Remote diagnosis and treatment method and system based on pulse simulator

Abstract

The invention discloses a remote diagnosis and treatment method and system based on a pulse simulator, relates to the technical field of medical care, and discloses a patient pulse acquisition module, a pulse condition parameter simulation setting module, a pulse condition dimension diagnosis module and a pulse remote diagnosis and treatment module. By arranging the patient pulse collection module, the pulse condition parameter simulation setting module, the pulse condition dimension diagnosis module and the pulse remote diagnosis and treatment module, pulse signals of a patient can be periodically simulated through the pulse simulator, and the diagnosis precision of pulse diagnosis on the patient is guaranteed; according to the method, the potential abnormal pulse condition dimension data of the patient can be preferentially diagnosed and analyzed, the pulse condition data of all dimensions does not need to be analyzed at the same time, the pulse condition data processing efficiency of pulse diagnosis of the patient can be improved, and meanwhile the pulse condition data processing difficulty of pulse diagnosis of the patient is effectively reduced.

Description

Technical Field

[0001] The present invention relates to the field of medical care technology, and more specifically, to a remote diagnosis and treatment method and system based on a pulse simulator. Background Art

[0002] In traditional Chinese medicine diagnosis and treatment, pulse diagnosis is an indispensable and important part. However, due to geographical restrictions and uneven distribution of medical resources, many patients find it difficult to directly meet experienced Chinese medicine practitioners for pulse diagnosis. With the advancement of medical standards, remote pulse measurement equipment has gradually been introduced. By collecting the patient's pulse signal, the remote pulse measurement equipment can remotely send the pulse signal to the doctor waiting in line for diagnosis and treatment. However, a large number of normal pulse signals mixed in the diagnosis and treatment queue will cause patients with abnormal pulses to be unable to receive effective diagnosis and treatment in time, and also cause increasing pressure on doctors to diagnose and treat. In addition, the remote pulse measurement equipment needs to analyze the pulse data of all dimensions at the same time before it can analyze whether the patient's pulse is abnormal. The efficiency of this pulse analysis is not high. Summary of the invention

[0003] In view of the deficiencies in the prior art, the present invention aims to provide a remote diagnosis and treatment method and system based on a pulse simulator.

[0004] To achieve the above object, the present invention provides the following technical solutions: A remote diagnosis and treatment method based on a pulse simulator comprises the following steps: Step 1: Collect the patient's pulse signal; Step 2: Periodically obtain simulation parameters of various types of pulse parameters of the patient; Step 3: After obtaining the simulation parameters of each type of pulse parameter of the patient, input the simulation parameters of each type of pulse parameter into the pulse simulator; Step 4: Set the diagnostic order of the patient's pulse dimension data; Step 5: After diagnosing each pulse dimension data, generate a dimension diagnosis record of the pulse dimension data; Step 6: Whenever a dimensional diagnosis record is generated, the remote diagnosis value of the patient is obtained, and based on the comparison result between the remote diagnosis value and its threshold, it is determined whether to mark the patient as a pulse diagnosis patient; Step 7: When the patient is marked as a pulse diagnosis and treatment patient, the pulse diagnosis and treatment patient is registered to the remote diagnosis and treatment doctor's terminal.

[0005] Further, a remote diagnosis and treatment system based on a pulse simulator includes a patient pulse acquisition module, a pulse parameter simulation setting module, a pulse dimension diagnosis module, and a pulse remote diagnosis and treatment module; The patient pulse acquisition module is used to acquire the patient's pulse signal; The pulse parameter simulation setting module is used to periodically obtain simulation parameters of various types of pulse parameters of the patient; After obtaining the simulation parameters of each type of pulse parameter of the patient, the pulse dimension diagnosis module inputs the simulation parameters of each type of pulse parameter into the pulse simulator, and sets the diagnosis order of the patient's pulse dimension data, generates a dimension diagnosis record of the pulse dimension data after diagnosing each pulse dimension data, and then continues to diagnose the next pulse dimension data according to the diagnosis order of the pulse dimension data; Whenever a dimensional diagnosis record is generated, the pulse remote diagnosis and treatment module obtains the patient's remote diagnosis and treatment value, and determines whether to mark the patient as a pulse diagnosis and treatment patient based on the comparison result between the remote diagnosis and treatment value and its threshold. When the patient is marked as a pulse diagnosis and treatment patient, the pulse diagnosis and treatment patient is registered to the remote diagnosis and treatment doctor's terminal.

[0006] Furthermore, simulation parameters of various types of pulse parameters of the patient are periodically obtained, specifically: based on a preset cycle, when a cycle node is reached, all pulse signals of the patient within the cycle are collected, actual parameters of various types of pulse parameters are obtained according to the pulse signals, the actual parameters of the same type of pulse parameters are summed and averaged to obtain simulation parameters of this type of pulse parameters, and then simulation parameters of various types of pulse parameters of the patient are obtained.

[0007] Furthermore, the dimensional diagnosis record includes the patient name, pulse dimension data name, dimensional diagnosis index, and dimensional diagnosis time.

[0008] Furthermore, the dimensional diagnostic index of the dimensional diagnostic record is obtained in the following manner: obtaining the pulse signal of the pulse simulator, synchronously obtaining the pulse dimensional index model of the pulse dimensional data, inputting the pulse signal into the pulse dimensional index model, and obtaining the dimensional diagnostic index of the pulse dimensional data.

[0009] Furthermore, the patient's remote diagnosis and treatment value is obtained in the following manner: obtain all abnormal pulse dimension data and all normal pulse dimension data of the patient in this period, analyze all abnormal pulse dimension data in pairs, when two abnormal pulse dimension data show a correlation line in the pulse dimension data spectrum, sum and average the dimensional diagnostic indexes of the two abnormal pulse dimension data to obtain the associated abnormal balance index, when the two abnormal pulse dimension data do not show a correlation line in the pulse dimension data spectrum, increase the abnormal pulse frequency by one, sum and average all associated abnormal balance indices to obtain the associated abnormal balance average index Fgc, sum all abnormal pulse frequencies to obtain the abnormal pulse sum Rew, mark the total number of abnormal pulse dimension data as Ty, mark the total number of normal pulse dimension data as Sy, and use the formula The remote diagnosis and treatment value Fs of the patient is obtained, where z1 is the associated abnormal balance index coefficient, z2 is the abnormal pulse and frequency coefficient, z3 is the abnormal pulse quantity coefficient, and z4 is the normal pulse quantity coefficient.

[0010] Furthermore, abnormal pulse dimension data and normal pulse dimension data are obtained in the following manner: whenever a dimension diagnosis record is generated, the pulse dimension data name and dimension diagnosis index of the dimension diagnosis record are obtained, and the dimension diagnosis limit index of the pulse dimension data is obtained; when the dimension diagnosis index is greater than the dimension diagnosis limit index, the pulse dimension data is marked as abnormal pulse dimension data; when the dimension diagnosis index is less than or equal to the dimension diagnosis limit index, the pulse dimension data is marked as normal pulse dimension data.

[0011] Furthermore, the patient's pulse dimension data diagnostic order is obtained in the following manner: Get all the dimensional diagnosis records of the patient before the current time of the system, get the pulse dimension data name of the dimensional diagnosis record, mark the dimensional diagnosis records with the same pulse dimension data name as the same pulse dimensional diagnosis record, sum and average the dimensional diagnosis indexes of all the same pulse dimensional diagnosis records, get the average dimensional diagnosis index TSD, sort all the same pulse dimensional diagnosis records in the chronological order of the dimensional diagnosis time, calculate the difference between the dimensional diagnosis indexes of the two adjacent dimensional diagnosis records with the same pulse after sorting and take the absolute value to get the dimensional diagnosis floating drop value, set the dimensional diagnosis floating drop threshold, when the dimensional diagnosis floating drop value is greater than or equal to the dimensional diagnosis floating drop threshold, increase the number of abnormal floating drops by one, sum and average all abnormal floating drops to get the abnormal floating drop sum number SKL, sum and average all dimensional diagnosis floating drop values ​​to get the dimensional diagnosis floating drop mean EW, use the formula The diagnostic sequence value Rg of the pulse dimension data is obtained, where y1 is the average dimension diagnostic index coefficient, y2 is the abnormal floating drop and number coefficient, and y3 is the dimension diagnostic floating drop mean coefficient. All pulse dimension data are sorted from large to small according to the value of the diagnostic sequence value, and then the patient's pulse dimension data diagnostic order is generated.

[0012] Furthermore, a remote diagnosis and treatment threshold is set. When the remote diagnosis and treatment value is greater than or equal to the remote diagnosis and treatment threshold, the patient is marked as a pulse diagnosis and treatment patient, the basic patient information of the pulse diagnosis and treatment patient and the simulated pulse signal of the pulse simulator are obtained, and the pulse diagnosis and treatment patient is registered to the remote diagnosis and treatment doctor's terminal. When the remote diagnosis and treatment value is less than the remote diagnosis and treatment threshold, no processing is performed.

[0013] Compared with the prior art, the present invention has the following beneficial effects: 1. The method of the present invention uses pulse data of various dimensions to make a detailed diagnosis of the pulse. During the diagnosis process, the pulse diagnosis and treatment patients are marked and registered in a timely manner, effectively improving the efficiency of remote diagnosis and treatment of the patient's pulse; 2. Set up a patient pulse acquisition module, a pulse parameter simulation setting module, a pulse dimension diagnosis module and a pulse remote diagnosis and treatment module. The patient's pulse signal can be periodically simulated through a pulse simulator to ensure the diagnostic accuracy of the patient's pulse diagnosis. Priority can be given to diagnosing and analyzing the patient's potentially abnormal pulse dimension data. There is no need to analyze the pulse data of all dimensions at the same time. This can not only improve the efficiency of pulse data processing for patient pulse diagnosis, but also effectively reduce the difficulty of pulse data processing for patient pulse diagnosis. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a flowchart of a remote diagnosis and treatment method based on a pulse simulator; Figure 2 It is a module block diagram of a remote diagnosis and treatment system based on a pulse simulator; Figure 3 A flowchart for obtaining abnormal pulse dimension data and normal pulse dimension data. DETAILED DESCRIPTION

[0015] Example 1 Reference Figure 1 , a remote diagnosis and treatment method based on a pulse simulator, comprising the following steps: Step 1: Collect the patient's pulse signal; Step 2: Periodically obtain simulation parameters of various types of pulse parameters of the patient; Step 3: After obtaining the simulation parameters of each type of pulse parameter of the patient, input the simulation parameters of each type of pulse parameter into the pulse simulator; Step 4: Set the diagnostic order of the patient's pulse dimension data; Step 5: After diagnosing each pulse dimension data, generate a dimension diagnosis record of the pulse dimension data; Step 6: Whenever a dimensional diagnosis record is generated, the remote diagnosis value of the patient is obtained, and based on the comparison result between the remote diagnosis value and its threshold, it is determined whether to mark the patient as a pulse diagnosis patient; Step 7: When the patient is marked as a pulse diagnosis and treatment patient, the pulse diagnosis and treatment patient is registered to the remote diagnosis and treatment doctor's terminal.

[0016] The method of the present invention performs a precise diagnosis of the pulse through pulse data of various dimensions. During the diagnosis process, the pulse diagnosis and treatment patients are marked and registered in a timely manner, thereby effectively improving the efficiency of remote diagnosis and treatment of the patient's pulse.

[0017] Example 2 Reference Figure 2-Figure 3 A remote diagnosis and treatment system based on a pulse simulator includes a patient pulse acquisition module, a pulse parameter simulation setting module, a pulse dimension diagnosis module, and a pulse remote diagnosis and treatment module.

[0018] The patient pulse acquisition module is used to collect the patient's pulse signal (the patient is equipped with a pulse acquisition device, and the patient can collect his or her own pulse signal through the pulse acquisition device. A pulse signal can be obtained each time the acquisition is performed. The frequency of the acquisition can be adjusted according to the doctor's instructions or the patient's needs, which is not the focus of this application).

[0019] The pulse parameter simulation setting module is based on a preset cycle (the cycle node interval of the preset cycle can be adjusted according to actual needs). When the cycle node is reached, all pulse signals of the patient in the cycle (between the current cycle node and the previous cycle node) are collected, and the actual parameters of various types of pulse parameters are obtained according to the pulse signal (the pulse signal can be processed by filtering, amplification, AD conversion, etc., and then the actual parameters of various types of pulse parameters are obtained by time domain analysis, frequency domain analysis, etc. The types of pulse parameters include but are not limited to pulse frequency, blood oxygen saturation, pulse intensity, waveform rising branch amplitude, waveform peak slope, etc.), the actual parameters of the same type of pulse parameters are summed and averaged to obtain the simulation parameters of this type of pulse parameters.

[0020] Pulse dimension diagnosis module: after obtaining the simulation parameters of each type of pulse parameter of the patient, the simulation parameters of each type of pulse parameter are input into the pulse simulator (the pulse simulator needs to rely on the input simulation parameters when simulating the pulse signal), and at the same time, the pulse dimension data diagnosis order of the patient is set, and each pulse dimension data (pulse dimension data is a key part of TCM diagnosis, which is used to reflect the state of the patient's qi and blood circulation and health status. Pulse dimension data includes but is not limited to pulse position, pulse rate, pulse strength, pulse length, pulse width, fluency, pulse position: refers to the part where the pulse appears, such as floating pulse, sinking pulse, etc., pulse shape: refers to the pulse After diagnosing the pulse dimension data (i.e., the name of the patient to whom the pulse dimension data belongs), the pulse dimension data name (i.e., the name of the pulse dimension data in medicine, such as pulse position, pulse number, pulse strength), dimension diagnosis index, dimension diagnosis time, and then continuing to diagnose the next pulse dimension data in the pulse dimension data diagnosis order (until all pulse dimension data in the pulse dimension data diagnosis order are diagnosed).

[0021] The dimensional diagnostic index of the dimensional diagnostic record is obtained in the following manner: obtain the pulse signal of the pulse simulator, synchronously obtain the pulse dimensional index model of the pulse dimensional data, input the pulse signal into the pulse dimensional index model, and obtain the dimensional diagnostic index of the pulse dimensional data.

[0022] Whenever a dimensional diagnosis record is generated, the pulse dimension data name and dimensional diagnosis index of the dimensional diagnosis record are obtained, and the dimensional diagnosis limit index of the pulse dimension data is obtained (different pulse dimension data correspond to different dimensional diagnosis limit indexes, and the dimensional diagnosis limit index is the threshold set by the system, which can be modified according to actual needs). When the dimensional diagnosis index is greater than the dimensional diagnosis limit index, the pulse dimension data is marked as abnormal pulse dimension data; when the dimensional diagnosis index is less than or equal to the dimensional diagnosis limit index, the pulse dimension data is marked as normal pulse dimension data.

[0023] Pulse remote diagnosis and treatment module: Whenever a dimensional diagnosis record is generated, the remote diagnosis and treatment value of the patient is obtained, and the remote diagnosis and treatment threshold is set (the remote diagnosis and treatment threshold is the threshold set by the system and can be modified according to actual needs). When the remote diagnosis and treatment value is greater than or equal to the remote diagnosis and treatment threshold, the patient is marked as a pulse diagnosis and treatment patient, and the basic patient information (such as name, age) of the pulse diagnosis and treatment patient and the simulated pulse signal of the pulse simulator are obtained. The pulse diagnosis and treatment patient is registered to the remote diagnosis and treatment doctor's terminal (the remote diagnosis and treatment doctor's terminal will display the queue number, basic patient information and simulated pulse signal of the pulse diagnosis and treatment patient, and the patient can queue up and wait for the remote diagnosis and treatment doctor to perform remote diagnosis and treatment on the pulse diagnosis and treatment patient). When the remote diagnosis and treatment value is less than the remote diagnosis and treatment threshold, no processing is performed.

[0024] The patient's remote diagnosis and treatment value is obtained in the following way: obtain all abnormal pulse dimension data and all normal pulse dimension data of the patient in this period, analyze all abnormal pulse dimension data in pairs, when two abnormal pulse dimension data show a correlation line in the pulse dimension data spectrum, sum and average the dimensional diagnostic indexes of the two abnormal pulse dimension data to obtain the associated abnormal balance index, when the two abnormal pulse dimension data do not show a correlation line in the pulse dimension data spectrum, increase the abnormal pulse frequency by one, sum and average all associated abnormal balance indices to obtain the associated abnormal balance average index Fgc, sum all abnormal pulse frequencies to obtain the abnormal pulse sum Rew, mark the total number of abnormal pulse dimension data as Ty, mark the total number of normal pulse dimension data as Sy, and use the formula The remote diagnosis and treatment value Fs of the patient is obtained, where z1 is the coefficient of the associated abnormal balance index, z2 is the abnormal pulse and frequency coefficient, z3 is the abnormal pulse quantity coefficient, and z4 is the normal pulse quantity coefficient. The value of z1 is 0.58, the value of z2 is 0.62, the value of z3 is 0.98, and the value of z4 is 0.95.

[0025] The pulse dimension data spectrum contains all pulse dimension data, and the correlation lines between all pulse dimension data are displayed in the pulse dimension data spectrum. For example, changes in pulse position will cause changes in pulse strength (when the pulse position changes, such as from floating to sinking or from sinking to floating, the pulse strength will also change accordingly. For example, when a floating pulse turns into a sinking pulse, the strength of the pulse may increase and the fluency may become more even; when a sinking pulse turns into a floating pulse, the strength may weaken and the fluency may deteriorate), changes in pulse strength will cause changes in pulse position (when the pulse shows stronger strength and tension, it may mean that the pulse position is deeper; and when the pulse strength is weaker and the tension is lower, it may mean that the pulse position is shallower), then the pulse position and pulse strength will show a correlation line in the pulse dimension data spectrum (indicating that the pulse position and pulse strength influence each other).

[0026] The patient's pulse dimension data diagnostic order is obtained in the following way: Get all the dimensional diagnosis records of the patient before the current time of the system, get the pulse dimension data name of the dimensional diagnosis record, mark the dimensional diagnosis records with the same pulse dimension data name as the same pulse dimensional diagnosis record, sum and average the dimensional diagnosis indexes of all the same pulse dimensional diagnosis records, get the average dimensional diagnosis index TSD, sort all the same pulse dimensional diagnosis records in the chronological order of the dimensional diagnosis time, calculate the difference between the dimensional diagnosis indexes of the two adjacent dimensional diagnosis records with the same pulse after sorting and take the absolute value to get the dimensional diagnosis floating drop value, set the dimensional diagnosis floating drop threshold (the dimensional diagnosis floating drop threshold is the threshold set by the system and can be modified according to actual needs), when the dimensional diagnosis floating drop value is greater than or equal to the dimensional diagnosis floating drop threshold, increase the number of abnormal floating drops by one, sum and average all abnormal floating drops to get the abnormal floating drop sum number SKL, sum and average all dimensional diagnosis floating drop values ​​to get the dimensional diagnosis floating drop mean EW, use the formula The diagnostic sequence value Rg of the pulse dimension data is obtained, where y1 is the average dimension diagnostic index coefficient, y2 is the abnormal floating drop and frequency coefficient, and y3 is the dimension diagnostic floating drop mean coefficient. The value of y1 is 2.83, the value of y2 is 3.97, and the value of y3 is 1.98. All pulse dimension data are sorted from large to small according to the numerical value of the diagnostic sequence value, and then the diagnostic order of the patient's pulse dimension data is generated (for example: the four pulse dimension data of patient a: pulse position, pulse rate, pulse strength, and pulse length, where the diagnostic sequence value of pulse position > the diagnostic sequence value of pulse strength > the diagnostic sequence value of pulse rate > the diagnostic sequence value of pulse length, then the diagnostic order of patient a's pulse dimension data is 1, pulse position; 2, pulse strength; 3, pulse rate; 4, pulse length. First diagnose the pulse position of patient a, and finally diagnose the pulse length of patient a. If the diagnostic sequence values ​​of two pulse dimension data are equal, the two pulse dimension data can be diagnosed in either order).

[0027] Each pulse dimension data corresponds to an independent pulse dimension index model. This embodiment will take the pulse as an example to introduce the construction method of the pulse dimension index model: collect p pulse signals, extract features from each pulse signal, obtain the pulse feature set of each pulse signal, use the pulse feature set of the p pulse signals as the training data of the neural network model, assign the dimension diagnosis index to the pulse feature set of each pulse signal, divide the p training data into a training set and a verification set according to a ratio of 2:3, perform neural network iterative training on the training set and the verification set, and obtain the pulse dimension index model. Among them, the larger the value of the dimension diagnosis index, the more abnormal the pulse is, and the smaller the value of the dimension diagnosis index, the more normal the pulse is. The construction method of the pulse dimension index model of the remaining pulse dimension data is the same as above. The index range of the dimension diagnosis index of all pulse dimension index models is (1~2).

[0028] By setting up a patient pulse acquisition module, a pulse parameter simulation setting module, a pulse dimension diagnosis module and a pulse remote diagnosis and treatment module, the patient's pulse signal can be periodically simulated through a pulse simulator to ensure the diagnostic accuracy of the patient's pulse diagnosis. The patient's potentially abnormal pulse dimension data can be given priority for diagnosis and analysis, and there is no need to analyze the pulse data of all dimensions at the same time. This can not only improve the efficiency of pulse data processing for patient pulse diagnosis, but also effectively reduce the difficulty of pulse data processing for patient pulse diagnosis.

[0029] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0030] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0031] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0032] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0033] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0034] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0035] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0036] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A remote diagnosis and treatment method based on a pulse simulator, characterized in that: The steps include: Step 1: Collect the patient's pulse signal; Step 2: Periodically obtain simulation parameters of various types of pulse parameters of the patient; Step 3: After obtaining the simulation parameters of each type of pulse parameter of the patient, input the simulation parameters of each type of pulse parameter into the pulse simulator; Step 4: Set the diagnostic order of the patient's pulse dimension data; Step 5: After diagnosing each pulse dimension data, generate a dimension diagnosis record of the pulse dimension data; Step 6: Whenever a dimensional diagnosis record is generated, the remote diagnosis value of the patient is obtained, and based on the comparison result between the remote diagnosis value and its threshold, it is determined whether to mark the patient as a pulse diagnosis patient; Step 7: When the patient is marked as a pulse diagnosis and treatment patient, the pulse diagnosis and treatment patient is registered to the remote diagnosis and treatment doctor's terminal.

2. A remote diagnosis and treatment system based on a pulse simulator, applied to the remote diagnosis and treatment method based on a pulse simulator as claimed in claim 1, characterized in that: It includes patient pulse acquisition module, pulse parameter simulation setting module, pulse dimension diagnosis module, and pulse remote diagnosis and treatment module; The patient pulse acquisition module is used to acquire the patient's pulse signal; The pulse parameter simulation setting module is used to periodically obtain simulation parameters of various types of pulse parameters of the patient; After obtaining the simulation parameters of each type of pulse parameter of the patient, the pulse dimension diagnosis module inputs the simulation parameters of each type of pulse parameter into the pulse simulator, and sets the diagnosis order of the patient's pulse dimension data, generates a dimension diagnosis record of the pulse dimension data after diagnosing each pulse dimension data, and then continues to diagnose the next pulse dimension data according to the diagnosis order of the pulse dimension data; Whenever a dimensional diagnosis record is generated, the pulse remote diagnosis and treatment module obtains the patient's remote diagnosis and treatment value, and determines whether to mark the patient as a pulse diagnosis and treatment patient based on the comparison result between the remote diagnosis and treatment value and its threshold. When the patient is marked as a pulse diagnosis and treatment patient, the pulse diagnosis and treatment patient is registered to the remote diagnosis and treatment doctor's terminal.

3. A remote diagnosis and treatment system based on a pulse simulator according to claim 2, characterized in that: The simulation parameters of various types of pulse parameters of the patient are periodically obtained, specifically: based on a preset cycle, when a cycle node is reached, all pulse signals of the patient in the cycle are collected, and the actual parameters of various types of pulse parameters are obtained according to the pulse signals. The actual parameters of the same type of pulse parameters are summed and averaged to obtain the simulation parameters of this type of pulse parameters, and then the simulation parameters of various types of pulse parameters of the patient are obtained.

4. A remote diagnosis and treatment system based on a pulse simulator according to claim 2, characterized in that: Dimensional diagnosis records include patient name, pulse dimension data name, dimensional diagnosis index, and dimensional diagnosis time.

5. A remote diagnosis and treatment system based on a pulse simulator according to claim 4, characterized in that: The dimensional diagnostic index of the dimensional diagnostic record is obtained in the following manner: obtain the pulse signal of the pulse simulator, synchronously obtain the pulse dimensional index model of the pulse dimensional data, input the pulse signal into the pulse dimensional index model, and obtain the dimensional diagnostic index of the pulse dimensional data.

6. A remote diagnosis and treatment system based on a pulse simulator according to claim 2, characterized in that: The patient's remote diagnosis and treatment value is obtained in the following way: obtain all abnormal pulse dimension data and all normal pulse dimension data of the patient in this period, analyze all abnormal pulse dimension data in pairs, when two abnormal pulse dimension data show a correlation line in the pulse dimension data spectrum, sum and average the dimensional diagnostic indexes of the two abnormal pulse dimension data to obtain the associated abnormal balance index, when the two abnormal pulse dimension data do not show a correlation line in the pulse dimension data spectrum, increase the abnormal pulse frequency by one, sum and average all associated abnormal balance indices to obtain the associated abnormal balance average index Fgc, sum all abnormal pulse frequencies to obtain the abnormal pulse sum Rew, mark the total number of abnormal pulse dimension data as Ty, mark the total number of normal pulse dimension data as Sy, and use the formula The remote diagnosis and treatment value Fs of the patient is obtained, where z1 is the associated abnormal balance index coefficient, z2 is the abnormal pulse and frequency coefficient, z3 is the abnormal pulse quantity coefficient, and z4 is the normal pulse quantity coefficient.

7. A remote diagnosis and treatment system based on a pulse simulator according to claim 6, characterized in that: Abnormal pulse dimension data and normal pulse dimension data are obtained in the following manner: whenever a dimension diagnosis record is generated, the pulse dimension data name and dimension diagnosis index of the dimension diagnosis record are obtained, and the dimension diagnosis limit index of the pulse dimension data is obtained; when the dimension diagnosis index is greater than the dimension diagnosis limit index, the pulse dimension data is marked as abnormal pulse dimension data; when the dimension diagnosis index is less than or equal to the dimension diagnosis limit index, the pulse dimension data is marked as normal pulse dimension data.

8. A remote diagnosis and treatment system based on a pulse simulator according to claim 2, characterized in that: The patient's pulse dimension data diagnostic order is obtained in the following way: Get all the dimensional diagnosis records of the patient before the current time of the system, get the pulse dimension data name of the dimensional diagnosis record, mark the dimensional diagnosis records with the same pulse dimension data name as the same pulse dimensional diagnosis record, sum and average the dimensional diagnosis indexes of all the same pulse dimensional diagnosis records, get the average dimensional diagnosis index TSD, sort all the same pulse dimensional diagnosis records in the chronological order of the dimensional diagnosis time, calculate the difference between the dimensional diagnosis indexes of the two adjacent dimensional diagnosis records with the same pulse after sorting and take the absolute value to get the dimensional diagnosis floating drop value, set the dimensional diagnosis floating drop threshold, when the dimensional diagnosis floating drop value is greater than or equal to the dimensional diagnosis floating drop threshold, increase the number of abnormal floating drops by one, sum and average all abnormal floating drops to get the abnormal floating drop sum number SKL, sum and average all dimensional diagnosis floating drop values ​​to get the dimensional diagnosis floating drop mean EW, use the formula The diagnostic sequence value Rg of the pulse dimension data is obtained, where y1 is the average dimension diagnostic index coefficient, y2 is the abnormal floating drop and number coefficient, and y3 is the dimension diagnostic floating drop mean coefficient. All pulse dimension data are sorted from large to small according to the value of the diagnostic sequence value, and then the patient's pulse dimension data diagnostic order is generated.

9. A remote diagnosis and treatment system based on a pulse simulator according to claim 2, characterized in that: Set the remote diagnosis and treatment threshold. When the remote diagnosis and treatment value is greater than or equal to the remote diagnosis and treatment threshold, mark the patient as a pulse diagnosis and treatment patient, obtain the basic patient information of the pulse diagnosis and treatment patient and the simulated pulse signal of the pulse simulator, and register the pulse diagnosis and treatment patient to the remote diagnosis and treatment doctor's terminal. When the remote diagnosis and treatment value is less than the remote diagnosis and treatment threshold, no processing will be performed.

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