Puncture needle tube early warning system and method based on electromagnetic signals

Abstract

The invention relates to the technical field of early warning of puncture needle tubes, and discloses a puncture needle tube early warning system and method based on electromagnetic signals, and the method comprises the steps: obtaining user information data, displacement data of a puncture needle tube in a 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 pre-configured resistance model; according to the relation between the primary resistance change data and the preset resistance data and the relation between the secondary resistance change data and the preset resistance data or the relation between the displacement data and the preset displacement data, whether the operation is abnormal or not is determined, and if it is determined that the operation is abnormal, alarm processing is conducted based on an audible and visual alarm device, and the puncture operation is terminated. According to the invention, real-time identification and intelligent early warning of a puncture abnormal state are realized by fusing user individual information, electromagnetic displacement monitoring and resistance data comparison, so that the accuracy and safety of puncture operation are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of puncture needle tube warning, and more particularly, to an electromagnetic signal-based puncture needle tube warning system and method. Background Art

[0002] In urological clinical operations, urethral puncture is a common interventional technique, often used for operations such as catheter implantation, tissue biopsy, or local treatment. Existing technologies mainly rely on doctors to visually observe the advancement of the puncture needle tube through endoscopes or ultrasonic devices to determine whether it has entered the urethra or the target area. However, this method has certain subjectivity and latency, and cannot reflect the specific position and resistance changes of the needle tube in the tissue in real time and quantitatively, resulting in limited puncture accuracy and increasing the risk of mis-puncture, over-puncture, or omission of the target area.

[0003] Currently, some studies have tried to introduce sensor devices, such as force sensors or displacement sensors, to assist in monitoring relevant physical parameters during the puncture process. However, there are generally problems such as low accuracy of sensing data, slow dynamic response, and lack of combination with individual physiological characteristics, making it difficult to meet the clinical requirements for precise puncture control in complex physiological structures. In addition, most existing systems lack an intelligent recognition and warning mechanism for abnormal states, and cannot timely identify abnormal tissue resistance or behavior deviating from the path during the puncture process, thus unable to effectively avoid tissue damage or intraoperative errors.

[0004] Therefore, there is an urgent need to invent a puncture needle tube warning technology to solve the problems of low sensing accuracy, slow response speed of existing puncture monitoring systems, lack of adaptation to individual physiological characteristics and intelligent recognition of abnormal states, and difficulty in achieving precise control and real-time warning of the puncture process in complex tissue structures. Summary of the Invention

[0005] In view of this, the present invention proposes an electromagnetic signal-based puncture needle tube warning system and method, aiming to solve the problems of low sensing accuracy, slow response speed of existing puncture monitoring systems, lack of adaptation to individual physiological characteristics and intelligent recognition of abnormal states, and difficulty in achieving precise control and real-time warning of the puncture process in complex tissue structures.

[0006] The present invention proposes an electromagnetic signal-based puncture needle tube warning method, including: Obtaining user information data, displacement data of the puncture needle tube in the urethra, primary resistance change data, and secondary resistance change data; According to the user information data and a pre-configured resistance model, obtaining preset resistance data and preset displacement data of the puncture needle tube in the urethra; Determine 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, where: If it is determined that the operation is abnormal, an alarm process is performed based on the acoustic-optic alarm device, and the puncture operation is terminated.

[0007] Further, when obtaining user information data, it includes: Obtain the age information of the user, the surface image of the urethra and / or the fluoroscopic image of the urethra; Perform image preprocessing on the surface image of the urethra and / or the fluoroscopic image of the urethra, where the image preprocessing includes denoising processing, grayscale processing, contrast enhancement processing, image edge detection and image segmentation processing; Extract the image features in the surface image of the urethra and / or the fluoroscopic image of the urethra after image preprocessing, where the image features include image feature data such as the urethral contour edge, texture distribution, gray-scale gradient change and image contrast; Determine the urethral wall thickness and tissue softness of the user according to the image features and the age information of the user.

[0008] Further, when determining the urethral wall thickness and tissue softness of the user according to the image features and the age information of the user, it includes: Calculate the urethral wall thickness based on the urethral contour edge information in the image features; Evaluate the softness of the urethral tissue based on the texture distribution and gray-scale gradient change in the image features, combined with the age information of the user.

[0009] Further, when obtaining the 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, it includes: Establish the puncture feature data of the user according to the age information, urethral wall thickness and tissue softness of the user; Match the puncture feature data with the resistance model, and determine the preset resistance data and preset displacement data of the puncture needle tube in the urethra according to the matching result: When the puncture feature data is consistent with any of the feature data in the resistance model, determine the puncture resistance data and puncture displacement data corresponding to the feature data as the preset resistance data and preset displacement data of the puncture needle tube in the urethra; When the puncture feature data is inconsistent with each of the feature data in the resistance model, obtain the feature vectors between the feature data and the feature data close to the puncture feature data, and determine the preset resistance data and preset displacement data of the puncture needle tube in the urethra according to the relationship between the feature vectors and the feature data close to the puncture feature data.

[0010] Further, when determining the preset resistance data and preset displacement data of the puncture needle tube in the urethra according to the relationship between the feature vector and the feature data close to the puncture feature data, it includes: Obtain the puncture feature vector between the puncture feature data and the close feature data, and obtain the vector ratio between the puncture feature vector and the feature vector; Determine the adjustment coefficient according to the relationship between the vector difference and the pre-configured first preset vector ratio and second preset vector ratio: When the vector ratio is lower than the first preset vector ratio, determine the adjustment coefficient as L1; When the vector ratio is higher than or equal to the first preset vector ratio and lower than the second preset vector ratio, determine the adjustment as L2; When the vector ratio is higher than or equal to the second preset vector ratio, determine the adjustment system as L3; Wherein, the first preset vector ratio is lower than the second preset vector ratio, and L1 < 1 < L2 < L3; When determining that the adjustment system is Li, i = 1, 2, 3, adjust the corresponding puncture resistance data and puncture displacement data of the feature data close to the puncture feature data according to the adjustment coefficient Li, and determine the adjusted puncture resistance data and puncture displacement data as the preset resistance data and preset displacement data of the puncture needle tube in the urethra.

[0011] Further, when pre-configuring the resistance model, it includes: Obtain the urethral thickness data, tissue softness of each tissue part, puncture resistance change data and puncture displacement depth of the puncture needle tube during urethral puncture for users of different ages; Establish a resistance correlation formula according to the age of each user, urethral thickness data during urethral puncture, tissue softness of the tissue part, puncture resistance change data of the puncture needle tube during advancement and puncture displacement depth; Obtain the Euclidean distance between each resistance correlation formula and establish a distance matrix; Perform iterative clustering on each resistance correlation formula according to the distance matrix and obtain each resistance correlation formula after clustering; According to the magnitude relationship between each resistance correlation formula and based on the magnitude relationship, establish a linear axis between each resistance correlation formula; Establish a resistance model according to the linear axis between each resistance correlation formula.

[0012] Further, when 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, it includes: Determine whether the operation is abnormal based on the relationship 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, it is determined that the operation is not abnormal, and based on 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, determine whether the operation is abnormal; When the primary resistance change data is higher than the preset resistance data, it is determined that the operation is abnormal.

[0013] Furthermore, when determining whether the operation is abnormal based on the relationship between the displacement data and the preset displacement data, it includes: When the displacement data exceeds the preset displacement data, it is determined that the operation is abnormal; When the displacement data does not exceed the preset displacement data, determine whether the operation is abnormal based on the relationship between the secondary resistance change data and the preset resistance data.

[0014] Furthermore, when determining whether the operation is abnormal based on the relationship between the secondary resistance change data and the preset resistance data, it includes: When the secondary resistance change data is lower than the preset resistance data, it is determined that the operation is not abnormal; When the secondary resistance change data is higher than or equal to the preset resistance data, it is determined that the operation is abnormal.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: By comparing and analyzing the actual puncture data with the pre-established resistance model and displacement model, it is possible to determine whether the puncture path and depth are in a normal state. Compared with the existing puncture methods that only rely on doctors' experience or visual assistance, this method greatly improves the objectivity and controllability of the operation process. In addition, the present invention adopts a combined method of electromagnetic sensing and mechanical sensing to achieve high-precision monitoring of the advancement process of the puncture needle tube. Among them, the electromagnetic induction module can real-time obtain the spatial displacement information of the needle tube in the urethra, while the resistance sensor can dynamically capture the mechanical feedback generated by the tissue on the puncture needle tube. By fusing these two types of sensing data and combining with the big data-driven resistance trend model, the present invention can intelligently identify and match-analyze the primary resistance (such as penetrating the urethral wall) and secondary resistance (such as entering the target tissue) that occur during the puncture process. It is worth emphasizing that when the system detects that the current resistance data deviates abnormally from the preset model (such as too high resistance, abnormal duration, or missing key resistance stages), it can immediately trigger the sound and light alarm mechanism to prompt the doctor that there is a risk in the current puncture state and automatically terminate the puncture operation when necessary to avoid further tissue damage or operation errors. This intelligent early warning mechanism significantly enhances the safety protection ability of the system, helps to reduce medical risks, and ensures patient safety. Finally, on the basis of improving the puncture accuracy, the present invention also has good adaptability and scalability. By continuously accumulating historical data during the operation process and optimizing the resistance model, the system can achieve self-learning and intelligent evolution, so as to better adapt to the personalized needs of patients of different ages and different anatomical structures, and further improve the individual adaptability and clinical universality of the puncture operation.

[0016] On the other hand, the present application also provides a puncture needle tube warning system based on electromagnetic signals, including: An acquisition module, configured to obtain user information data, displacement data of the puncture needle tube in the urethra, and primary resistance change data and secondary resistance change data; An analysis module, electrically connected to the acquisition module. The analysis module is configured to obtain 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 analysis module is further configured to determine 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; A sound and light alarm module, respectively electrically connected to the analysis module and the puncture needle tube. The sound and light alarm module is configured to perform alarm processing and terminate the puncture operation when the analysis module determines that the operation is abnormal.

[0017] It can be understood that the puncture needle tube warning system and method based on electromagnetic signals in the above embodiments of the present invention have the same beneficial effects and will not be elaborated herein. Brief Description of the Drawings

[0018] By reading the following detailed description of the preferred embodiments, various other advantages and benefits will become clear to those of ordinary skill in the art. The drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present invention. Moreover, throughout the drawings, the same reference numerals are used to represent the same components. In the drawings: Figure 1 is a flowchart of a method for warning a puncture needle tube based on electromagnetic signals provided by an embodiment of the present invention; Figure 2 is a functional block diagram of a warning system for a puncture needle tube based on electromagnetic signals provided by an embodiment of the present invention. Detailed Embodiments

[0019] Hereinafter, exemplary embodiments of the present disclosure will be described in more detail with reference to the drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be fully conveyed to those skilled in the art. It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other. Hereinafter, the present invention will be described in detail with reference to the drawings and in conjunction with the embodiments.

[0020] As Figure 1 shown, in some embodiments of the present application, this embodiment provides a method for warning a puncture needle tube based on electromagnetic signals, including: Step S100, obtaining user information data, displacement data of the puncture needle tube in the urethra, primary resistance change data, and secondary resistance change data.

[0021] Specifically, when obtaining user information data, it includes: obtaining the age information of the user, the surface image of the user's urethra, and / or the fluoroscopic image of the urethra; performing image preprocessing on the surface image of the urethra and / or the fluoroscopic image of the urethra, where the image preprocessing includes denoising processing, grayscale processing, contrast enhancement processing, image edge detection, and image segmentation processing; extracting image features in the surface image of the urethra and / or the fluoroscopic image of the urethra after image preprocessing, where the image features include image feature data such as the urethral contour edge, texture distribution, grayscale gradient change, and image contrast; and determining the urethral wall thickness and tissue softness of the user according to the image features and the age information of the user.

[0022] Specifically, when determining the urethral wall thickness and tissue softness of a user based on image features and the user's age information, it includes: calculating the urethral wall thickness based on the urethral contour edge information in the image features; evaluating the softness of the urethral tissue based on the texture distribution and gray-scale gradient change in the image features in combination with the user's age information.

[0023] It can be understood that by combining image processing with individualized data, the structural features and tissue properties of the urethra are accurately analyzed, thereby providing personalized physiological parameter support for the puncture process. Specifically, first, by collecting the urethral surface image and / or urethral fluoroscopy image of the user, and using various image preprocessing techniques such as denoising, grayscale conversion, contrast enhancement, edge detection, and image segmentation, the quality of the image and the recognizability of key structures are improved, providing an accurate data basis for subsequent feature extraction. Secondly, by extracting key features in the image, such as the urethral contour edge, texture distribution, gray-scale gradient change, and image contrast, the morphology and internal tissue structure of the urethra can be accurately characterized. The urethral contour edge information reflects the morphology and thickness change of the urethral wall, and the texture distribution and gray-scale gradient reveal the subtle structural differences of the tissue. These features together provide rich visual information for evaluating tissue softness. Finally, the extracted image features are combined with the user's age information, and the urethral wall thickness and tissue softness are calculated and evaluated through an algorithm model. As an important physiological parameter affecting tissue elasticity and thickness, age can effectively assist in the interpretation of image features and improve the accuracy and individual adaptability of the evaluation. This technical principle realizes starting from multi-modal images and individual features, and using the method of fusing image processing and physiological parameters to provide a scientific basis for the personalized configuration of the puncture path and resistance model, thereby improving the accuracy and safety of the puncture process.

[0024] It can be seen that through image preprocessing operations (such as denoising, grayscale conversion, contrast enhancement, edge detection, and image segmentation), the clarity and feature recognizability of the image can be significantly improved, the recognition error caused by poor image quality can be effectively reduced, and the accuracy and stability of subsequent image feature extraction can be ensured. This processing process improves the adaptability to complex anatomical structures and enhances the robustness of the overall detection. Secondly, in the image feature extraction stage, multi-dimensional information such as the urethral contour edge, texture distribution, gray-scale gradient change, and image contrast is concerned, so as to achieve a deep perception of the urethral wall morphology and tissue state. This method not only has high local resolution ability, but also can achieve accurate evaluation of the urethral wall thickness and tissue softness through the joint analysis of image features and physiological indicators (such as age). Furthermore, customizing the interpretation of image features by combining user age information effectively improves the model's recognition ability of tissue characteristic differences in different age groups, making the evaluation results more in line with clinical practice. For example, elderly users may have tissue calcification or atrophy, while young users may have softer tissues. Such individual differences can be effectively quantified and fed back through this method, providing a basis for personalized puncture path planning.

[0025] Step S200: According to the user information data and the pre-configured resistance model, obtain the preset resistance data and preset displacement data of the puncture needle tube in the urethra.

[0026] Specifically, when obtaining the 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, it includes: establishing the puncture feature data of the user according to the user's age information, urethral wall thickness, and tissue softness; matching the puncture feature data with the resistance model, and determining the preset resistance data and preset displacement data of the puncture needle tube in the urethra according to the matching result: when the puncture feature data is consistent with any feature data in the resistance model, the corresponding puncture resistance data and puncture displacement data of the feature data are determined as the preset resistance data and preset displacement data of the puncture needle tube in the urethra; when the puncture feature data is inconsistent with each feature data in the resistance model, obtain the feature vectors between each feature data and the feature data close to the puncture feature data, and determine the preset resistance data and preset displacement data of the puncture needle tube in the urethra according to the relationship between the feature vectors and the feature data close to the puncture feature data.

[0027] Specifically, when determining the preset resistance data and preset displacement data of the puncture needle tube in the urethra according to the relationship between the feature vector and the feature data close to the puncture feature data, it includes: obtaining the puncture feature vector between the puncture feature data and the close feature data, and obtaining the vector ratio between the puncture feature vector and the feature vector; determining the adjustment coefficient according to the relationship between the vector difference and the pre-configured first preset vector ratio and second preset vector ratio: when the vector ratio is lower than the first preset vector ratio, the adjustment coefficient is determined to be L1; when the vector ratio is higher than or equal to the first preset vector ratio and lower than the second preset vector ratio, the adjustment is determined to be L2; when the vector ratio is higher than or equal to the second preset vector ratio, the adjustment system is determined to be L3; where the first preset vector ratio is lower than the second preset vector ratio, and L1 < 1 < L2 < L3; when the adjustment system is determined to be Li, i = 1, 2, 3, the puncture resistance data and puncture displacement data corresponding to the feature data close to the puncture feature data are adjusted according to the adjustment coefficient Li, and the adjusted puncture resistance data and puncture displacement data are determined as the preset resistance data and preset displacement data of the puncture needle tube in the urethra.

[0028] Specifically, when pre-configuring the resistance model, it includes: obtaining the urethral thickness data, tissue softness of each tissue part, puncture needle tube puncture resistance change data and puncture displacement depth during urethral puncture for users of different ages; establishing a resistance correlation formula according to the age of each user, urethral thickness data during urethral puncture, tissue softness of the tissue part, puncture needle tube puncture resistance change data and puncture displacement depth during propulsion; obtaining the Euclidean distance between each resistance correlation formula and establishing a distance matrix; performing iterative clustering on each resistance correlation formula according to the distance matrix and obtaining each resistance correlation formula after clustering; establishing a linear axis between each resistance correlation formula according to the magnitude relationship between each resistance correlation formula; and establishing a resistance model according to the linear axis between each resistance correlation formula.

[0029] It is understandable that by collecting key physiological parameters such as the user's age information, urethral wall thickness, and tissue softness, user-specific puncture feature data can be constructed. These feature data reflect the individual physiological structure differences and tissue mechanical properties, and are a quantitative expression of the actual environment inside the user's urethra. As an important factor affecting tissue elasticity and thickness, age information, combined with the urethral wall morphology and texture features obtained through image processing, can effectively infer the urethral wall thickness and tissue softness, providing an important reference for subsequent resistance prediction. Secondly, a pre-established resistance model is used for feature matching. This model is based on a large amount of clinical puncture data of users of different ages, covering the puncture resistance curves and corresponding displacement information under different urethral wall thicknesses and tissue softness conditions. During the matching process, if the user's puncture feature data is highly consistent with a certain typical feature data in the model, the resistance and displacement data corresponding to this feature are directly adopted to ensure calculation efficiency and accuracy. If there are differences in the matching, the ratio of the user's puncture feature vector to the similar feature vector in the model will be calculated, and the similarity between the two is quantitatively reflected through the mathematical operations in the vector space. Based on the magnitude of the vector ratio, multiple preset threshold intervals are set, each corresponding to a different adjustment coefficient. The adjustment coefficient reflects the amplification or reduction of the preset values of resistance and displacement, ensuring that the preset data is more in line with the individual differences of users. For example, when the vector ratio is low, it indicates that the user's features deviate greatly from the model features, and the adjustment coefficient is less than 1 to reduce the preset values of resistance and displacement; conversely, when the vector ratio is high, an adjustment coefficient greater than 1 is adopted to moderately amplify the preset parameters, thereby achieving dynamic adaptive adjustment of the data. This mechanism effectively avoids the preset data deviation caused by physiological differences and improves the accuracy and safety of puncture prediction. Finally, the construction of the resistance model is based on a complex multi-dimensional data processing process. Urethral puncture data of users of different ages are collected, including urethral wall thickness, tissue softness, and the measured resistance changes and syringe advancement depth during the puncture process. By calculating the Euclidean distance between each resistance correlation formula, a distance matrix is constructed, and the iterative clustering algorithm is used to group similar resistance curves to extract typical resistance patterns. Based on these clustering results, a linear axis of the resistance correlation formula is established, and then a resistance model with strong generalization ability is constructed. This model can reflect the diversity and complexity of resistance changes and realize effective simulation and prediction of the puncture process of different users.

[0030] It can be seen that by combining the user's age information, urethral wall thickness, and tissue softness, personalized puncture feature data is accurately established, realizing the individualized preset of resistance and displacement during the puncture process. This matching mechanism based on individual characteristics and a pre-configured resistance model effectively improves the accuracy of the preset resistance and displacement data, thereby enhancing the safety and reliability of the puncture operation. In addition, by comparing and dynamically adjusting the puncture feature data with multiple feature data in the resistance model, it can flexibly adapt to the physiological differences of users. Using a multi-level adjustment coefficient to finely adjust the preset data according to the vector ratio ensures that even when the matching is not completely consistent, a reasonable and near-real resistance and displacement estimate can still be obtained, greatly reducing the risk of misjudgment and the probability of operation errors. Finally, the pre-constructed resistance model is based on a large amount of clinical data and, through clustering and linear axis modeling, can reflect the resistance change laws under different ages and tissue conditions. This model provides a scientific basis for puncture early warning, enabling effective coverage of complex individual differences in practical applications, further enhancing the precise control and intelligent early warning capabilities during the puncture process, and contributing to improving the surgical success rate and patient safety.

[0031] Step S300: Determine 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.

[0032] Specifically, when 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, it includes: determining whether the operation is abnormal according to the relationship 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, it is determined that the operation is not abnormal, and 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, it is determined whether the operation is abnormal; when the primary resistance change data is higher than the preset resistance data, it is determined that the operation is abnormal.

[0033] Specifically, when determining whether the operation is abnormal according to the relationship between the displacement data and the preset displacement data, it includes: when the displacement data exceeds the preset displacement data, it is determined that the operation is abnormal; when the displacement data does not exceed the preset displacement data, it is determined whether the operation is abnormal according to the relationship between the secondary resistance change data and the preset resistance data.

[0034] Specifically, when determining whether the operation is abnormal according to the relationship between the secondary resistance change data and the preset resistance data, it includes: when the secondary resistance change data is lower than the preset resistance data, it is determined that the operation is not abnormal; when the secondary resistance change data is higher than or equal to the preset resistance data, it is determined that the operation is abnormal.

[0035] It is understandable that through comparing multiple groups of key data collected in real time during the puncture process with preset standards, a multi-level and multi-dimensional abnormal recognition mechanism has been established. Its core principle lies in using the primary resistance change data as the first judgment threshold. If the resistance data does not exceed the preset range, displacement data and secondary resistance change data are further introduced for auxiliary judgment to achieve a step-by-step judgment process from "coarse screening" to "precision judgment". This method not only improves the response speed but also greatly enhances the accuracy and robustness of the judgment. In the first step, the primary resistance change data generated during the advancement of the puncture needle tube is obtained in real time and compared with the preset resistance data established according to the individual characteristics of the user. When this data does not exceed the safety threshold, that is, when it is lower than or equal to the preset resistance data, it is initially considered that the current puncture environment is in a normal state. This design can effectively avoid false alarms due to slight fluctuations while ensuring a sensitive response to sudden high resistance situations. If the primary resistance change data is within the safety range, the difference between the current displacement data and the individualized preset displacement data will continue to be evaluated. This step is an effective monitoring of the puncture path and depth control. When the actual displacement exceeds the upper limit of the preset displacement, it may indicate that the puncture has exceeded the safe physiological area, such as having passed through the boundary of the target tissue or entered a high-risk tissue area. At this time, an abnormal determination will be triggered and an alarm will be issued in a timely manner to prevent further operation. If the displacement data does not exceed the preset range, the secondary resistance change data is introduced for the final verification. The secondary resistance reflects the stability and continuity of the resistance change trend during the puncture process and belongs to a more refined dynamic signal criterion. When the secondary resistance change data is significantly higher than the preset resistance data, it may indicate problems such as sudden changes in tissue structure during the puncture process, the needle encountering high-density tissue, or mechanical jamming, thus triggering the final determination of the abnormal state. This layer of judgment makes up for the detection blind spots of the instantaneous change and local fluctuations of the resistance and effectively improves the comprehensive recognition ability. To sum up, through the joint judgment of three-dimensional parameters (primary resistance, secondary resistance, displacement), this technical solution realizes the dynamic monitoring and high-precision abnormal recognition of the puncture operation process, and has technical advantages such as high recognition sensitivity, low false judgment rate, and strong adaptability. Especially in complex or clinically significant individual difference environments, this method can significantly improve the safety and accuracy of the puncture operation, effectively reduce the incidence of intraoperative complications, and has good application prospects and clinical practical value.

[0036] Step S400: If it is determined that the operation is abnormal, an alarm process is carried out based on the acoustic and optical alarm device, and the puncture operation is terminated.

[0037] In the above embodiments, by comparing and analyzing the actual puncture data with the pre-established resistance model and displacement model, it is determined whether the puncture path and depth are in a normal state. Compared with the existing puncture methods that only rely on doctors' experience or visual assistance, this method greatly improves the objectivity and controllability of the operation process. In addition, the present invention adopts a combined method of electromagnetic sensing and mechanical sensing to achieve high-precision monitoring of the process of advancing the puncture needle tube. Among them, the electromagnetic induction module can obtain the spatial displacement information of the needle tube in the urethra in real time, while the resistance sensor can dynamically capture the mechanical feedback generated by the tissue on the puncture needle tube. By fusing these two types of sensing data and combining with the resistance trend model driven by big data, the present invention can intelligently identify and match-analyze the primary resistance (such as penetrating the urethral wall) and secondary resistance (such as entering the target tissue) that occur during the puncture process. It is worth emphasizing that when the system detects that the current resistance data deviates abnormally from the preset model (for example, the resistance is too high, the duration is abnormal, or a key resistance stage is missing), the acoustic and optical alarm mechanism can be immediately triggered to prompt the doctor that there is a risk in the current puncture state and automatically terminate the puncture operation when necessary to avoid further tissue damage or operation errors. This intelligent early warning mechanism significantly enhances the safety protection ability of the system, helps to reduce medical risks, and ensures the safety of patients. Finally, on the basis of improving the puncture accuracy, the present invention also has good adaptability and scalability. By continuously accumulating historical data during the operation process and optimizing the resistance model, the system can achieve self-learning and intelligent evolution, so as to better adapt to the personalized needs of patients of different ages and different anatomical structures, and further improve the individual adaptability and clinical universality of the puncture operation.

[0038] In another preferred embodiment based on the above embodiments, as Figure 2 shown, this embodiment provides a puncture needle tube early warning system based on electromagnetic signals, including: a collection module, an analysis module, and an acoustic and optical alarm module.

[0039] Specifically, the collection module is configured to obtain user information data, displacement data of the puncture needle tube in the urethra, and primary resistance change data and secondary resistance change data; the analysis module is electrically connected to the collection module, and the analysis module is configured to obtain 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 analysis module is further configured to determine 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; the acoustic and optical alarm module is respectively electrically connected to the analysis module and the puncture needle tube, and the acoustic and optical alarm module is configured to perform an alarm process and terminate the puncture operation when the analysis module determines that the operation is abnormal.

[0040] It is understandable that the above-mentioned embodiments of the present invention, a puncture needle tube warning system and method based on electromagnetic signals, have the same beneficial effects and will not be elaborated herein.

[0041] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system or a computer program product. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0042] The present application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems) and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowchart and / or block diagram can also be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for realizing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0043] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device realizes the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0044] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for realizing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0045] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications or equivalent substitutions can still be made to the specific implementation manners of the present invention, and any modification or equivalent substitution that does not depart from the spirit and scope of the present invention shall be covered by the protection scope of the claims of the present invention.

Claims

1. A warning method for a puncture needle tube based on electromagnetic signals, characterized in that, Including: Obtaining user information data, displacement data of the puncture needle tube in the urethra, primary resistance change data, and secondary resistance change data; Obtaining 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; 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, where: If it is determined that the operation is abnormal, an alarm process is performed based on the acoustic-optic alarm device, and the puncture operation is terminated.

2. The puncture needle tube warning method based on electromagnetic signals according to claim 1, wherein, When obtaining user information data, it includes: Obtaining the age information of the user, the urethral surface image and / or the urethral fluoroscopy image of the user; Performing image preprocessing on the urethral surface image and / or the urethral fluoroscopy image, where the image preprocessing includes denoising processing, grayscale processing, contrast enhancement processing, image edge detection, and image segmentation processing; Extracting image features from the urethral surface image and / or the urethral fluoroscopy image after image preprocessing, where the image features include image feature data such as urethral contour edges, texture distribution, grayscale gradient changes, and image contrast; Determining the urethral wall thickness and tissue softness of the user according to the image features and the age information of the user.

3. The warning method for a puncture needle tube based on electromagnetic signals according to claim 2, wherein, When determining the urethral wall thickness and tissue softness of the user according to the image features and the age information of the user, it includes: Calculating the urethral wall thickness based on the urethral contour edge information in the image features; Evaluating the softness of the urethral tissue based on the texture distribution and grayscale gradient changes in the image features, in combination with the age information of the user.

4. The puncture needle tube warning method based on electromagnetic signals according to claim 3, characterized in that, When obtaining the 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, it includes: Establishing puncture feature data of the user according to the age information, urethral wall thickness, and tissue softness of the user; Matching the puncture feature data with the resistance model, and determining the preset resistance data and preset displacement data of the puncture needle tube in the urethra according to the matching result: When the puncture feature data is consistent with any feature data in the resistance model, the puncture resistance data and puncture displacement data corresponding to the feature data are determined as the preset resistance data and preset displacement data of the puncture needle tube in the urethra; When the puncture feature data is inconsistent with each feature data in the resistance model, the feature vectors between the feature data and the feature data close to the puncture feature data are obtained, and the preset resistance data and preset displacement data of the puncture needle tube in the urethra are determined according to the relationship between the feature vectors and the feature data close to the puncture feature data.

5. The puncture needle tube warning method based on electromagnetic signals according to claim 4, wherein When determining the preset resistance data and preset displacement data of the puncture needle tube in the urethra according to the relationship between the feature vectors and the feature data close to the puncture feature data, it includes: Obtaining the puncture feature vector between the puncture feature data and the close feature data, and obtaining the vector ratio between the puncture feature vector and the feature vector; Determining the adjustment coefficient according to the relationship between the vector difference and the pre-configured first preset vector ratio and second preset vector ratio: When the vector ratio is lower than the first preset vector ratio, the adjustment coefficient is determined to be L1; When the vector ratio is higher than or equal to the first preset vector ratio and lower than the second preset vector ratio, the adjustment is determined to be L2; When the vector ratio is higher than or equal to the second preset vector ratio, the adjustment system is determined to be L3; Among them, the first preset vector ratio is lower than the second preset vector ratio, and L1 < 1 < L2 < L3; When it is determined that the adjustment system is Li, i = 1, 2, 3, the characteristic data close to the puncture characteristic data, the corresponding puncture resistance data and puncture displacement data are adjusted according to the adjustment coefficient Li, and the adjusted puncture resistance data and puncture displacement data are determined as the preset resistance data and preset displacement data when the puncture needle tube is in the urethra.

6. The puncture needle tube warning method based on electromagnetic signals according to claim 4, characterized in that, When the pre-configured resistance model includes: Obtain the urethral thickness data, the tissue softness of each tissue part, and the puncture resistance change data and puncture displacement depth of the puncture needle tube during each advancement when users of different ages perform urethral puncture; According to the age of each user, the urethral thickness data during urethral puncture, the tissue softness of the tissue part, the puncture resistance change data of the puncture needle tube during advancement, and the puncture displacement depth, establish a resistance correlation formula; Obtain the Euclidean distance between each resistance correlation formula and establish a distance matrix; According to the distance matrix, perform iterative clustering between each resistance correlation formula and obtain each resistance correlation formula after clustering; According to the magnitude relationship between each resistance correlation formula, and based on the magnitude relationship, establish a linear axis between each resistance correlation formula; According to the linear axis between each resistance correlation formula, establish a resistance model.

7. The puncture needle tube warning method based on electromagnetic signals according to claim 1, wherein, When 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, it includes: Determine whether the operation is abnormal according to the relationship 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, it is determined that the operation is normal, and 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, determine whether the operation is abnormal; When the primary resistance change data is higher than the preset resistance data, it is determined that the operation is abnormal.

8. The puncture needle tube warning method based on electromagnetic signals according to claim 7, wherein, When determining whether the operation is abnormal according to the relationship between the displacement data and the preset displacement data, it includes: When the displacement data exceeds the preset displacement data, it is determined that the operation is abnormal; When the displacement data does not exceed the preset displacement data, determine whether the operation is abnormal according to the relationship between the secondary resistance change data and the preset resistance data.

9. The puncture needle tube warning method based on electromagnetic signals according to claim 8, wherein, When determining whether the operation is abnormal according to the relationship between the secondary resistance change data and the preset resistance data, it includes: When the secondary resistance change data is lower than the preset resistance data, it is determined that the operation is not abnormal; When the secondary resistance change data is higher than or equal to the preset resistance data, it is determined that the operation is abnormal.

10. A puncture needle tube warning system based on electromagnetic signals, configured with a method for warning a puncture needle tube based on electromagnetic signals as described in any one of claims 1-9, characterized in that, It includes: A collection module configured to obtain user information data, the displacement data of the puncture needle tube in the urethra, and the primary resistance change data and the secondary resistance change data; An analysis module, electrically connected to the acquisition module, is configured to obtain preset resistance data and preset displacement data of the puncture needle tube in the urethra according to user information data and a pre-configured resistance model; The analysis module is further configured to determine 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; An acoustic-optic alarm module, electrically connected to the analysis module and the puncture needle tube respectively, is configured to perform an alarm process and terminate the puncture operation when the analysis module determines that the operation is abnormal.

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