Morphological detection method and wearable device for superficial aneurysms

Abstract

The present invention provides a morphological detection method and wearable device for superficial aneurysms. The method comprises: Step 1: constructing and training a diameter-to-neck ratio prediction neural network model; Step 2: acquiring synchronized ECG and PPG signals from a subject, and extracting characteristic parameters from these signals, including maximum blood flow velocity, blood flow velocity variation, blood flow rate, and blood pressure; Step 3: generating a feature vector for the subject based on the extracted characteristic parameters, and inputting this feature vector into the trained diameter-to-neck ratio prediction neural network model to obtain the subject's diameter-to-neck ratio.

Description

Technical Field

[0001] The present invention relates to the technical field of aneurysm detection, and in particular to a morphological detection method and wearable device based on superficial aneurysms. Background Art

[0002] Arterial disease carries a high risk of death or disability, and aneurysms are a readily detectable symptom of this disease. Aneurysms are pathological, dilated lesions caused by the impact of blood flow on the blood vessel wall, leading to bulging of the arterial wall. These lesions are closely related to a variety of congenital and acquired causes. A variety of morphological parameters can be used to assess the risk of aneurysm rupture, such as aneurysm location, aspect ratio, diameter-to-neck ratio, length-to-width ratio, and size ratio. The diameter-to-neck ratio and size ratio are particularly closely associated with rupture. If an aneurysm is not discovered promptly, rupture can lead to extensive subarachnoid hemorrhage. Without prompt treatment, this can result in severe brain damage, posing a serious threat to human life. Therefore, the ability to monitor changes in aneurysm morphological parameters in real time is of great clinical significance.

[0003] Currently, clinical aneurysm detection methods include CT angiography for initial screening and the gold standard, digital subtraction angiography (DSA). These techniques can assess the activity of the aneurysm wall's inflammatory response and, by examining the mechanisms of aneurysm growth and rupture, can assess the stability of intracranial aneurysms. However, these methods have several drawbacks: 1) Patients may experience varying degrees of allergic and adverse reactions to contrast agents, depending on their individual constitutions. Severe cases may result in anaphylactic shock. Furthermore, since contrast agents are excreted through the kidneys, they can cause renal damage, leading to contrast-induced nephropathy. 2) Only highly trained medical personnel can perform these procedures skillfully. Improper operation can cause injury, leading to bleeding and infection at the puncture site, and in severe cases, vascular rupture, respiratory and cardiac arrest, and other serious conditions. 3) These techniques, particularly DSA, are expensive, and monitoring the progression of aneurysms requires hospitalization for regular angiography, making them unsuitable for routine patient monitoring. Summary of the Invention

[0004] In response to the above-mentioned problems existing in existing aneurysm detection methods, the present invention provides a morphological detection method and wearable device for superficial aneurysms.

[0005] In a first aspect, the present invention provides a morphological detection method for superficial aneurysms based on ECG and PPG, comprising:

[0006] Step 1: Build and train a neural network model for diameter-to-neck ratio prediction;

[0007] Step 2: Acquire the subject's synchronized ECG signal and PPG signal, and extract characteristic parameters based on the ECG signal and PPG signal, wherein the characteristic parameters include maximum blood flow velocity, blood flow velocity change, blood flow rate, and blood pressure;

[0008] Step 3: Generate a feature vector of the subject based on the extracted feature parameters, and input the feature vector into the trained diameter-to-neck ratio prediction neural network model to obtain the diameter-to-neck ratio of the subject.

[0009] Furthermore, the training of the diameter-to-neck ratio prediction neural network model in step 1 specifically includes:

[0010] Obtain feature vectors of multiple subjects according to steps 2 and 3;

[0011] measuring the neck diameter ratios of the plurality of subjects using digital subtraction angiography;

[0012] For each subject, the corresponding feature vector and neck-diameter ratio constitute a training data pair;

[0013] The diameter-to-neck ratio prediction neural network model is trained using a plurality of training data.

[0014] Furthermore, in step 2, extracting the maximum blood flow velocity according to the ECG signal and the PPG signal specifically includes:

[0015] For ECG and PPG signals collected at the same time, the R peak of the ECG signal is marked as the starting point, and the main wave peak of the PPG signal is marked as the end point. The time difference between the starting point and the end point is calculated and used as the pulse wave propagation time. PWTT ;

[0016] According to the pulse wave propagation time PWTT and propagation distance According to formula (5), the maximum blood flow velocity is obtained :

[0017]

[0018] In a second aspect, the present invention provides a wearable device for superficial aneurysm morphology detection based on ECG and PPG, comprising a signal acquisition module and a human-computer interaction module; the human-computer interaction module comprises a data processing module and a morphology prediction module;

[0019] The signal acquisition module is used to collect the synchronized ECG signal and PPG signal of the subject and send the collected signals to the human-computer interaction module;

[0020] The data processing module is used to extract characteristic parameters and generate characteristic vectors based on the ECG signal and the PPG signal; the characteristic parameters include maximum blood flow velocity, blood flow velocity change, blood flow rate and blood pressure;

[0021] The morphology prediction module is used to construct and train a diameter-to-neck ratio prediction neural network model; and input the subject's feature vector into the trained diameter-to-neck ratio prediction neural network model to obtain the subject's diameter-to-neck ratio.

[0022] Furthermore, the signal acquisition module includes a MAX86150 chip.

[0023] Furthermore, in the process of collecting PPG signals, the signals are collected based on the modified Lambert-Beer law shown in formula (6);

[0024]

[0025] in, is the intensity of the incident light entering the human body, is the intensity of the outgoing light, is the hemoglobin concentration, is the equivalent optical path length, is the scattering factor, is the extinction coefficient, is the interference factor.

[0026] Furthermore, the data processing module is also used to preprocess the acquired synchronized ECG signal and PPG signal, and the preprocessing process includes dual signal time alignment, noise filtering, baseline drift removal and invalid signal segment elimination.

[0027] Furthermore, the human-computer interaction module also includes a data transmission module; the data transmission module is used to upload the acquired ECG signal and PPG signal, the extracted characteristic parameters and the predicted neck diameter ratio to the server, so that the server can store the data in the corresponding personal database.

[0028] Beneficial effects of the present invention:

[0029] (1) Non-invasive measurement: By synchronously collecting ECG and PPG signals, physiological and pathological information can be extracted from the signals for tumor morphology detection, avoiding many risks that may be caused by invasive methods.

[0030] (2) Simple operation method: Compared with invasive and complex operations, the present invention can ensure real-time and continuity, and can often reduce costs when long-term monitoring is required. The use of a linear regression neural network model can ensure the computing speed of the monitoring model.

[0031] (3) Wearable: The measurement location is more flexible and the measurement scenarios are more extensive. It can be designed into a miniaturized wearable product to achieve daily monitoring of the disease, obtain feedback information in a timely manner, and ensure the patient's life safety.

[0032] (4) Various measurement methods: The present invention is suitable for monitoring superficial aneurysms in various parts of the human body. It uses a reflective photoelectric sensor, which is more convenient and comfortable than a transmissive device. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 The AC and DC components of the PPG signal provided in the embodiment of the present invention;

[0034] Figure 2 A schematic flow chart of a method for morphological detection of superficial aneurysms provided by an embodiment of the present invention;

[0035] Figure 3 A schematic diagram of an inlet velocity fitting curve provided by an embodiment of the present invention;

[0036] Figure 4 Provided in the embodiment of the present invention: (a) is a velocity streamline diagram of a tumor-bearing artery; (b) is a velocity streamline diagram of a normal artery;

[0037] Figure 5 A linear regression curve estimation diagram provided by an embodiment of the present invention;

[0038] Figure 6 A schematic diagram of PWTT measurement provided in an embodiment of the present invention;

[0039] Figure 7 A schematic diagram of the structure of a wearable device for superficial aneurysm morphology detection based on ECG and PPG provided in an embodiment of the present invention;

[0040] Figure 8 A schematic diagram of the collection location provided by an embodiment of the present invention;

[0041] Figure 9 A structural diagram of a reflective photoelectric sensor provided in an embodiment of the present invention;

[0042] Figure 10 This is the light absorption coefficient of hemoglobin provided in the embodiment of the present invention. DETAILED DESCRIPTION

[0043] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly described below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0044] Before introducing the technical solution of the present invention, the professional terms involved in the present invention are explained as follows:

[0045] Blood flow velocity: refers to the linear velocity of a particle in the blood flowing in the blood vessel. According to the continuity equation of fluid, blood flow velocity is proportional to the blood flow rate and inversely proportional to the cross-sectional area of ​​the blood vessel;

[0046] PPG signal: When light source illuminates human tissue, part of the light intensity is absorbed by human tissue. The absorption of light by human muscles, bones, venous blood, etc. is roughly constant, while arterial blood will show continuous periodic pulsation with the beating of the heart. The volume of blood will also change accordingly, causing the absorption degree of arterial blood to change periodically with the pulsation of arterial blood. The photoelectric converter receives the light emitted from the human body and converts it into an electrical signal, forming a periodic signal with the same heartbeat cycle. The PPG signal components are as follows: Figure 1 The signal reflecting the arterial blood pulsation caused by the change in light absorption due to the change in blood vessel volume is called the PPG signal.

[0047] ECG signal: A physiological signal that reflects cardiovascular activity by recording the timing and intensity of the electrical signal sequence that triggers the heartbeat. This signal can be obtained by placing multiple electrodes on the skin to capture electrical impulses in the heart.

[0048] Example 1

[0049] Based on the above, if Figure 2 As shown, an embodiment of the present invention provides a morphological detection method for superficial aneurysms based on ECG and PPG, comprising the following steps:

[0050] S101: Build and train a neural network model for diameter-to-neck ratio prediction;

[0051] S102: Acquire synchronized ECG and PPG signals of the subject, and extract characteristic parameters based on the ECG and PPG signals, wherein the characteristic parameters include maximum blood flow velocity, blood flow velocity variation, blood flow rate, and blood pressure;

[0052] S103: Generate a feature vector of the subject according to the extracted feature parameters, input the feature vector into a trained diameter-to-neck ratio prediction neural network model, and obtain the diameter-to-neck ratio of the subject.

[0053] In this embodiment, the four physiological parameters of maximum blood flow velocity, blood flow velocity variation, blood flow rate, and blood pressure are used as relevant parameters for predicting the neck-diameter ratio. These parameters are selected through correlation analysis. The research and analysis process is as follows:

[0054] Computational fluid dynamics (CFD) was used to analyze the hemodynamics of eleven groups of carotid aneurysms. Three-dimensional models of the vessels were cut and smoothed, then imported into the ANSYS Fluent tool to create volumetric grid points for CFD simulation. The total number of grid points in each model ranged from 1,000,000 to 2,500,000.

[0055] The movement of blood flow in the human cardiovascular system follows the general laws of fluid mechanics, namely the law of conservation of mass, the law of conservation of momentum and the law of conservation of energy.

[0056] The mass conservation equation:

[0057]

[0058] Momentum equation:

[0059]

[0060] Energy equation:

[0061]

[0062] Under the premise of following the three conservation laws, we supplement the boundary conditions and initial conditions. Assume that the blood vessels are rigid and have no slip, and the blood is an isotropic and incompressible Newtonian fluid with a constant density ( =1060kg / m 3 ) and viscosity ( =0.00441pa / s).

[0063] (1) The relationship between the diameter-to-neck ratio and the maximum blood flow velocity, as well as the maximum flow velocity difference between the healthy artery model and the case artery model, was studied by solving the Navior-Stokes equation.

[0064] The actual case blood flow velocity is used as a data fitting curve and used as the inlet velocity setting to make the inlet velocity of each model have a typical flow velocity waveform. The inlet velocity fitting curve is as follows: Figure 3 shown.

[0065] The convergence criterion is that the velocity vector residual is less than 1×10 -4 Because the Reynolds number of the carotid artery is less than 2000, a laminar flow model was used for calculations. The time step was set to 0.001 s, and the entire heartbeat cycle (lasting 0.6 s) was discretized. Two heartbeat cycles were collected from each case vessel for subsequent measurement and analysis.

[0066] The simulation results were imported into CFD-Post for post-processing, and the hemodynamic parameters at the systolic peak of the second cycle of the arterial model were obtained and visualized, as shown in Figure 2. Figure 4 The velocity streamline diagram shown in . Figure 4 It can be seen that the fluid flow rate increases at the distal end of the tumor.

[0067] The experimental results collected the maximum blood flow velocity at a fixed location at the distal end of the carotid bifurcation aneurysm for each normal model and case model. Statistical analysis was performed using IBM SPSS Statistics 27 software. A paired-sample T-test was performed comparing the velocities in the normal and case groups. The Sig (two-tailed) value was 0.000426, less than 0.01, rejecting the null hypothesis and demonstrating statistical significance. This indicates a significant difference between the two paired samples. Specifically, when the detection location remains unchanged, the carotid aneurysm increases the maximum blood flow velocity within a certain distance, as shown in Table 1.

[0068] Table 1 Paired sample T test calculation results

[0069]

[0070] (2) To further explore the geometric variation of the velocity difference between the two groups, a correlation analysis was conducted between the velocity difference and the tumor diameter-to-neck ratio. Since the data were paired continuous variables, followed a normal distribution, and the two groups of data were linearly related, the Pearson correlation analysis method was used. The results show that the correlation coefficient between the velocity difference and the tumor diameter-to-neck ratio was 0.845, and the significance (Sig) was less than 0.001, indicating that the degree of velocity reduction by the tumor was highly significantly positively correlated with the tumor diameter-to-neck ratio. The results are shown in Table 2.

[0071] Table 2 Results of bivariate Pearson correlation analysis

[0072]

[0073] (3) In order to determine the causal relationship between velocity difference and tumor diameter-to-neck ratio, regression analysis was used to establish a regression model between variables, and the linear fitting effect of the model was evaluated. 2The value is about 0.714, and the test significance (Sig) of the regression model and regression coefficient are both less than 0.001, which is statistically significant, as shown in Table 3 and Figure 5 As shown. Finally, the diameter-to-neck ratio Ar Speed ​​difference D v The model between is expressed by formula (4):

[0074]

[0075] Table 3 Linear regression calculation results

[0076]

[0077] Based on the conclusions drawn from the above analysis, the maximum blood flow velocity, blood flow velocity change, and blood flow rate can be used as important parameters to evaluate the aneurysm diameter-to-neck ratio and monitor the expansion of internal carotid artery aneurysms, and to establish a relationship model between aneurysm morphological parameters and physiological parameters.

[0078] (4) When the measurement location and pulse wave conduction distance remain unchanged, pulse wave velocity and blood pressure show a good correlation. The results of Pearson correlation analysis show that pulse wave velocity is positively correlated with hypertension grade, and pulse wave velocity can usually be equivalent to blood flow velocity. Therefore, the aneurysm diameter-to-neck ratio is positively proportional to blood pressure within a certain range, and blood pressure can be used as one of the important indicators for evaluating the diameter-to-neck ratio.

[0079] Furthermore, in this embodiment, training the diameter-to-neck ratio prediction neural network model specifically includes: obtaining feature vectors of multiple subjects in accordance with step S102 and step S103; obtaining the neck-to-diameter ratios of the multiple subjects using digital subtraction angiography; for each subject, the corresponding feature vector and neck-to-diameter ratio form a training data pair; and using multiple training data to train the diameter-to-neck ratio prediction neural network model.

[0080] Furthermore, since the propagation speed of electrical signals is faster than the flow rate of blood, there is a certain delay between the time when the main wave peak of the PPG signal appears and the pulse moment of the ECG signal. Based on this, the following method is used to extract the maximum blood flow velocity from the ECG signal and the PPG signal: for the ECG signal and PPG signal collected at the same time, the R wave peak of the ECG signal is marked as the starting point, and the main wave peak of the PPG signal is marked as the end point. The time difference between the starting point and the end point is calculated and used as the pulse wave propagation time PWTT ,like Figure 6 As shown; according to the pulse wave propagation time PWTT and propagation distance According to formula (5), the maximum blood flow velocity is obtained :

[0081]

[0082] Example 2

[0083] In order to implement the above method, an embodiment of the present invention provides a wearable device for superficial aneurysm morphology detection based on ECG and PPG, such as Figure 7 As shown, it includes: a signal acquisition module and a human-computer interaction module; the human-computer interaction module includes a data processing module and a morphology prediction module;

[0084] The signal acquisition module is used to collect the synchronized ECG signal and PPG signal of the subject and send the collected signals to the human-computer interaction module;

[0085] The data processing module is used to extract characteristic parameters and generate characteristic vectors based on the ECG signal and the PPG signal; the characteristic parameters include maximum blood flow velocity, blood flow velocity change, blood flow rate and blood pressure;

[0086] The morphology prediction module is used to construct and train a diameter-to-neck ratio prediction neural network model; and input the subject's feature vector into the trained diameter-to-neck ratio prediction neural network model to obtain the subject's diameter-to-neck ratio.

[0087] Preferably, in this embodiment, the signal acquisition module uses an acquisition kit based on the MAX86150 chip to synchronously acquire ECG signals and PPG signals. The signal acquisition module is placed at the bifurcation of the internal carotid artery, such as Figure 8 shown.

[0088] Specifically, the MAX86150 chip integrates both an ECG sensor and a PPG sensor. ECG signals are collected using two electrodes. The PPG acquisition unit utilizes a reflective structure, using near-infrared light with a wavelength of approximately 840nm as the incident light source. The incident light source is placed against the neck. Due to changes in blood flow and volume in the internal carotid artery, the reflected light signal is received by the photoelectric sensor and converted into an electrical signal.

[0089] Among them, the reflective structure is to place the light source and the receiving device on the same side of the position to be measured. The light source on the same side emits light of a specific wavelength, and the photoelectric sensor on the same side receives the scattered light after being absorbed by the blood. The structure is as follows Figure 9 At the same time, near-infrared light with a wavelength of about 840nm can ensure that the absorption of the collected light by oxygenated hemoglobin and reduced hemoglobin can remain stable, as shown in Figure 2. Figure 10 shown.

[0090] Preferably, the data processing module is further configured to preprocess the acquired synchronized ECG and PPG signals, including time alignment of the two signals, noise filtering, baseline drift removal, and invalid signal segment rejection. Correspondingly, the feature extraction module extracts feature parameters based on the preprocessed ECG and PPG signals.

[0091] It is understandable that the human-computer interaction module and the signal acquisition module can be located on the same device or on different devices. When located on different devices, Bluetooth communication can be used between the signal acquisition module and the human-computer interaction module. For example, when the computing resources on the device where the signal acquisition module is located cannot meet the data processing requirements of the human-computer interaction module, the human-computer interaction module can be located on the mobile terminal side, and the mobile terminal can be used to control the signal acquisition module to collect signals and return them. After signal processing and feature extraction in the mobile terminal, the trained diameter-to-neck ratio prediction neural network model is used for calculation and display.

[0092] Furthermore, to facilitate subsequent analysis of personal data, the human-computer interaction module also includes a data transmission module, which uploads the acquired ECG and PPG signals, extracted feature parameters, and predicted neck-to-diameter ratio to a server via the internet. The server then stores the data in a corresponding personal database. This server can also interface with the hospital's server, allowing doctors to review user data.

[0093] Furthermore, in the process of collecting PPG signals, the signals are collected based on the modified Lambert-Beer law shown in formula (6);

[0094]

[0095] in, is the intensity of the incident light entering the human body, is the intensity of the outgoing light received by the receiving end, is the hemoglobin concentration, is the equivalent optical path length, is the scattering factor (used to indicate the effect of human tissue on the optical path length after light scattering occurs). is the extinction coefficient, is the interference factor.

[0096] Specifically, the hemoglobin in human blood responds to incident light according to the Lambert-Beer law, which states that the intensity of light absorbed by absorbing substances, solvents, and the like is an exponential function of the concentration of the absorbing substance and the optical path length. After light emitted by an LED light source passes through the skin's surface and enters the human body, a portion of the light is transmitted through the body, while the remaining portion is reflected and received by a photosensor. However, in the human body, tissues such as blood, bone, and muscle scatter the incident light, resulting in the output light at the receiving end not being the ideal intensity obtained after absorption by the absorbing substance, but rather the intensity obtained after multiple scattering. Based on this, the modified Lambert-Beer law can be obtained, as shown in Formula (6).

[0097] Combining the light scattering theory with the Lambert-Beer law results in a modified Lambert-Beer law. The modified Lambert-Beer law more accurately reflects the relationship between the incident and outgoing light intensities when light enters human tissue. This can be further used to collect photoplethysmographic signals using reflective equipment, leading to a more accurate aneurysm monitoring model.

[0098] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A morphological detection method for superficial aneurysms based on ECG and PPG, characterized in that: include: Step 1: Build and train a neural network model for diameter-to-neck ratio prediction; Step 2: Acquire the subject's synchronized ECG signal and PPG signal, and extract characteristic parameters based on the ECG signal and PPG signal, wherein the characteristic parameters include maximum blood flow velocity, blood flow velocity change, blood flow rate, and blood pressure; Step 3: Generate a feature vector of the subject based on the extracted feature parameters, and input the feature vector into the trained diameter-to-neck ratio prediction neural network model to obtain the diameter-to-neck ratio of the subject; The training of the diameter-to-neck ratio prediction neural network model in step 1 specifically includes: Obtain feature vectors of multiple subjects according to steps 2 and 3; measuring the neck diameter ratios of the plurality of subjects using digital subtraction angiography; For each subject, the corresponding feature vector and neck-diameter ratio constitute a training data pair; The diameter-to-neck ratio prediction neural network model is trained using a plurality of training data.

2. The method for morphological detection of superficial aneurysms based on ECG and PPG according to claim 1, characterized in that: In step 2, the maximum blood flow velocity is extracted according to the ECG signal and the PPG signal, specifically including: For ECG and PPG signals collected at the same time, the R peak of the ECG signal is marked as the starting point, and the main wave peak of the PPG signal is marked as the end point. The time difference between the starting point and the end point is calculated and used as the pulse wave propagation time. PWTT ; According to the pulse wave propagation time PWTT and propagation distance According to formula (5), the maximum blood flow velocity is obtained : 。 3. A wearable device for superficial aneurysm morphology detection based on ECG and PPG, characterized by: The ECG and PPG-based morphology detection method for superficial aneurysms as claimed in claim 1 comprises a signal acquisition module and a human-computer interaction module; the human-computer interaction module comprises a data processing module and a morphology prediction module; The signal acquisition module is used to collect the synchronized ECG signal and PPG signal of the subject and send the collected signals to the human-computer interaction module; The data processing module is used to extract characteristic parameters and generate characteristic vectors based on the ECG signal and the PPG signal; the characteristic parameters include maximum blood flow velocity, blood flow velocity change, blood flow rate and blood pressure; The morphology prediction module is used to construct and train a diameter-to-neck ratio prediction neural network model; and input the subject's feature vector into the trained diameter-to-neck ratio prediction neural network model to obtain the subject's diameter-to-neck ratio.

4. The wearable device for superficial aneurysm morphology detection based on ECG and PPG according to claim 3, characterized in that: The signal acquisition module includes a MAX86150 chip.

5. The wearable device for superficial aneurysm morphology detection based on ECG and PPG according to claim 4, characterized in that: In the process of collecting PPG signals, the signals are collected based on the modified Lambert-Beer law shown in formula (6); in, is the intensity of the incident light entering the human body, is the intensity of the outgoing light, is the hemoglobin concentration, is the equivalent optical path length, is the scattering factor, is the extinction coefficient, is the interference factor.

6. The wearable device for superficial aneurysm morphology detection based on ECG and PPG according to claim 3, characterized in that: The data processing module is further used to preprocess the acquired synchronized ECG signal and PPG signal, and the preprocessing process includes dual signal time alignment, noise filtering, baseline drift removal and invalid signal segment elimination.

7. The wearable device for superficial aneurysm morphology detection based on ECG and PPG according to claim 3, characterized in that: The human-computer interaction module also includes a data transmission module; The data transmission module is used to upload the acquired ECG signal and PPG signal, the extracted characteristic parameters and the predicted neck diameter ratio to the server, so that the server can store the data in the corresponding personal database.

Images