surgeons can have deep knowledge and accurate prediction on tissue types and characteristics before operation, operation simulation by utilizing computer auxiliary design software can be used for planning an operation path in advance, operation preparation time and operation time can be effectively shortened, turnover efficiency of an operation room is improved, individual individuation and refinement treatment from one cut is realized by comprehensively considering the individual difference, tissue characteristics and operation requirements of the operation room, treatment effect and patient satisfaction are improved, immediate sharing of preoperative multidisciplinary discussion and AI auxiliary information is promoted, operation is ensured to be based on most comprehensive and accurate information, and the cooperation decision level and decision quality of a modern operation are improved, and S1 step is realized through the application of an electric accurate and intelligent planning and pre-operation image, and the method is used for controlling the preoperation.

S2, inputting the wound size characteristics and the wound tissue position characteristics into a pre-constructed anastomat pressure matching model to obtain initial pressure on the anastomat forceps;

The anastomat pressure matching model can predict proper anastomat pressure according to the wound characteristics, and comprises a series of rules and parameters for matching and calculating the input wound characteristics with preset pressure values;

The structure of the anastomat pressure matching model comprises:

Input layer for received data including lesion size features and lesion tissue site features, which require appropriate pre-processing and encoding to enable understanding and processing by the neural network, processing with an embedded layer for classification features, normalization or normalization operations for numerical features;

The hidden layer is used for learning and extracting complex relations in input data, consists of a plurality of neurons, each neuron receives the output of a previous layer of neurons as input and generates output through an activation function, the number of layers of the hidden layer and the number of neurons of each layer can be adjusted according to the complexity of the problem and the scale of the data, in a pressure matching model of the anastomat, the design of the hidden layer needs to consider the interaction and influence between the characteristics of the size of a wound and the characteristics of the tissue part of the wound;

And the output layer is used for receiving the output of the hidden layer and generating a final prediction result, and in the anastomat pressure matching model, the output layer has only one neuron and outputs a predicted initial pressure value on the anastomat clamp.

In the step, the model can provide personalized pressure setting suggestions based on specific characteristics of each operation case, the pertinence and the accuracy of the operation are improved, the hidden layer design of the neural network allows the model to capture complex nonlinear relations among input characteristics, the prediction accuracy is improved, the model can continuously optimize internal parameters through learning of a large amount of training data, so that a prediction result is closer to the actual situation, subjectivity and potential errors of artificial experience judgment are reduced, adaptability and generalization capability of the model are improved as the model receives more types of operation cases and data, diversified operation requirements and continuously-changed clinical practices can be better served, the application of the model is beneficial to standardization of operation preparation flow, surgeons can quickly set anastomat pressure according to the suggestions of the model, the preoperative preparation time is reduced, meanwhile, the use of operating room resources is optimized, the personalized and accurate initial pressure setting is beneficial to reducing operation complications, the quality of postoperative recovery of an operation is directly promoted, and the pressure of the anastomat in the step S2 is matched with the model through high degree of customization, and the safety of the prediction of the model is improved.

S3, acquiring hardness characteristics and thickness characteristics of the wound tissues in real time, and carrying out data fusion on the hardness characteristics and the thickness characteristics of the wound tissues to obtain a characteristic vector of the anastomosis influence of the wound;

A high-sensitivity pressure sensor is arranged in a jaw of the electric anastomat, and when the jaw contacts and lightly presses the tissue, the sensor can detect the counter pressure of the tissue in real time to indirectly reflect the hardness of the tissue;

The ultrasonic probe is integrated in the jaw structure, transmits ultrasonic waves and receives the reflected waves, and judges the tissue density and hardness by analyzing echo signals;

Embedding a capacitance sensor in the jaw design, when a tissue is positioned between two polar plates, changing a capacitance value, and calculating the thickness of the tissue through the change of the capacitance value and a preset calibration curve;

the tissue hardness and thickness data obtained in real time are fused through a machine learning algorithm to form a wound anastomosis influence feature vector, and the wound anastomosis influence feature vector can comprehensively reflect the tissue state of the current wound and provide comprehensive indexes for subsequent pressure regulation.

In the step, the tissue hardness and thickness are monitored in real time, so that the anastomat can dynamically adjust the pressure according to the actual tissue characteristics, the problems that the tissue damage or the anastomosis is not tight and the like possibly caused by the traditional fixed pressure setting are avoided, the safety and success rate of the operation are remarkably improved, the tissue characteristics of different patients and different operation positions are extremely different, the step S3 can ensure that the anastomat can make adaptive adjustment when facing different tissue types and conditions, the personalized operation requirement is met, the treatment effect is improved, the data are directly acquired in the operation process through an integrated sensor, the preoperative preparation time is reduced, a doctor can quickly make decisions, the operation process is accelerated, the high-quality treatment standard is simultaneously kept, the anastomosis pressure is accurately controlled, the adverse effect of the excessive high or low pressure on the tissue is avoided, the postoperative recovery of a patient is facilitated, the data fusion technology of a machine learning algorithm is combined, the efficiency and the accuracy of data processing are improved, the technical foundation is also laid for a future intelligent surgical operation system, the surgical operation technology is advanced, the step S3 is realized through the highly integrated sensing technology and intelligent operation, the accurate control of the data is realized, and the self-adaptive control of the pressure is realized, and the key state is assessed for the accurate and self-adaptive control is realized.

S4, inputting the wound anastomosis influence feature vector into a pre-constructed anastomosis pressure influence evaluation model to obtain an anastomosis pressure regulating factor;

The anastomotic pressure influence evaluation model can accurately predict the optimal pressure required by the anastomat under different tissue characteristics;

The input of the model is a wound anastomosis influence characteristic vector which comprises a wound tissue hardness characteristic and a thickness characteristic which are acquired in real time;

the output of the model is an anastomosis pressure adjustment factor, which is used to indicate to what extent an adjustment of the initial pressure is required;

The construction method of the anastomosis pressure influence evaluation model comprises the following steps:

Collecting a large amount of data from past surgical cases, including tissue stiffness, tissue thickness, surgical site, wound size, pressure settings used, and surgical outcome;

cleaning the collected data, removing abnormal values, and filling or deleting the missing data;

dividing the data set into a training set, a verification set and a test set, wherein the dividing ratio is 70%, 15% and 15% so as to ensure the effectiveness and generalization capability of the model;

evaluating the performance of the model on the verification set, and adjusting the parameters and the structure of the model according to the verification result to prevent overfitting;

the trained model is embedded into the control communication system of the electric anastomat, so that the real-time response of the model in actual operation is ensured.

In the step, the optimal anastomosis pressure adjusting factors can be dynamically predicted according to specific characteristics such as tissue hardness and thickness monitored in real time in an operation, personalized pressure control of different patients and different operation positions is realized, operation complications are reduced, operation success rate is improved, through accurate anastomosis pressure adjustment, damage caused by excessive compression of soft tissues is avoided, full anastomosis of hard tissues is ensured, operation stability and healing quality are improved, postoperative recovery of the patients is accelerated, real-time response capability of a model ensures that even if tissue conditions change in the operation process, pressure setting can be adjusted in real time, operation flexibility of a surgeon and reliability of the operation process are enhanced, operation complications are reduced, operation success rate is improved, nursing cost is reduced, requirement of repeated operation is reduced, medical resources are more effectively utilized, operation risk is reduced, operation effect is improved, overall medical service quality is finally improved, and satisfaction degree and trust of the operation effect of the patient are enhanced.

S5, calculating to obtain actual pressure parameters of the electric anastomat aiming at the operation according to the anastomosis pressure adjusting factor and the initial pressure on the anastomat pliers;

Acquiring initial pressure, and reading an initial pressure value on the anastomat clamp, wherein the initial pressure value on the anastomat clamp is calculated by a pre-constructed anastomat pressure matching model based on a surgical scheme and the characteristics of a wound tissue part;

confirming an anastomosis pressure adjusting factor, wherein the anastomosis pressure adjusting factor is calculated by a pre-constructed anastomosis pressure influence evaluation model according to the hardness and thickness characteristics of the wound tissue acquired in real time and is used for adjusting an initial pressure value;

Calculating an actual pressure parameter by combining the initial pressure on the stapler forceps and the anastomotic pressure regulating factor;

the calculation formula of the actual pressure parameter of the electric anastomat is as follows:

P_actual=P_initial+F_adjust×P_initial

wherein, P _initial represents the initial pressure on the anastomat clamp, F _adjust represents the anastomotic pressure regulating factor, and P _actual represents the actual pressure parameter of the electric anastomat;

after the actual pressure parameter is calculated, verification is carried out to ensure that the actual pressure parameter is in a safe and effective range, a threshold value of a pressure range is set according to clinical experience, equipment limit or safety standard, and if the calculated actual pressure parameter exceeds the range, the regulating factor is required to be readjusted;

Finally, outputting the verified actual pressure parameter of the electric anastomat for controlling the electric anastomat to press the wound, wherein the parameter directly influences the quality and effect of the anastomosis process, so that the accuracy and reliability of the electric anastomat are required to be ensured.

The method comprises the steps of calculating and adjusting pressure parameters in real time, ensuring high efficiency and accuracy of an anastomosis process, reducing operation time, reducing dependence on manual adjustment pressure of an operator, improving overall efficiency of the operation, setting a pressure range threshold value, verifying, ensuring that the actually applied pressure meets operation requirements, not exceeding a tissue bearing limit, enhancing patient safety guarantee in the operation process, integrating a modern sensing technology and an intelligent algorithm by accurately matching actual demands of operation wounds, realizing intelligent and accurate development of surgical instruments, promoting automatic and remote operation of the surgical operation, providing technical support for future automatic and remote operation of the surgical operation, reducing the concurrency, not beneficial to further improvement of electric control, realizing the safe and optimal treatment of the patient, and realizing the important medical care in the direction of the improvement of the safety of the medical device.

S6, controlling the electric anastomat to press the wound according to the actual pressure parameters of the electric anastomat;

the method for controlling the electric anastomat to press the wound comprises the following steps:

Checking the calculated actual pressure parameters, ensuring that the parameters are in the effective working range of the electric anastomat and meet the safety requirements of the operation, and if the parameters are out of range or potential safety hazards exist, sending out an alarm and suspending the operation by the system to wait for the further processing of operators;

Once the parameter verification is passed, the electric anastomat is activated, and an operator can start the pressing operation of the anastomat through a control panel or a remote control system;

Through the built-in sensor and control system, the anastomat can monitor and adjust the pressure of the jaw in real time, ensure that the pressure applied in the stitching process always keeps consistent with the preset actual pressure parameter;

when the jaw is closed and proper pressure is applied, the suturing mechanism inside the anastomat starts to work;

In the whole pressing and suturing process, the electric anastomat continuously monitors the condition of the wound and collects related data through a sensor, is used for evaluating the suturing effect and providing feedback or adjustment advice when necessary;

When the suturing operation is completed, the electric anastomat automatically releases the jaws and sends out a completion signal, and an operator checks the suturing effect and confirms whether the wound has been accurately and firmly sutured together.

The method ensures that the used pressure parameters are effective and safe, prevents complications such as tissue damage, staple line leakage and the like caused by improper pressure, remarkably reduces operation risks, ensures that an anastomat can stably and accurately exert pressure in an operation process, ensures that each suture can achieve the optimal tissue apposition and healing effect, improves the success rate of the operation, reduces the complexity and time consumption of manual operation, accelerates the operation process, continuously monitors and collects the wound condition in the compression process, provides instant feedback for the operation effect, ensures that an electric anastomat can make timely adjustment according to actual conditions, enhances the flexibility and adaptability of the operation process, reduces the damage to surrounding healthy tissues by adopting an accurate suture technology, is beneficial to reducing postoperative pain, shortening recovery time and reducing infection risk, improving postoperative life quality of patients, is convenient for immediate evaluation of the operation effect, also provides advanced quality control and clinical control and improvement for subsequent medical control, improves the clinical control and the clinical control, and improves the quality of the operation, and ensures that the intelligent control and the safety management of the operation quality is improved by the advanced technology, and the method is realized by the advanced technology is realized for the patients.

In a second embodiment, as shown in fig. 3, the pressure adaptive control communication device of the electric anastomat of the invention specifically comprises the following modules;

The device provides personalized starting points for different types of operations according to specific wound sizes and tissue positions in an operation scheme by the aid of the wound characteristic acquisition module and the pressure matching module, avoids a one-cut fixed pressure strategy, enables a real-time tissue characteristic monitoring module to continuously monitor tissue hardness and thickness, combines a characteristic fusion and vector generation module, can respond to tissue changes in real time, ensures dynamic and adaptive pressure influence evaluation modules of pressure control to calculate pressure regulating factors according to the real-time changes of tissue characteristics, enables an actual pressure calculation module to finely adjust anastomosis pressure according to the pressure regulating factors, remarkably reduces risks of complications such as tissue damage and joint line leakage caused by improper pressure, improves operation safety and success rate, ensures proper and effective anastomosis each time by means of a highly customized pressure control strategy, is beneficial to promoting tissue healing, maintains organ functions, quickens the postoperative recovery process of patients, can flexibly cope with requirements of different operation positions such as stomach, lungs and hearts and the like and different tissue hardness, improves the universality and the operation application range of an electric anastomat, reduces the requirements of operation appliances, improves the operation efficiency, and the device is remarkably limited by the traditional pressure control method.

The various modifications and embodiments of the pressure adaptive control communication system of the electric stapler in the first embodiment are equally applicable to the pressure adaptive control communication device of the electric stapler in this embodiment, and by the foregoing detailed description of the pressure adaptive control communication system of the electric stapler, those skilled in the art can clearly know the implementation method of the pressure adaptive control communication device of the electric stapler in this embodiment, so that the details of this embodiment will not be described herein for brevity.

In addition, the application also provides an electronic device, which comprises a bus, a transceiver, a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the transceiver, the memory and the processor are respectively connected through the bus, and when the computer program is executed by the processor, the processes of the method embodiment for controlling output data are realized, and the same technical effects can be achieved, so that repetition is avoided and redundant description is omitted.

The foregoing is merely a preferred embodiment of the present invention, and it should be noted that it will be apparent to those skilled in the art that modifications and variations can be made without departing from the technical principles of the present invention, and these modifications and variations should also be regarded as the scope of the invention.

Claims

1. An electric stapler pressure adaptive control communication system, characterized by comprising an operating room control terminal, a central processing unit, an electric stapler controller and a pressure adaptive control module;

The operating room control terminal sends the wound size characteristics and wound tissue location characteristics to the central processing unit;

The central processing unit converts the wound size characteristics and wound tissue location characteristics into data formats, and inputs the converted data information into a pre-built stapler pressure matching model to obtain an initial pressure setting value, and sends it to the electric stapler controller via the CAN bus;

The sensor integrated on the electric stapler controller collects the hardness and thickness characteristics of the wound tissue in real time and transmits them to the central processing unit;

The central processing unit fuses the real-time collected wound tissue hardness and thickness characteristics into a feature vector, and inputs it into the anastomotic pressure impact assessment model to obtain the anastomotic pressure adjustment factor;

The central processing unit calculates the actual pressure parameter based on the anastomotic pressure adjustment factor and the initial pressure setting value, and sends it to the pressure adaptive control module via the CAN bus;

The electric stapler controller is integrated with a communication confirmation unit and a communication synchronization unit; the pressure adaptive control module is integrated with a communication request monitoring unit and a communication synchronization unlocking unit;

During the communication process, the pressure adaptive control module sends a communication request signal to the electric stapler controller through the communication request monitoring unit; after receiving the request, the communication confirmation unit responds and sends a confirmation receipt signal;

In response to the communication request monitoring unit receiving the confirmation receipt signal, the communication synchronization unlocking unit sends a synchronization unlocking signal for performing communication synchronization confirmation with the communication synchronization unit;

In response to the communication synchronization unit receiving the synchronization unlocking signal, the communication synchronization unit replies with a synchronization confirmation signal; if the communication synchronization unlocking unit successfully receives the synchronization confirmation signal from the communication synchronization unit after sending the synchronization unlocking signal, the communication link between the electric stapler controller and the pressure adaptive control module is successfully established;

After the communication link is successfully established, the pressure adaptive control module transmits the calculated actual pressure parameters to the electric stapler controller via the CAN bus to achieve pressure adjustment;

The central processing unit calculates the actual pressure parameters, including:

Based on the surgical plan, the wound size characteristics and wound tissue location characteristics are obtained;

Inputting wound size characteristics and wound tissue location characteristics into a pre-built stapler pressure matching model to obtain the initial pressure on the stapler clamp;

The hardness characteristics and thickness characteristics of wound tissue are acquired in real time, and the data of the hardness characteristics and thickness characteristics of wound tissue are fused to obtain the wound anastomosis influence characteristic vector;

Inputting the wound anastomosis influence feature vector into the pre-built anastomosis pressure influence evaluation model to obtain the anastomosis pressure adjustment factor;

According to the anastomotic pressure adjustment factor and the initial pressure on the stapler clamp, the actual pressure parameter of the electric stapler for the operation is calculated;

According to the actual pressure parameters of the electric stapler, the electric stapler is controlled to press the wound;

The calculation formula of the actual pressure parameter of the electric stapler is:

P _actual = P _initial + F _adjust × P _initial

Wherein, P _initial represents the initial pressure on the stapler clamp, F _adjust represents the stapler pressure adjustment factor, and P _actual represents the actual pressure parameter of the electric stapler.

2. The pressure adaptive control communication system for an electric stapler according to claim 1, wherein the method for acquiring wound size characteristics comprises:

Through preoperative CT scans, magnetic resonance imaging, and ultrasound examinations, the surgical area was reconstructed in three dimensions and the size of the wound was measured;

Based on preoperative imaging data, surgical simulation is performed to plan the size, position and surgical path of the wound in advance and obtain accurate dimensional characteristics.

3. The pressure adaptive control communication system of an electric stapler according to claim 1, wherein the method for identifying the wound tissue site characteristics comprises:

Based on knowledge of the anatomy of the surgical site, identify tissue types;

Based on the patient's specific condition, evaluate the tissue status of the surgical area and predict tissue changes;

Perform pathological analysis to confirm tissue type and characteristics;

By analyzing preoperative imaging data, tissue type and location are automatically identified to obtain wound tissue site characteristics.

4. The electric stapler pressure adaptive control communication system according to claim 1, wherein the method for constructing the anastomotic pressure impact assessment model comprises:

Data were collected from historical surgical cases, including tissue stiffness, tissue thickness, surgical site, wound size, pressure settings used, and surgical outcomes;

Clean the collected data, remove outliers, and fill and delete missing data;

Selecting a machine learning model as the model's infrastructure, the machine learning model including linear regression, support vector machine, random forest, and neural network;

Divide the dataset into training, validation and test sets;

Use the training set data to train the model and iteratively optimize the loss function to learn the mapping relationship between features and pressure regulation factors;

Evaluate model performance on the validation set and adjust model parameters and structure based on the validation results;

Evaluate the model on an independent test set to get the performance of the model on unknown data;

Embed the trained model into the electric stapler control communication system.

5. The pressure adaptive control communication system for an electric stapler according to claim 1, wherein the method for controlling the electric stapler to pressurize the wound comprises:

Verify the actual pressure parameters;

If the actual pressure parameter verification is passed, the electric stapler is activated, otherwise an alarm is issued and the operation is suspended;

During the pressing process, the electric stapler accurately controls the closing force of the jaws according to the actual pressure parameters;

While the jaws are closed and appropriate pressure is applied, suture is performed;

During the entire compression and suturing process, the electric stapler continuously monitors the wound condition and collects relevant data through sensors;

When the suturing operation is completed, the electric stapler automatically releases the jaws and sends a completion signal; the operator checks the suturing effect.

6. A pressure adaptive control communication device for an electric stapler, characterized in that the communication device adopts the pressure adaptive control communication system for an electric stapler as claimed in claim 1, and the communication device comprises:

The wound feature acquisition module acquires the wound size features and wound tissue location features based on the surgical plan;

A pressure matching module inputs wound size characteristics and wound tissue location characteristics into a pre-built stapler pressure matching model to obtain an initial pressure on the stapler clamp;

Real-time tissue characteristic monitoring module, which obtains the characteristics of wound tissue hardness and thickness in real time;

The feature fusion and vector generation module fuses the wound tissue hardness feature and wound tissue thickness feature to obtain the wound anastomosis influence feature vector;

A pressure impact assessment module inputs the wound anastomosis impact feature vector into a pre-built anastomosis pressure impact assessment model to obtain an anastomosis pressure adjustment factor;

The actual pressure calculation module calculates the actual pressure parameters of the electric stapler for the operation according to the anastomosis pressure adjustment factor and the initial pressure on the stapler clamp;

The electric stapler control module controls the electric stapler to press the wound according to the actual pressure parameters of the electric stapler.

7. A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps in the communication system according to any one of claims 1 to 5 are implemented.