CN110522512A - Model-Based Radiofrequency Ablation Surgical Assisting System - Google Patents

Abstract

The radio-frequency ablation procedure auxiliary system based on model that the present invention relates to a kind of.The general cardiac module of the proposed generation for founding intracardiac electric signal of the present invention and conduction is enumerated doubtful heart state, is modeled and carry out parameter identification in conjunction with the relevant knowledge in electric signal observation and cardiac electrophysiology field in radio-frequency ablation procedure center；Intracardiac electric signal is labeled using the model of doubtful heart state, provides the estimation of current cardiac possible state for doctor, to reach more quickly accurate diagnosis.

Description

Model-Based Radiofrequency Ablation Surgical Assisting System

technical field

The invention relates to an auxiliary system which can be used in radio frequency ablation operation for assisting doctors in judging the heart state of patients.

Background technique

With the acceleration of the aging population in our country, arrhythmia, especially tachycardia, has become one of the important diseases that endanger the health of our people. Arrhythmia is caused by abnormalities in the generation and conduction of electrical signals in the heart, resulting in a decrease in the pumping efficiency of the heart, causing myocardial ischemia, and even death. The most common mechanism of tachyarrhythmia is reentry: the electrical conduction channel composed of the myocardium is connected as a reentry circuit, and the electrical signal circulates rapidly in the reentry circuit, triggering rapid and abnormal contraction of the myocardium, resulting in heart failure. Reduced pumping efficiency.

Radiofrequency ablation is one of the main treatments for tachyarrhythmia. By puncturing catheters (Catheters) deep into the heart through the femoral vein to observe the intracardiac electrical signal (EGM), doctors can analyze the generation and conduction mode of electrical signals in the patient's heart. , realize the diagnosis of the disease and locate the reentry loop. After that, the doctor can release radio frequency (RF) signals through the catheter to ablate part of the conduction pathway of the reentry loop, cutting off the reentry loop while killing the corresponding heart tissue, and restoring the normal rhythm of the heart.

Radiofrequency ablation has been shown to be very effective in the treatment of ventricular tachycardia, atrial tachycardia, and junctional tachycardia. It has also achieved better efficacy than drugs in complex tachycardia cases such as atrial fibrillation (Atrial Fibrillation). However, radiofrequency ablation surgery still faces some insurmountable challenges, resulting in high cost of surgery, high threshold and low penetration rate. The main challenges of radiofrequency ablation procedures include:

Challenge 1: Indirectness and discontinuity of patient observation

Since radiofrequency ablation surgery is a minimally invasive surgery, doctors cannot directly observe the specific position of the catheter in the heart during the operation. They can only infer the position of the catheter in three-dimensional space indirectly through the two-dimensional projections of the catheter generated by two sets of X-rays, and The positional relationship of the catheter to the various chambers of the heart is empirically inferred. At the same time, in order to control the length of time that the patient receives X-ray irradiation, the X-ray projection can only be acquired intermittently, resulting in discontinuous temporal information on the position of the catheter.

Due to the limitation of the number of catheters in the heart at the same time, doctors can only observe limited positions in the heart at the same time. To deal with this unfavorable situation, the current solution is to use several fixed diagnostic catheters as reference points, and continuously move an ablation catheter to locate and ablate the reentrant pathway. The discontinuity in time and space in the observation of intracardiac electrical signals has created a large diagnostic blind spot, which has caused great difficulties in the accurate and rapid diagnosis of the patient's condition.

Challenge 2: Correspondence between current and historical observations and the actual heart condition of the patient

Due to the indirect nature of observation in radiofrequency ablation surgery, doctors need to piece together the information contained in current and historical observations during the operation to restore the generation and conduction patterns of electrical signals in the patient's heart. This "brain supplement" process puts forward very high requirements on the doctor's experience and spatial imagination ability, which greatly increases the brainpower consumption of the doctor during the operation.

Challenge Three: Diversity of Patient Conditions

Due to the limited observation of the patient's heart by doctors during radiofrequency ablation, different heart conditions can produce very similar observations, resulting in current and historical observations that can be explained by a variety of suspected heart conditions. Physicians need to consider all suspected cardiac conditions during surgery and rule out some of them if they cannot explain the new observations, and finally arrive at a single correct diagnosis. In order to distinguish suspected cardiac conditions, doctors need to apply electrical signal stimulation sequences to the patient's heart through the catheter, using active stimulation to induce the heart to produce different signals from historical observations. In the fast-paced radiofrequency ablation surgery, considering multiple cardiac conditions at the same time and distinguishing them greatly increases the burden on doctors. In complex cases, the selection of electrical signal stimulation sequences mainly depends on the doctor's experience, which is inefficient and not easy for patients. create an unnecessary burden.

Challenge 4: Controversy over the mechanism of complex tachyarrhythmias

In cases where the position of the reentry circuit is relatively fixed, the doctor can look for the law by observing the periodic changes of the electrical signal, which is helpful for locating the reentry circuit pathway. However, in the case of atrial/ventricular fibrillation (Fibrillation) where the center of the reentry loop is constantly moving, the periodicity of electrical signal observation is weak, and it is difficult to summarize the rules. more distant. Therefore, there are still controversies in the medical field about the generation and maintenance mechanism of fibrillation, and the treatment methods are also lack of pertinence. The main principle is to segment the area in the atrium that is prone to generate/maintain reentry loops, and narrow the range that can be affected by chaotic electrical signals.

To sum up, radiofrequency ablation surgery needs to consider various and complex heart conditions of patients, and requires doctors to perform complex reasoning and operations, which leads to the following problems:

1) The operation takes a long time

A radiofrequency ablation operation usually takes about 2-6 hours, which poses a great challenge to the doctor's endurance and concentration, and also poses a safety hazard to the patient's health.

2) It is highly dependent on the experience of doctors and difficult to popularize

Due to the different conditions of patients, the diagnosis and treatment of radiofrequency ablation requires specific analysis of specific issues. The success rate and efficiency of surgery largely depend on the experience of doctors, which greatly increases the threshold of radiofrequency ablation surgery and limits the popularity of radiofrequency ablation surgery.

The domestic demand for radiofrequency ablation surgeries year by year, from 54,559 cases in 2010 to 133,897 cases in 2017, an increase of 1,393 cases compared to 2016. Using information technology to develop intelligent ablation equipment, explore the mechanism of complex arrhythmias, optimize the procedure of radiofrequency ablation surgery, and provide assistance to doctors can reduce the threshold of radiofrequency ablation surgery, reduce surgical costs, and improve the safety of surgery.

With the advancement of technology, medical equipment manufacturers have developed various auxiliary systems to reduce the burden on doctors in ablation surgery in response to the challenges in radiofrequency ablation surgery.

Challenge 1: Indirectness and discontinuity of patient status observation

Medical instrument manufacturers have developed catheters that can observe ECG signals from more locations at the same time, improving the spatial continuity of measurements in specific heart regions. The resulting reduction in the number of catheter movements also improves the temporal continuity of the measurement. However, this has also led to a surge in the amount of raw data, and the processing of the supporting system is limited to visualization of the new data, which is of limited help to doctors in diagnosis.

For challenge 2: Correspondence between current and historical observations and the patient's actual heart condition

Medical instrument manufacturers have developed trackable catheters and matching catheter tracking systems using the principle of electromagnetic positioning. Using the historical position information of the catheter, the system can realize the following functions: 1) The doctor can use the catheter to perform position sampling on the inner wall of the target chamber at the early stage of the operation, and use the historical position information of the catheter to generate a three-dimensional view of the inner wall of the heart for subsequent The operation provides a frame of reference; 2) Visualize the phase difference of the signals collected at different positions in the same stage of the cardiac cycle, based on which the doctor can infer the conduction mode of the ECG signal in the heart to a certain extent; By visualizing the electrical signal strength measured at different locations, the doctor can roughly determine the location of the scar tissue, which is helpful for the positioning of the reentry loop. To a certain extent, such auxiliary systems correspond historical observations to patients' actual heart conditions, provide doctors with effective data visualization, reduce the burden on doctors, and improve the efficiency of radiofrequency ablation operations.

There are also some model-based diagnosis attempts in the medical and academic circles, using patient data to adjust the parameters of the heart model, establishing a patient-specific heart model, and performing diagnosis and reentry loop positioning based on the simulation of the model. However, due to the high complexity of such models, the patient's data cannot identify all the parameters of the model, and the degree of "exclusiveness" is limited, which can only play a certain guiding role in diagnosis. At the same time, due to the large amount of calculation, this type of model is only suitable for preoperative and postoperative analysis, and has limited real-time guidance for diagnosis and positioning during the operation.

Addressing Challenge 3: Diversity of Patient Conditions

The existing auxiliary system for radiofrequency ablation surgery mainly provides visualization of historical data, and the analysis of historical data is still in a relatively preliminary stage. The most time-consuming heart state estimation and suspected pathological tracking in radiofrequency ablation still rely on the doctor's experience and continuous trial and error, so this is also the main entry point of this project.

Challenge 4: Controversy over the mechanism of complex tachyarrhythmias

The academic and medical circles have developed some complex heart models based on cardiac electrophysiological knowledge for the simulation and exploration of the mechanism of complex arrhythmias such as fibrillation. But also due to the complexity of the model, the model is difficult to achieve patient specificity, and has no guiding role in the diagnosis and positioning of a specific patient during surgery.

To sum up, the existing technology has a limited role in assisting doctors in diagnosis and lesion location during radiofrequency ablation surgery. In order to improve the success rate and efficiency of ablation surgery, reduce the burden on doctors, and provide cheap and efficient medical conditions for the general public , we need to develop a radiofrequency ablation surgery assistance system that provides diagnostic and therapeutic assistance to doctors during surgery.

Contents of the invention

The purpose of the present invention is to assist the doctor in judging the heart state of the patient and locating the lesion during the radiofrequency ablation operation, thereby improving the efficiency of the doctor and reducing the burden on the doctor.

In order to achieve the above object, the technical solution of the present invention is to provide a model-based radiofrequency ablation surgery assisting system, which is characterized in that the heart model is used to explain and distinguish the differences that may arise during the surgical diagnosis process, and the The new information obtained updates and excludes the heart model, providing doctors with possible diagnoses and corresponding evidence. It includes the following units:

The initial heart model building unit is used to set up K heart models H1, H2,..., HK, including the following steps:

Establish K heart models H1, H2,..., HK based on known patient information before the operation, corresponding to K suspected heart conditions of the patient. Each heart model includes a point state machine and a line state machine. The point state machine models the observable and unobservable key tissues in the heart, including common tissues such as the sinoatrial node, and case-related tissues such as the entrance and exit of the reentry loop. The main simulation The generation and blocking of electrical signals in cardiac tissue, while the line state machine simulates the transmission characteristics of electrical signals between key tissues in the heart, including transmission delays, etc. By adjusting the topology and parameters of point and line state machines, doctors can distinguish different heart conditions and explain the corresponding pathology;

The intracardiac electrical signal acquisition unit is used to obtain the intracardiac electrical signal, comprising the following steps:

There are N catheters in the patient's heart during the operation, and each catheter has a corresponding signal label list. The signal label list lists all possible labels of various stress signals that can be observed on the current catheter, and labels the source of the corresponding signal Or properties, can help doctors in pathological analysis. At a certain moment, the catheter n obtains the intracardiac electrical signal, and the stress signal observed by the catheter is transmitted to the catheter by the electrical signal generated by the excitation signal source, and the intracardiac electrical signal is obtained after extraction and processing;

The heart model screening unit screens out a heart model for doctors to refer to after each intracardiac electrical signal, including the following steps:

Step 1. Set the number of suspected heart conditions in the current round Q=K, and the number of suspected heart conditions in the next round Q'=0; obtain the intracardiac electrical signal through the intracardiac electrical signal acquisition unit, and determine the source of the excitation signal that generates the current intracardiac electrical signal There are L possible situations, set l=1, and extract J possible stress signal labels of the current catheter;

Step 2, initialize j to 1;

Step 3, initialize k to 1;

Step 4. Determine whether there is a path corresponding to the l-th excitation signal source to the j-th stress signal label in the k-th heart model Hk, and if so, mark the current stress signal as the j-th signal label, According to this assumption, the heart model Hkj is generated based on the heart model Hk when the assumption is marked as the j-th signal label, and the internal parameters of the heart model Hkj are used as the constraints of the independent variable, and then go to step 5. If it does not exist, go to step 6 ;

In the above step 4, there may be multiple hypothesis labels based on the same heart model Hk, and each hypothesis label corresponds to a heart model (for the next round);

Step 5. Compare the constraints obtained in step 4 with the physiological category of the model parameters. If the model parameters calculated according to the constraints violate physiological common sense, exclude the heart model Hkj obtained in step 4 and proceed to step 6. If the model If the parameters conform to physiological common sense, the heart model Hkj obtained in step 4 is included in the next round of suspected heart conditions, and the number of suspected heart conditions in the next round is Q'=Q'+1, and then enter step 6;

Step 6. Update j to j+1, if the updated j ≥ J, go to step 7, otherwise return to step 4;

Step 7. Update l to l+1, if the updated l≥L, go to step 8, otherwise return to step 4;

Step 8. Update k to k+1, if the updated k≥Q, go to step 9, otherwise return to step 4;

Step 9: Show all the heart models and corresponding ECG labels in the next round of suspected heart conditions to the doctor, update Q=Q', and obtain new intracardiac electrical signals through the intracardiac electrical signal acquisition unit.

Preferably, in the step 1, all possible situations of the source of the excitation signal include self-generated, external signal, last source of the stress signal and so on.

Preferably, updating the heart model so as to obtain a new heart model includes the following steps:

Extract the constraints related to the model parameters from the relationship between the current intracardiac electrical signal and the historical intracardiac electrical signal obtained by the intracardiac electrical signal acquisition unit, and obtain a set of model parameters after linear optimization to complete the heart model. renew.

The present invention intends to establish a general heart model for the generation and conduction of intracardiac electrical signals, combined with the observation of electrical signals in the radiofrequency ablation surgery center and relevant knowledge in the field of cardiac electrophysiology, to enumerate, model and identify suspected heart states; use The model of suspected heart state marks the intracardiac electrical signal to provide doctors with an estimate of the current possible state of the heart to achieve a more rapid and accurate diagnosis.

Description of drawings

Fig. 1 is a schematic diagram of a heart model;

Fig. 2 is a schematic diagram of catheter arrangement in radiofrequency ablation of the heart;

Figure 3 is the body surface electrocardiogram (I, II, III) and intracardiac electrical signals (HRA, HBE);

4A to 4C are diagrams of heart models used in radiofrequency ablation of the heart;

Figure 5 is a roadmap of the present invention.

Detailed ways

Below in conjunction with specific embodiment, further illustrate the present invention. It should be understood that these examples are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the teachings of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of the present application.

The present invention is based on a heart model proposed by the inventor in 2010 that can simulate a patient's heart condition. The heart model follows the understanding of the heart in clinical practice of cardiac electrophysiology, modeling the transmission mode and delay of electrical signals in the heart. The electrical signal activity in the heart mainly has three properties: generation, blocking and conduction. As shown in the figure, in the heart model, the inventor designed two state machines, point and line, corresponding to the point and line segment in Figure 1, respectively. Among them, the point state machine models the properties of specific cardiac tissue to generate and block electrical signals, while the line state machine models the transmission delay of electrical signals between points. In this way, different heart states can be modeled by adjusting the number, connection mode, and parameters of point and line state machines, and corresponding ECG signals can be generated. By changing the topological structure and parameters of the model, the heart model proposed by the inventor can simulate different heart conditions.

As shown in Figure 2, during radiofrequency ablation of the heart, the doctor moves the catheters HRA, HIS, CS, ABL, and RVA in the heart to observe the generation and conduction of electrical signals in the heart, diagnose the heart condition and locate the lesion.

It can be seen from Figure 3 that in the intracardiac electrical signals, each electrical signal represents the electrical activity of the heart tissue near the catheter electrodes. By analyzing the sequence and time delay of the electrical signals between different catheter electrodes, doctors can infer that the electrical signals are distributed throughout the heart. production and conduction modes.

Common catheters in ablation surgery are mainly HRA, His, CS, and RVA. The sources and positions of electrical signals that can be received by each catheter are different. Each catheter has a list of signal sources. For the electrical signal sources that can be observed on the current catheter, a point state machine can be used to establish a heart model for each electrical signal source (hereinafter defined as "stress signal source"), and a line state machine can be used to represent the connection between sources. There are some known but unobservable structures in different heart states that will affect electrical signals, and these structures are also represented by point and line state machines in the present invention, as shown by the hollow points in Fig. 4A to Fig. 4C . Due to the limited number of observation points, there may be multiple cardiac conditions that could explain the current observations. We model these ambiguities by adopting different cardiac models and using physiological knowledge to rule out some of these situations. The main steps of the invented operation are as follows:

Step 1. Model all suspected cardiac conditions using preoperative diagnoses;

Step 2, receiving an electrical signal in a catheter (such as His catheter);

Step 3. Enumerate the possible initial source of the signal (hereinafter defined as "excitation signal source") {self-generated, external signal, previous signal};

Step 4, enumerate the stress signal annotations that may generate electrical signals in the catheter that received the signal (such as His_A, His_H and His_V of the His catheter);

In Step 3 and Step 4, if there is a reasonable explanation from the source of the excitation signal to the labeling of the emergency signal, the constraints related to the model parameters are extracted from the relationship between the current electrical signal and the historical electrical signal, and a set of models is obtained after linear optimization parameters to generate a new model;

Step 5, according to the network structure of the heart model, exclude a part of excitation signal sources and stress signal sources;

Step 6. If the updated new model parameters, that is, the optimized model parameters exceed the physiological range, exclude the model;

Step 7. Repeat steps 2-6, and show the remaining models to the doctor.

Use an example to specifically show a specific implementation of the above steps 3, 4, and 5:

Assuming that a normal person is tested, an electrical signal is stimulated through the HRA_A electrode, that is, the source of the excitation signal is the HRA_A electrode. Two electrical signals are continuously received in the His catheter, and can be obtained according to the above steps:

1) His catheter receives the first signal

2) The source of the excitation signal is an external signal (HRA_A is known)

3) The stress signal label may be His_A, His_H or His_V

4) Find the pathway from HRA_A to His_A in the heart model, the pathway exists, build a new heart model and mark the first signal as His_A;

5) At the same time, the transmission delay parameter of the line state machine from HRA_A to His_A is equal to the time difference between the signals from HRA_A to His_A;

6) Find the pathway from HRA_A to His_H in the heart model, the pathway exists, update the original model, establish a new heart model and mark the first signal as His_H;

7) Since the time difference from HRA_A to His_A is known to be smaller than the time difference from HRA_A to His_H (physiological common sense), this model is excluded.

8) Look for the pathway from HRA_A to His_V in the heart model. This pathway exists, but His_H exists on this pathway and His_H did not appear before (physiological common sense), so this situation is excluded.

At this point, the first signal is only His_A. For the second signal, we can know:

1) The source of the excitation signal is an external signal or the source of the previous stress signal;

2) If it is His_A, the source of the last stress signal, look for the pathway from His_A to His_H. This pathway exists, but HRA_A does not appear on this pathway, so this situation is ruled out;

3) If the source of the excitation signal is an external signal (HRA_A is known)

4) The source of the stress signal may be His_A, His_H or His_V

5) Since the previous signal was His_A, and the source of the signal was not generated by itself, the case where the source of the stress signal was His_A was excluded;

6) Find the pathway from HRA_A to His_H in the heart model, the pathway exists, update the existing heart model, build a new heart model and mark the first signal as His_H;

7) Look for the pathway from HRA_A to His_V in the heart model. This pathway exists, but His_H exists on this pathway and His_H did not appear before, so this situation is excluded

8) The path from HRA_A to His_H is divided into two parts by the AV point state machine. From the existing information, the time delay of the line state machine from HRA_A to AV plus the time delay from AV to His_H is equal to the measurement from HRA_A to His_H the delay;

Therefore, the second signal has only one case of His_H.

Utilizing the present invention, the doctor can obtain an ever-growing tree structure during the operation, in which each leaf node represents a heart model that can explain the current heart condition at a certain moment, and more ambiguities appear as the operation progresses , causing the "fork" of the tree, but at the same time, as the amount of information gradually increases, the tree is "cut" thinner. Part of the medical-related knowledge is collected in the heart model, and part of it is collected in the exclusion rules and extraction model parameter constraints, which can be gradually expanded with the progress of knowledge, providing assistance for doctors' diagnosis, and giving readable suggestions explanation of.

In the heart model, we established a point state machine model for various sources of intracardiac electrical signals, and distinguished the source of each electrical signal during the auxiliary diagnosis process, and the final differentiated results can be used as intracardiac electrical signals The label of is placed on each electrical signal, as shown in Figure 3, the HBE signal corresponds to the His catheter in the previous example, and A and H in it also correspond to His_A and His_H in the previous example. Due to the existence of ambiguity, there may be multiple labeling methods for the current intracardiac electrical signal at a certain moment during the operation, but as the ambiguity of information acquisition is gradually eliminated, the labeling of intracardiac electrical signal can help doctors gradually understand the basis of a certain diagnosis , is an important part of surgical assistance.

Claims (3)

1. A model-based radiofrequency ablation surgery assisting system, characterized in that, using the heart model to explain and distinguish the differences that may occur in the surgical diagnosis process, and utilizing new information obtained during the operation to update and exclude the heart model, for The doctor provides the possible diagnosis and the corresponding basis, which includes the following units: The initial heart model building unit is used to set up K heart models H1, H2,..., HK, including the following steps: K heart models H1, H2,..., HK are established according to the known patient information before the operation, corresponding to K suspected heart conditions of the patient. Each heart model includes a point state machine and a line state machine. Observable and unobservable key tissues and case-related tissues are modeled to simulate the generation and blockage of cardiac tissue electrical signals, while the line state machine simulates the transmission characteristics of electrical signals between key tissues in the heart; by adjusting the point and line states The topological structure and parameters of the machine, the doctor can distinguish different heart conditions and explain the corresponding pathology; The intracardiac electrical signal acquisition unit is used to obtain the intracardiac electrical signal, comprising the following steps: There are N catheters in the patient's heart during the operation, and each catheter has a corresponding signal label list. The signal label list lists all possible labels of various stress signals that can be observed on the current catheter, and labels the source of the corresponding signal or nature, to help doctors conduct pathological analysis; at a certain moment, the catheter n obtains the intracardiac electrical signal, and the stress signal observed by the catheter is transmitted to the catheter by the electrical signal generated by the excitation signal source, and the intracardiac electrical signal is obtained after extraction and processing ; The heart model screening unit screens out a heart model for doctors to refer to after each intracardiac electrical signal, including the following steps: Step 1. Obtain the intracardiac electrical signal through the intracardiac electrical signal acquisition unit, judge all possible situations of the source of the excitation signal that generates the current intracardiac electrical signal, set L possible situations, set l=1, and extract the current possible situation of the catheter J kinds of stress signal labeling; Step 2, initialize j to 1; Step 3, initialize k to 1; Step 4. Determine whether there is a path corresponding to the l-th excitation signal source to the j-th stress signal label in the k-th heart model Hk, and if so, mark the current stress signal as the j-th signal label, According to this assumption, the heart model Hkj is generated based on the heart model Hk when the assumption is marked as the j-th signal label, and the internal parameters of the heart model Hkj are used as the constraints of the independent variable, and then go to step 5. If it does not exist, go to step 6 ; Step 5. Compare the constraints obtained in step 4 with the physiological category of the model parameters. If the model parameters calculated according to the constraints violate physiological common sense, exclude the heart model Hkj obtained in step 4 and proceed to step 6. If the model If the parameters conform to physiological common sense, the heart model Hkj obtained in step 4 is included in the next round of suspected heart conditions, and the number of suspected heart conditions in the next round is Q'=Q'+1, and then enter step 6; Step 6. Update j to j+1, if the updated j ≥ J, go to step 7, otherwise return to step 4; Step 7. Update l to l+1, if the updated l≥L, go to step 8, otherwise return to step 4; Step 8. Update k to k+1, if the updated k≥Q, go to step 9, otherwise return to step 4; Step 9: Show all the heart models and corresponding ECG labels in the next round of suspected heart conditions to the doctor, update Q=Q', and obtain new intracardiac electrical signals through the intracardiac electrical signal acquisition unit. . 2. A method for generating an auxiliary heart model that can be used for radiofrequency ablation as claimed in claim 1, wherein in said step 1, all possible situations of the excitation signal source include self-generated, external signal, last application Source of excitation signal. 3. A method for generating an auxiliary heart model that can be used for radiofrequency ablation as claimed in claim 1, wherein updating the heart model so as to obtain a new heart model comprises the following steps: Extract the constraints related to the model parameters from the relationship between the current intracardiac electrical signal and the historical intracardiac electrical signal obtained by the intracardiac electrical signal acquisition unit, and obtain a set of model parameters after linear optimization to complete the heart model. renew.