91 results about "Electrical impedance tomography" patented technology

The invention provides a dynamic lung compliance monitoring method based on electrical impedance tomography, and the method comprises the steps: obtaining an electrical impedance signal and pressure-volume curve data, recording a time sequence signal of lung tissue in a dynamic ventilation process through a synchronous collection device, and obtaining an original multi-dimensional data set; aiming at the second feature set, eliminating redundant parameters by applying a feature screening mechanism, and evaluating the importance of each feature in different breathing stages through an information gain algorithm to obtain a third feature set; constructing a dynamic compliance monitoring model through the weighted feature set, and fitting a lung compliance change trend by using a support vector regression algorithm to obtain a real-time prediction result; and according to the updated prediction result, evaluating the improvement degree of the calculation efficiency, and judging whether the real-time performance meets clinical requirements or not by recording the model operation time and the resource occupancy rate so as to obtain final monitoring output.

The invention discloses a head space positioning method, device and system based on electrical impedance tomography, and the method comprises the steps: constructing a corresponding three-dimensional model according to the basic parameters of a flexible electrode cap, and carrying out the finite element meshing, and obtaining a three-dimensional mesh model; performing electric field distribution calculation on sampling points of the three-dimensional grid model according to a preset calculation rule to obtain corresponding touch electrode response information; generating a sensitive field matrix corresponding to the sampling points and the electrode pairs in the flexible electrode cap according to the touch electrode response information; performing projection matching according to the initial voltage data of the electrode pair and the sensitive field matrix to obtain projection matching information; and performing model training according to the projection matching information and the tensile deformation data of the flexible electrode cap to obtain a voltage feature-space coordinate mapping relation, and analyzing the induced voltage data of the electrode pair to obtain corresponding target coordinate information. According to the method, the voltage change of the flexible electrode cap is obtained and analyzed to obtain the coordinate information, and the positioning accuracy and stability are improved.

The invention relates to a petroleum polluted soil polycyclic aromatic hydrocarbon migration path simulation experiment system, which comprises a main reaction cabin, a mechanical arm collaborative operation module, a multi-mode sensing module, a whole natural environment regulation and control module and an edge intelligent decision-making platform, an annular magnetic suspension track is arranged at the top of the main reaction cabin, and a soil sample chamber is arranged at the bottom of the main reaction cabin; the multi-modal sensing module comprises an EIT (electrical impedance tomography) module, an LIBS (laser-induced breakdown spectroscopy) module and a terahertz time-domain spectroscopy module and is used for measuring global conductivity distribution of soil in a soil sample chamber, inverting the porosity of the soil sample and a pollutant concentration field in pore water, analyzing the concentration of carbon, hydrogen and oxygen elements of pollutants and specifically detecting polycyclic aromatic hydrocarbon molecules; the edge intelligent decision-making platform interacts with the multi-mode sensing module, the full-natural-environment regulation and control module and the mechanical arm collaborative operation module to actively adjust system parameters, and repair intervention is carried out on soil body degradation. And automatic preparation of the polluted soil can be realized, and migration monitoring under different practical engineering application working conditions can be realized.

The invention discloses a reverse osmosis membrane concentration polarization layer thickness prediction method and device based on electrical impedance tomography, and relates to the technical field of membrane process nondestructive monitoring, and the method comprises the following steps: constructing a simulation model based on an electrode array membrane filtration sensor; virtual media with different conductivities are arranged on the surface of the membrane, a simulation conductivity image is reconstructed through a conjugate gradient least square algorithm and a sensitivity matrix, and a neural network is improved through known conductivity training; and reconstructing an actually measured conductivity image by an actually measured boundary voltage data set, predicting a membrane surface conductivity estimated value by using the trained improved neural network, and performing concentration polarization layer thickness mapping. A conductivity image with a conductivity label is generated through numerical simulation, so that the problem that the thickness of the concentration polarization layer is difficult to calibrate is solved, then a neural network is improved through training so that the truth value of the conductivity can be predicted according to the conductivity image, and interpretable mapping of the thickness of the concentration polarization layer is carried out in combination with a membrane mass transfer theory. The thickness of the concentration polarization layer can be subjected to online lossless quantitative detection.

The invention relates to the technical field of intelligent nursing, in particular to an electrical impedance tomography-based pressure sore risk perception and prevention control system, which comprises an EIT signal acquisition module, an impedance trend grading module, a risk area judgment module, a bed body intervention control module and an intervention feedback regulation module. According to the invention, through an electrical impedance imaging principle, fine distinguishing of body surface and superficial tissue physiological states of a patient is realized, multi-region impedance signals are continuously collected and dynamically integrated, local tissue perfusion changes and abnormal stress trends are accurately mapped, high-risk regions are automatically identified and classified, bed body action intervention is triggered in real time, and an intervention effect is dynamically tracked; according to the method, intervention parameters are cooperatively adjusted, the response logic and the intervention rhythm of each region are gradually improved, intelligent risk judgment and closed-loop adaptive intervention are completed, individuation, initialization and process data traceability in a nursing scene are promoted, and adaptive response aiming at complex illness conditions and variable nursing requirements is supported.

The invention discloses an electrical impedance cancer detection method based on frequency domain information enhancement. The method comprises the following steps: S1, acquiring an electrical impedance signal in the body of a patient through an electrical impedance imaging technology; s2, converting the signal into frequency domain representation by using discrete cosine transform, and performing frequency domain enhancement; s3, inputting the features subjected to frequency domain enhancement into the model, and processing the features subjected to frequency domain enhancement in combination with frequency domain information and a global dependency relationship to obtain a global feature matrix; and S4, inputting the global feature matrix into a classifier for cancer detection, and giving a corresponding detection result. According to the method, the time domain signals are subjected to frequency domain conversion, the features subjected to frequency domain enhancement are input into the network model, the global matrix features are obtained by combining the frequency domain information and the global dependency relationship, the global matrix features are input into the classifier for cancer detection, the robustness of the frequency domain data is improved, and the application effect of the electrical impedance signals in cancer detection is enhanced.

The invention relates to the technical field of bridge health monitoring, in particular to a bridge support corrosion current field imaging monitoring method and system, and the method comprises the steps: presetting a matrix type electrochemical sensor on a support steel plate, and collecting the inductance data of a collector at a sampling frequency of 0.1-0.5 Hz; ohmic resistance drift caused by temperature is eliminated through adaptive quantum Kalman filtering, and a resistance-current density distribution diagram is constructed; constructing a current density distribution diagram of the cross section of the support by adopting a back propagation electrical impedance tomography technology; when the corrosion rate exceeds 0.15 mm / year, an early warning system is triggered, the bearing capacity attenuation rate of the support is calculated, and the support is guided to be replaced; a topological separation technology of a multi-dimensional state space and quantum heuristic adaptive parameter optimization effectively eliminate temperature interference; through current field topology reconstruction and multi-source data fusion, the imaging precision is improved; the quantitative relation between the corrosion rate and bearing capacity attenuation of the support is established, and a scientific basis is provided for bridge maintenance.

The invention discloses an angle identification method and device for data enhancement of a thin film bending sensor, and belongs to the field of deep learning. The invention provides an electrical impedance tomography (EIT) inspired angle identification method for data enhancement of a thin film bending sensor, which comprises the following steps of: arranging a series of metal electrodes on the edge of a microstructure etching pattern to detect impedance values pairwise; therefore, the output signal of the thin film sensor is enhanced into a feature vector reflecting the impedance value distribution condition, and finally angle prediction is carried out based on the feature vector through a deep learning network. According to the invention, the impedance change on the thin film bending sensor can be monitored and analyzed more accurately, and the angle identification performance of the bending sensor is greatly improved.

The invention discloses a thoracic cavity three-dimensional electrical impedance tomography method and thoracic cavity three-dimensional electrical impedance tomography equipment. The method comprises the following steps: acquiring a three-dimensional point cloud of the appearance of a chest area of a testee to establish a three-dimensional chest model; carrying out equipment self-inspection and checking the bonding condition of the electrode; generating a determined excitation signal and injecting the excitation signal into the testee; acquiring a voltage signal of each electrode; separating EIT and ECG signals and filtering the EIT and ECG signals; according to a three-dimensional thoracic cavity model of the testee, performing positive problem calculation on the voltage signal to obtain the potential of each electrode of the three-dimensional thoracic cavity model; and performing three-dimensional reconstruction by adopting a single-step Gaussian Newton method to obtain a lung ventilation change electrical impedance imaging graph. According to the method, the three-dimensional thoracic cavity model of the testee is constructed, the positive problem solution is performed on the voltage signal, and the image reconstruction is further performed, so that the real-time high-precision three-dimensional dynamic imaging of the thoracic cavity of the testee can be completed, and the imaging accuracy is high.

The invention discloses a dam anti-seepage body integrity detection method based on an artificial power supply. Comprising the following steps: injecting a broadband excitation current signal into a dam anti-seepage body through a multi-frequency program control constant current source; a modular distributed electrode array is adopted to collect and obtain voltage data of the surface of the dam anti-seepage body in real time; high signal-to-noise ratio voltage data is obtained by adopting filtering processing and a digital phase-locked amplification technology; carrying out three-dimensional inversion calculation by adopting an improved electrical impedance tomography algorithm, and reconstructing an internal conductivity distribution image of the dam anti-seepage body; analyzing, identifying and positioning defects through a deep learning model; and constructing an electro-seepage coupling inversion model, converting the internal conductivity distribution image based on the dam anti-seepage body into permeability coefficient distribution, and generating an integrity evaluation report of the dam anti-seepage body. Compared with a traditional detection method, the method is high in detection precision, wide in application range and high in detection efficiency, and a brand new technical means is provided for evaluating the health state of the dam seepage-proofing body.

This invention provides a permanent antistatic PC material preparation system, comprising a mixing unit, an extrusion granulation unit, and an injection molding unit connected in sequence. The injection molding unit includes a barrel, a screw assembly rotatably disposed within the barrel, and an ERT sensor disposed at a nozzle at the end of the barrel. The ERT sensor includes an electrode array for online acquisition of electrical impedance tomography (EIT) data of the melt passing through the nozzle. The screw assembly includes a screw spindle with a longitudinally penetrating internal heat conduction oil channel. This internal heat conduction oil channel is connected to an external temperature control system via a connector. One section of the barrel is a compression section. A segmented thermal response sleeve is fitted around the outer periphery of the screw spindle within the compression section. The outer surface of the thermal response sleeve is provided with an outer peripheral conveying spiral. The thermal response sleeve responds to changes in the fluid temperature within the internal heat conduction oil channel by generating radial expansion displacement, thereby dynamically adjusting the compression ratio by changing the effective root diameter of the screw assembly within the compression section.

1. Name of the product in this design: Electrical impedance tomography (EIT) imaging system. 2. Application of this design: This design is used in electrical impedance tomography (EIT) imaging. 3. The key design features of this product are the overall shape of the electrical impedance tomography (EIT) imaging device. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The invention relates to the technical field of medical instruments, and particularly discloses a bladder function training guide and control system and method based on a multi-modal sensor, and the system comprises an integrated sensing module which monitors the body surface pressure of a bladder area through a pressure sensor array, obtains the geometric parameters of the bladder in combination with an ultrasonic probe, and transmits the parameters to a central processing module; and meanwhile, conductivity data of liquid in the bladder is acquired by using an impedance tomography technology. The bladder parameter inference module is fused with multi-source data to calculate real-time bladder wall tension and limit capacity to construct a personalized tension-capacity model. The urination demand evaluation module calculates a urination demand value based on the real-time tension, the model parameters, and the limit capacity. And the training plan optimization module is used for dynamically adjusting the initial training scheme according to the urination demand of the day. And the training guide and control module is used for executing the optimization plan and monitoring in real time, and triggering an acousto-optic vibration reminding or urethral catheterization device when a required value reaches a threshold value. The system realizes intelligent and personalized guidance and control of bladder function training through multi-modal data fusion and closed-loop control.

The application discloses an electrode ring and an electrical impedance imaging system for electrical impedance imaging. The electrode ring comprises a metal ring, a filler, an elastic fabric, a plurality of electrodes and a plurality of electrode lines, wherein the metal ring can adjust its diameter in a circular structure; the filler is arranged between the metal ring and the elastic fabric; the elastic fabric covers the metal ring, the filler and the plurality of electrodes; the plurality of electrode lines are wrapped between the filler and are led out as an electrode belt after being gathered together and are connected with an external electrical impedance imaging system; the plurality of electrodes are fixed on the surface of the elastic fabric in an equidistance manner, each electrode is connected by a corresponding electrode line, and the electrodes are not connected with each other. The electrode ring designed in the application can freely stretch and shrink in different limb diameter ranges, solves the problem of unfixed electrode spacing in the existing electrical impedance tomography electrode technology, and improves the wearing comfort and the stability of signal acquisition.

The invention discloses a non-intrusive sewage pH measuring method based on an electrical impedance tomography technology, which comprises the following steps of: based on an electromagnetic field theory, acquiring a sewage boundary electric signal through the electrical impedance tomography technology, establishing theoretical correlation between pH and electrode potential by combining a Nernst equation, constructing a constitutive equation, and finally, inverting a pH value by measuring the boundary electric signal, so as to measure the pH value of the sewage. Therefore, a measurement mode which does not need to intrude into a pipeline and avoids pollution and interference is realized, the defects that a traditional electrode is fragile and difficult to miniaturize, and an optical fiber sensor is easily disturbed by the environment and is complex in high-precision assembly are overcome, the influence of the complex environment of a water body is avoided, and the measurement and calculation precision of the pH is improved.

The present invention discloses a cardiac region localization method based on electrical impedance tomography technology, belonging to the field of electrical impedance tomography technology, which comprises the following steps: collecting EIT data, and dividing into a localization group and a control group; reconstructing the EIT data to obtain an EIT time series signal map; processing each pixel in the EIT time series signal map to obtain a time series signal intensity map of each pixel; performing standard deviation normalization calculation on the time series signal intensity of each pixel to obtain a time series signal intensity distribution map, selecting the pixel point where the highest intensity value is located as the central position of the cardiac region of interest, and calculating the phase difference between each pixel position and the central position; obtaining the cardiac region localization results of the localization group and the control group according to the phase difference and the time series signal intensity map; comparing the results of the localization group and the control group, and determining the final cardiac localization region after verification, which no longer relies on simple signal intensity threshold division, can expand the clinical application scenarios of EIT, and further enhances the non-invasive superiority of EIT technology.

The invention relates to the technical field of grounding grid fault diagnosis, and provides a grounding grid fault diagnosis method, which comprises the following steps: S1, building a corrosion fault diagnosis model according to an electric network theory method, iteratively solving the corrosion fault diagnosis model by adopting a seasonal optimization algorithm SOA, obtaining resistance change multiplied speed of each branch in a grounding grid, and determining a corroded branch or region; s2, based on the determined corroded branch circuit or region, injecting current through a grounding down lead of the power equipment, performing finite element analysis on the corroded branch circuit or region by utilizing an electrical impedance tomography (EIT) technology, and reversely deducing conductivity distribution to generate a two-dimensional chromatographic image; and S3, based on the resistance change multiplied speed of each branch and the generated two-dimensional chromatographic image, determining the specific position and corrosion degree of the corrosion fault of the grounding grid in the soil environment through a preset threshold value and a chromatographic gradient. The method aims to make full use of the advantages of respective technologies and make up for the defects of the technologies, so that the high efficiency and accuracy of grounding grid corrosion fault detection are realized.

Systems and methods for generating a finite element model (FEM) of current flow in an anatomical human forearm are disclosed. The disclosed FEM may assist in determining optimal stimulation parameters in electrical stimulation systems for achieving movement of paralyzed limbs or enhancement of able limbs. This model will allow users to determine which muscle groups are receiving stimulation under different parameters. Systems and methods which leverage electrical impedance tomography (EIT) for autonomous recalibration following garment donning are also disclosed. The method may comprise performing an EIT measurement across an electrode array of an electrode garment and constructing an anatomical model based on the EIT measurement. Next, one or more alignment variations may be estimated based on an alignment variation model. Finally, the electrode array is adjusted, automatically or manually, to accommodate the alignment variations using an alignment adjustment function.

The present invention discloses an electrical impedance monitoring device, system and method for nematode movement behavior, wherein: a microfluidic layer and a pneumatic channel layer are bonded to form a double-layer structure, and then tightly fixed to a circuit board with nylon screws. An electrode array with a concentric circle structure is provided on the circuit board for realizing electrical impedance tomography monitoring of nematodes; the microfluidic layer includes a culture monitoring chamber, a nematode transition channel, etc., for long-term culture and circulation monitoring of nematodes; the pneumatic channel layer includes a gas inlet, a gas passage, etc., for applying air pressure to squeeze the upper wall of the microfluidic layer to form a thin film valve, thereby closing the microfluidic layer channel. Through the above-mentioned monitoring device, the nematodes are controlled to circulate between the culture monitoring chamber and the nematode transition channel, and electrical impedance tomography monitoring and long-term culture of the nematodes are completed. The device and method have a simple structure and are easy to integrate, and can realize culture and non-optical real-time imaging monitoring of nematodes throughout their life cycle.

The application discloses a brain injury identification method and an identification system. The identification system identifies the injury of a patient according to the identification method. The identification method comprises the following steps: firstly, the electrical impedance tomography (EIT) of the brain of the patient is performed to obtain the EIT image of the brain of the patient; then, the region with abnormal resistivity distribution in the EIT image of the brain is taken as a reference for scanning of a near-infrared spectrometer, and a scanning path of the near-infrared spectrometer is planned; finally, the near-infrared spectrometer is scanned along the scanning path, and the lesion range and the lesion type are determined according to the obtained near-infrared spectral data. The electrodes need not be arranged on the whole head of the patient, and the automatic and rapid identification of the lesion range and the nature of the brain injury is realized.

The invention discloses an electrical impedance tomography method based on parameter optimization and boundary clustering, which combines penalty functions of two regularization algorithms Tikhonov and TV for application, proposes that a particle swarm algorithm is used for regularization parameter optimization of the combined penalty functions, and takes an image quality index (AL) as a fitness value of the particle swarm algorithm, so as to determine an optimal regularization parameter, and finally to obtain the electrical impedance tomography based on the parameter optimization and boundary clustering. The conductivity is obtained through a Newton iteration method, in order to further remove the artifacts, a boundary object B (artifacts) of the target is obtained through a Niblack algorithm, deep retrieval is conducted on the boundary object B of the target through a boundary clustering algorithm, all background pixels A are obtained, and the final conductivity distribution can be obtained. Simulation and actual measurement results show that the image reconstructed by the paper method can more accurately reflect the position information of the target object in the electric field, artifacts are effectively inhibited, and the reconstruction effect is improved.

Embodiments of the present techniques provide a tactile sensor, a method for making a tactile sensor, and a system for using a tactile sensor to obtain information about a contact on the tactile sensor. The tactile sensor comprises a multilayer structure which is flexible and stretchable and may be termed a sensor skin. Electrodes are attached physically and electrically to the edges of the multilayer structure and electrical impedance tomography EIT techniques are used to obtain information from the electrodes to determine a location and other information about a contact on the multilayer structure.

The invention relates to a multi-respiration mechanical state monitoring method and device for electrical impedance tomography. The method comprises the following steps: acquiring an analog physiological signal of a user based on a multi-channel acquisition unit; performing data processing and analog-to-digital conversion on the analog physiological signal to obtain a digital physiological signal; the digital physiological signals are packaged, and obtained packaged digital physiological data are sent to an electrical impedance tomography device, so that the electrical impedance tomography device performs conjoint analysis on the breathing state of the user based on the electrical impedance tomography data collected by the electrical impedance tomography device and the received packaged digital physiological data. A breathing state analysis result is obtained; compared with the prior art, the technical scheme of the invention breaks through the limitation of a specific communication protocol by collecting, processing, packaging and transmitting the analog physiological signal, realizes the universal joint monitoring of the electrical impedance tomography equipment and the respirator, and improves the comprehensiveness and accuracy of the subsequent breathing state analysis.

1. The name of this design product: Chest electrical impedance tomography (EIT) branch line. 2. Purpose of this design product: This design product is a chest electrical impedance tomography (EIT) branch line. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the design points: three-dimensional picture.

The invention discloses an electrical impedance tomography detection method for a dike termite channel, which relates to dike detection and comprises the following steps: vertically burying an electrode array in a dike, establishing a three-dimensional geometric model in finite element analysis software, and obtaining a dike internal conductivity distribution diagram by adopting a dynamic electrical impedance tomography algorithm. And extracting a suspected ant cave feature position based on the conductivity distribution diagram, carrying out field verification on the suspected ant cave feature position, and confirming the existence and position of the ant cave. According to the method, the dynamic electrical impedance tomography algorithm is combined with finite element model construction, so that three-dimensional visual detection of the ant-suffering channel in the dam is realized, the limitation that a detection area cannot be fully covered by traditional manual drilling is solved, and the space precision and range integrity of ant-suffering positioning are improved.

The application provides an electric field tomography detection system and method with adjustable electrode plate distance, which comprises a cylindrical shielding layer (1), a plate electrode array (2), a control module (3), a sinusoidal excitation voltage module (4), a multi-channel electronic switch module (5), a stepping motor transmission module (6), a voltage detection module (7), a Fourier phase extraction module (8) and an electrical impedance tomography module (9). The stepping motor transmission module (6) can accurately move the electrode plate to a suitable position, and the Fourier phase extraction module (8) is used for fast Fourier transform to simplify the phase offset calculation in the electric field tomography system. The application solves the problem of fixed electrode plate in the electric field tomography detection system, and the high accuracy of the stepping motor can accurately adjust the positions of the plate electrode array and the target object, which is beneficial to signal detection.

The invention discloses a skin tumor three-dimensional electrical impedance tomography method and device and a storage medium. The method comprises the following steps: acquiring a skin surface boundary voltage signal by using a planar electrode, and generating a space virtual electrode equivalent voltage through nonlinear mapping from a planar electrode domain to a space virtual electrode domain; mapping the voltage into a two-dimensional voltage feature map through bilinear interpolation, inputting the feature as prior information into a three-dimensional electrical impedance imaging reconstruction network, and performing depth matching inversion on the body area conductivity distribution based on a sliding window SwinUNet network to obtain a three-dimensional conductivity image; constructing a skin tissue finite element model, and generating a simulation data set; and training nonlinear mapping by adopting the simulation data set and verifying the depth matching inversion performance. The method can still keep stable reconstruction quality under uncertain conditions such as poor electrode contact, channel loss and skin structure change, has high robustness and adaptability, and has good clinical application value.

The method includes extracting a lung volume waveform from an electrical impedance tomography device. The method further includes extracting at least one of a flow waveform and a pressure waveform. The method also includes aligning the lung volume waveform and at least one of the flow waveform and the pressure waveform with respect to time. The method further includes comparing the lung volume waveform and at least one of the flow waveform and the pressure waveform. The method also includes determining whether an asynchronous breathing event has occurred based on comparing the lung volume waveform and at least one of the flow waveform and the pressure waveform. The method further includes classifying the asynchronous breathing event. The method also includes providing a warning identifying the asynchronous breathing event. The system includes a receiver, a processor, and a memory device configured to execute the method.

The invention relates to an electrical impedance tomography system for controlling hydrocephalus shunting and a storage medium, the electrical impedance tomography system for controlling hydrocephalus shunting comprises a brain impedance evaluation model module, an electrical impedance data acquisition module, a control module, a pressure-adjustable valve and a group of electrodes annularly distributed on the head of a human body; the brain impedance evaluation model module is used for generating a local area standard impedance range based on the physiological characteristic parameters of the patient; the local regions are a plurality of regions divided by the brain impedance evaluation model module into the whole brain; the electrical impedance data acquisition module is used for acquiring real-time local impedance sent by the electrodes; the real-time local impedance corresponds to a local area where the hydrocephalus position of the patient is located; and the control module is used for adjusting the pressure value of the pressure-adjustable valve based on the real-time local impedance and the local area standard impedance range. According to the invention, the problem of poor timeliness of hydrocephalus shunting is solved.

The invention discloses a pulmonary embolism identification and evaluation method based on electrical impedance tomography of a pulsation method, and belongs to the technical field of medical treatment. The method comprises the following steps: acquiring an electrical impedance signal through an electrode array surrounding the chest, separating a ventilation signal from a perfusion signal by using a preset algorithm, calculating a matching index, an image matching degree, a perfusion deficiency index and a ventilation deficiency index, judging a pulmonary embolism risk level by combining a blood flow to ventilation volume ratio, and generating a visual report; the method further comprises the steps of dynamic treatment effect monitoring, data processing, bedside monitoring, preparation before signal acquisition and the like. Noninvasive bedside identification of pulmonary embolism is achieved, the invasiveness, radiation risk and transfer limitation of traditional examination are avoided, the treatment effect can be evaluated in real time to assist scheme adjustment, diagnosis and treatment convenience and universality are improved, and reasonable allocation of medical resources and diagnosis and treatment standardization are assisted.