Disclosure of Invention
In view of the above, the invention provides a puncture needle tube early warning system and method based on electromagnetic signals, which aim to solve the problems that in the prior art, a puncture monitoring system is low in sensing precision and response speed, and is lack of adaptation to individual physiological characteristics and intelligent recognition of abnormal states, and accurate control and real-time early warning of a puncture process in a complex tissue structure are difficult to realize.
The invention provides a puncture needle tube early warning method based on electromagnetic signals, which comprises the following steps:
Acquiring user information data, displacement data of a puncture needle tube in the urethra, primary resistance change data and secondary resistance change data;
acquiring preset resistance data and preset displacement data of the puncture needle tube in the urethra according to the user information data and a preset resistance model;
Determining whether the operation is abnormal according to the relation between the primary resistance change data and the secondary resistance change data and the preset resistance data or the relation between the displacement data and the preset displacement data, wherein:
if the operation is determined to be abnormal, the alarm processing is carried out based on the audible and visual alarm device, and the puncturing operation is terminated.
Further, when obtaining the user information data, the method includes:
acquiring age information of a user, a urethral surface image and/or a urethral perspective image of the user;
Performing image preprocessing on the urethral surface image and/or the urethral perspective image, wherein the image preprocessing comprises denoising processing, graying processing, contrast enhancement processing, image edge detection and image segmentation processing;
extracting image features in the image-preprocessed urethral surface image and/or the urethral perspective image, wherein the image features comprise urethral contour edges, texture distribution, gray gradient change and image contrast image feature data;
based on the image features and the age information of the user, the urethral wall thickness and tissue softness of the user are determined.
Further, determining the urethral wall thickness and tissue softness of the user based on the image features and the age information of the user comprises:
calculating a urethral wall thickness based on urethral profile edge information in the image features;
Based on the texture distribution and gray gradient changes in the image features, the softness of the urethral tissue is evaluated in combination with the age information of the user.
Further, when obtaining preset resistance data and preset displacement data of the puncture needle tube in the urethra according to the user information data and the pre-configured resistance model, the method comprises the following steps:
establishing puncture characteristic data of the user according to age information, urethral wall thickness and tissue softness of the user;
according to the puncture characteristic data and the resistance model, the preset resistance data and the preset displacement data of the puncture needle tube in the urethra are determined according to the matching result:
When the puncture characteristic data is matched with any characteristic data in the resistance model, determining puncture resistance data and puncture displacement data corresponding to the characteristic data as preset resistance data and preset displacement data of the puncture needle tube in the urethra;
When the matching between the puncture characteristic data and the characteristic data in the resistance model is inconsistent, the characteristic vector between the characteristic data and the characteristic data close to the puncture characteristic data are acquired, and the preset resistance data and the preset displacement data of the puncture needle tube in the urethra are determined according to the relation between the characteristic vector and the characteristic data close to the puncture characteristic data.
Further, when determining preset resistance data and preset displacement data of the puncture needle tube in the urethra according to the relation between the characteristic vector and characteristic data close to the puncture characteristic data, the method comprises the following steps:
Acquiring a puncture feature vector between puncture feature data and the feature data which are close to each other, and acquiring a vector ratio between the puncture feature vector and the feature vector;
Determining an adjustment coefficient according to the relation between the vector difference value and a first preset vector ratio and a second preset vector ratio which are preset:
when the vector ratio is lower than a first preset vector ratio, determining that the adjustment coefficient is L1;
When the vector ratio is higher than or equal to the first preset vector ratio and the vector ratio is lower than the second preset vector ratio, determining to adjust to L2;
When the vector ratio is higher than or equal to a second preset vector ratio, determining that the adjustment system is L3;
Wherein the first preset vector ratio is lower than the second preset vector ratio, and L1< L2< L3;
when the adjustment system is determined to be Li and i=1, 2 and 3, the characteristic data close to the puncture characteristic data are adjusted according to the adjustment coefficient Li, and the puncture resistance data and the puncture displacement data which are adjusted are determined to be preset resistance data and preset displacement data of the puncture needle tube in the urethra.
Further, when the drag model is preconfigured, the drag model comprises:
Acquiring thickness data of each urethra, tissue softness of each tissue part, puncture resistance change data of a puncture needle tube and puncture displacement depth when users of different ages puncture the urethra;
Establishing resistance correlation according to the age of each user, the urethral thickness data during urethral penetration, the tissue softness of a tissue part, the penetration resistance change data and penetration displacement depth of the penetration needle tube during pushing;
acquiring Euclidean distance between each resistance association type, and establishing a distance matrix;
according to the distance matrix, iterative clustering is carried out among the resistance correlation formulas, and each resistance correlation formula after clustering is obtained;
establishing a linear shaft between the resistance associated formulas according to the magnitude relation between the resistance associated formulas and the magnitude relation;
And establishing a resistance model according to the linear axes among the resistance correlations.
Further, determining whether the operation is abnormal according to the relationship between the primary resistance change data and the secondary resistance change data and the preset resistance data or the relationship between the displacement data and the preset displacement data, includes:
Determining whether the operation is abnormal or not according to the relation between the primary resistance change data and the preset resistance data:
when the primary resistance change data is lower than or equal to the preset resistance data, determining that no abnormality exists in operation, and determining whether the abnormality exists in operation according to the relationship between the displacement data and the preset displacement data and the relationship between the secondary resistance change data and the preset resistance data;
when the primary resistance change data is higher than the preset resistance data, it is determined that the operation is abnormal.
Further, determining whether the operation is abnormal according to the relation between the displacement data and the preset displacement data includes:
When the displacement data exceeds the preset displacement data, determining that the operation is abnormal;
when the displacement data does not exceed the preset displacement data, determining whether the operation is abnormal or not according to the relation between the secondary resistance change data and the preset resistance data.
Further, determining whether the operation is abnormal according to the relation between the secondary resistance change data and the preset resistance data includes:
When the secondary resistance change data is lower than the preset resistance data, determining that no abnormality exists in the operation;
when the secondary resistance change data is higher than or equal to the preset resistance data, it is determined that the operation is abnormal.
Compared with the prior art, the method has the beneficial effects that the puncture path and the puncture depth are judged to be in a normal state or not by comparing and analyzing the actual puncture data with the pre-established resistance model and the displacement model. Compared with the existing puncturing mode which only depends on doctor experience or vision assistance, the method greatly improves the objectivity and controllability of the operation process. In addition, the invention adopts a combination mode of electromagnetic sensing and mechanical sensing, thereby realizing high-precision monitoring of the pushing process of the puncture needle tube. The electromagnetic induction module can acquire the space displacement information of the needle tube in the urethra in real time, and the resistance sensor can dynamically capture the mechanical feedback of the tissue to the puncture needle tube. By combining the two types of sensing data and combining a resistance trend model driven by big data, the invention can carry out intelligent identification and matching analysis on primary resistance (such as penetrating through the urethral wall) and secondary resistance (such as entering into target tissues) which occur in the puncturing process. It is worth emphasizing that when the system detects that the current resistance data and the preset model deviate abnormally (such as excessively high resistance, abnormal duration or missing key resistance stage), an audible and visual alarm mechanism can be immediately triggered to prompt the doctor that the current puncture state is at risk, and the puncture operation is automatically stopped when necessary, so that further tissue injury or misoperation is avoided. The intelligent early warning mechanism remarkably enhances the safety protection capability of the system, is beneficial to reducing medical risks and guaranteeing the safety of patients. Finally, the invention has good adaptability and expansibility on the basis of improving the puncture precision. By continuously accumulating historical data in the operation process and optimizing the resistance model, the self-learning and intelligent evolution of the system can be realized, so that the system is better suitable for individual requirements of patients with different age ranges and different anatomical structures, and the individual adaptability and clinical universality of the puncture operation are further improved.
On the other hand, the application also provides a puncture needle tube early warning system based on electromagnetic signals, which comprises:
The acquisition module is configured to acquire user information data, displacement data of the puncture needle tube in the urethra, primary resistance change data and secondary resistance change data;
The analysis module is electrically connected with the acquisition module and is configured to acquire preset resistance data and preset displacement data of the puncture needle tube in the urethra according to user information data and a preset resistance model, and the analysis module is further configured to determine whether the operation is abnormal according to the relation between the primary resistance change data and the secondary resistance change data and the preset resistance data or the relation between the displacement data and the preset displacement data;
And the sound-light alarm module is respectively and electrically connected with the analysis module and the puncture needle tube, and is configured to carry out alarm processing and terminate the puncture operation when the analysis module determines that the operation is abnormal.
It can be appreciated that the puncture needle tube early warning system and method based on electromagnetic signals in the above embodiments of the present invention have the same beneficial effects and are not repeated.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art. It should be noted that, without conflict, the embodiments of the present invention and features of the embodiments may be combined with each other. The invention will be described in detail below with reference to the drawings in connection with embodiments.
As shown in fig. 1, in some embodiments of the present application, a puncture needle tube early warning method based on electromagnetic signals is provided, including:
And step S100, acquiring user information data, displacement data of the puncture needle tube in the urethra, primary resistance change data and secondary resistance change data.
The method comprises the steps of obtaining age information of a user, obtaining an image of the urethral surface and/or a urethral perspective image of the user, carrying out image preprocessing on the image of the urethral surface and/or the urethral perspective image, wherein the image preprocessing comprises denoising processing, graying processing, contrast enhancement processing, image edge detection and image segmentation processing, extracting image features in the image of the urethral surface and/or the urethral perspective image after the image preprocessing, wherein the image features comprise image feature data of urethral contour edges, texture distribution, gray gradient change and image contrast, and determining urethral wall thickness and tissue softness of the user according to the image features and the age information of the user.
Specifically, when determining the thickness of the urethral wall and the softness of the tissue of the user according to the image characteristics and the age information of the user, the method comprises the steps of calculating the thickness of the urethral wall based on the urethral outline edge information in the image characteristics, and evaluating the softness of the urethral tissue based on the texture distribution and the gray gradient change in the image characteristics and the age information of the user.
It will be appreciated that by combining image processing with individualized data, the structural features and tissue properties of the urethra are precisely analyzed, thereby providing individualized physiological parameter support for the lancing process. Specifically, firstly, through collecting the urethral surface image and/or the urethral perspective image of the user, the quality of the image and the identifiability of a key structure are improved by utilizing various image preprocessing technologies such as denoising, graying, contrast enhancement, edge detection, image segmentation and the like, and an accurate data basis is provided for subsequent feature extraction. Secondly, by extracting key features in the image, such as the contour edge of the urethra, texture distribution, gray gradient change, image contrast and the like, the morphology and internal tissue structure of the urethra can be accurately depicted. The urethral profile edge information reflects the morphological and thickness changes of the urethral wall, and the texture distribution and the gray gradient reveal the microstructure differences of the tissues, and the characteristics together provide rich visual information for evaluating the softness of the tissues. Finally, the extracted image features are combined with age information of the user, and the urethral wall thickness and the tissue softness are calculated and evaluated through an algorithm model. Age is used as an important physiological parameter affecting tissue elasticity and thickness, and can effectively assist interpretation of image characteristics, so that accuracy and individual adaptability of evaluation are improved. The technical principle realizes that from multi-mode images and individual characteristics, a mode of fusion of image processing and physiological parameters is utilized to provide scientific basis for personalized configuration of puncture paths and resistance models, and further improves accuracy and safety of the puncture process.
It can be seen that the definition and the feature recognizability of the image can be greatly improved through image preprocessing operations (such as denoising, graying, contrast enhancement, edge detection and image segmentation), the recognition error caused by poor image quality is effectively reduced, and the accuracy and the stability of the feature extraction of the subsequent image are ensured. The processing procedure improves the adaptability to complex anatomical structures and improves the robustness of overall detection. And secondly, in the image feature extraction stage, multidimensional information such as urethral outline edges, texture distribution, gray gradient change, image contrast and the like is focused, so that depth perception of urethral wall morphology and tissue state is realized. The method not only has higher local resolving power, but also can realize accurate assessment of the thickness of the urethral wall and the softness of the tissue through the joint analysis of the image characteristics and the physiological indexes (such as age). Moreover, the image features are customized and interpreted by combining the age information of the user, so that the recognition capability of the model on the tissue characteristic differences of different age groups is effectively improved, and the evaluation result is more in line with clinical practice. For example, elderly users may have calcification or atrophy of tissue, while young users may have softer tissue, and such individual differences can be effectively quantified and fed back by this method, thereby providing a basis for personalized puncture path planning.
Step 200, acquiring preset resistance data and preset displacement data of the puncture needle tube in the urethra according to the user information data and the pre-configured resistance model.
The method comprises the steps of establishing puncture characteristic data of a user according to age information of the user, urethral wall thickness and tissue softness, matching the puncture characteristic data with the resistance model, determining the preset resistance data and the preset displacement data of the puncture needle tube in the urethra according to a matching result, determining puncture resistance data and puncture displacement data corresponding to the characteristic data when the matching between the puncture characteristic data and any characteristic data in the resistance model is consistent, determining characteristic vector and characteristic data close to the puncture characteristic data when the matching between the puncture characteristic data and each characteristic data in the resistance model is inconsistent, and determining preset resistance data and preset displacement data of the puncture needle tube in the urethra according to the relation between the characteristic vector and the characteristic data close to the puncture characteristic data.
The method comprises the steps of obtaining a puncture characteristic vector between puncture characteristic data and approaching characteristic data, obtaining a vector ratio between the puncture characteristic vector and the characteristic vector, determining an adjustment coefficient according to the relation between a vector difference and a first preset vector ratio and a second preset vector ratio which are preset, determining the adjustment coefficient as L1 when the vector ratio is lower than the first preset vector ratio, determining the adjustment as L2 when the vector ratio is higher than or equal to the first preset vector ratio and the vector ratio is lower than the second preset vector ratio, determining an adjustment system as L3 when the vector ratio is higher than or equal to the second preset vector ratio, determining the adjustment system as L1< L2< L3 when the vector ratio is higher than or equal to the second preset vector ratio, and determining the puncture resistance and the displacement of the puncture needle tube to the puncture characteristic data according to the characteristic data which are approaching to the adjustment coefficient as Li=1, 2, and determining the puncture resistance and the displacement data after the puncture needle tube is positioned in the urethra.
The pre-configured resistance model comprises the steps of obtaining urethral thickness data, tissue softness of tissue parts and puncture needle tube puncture resistance change data and puncture displacement depth of puncture needle tubes when users of different ages perform urethral puncture, establishing resistance correlation according to the ages of the users, the urethral thickness data, the tissue softness of the tissue parts and the puncture needle tube puncture resistance change data and puncture displacement depth of the puncture needle tubes when the users are pushed, obtaining Euclidean distances between the resistance correlation and establishing a distance matrix, performing iterative clustering on the resistance correlation according to the distance matrix and obtaining clustered resistance correlation, establishing a linear axis between the resistance correlation according to the size relation between the resistance correlation and the size relation, and establishing a resistance model according to the linear axis between the resistance correlation.
It can be appreciated that the user-specific puncture feature data is constructed by collecting the user's age information, urethral wall thickness, tissue softness, and other key physiological parameters. The characteristic data reflect the physiological structure difference and the tissue mechanics characteristic of the individual, and are quantitative expression of the actual environment in the urethra of the user. Age information is taken as an important factor affecting tissue elasticity and thickness, and by combining the urethral wall morphology and texture characteristics obtained through image processing, the urethral wall thickness and the tissue softness degree can be effectively deduced, so that an important reference is provided for subsequent resistance prediction. And secondly, performing feature matching by using a pre-established resistance model. The model is based on clinical puncture data of a large number of users with different ages, and covers puncture resistance curves and corresponding displacement information under the conditions of different urethral wall thicknesses and tissue softness. In the matching process, if the puncture characteristic data of the user is highly consistent with certain typical characteristic data in the model, the resistance and displacement data corresponding to the characteristic are directly adopted, so that the calculation efficiency and accuracy are ensured. If the matching has a difference, calculating the ratio of the user puncture feature vector to the similar feature vector in the model, and quantitatively reflecting the similarity of the user puncture feature vector and the similar feature vector through mathematical operation of a vector space. Based on the magnitude of the vector ratio, a plurality of preset threshold intervals are set, and different adjustment coefficients are respectively corresponding to the preset threshold intervals. The adjustment coefficient reflects the expansion or contraction of the preset resistance and displacement values, and ensures that preset data are more fit with the individual differences of users. For example, when the vector ratio is low, the deviation between the user characteristic and the model characteristic is larger, the adjustment coefficient is smaller than 1 to reduce the resistance and displacement preset value, otherwise, when the vector ratio is high, the adjustment coefficient larger than 1 is adopted to moderately amplify the preset parameter, so that the dynamic self-adaptive adjustment of the data is realized. The mechanism effectively avoids preset data deviation caused by physiological difference, and improves accuracy and safety of puncture prediction. Finally, the construction of the resistance model is based on a complex multidimensional data processing flow. Urethral penetration data is collected for users of different ages, including urethral wall thickness, tissue softness, resistance changes measured during penetration, and needle cannula penetration depth. And constructing a distance matrix by calculating Euclidean distance between each resistance association, and clustering similar resistance curves by using an iterative clustering algorithm to extract a typical resistance mode. Based on the clustering results, a linear axis of resistance association is established, and then a resistance model with stronger generalization capability is established. The model can reflect the diversity and complexity of resistance change, and realize effective simulation and prediction of different user puncture processes.
It can be seen that by combining the age information, the urethral wall thickness and the tissue softness of the user, personalized puncture characteristic data are accurately established, and personalized presetting of resistance and displacement in the puncture process is realized. The matching mechanism based on the individual characteristics and the pre-configured resistance model effectively improves the accuracy of preset resistance and displacement data, thereby enhancing the safety and reliability of puncture operation. In addition, the puncture characteristic data and a plurality of characteristic data in the resistance model are compared and dynamically adjusted, so that the device can flexibly adapt to physiological differences of users. The adoption of the multistage adjustment coefficient finely adjusts preset data according to the vector ratio, ensures that reasonable and nearly real resistance and displacement estimation can be obtained even if the matching is not completely consistent, and greatly reduces the misjudgment risk and the misoperation probability. Finally, the pre-constructed resistance model can reflect the resistance change rules under different ages and tissue conditions through clustering and linear axis modeling based on a large amount of clinical data. The model provides scientific basis for puncture early warning, so that effective coverage of complex individual differences can be realized in practical application, the accurate control and intelligent early warning capability of the puncture process are further improved, and the success rate of operation and the safety of patients are improved.
Step S300, determining whether the operation is abnormal according to the relation between the primary resistance change data and the secondary resistance change data and the preset resistance data or the relation between the displacement data and the preset displacement data.
The method comprises the steps of determining whether operation is abnormal according to the relation between primary resistance change data and secondary resistance change data and preset resistance data or the relation between displacement data and preset displacement data, determining whether operation is abnormal according to the relation between the primary resistance change data and the preset resistance data, determining whether operation is abnormal when the primary resistance change data is lower than or equal to the preset resistance data, determining whether operation is abnormal according to the relation between the displacement data and the preset displacement data, determining whether operation is abnormal according to the relation between the secondary resistance change data and the preset resistance data, and determining whether operation is abnormal when the primary resistance change data is higher than the preset resistance data.
The method comprises the steps of determining whether the operation is abnormal according to the relation between displacement data and preset displacement data, wherein the step of determining whether the operation is abnormal or not comprises the steps of determining whether the operation is abnormal when the displacement data exceeds the preset displacement data, and determining whether the operation is abnormal or not according to the relation between secondary resistance change data and preset resistance data when the displacement data does not exceed the preset displacement data.
Specifically, according to the relation between the secondary resistance change data and the preset resistance data, determining whether the operation is abnormal comprises determining that the operation is not abnormal when the secondary resistance change data is lower than the preset resistance data and determining that the operation is abnormal when the secondary resistance change data is higher than or equal to the preset resistance data.
It can be understood that by comparing a plurality of groups of key data acquired in real time in the puncturing process with preset standards, a multi-level and multi-dimensional abnormality recognition mechanism is established. The key principle of the method is that the primary resistance change data is used as a first judgment threshold, if the resistance data does not exceed a preset range, the displacement data and the secondary resistance change data are further introduced to carry out auxiliary judgment, and a step-by-step judgment flow from 'coarse screening' to 'fine judgment' is realized. The method improves the response speed and greatly enhances the accuracy and the robustness of judgment. In the first step, primary resistance change data generated in the process of pushing the puncture needle tube are obtained in real time and compared with preset resistance data established according to individual characteristics of a user. When the data does not exceed the safety threshold, namely is lower than or equal to the preset resistance data, the current puncture environment is initially considered to be in a normal state. The design can effectively avoid false alarms caused by slight fluctuation, and simultaneously ensure sensitive response to sudden high-resistance conditions. If the primary resistance change data is in the safety range, the difference between the current displacement data and the individuation preset displacement data is continuously evaluated. This step is an effective monitoring of penetration path and depth control. When the actual displacement exceeds the preset upper displacement limit, the puncture is possibly prompted to exceed a safe physiological area, for example, the puncture passes through a target tissue boundary or enters a high-risk tissue area, and at the moment, abnormal judgment is triggered and an alarm is timely sent out to prevent the operation from further proceeding. If the displacement data does not exceed the preset range, introducing secondary resistance change data to carry out final verification. The secondary resistance reflects the stability and continuity of the resistance change trend in the puncturing process, and belongs to finer dynamic signal criteria. When the secondary resistance change data is obviously higher than the preset resistance data, the problems that the tissue structure is suddenly changed, the needle head encounters high-density tissue or mechanical clamping stagnation occurs in the puncturing process can be described, and therefore final judgment of an abnormal state is triggered. The layer judges and complements detection blind areas for instantaneous change and local fluctuation of resistance, and the comprehensive recognition capability is effectively improved. In summary, the technical scheme realizes the dynamic monitoring and high-precision abnormality identification of the puncture operation process by the combined judgment of the three-dimensional parameters (primary resistance, secondary resistance and displacement), and has the technical advantages of high identification sensitivity, low misjudgment rate, strong adaptability and the like. Particularly in a complex or individual difference obvious clinical environment, the method can obviously improve the safety and accuracy of puncture operation, effectively reduce the incidence rate of complications in operation, and has good application prospect and clinical practical value.
Step 400, if the operation is abnormal, the alarm processing is performed based on the audible and visual alarm device, and the puncturing operation is terminated.
In the above embodiment, the puncture path and depth are judged to be in a normal state by comparing the actual puncture data with the pre-established resistance model and displacement model. Compared with the existing puncturing mode which only depends on doctor experience or vision assistance, the method greatly improves the objectivity and controllability of the operation process. In addition, the invention adopts a combination mode of electromagnetic sensing and mechanical sensing, thereby realizing high-precision monitoring of the pushing process of the puncture needle tube. The electromagnetic induction module can acquire the space displacement information of the needle tube in the urethra in real time, and the resistance sensor can dynamically capture the mechanical feedback of the tissue to the puncture needle tube. By combining the two types of sensing data and combining a resistance trend model driven by big data, the invention can carry out intelligent identification and matching analysis on primary resistance (such as penetrating through the urethral wall) and secondary resistance (such as entering into target tissues) which occur in the puncturing process. It is worth emphasizing that when the system detects that the current resistance data and the preset model deviate abnormally (such as excessively high resistance, abnormal duration or missing key resistance stage), an audible and visual alarm mechanism can be immediately triggered to prompt the doctor that the current puncture state is at risk, and the puncture operation is automatically stopped when necessary, so that further tissue injury or misoperation is avoided. The intelligent early warning mechanism remarkably enhances the safety protection capability of the system, is beneficial to reducing medical risks and guaranteeing the safety of patients. Finally, the invention has good adaptability and expansibility on the basis of improving the puncture precision. By continuously accumulating historical data in the operation process and optimizing the resistance model, the self-learning and intelligent evolution of the system can be realized, so that the system is better suitable for individual requirements of patients with different age ranges and different anatomical structures, and the individual adaptability and clinical universality of the puncture operation are further improved.
In another preferred mode based on the above embodiment, as shown in fig. 2, the present embodiment provides a puncture needle tube early warning system based on electromagnetic signals, which includes an acquisition module, an analysis module and an acousto-optic warning module.
The system comprises an acquisition module, an analysis module, an audible and visual alarm module, an analysis module and a puncture needle tube, wherein the acquisition module is configured to acquire user information data, displacement data of the puncture needle tube in a urethra and primary resistance change data and secondary resistance change data, the analysis module is electrically connected with the acquisition module, the analysis module is configured to acquire preset resistance data and preset displacement data of the puncture needle tube in the urethra according to the user information data and a pre-configured resistance model, the analysis module is further configured to determine whether operation is abnormal according to the relation between the primary resistance change data and the secondary resistance change data or the preset resistance data or the relation between the displacement data and the preset displacement data, the audible and visual alarm module is electrically connected with the analysis module and the puncture needle tube respectively, and the audible and visual alarm module is configured to carry out alarm processing and terminate the puncture operation when the analysis module determines that the operation is abnormal.
It can be appreciated that the puncture needle tube early warning system and method based on electromagnetic signals in the above embodiments of the present invention have the same beneficial effects and are not repeated.
It will be appreciated by those skilled in the art that embodiments of the application may be provided as methods, systems, or computer program products. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flowchart and/or block of the flowchart illustrations and/or block diagrams, and combinations of flowcharts and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the above embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the specific embodiments of the present invention without departing from the spirit and scope of the present invention, and any modifications and equivalents are intended to be included in the scope of the claims of the present invention.