Electronic track analysis system and analysis method for built-in guide wire of medical gastrointestinal tube

Abstract

The invention relates to the technical field of medical instruments, in particular to a medical gastrointestinal tube built-in guide wire electronic track analysis system and analysis method. According to the system, a guide wire body is sequentially provided with sensing units in the length direction, and the sensing units are connected to a data interface module through a signal transmission line in the guide wire; the data interface module is used for receiving original sensing data acquired by each sensing unit and converting the original sensing data into sensing data frames; the mobile terminal processing device establishes connection through a wireless communication protocol so as to receive the sensing data frame and analyze the sensing data frame to obtain multi-dimensional sensing parameters; the track calculation module constructs a guide wire kinematics model based on the multi-dimensional sensing parameters and calculates and generates real-time three-dimensional motion track data, and meanwhile, comparison is carried out to generate a track matching degree score; and the feedback output unit generates real-time operation guidance information according to the track matching degree score and outputs the real-time operation guidance information. The motion trail of the gastrointestinal tube can be monitored and analyzed in real time through a built-in guide wire electronic trail analysis technology.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of medical devices, and in particular to a medical gastrointestinal tube in-place guide wire electronic trajectory analysis system and analysis method. BACKGROUND

[0002] In recent years, with the development of electronic navigation technology, sensor technology and medical image processing technology, more and more researches have begun to try to combine electronic trajectory analysis with correct insertion of gastrointestinal tubes. Some existing technical solutions usually rely on sensor or image guided systems, using sensor data and image information for real-time tracking and analysis to guide accurate placement of gastrointestinal tubes. However, these existing technologies still have certain limitations in data integration and path analysis, and cannot fully reflect the real-time dynamic trajectory of the gastrointestinal tube, and it is difficult to efficiently and intelligently analyze and feedback complex intubation paths. In addition, similar patents such as CN119601189A disclose a medical instrument equipment position dynamic trajectory tracking intelligent management system, which relates to the technical field of medical equipment management, and assigns labels to the pre-managed medical instrument equipment through a trajectory data mining unit, mines a trajectory database based on equipment location characteristics; a multi-dimensional management construction unit constructs an intelligent management block in combination with the trajectory database for multi-dimensional management dimensions; a device tracking and state analysis unit receives device update information, combines the intelligent management block, performs device tracking and state analysis, and generates device data flow; a device location management unit applies the device data flow to multiple functional modules in reverse to perform device location management. The present application solves the technical problems of low efficiency and poor real-time performance of medical instrument management in the prior art, which leads to the inability to obtain device location and real-time state in a timely manner, thereby affecting device use and maintenance, and improves the real-time performance, accuracy and management efficiency of medical instrument management. Although it can use medical device data flow for real-time tracking and analysis to guide the determination of the trajectory condition of the medical device, it mainly relies on tracking management of the device data flow, is limited by traditional visualization technology, and is difficult to achieve real-time and accurate tracking and evaluation, and at the same time, it often cannot provide full-process electronic trajectory recording during medical catheter insertion, lacks dynamic monitoring of intubation path and position, and thus it is difficult to achieve accurate operation control and feedback. SUMMARY

[0003] The present application provides a kind of through guide wire main body and the cooperation of multiple sensing units, realizes real-time monitoring and accurate tracking of the movement track of guide wire in body, converts original sensing data into standardized format through data interface module, and obtains multidimensional sensing parameters by mobile terminal processing device analysis, to provide real-time guide wire three-dimensional movement track data for doctor, ensure accurate positioning and accurate control of guide wire in operation process, trajectory calculation module is based on kinematic model and iteratively calculated, realizes accurate three-dimensional trajectory generation of guide wire in body.Simultaneously, by comparing with standard anatomical structure data through anatomical matching database, generate trajectory matching degree score, provide real-time, accurate tracking and evaluation for doctor, in addition, feedback output unit is through voice prompt, text description and trajectory deviation indication, effectively realize the dynamic monitoring of intubation path and position, so as to realize accurate operation control and feedback medical gastrointestinal tube built-in guide wire electronic trajectory analysis system, comprising:

[0004] The guide wire body is sequentially provided with a head sensing unit, a middle sensing unit and a tail sensing unit along the length direction, and each sensing unit is connected to a data interface module through a signal transmission line inside the guide wire; the data interface module is integrated at the tail end of the guide wire body, used for receiving original sensing data collected by each sensing unit, and converting the original sensing data into a standardized data format to generate a sensing data frame containing a data collection time stamp and a sensor identifier; a mobile terminal processing device is connected with the data interface module through a wireless communication protocol, receives the sensing data frame and analyzes to obtain multi-dimensional sensing parameters, including three-dimensional space coordinate parameters, motion state parameters, deformation parameters and environmental parameters; a trajectory calculation module constructs a guide wire kinematics model based on the multi-dimensional sensing parameters, and generates real-time three-dimensional motion trajectory data of the guide wire in the body through model iterative calculation; an anatomical matching database stores standard anatomical structure data corresponding to the human digestive tract, and the mobile terminal processing device calls the anatomical matching database to compare the real-time three-dimensional motion trajectory data with the standard anatomical structure data to generate a trajectory matching degree score; a feedback output unit generates real-time operation guidance information containing voice prompts, text instructions and trajectory deviation indications according to the trajectory matching degree score, and outputs through the display interface and the audio module of the mobile terminal processing device. In the application, through the cooperation of the guide wire body and the multiple sensing units, comprehensive monitoring and real-time tracking of the guide wire motion process are realized, the motion state, spatial position, deformation and environmental change data of the guide wire are collected through the built-in sensing units, and are transmitted to the mobile terminal through the data interface module, and through standardized processing, the sensing data is converted into a unified format, which is convenient for further analysis, the mobile terminal processing device connects with the data interface module through a wireless communication protocol, and analyzes these multi-dimensional sensing parameters in real time, providing accurate motion state feedback for doctors, which helps to optimize the precise positioning and operation of the guide wire during the operation. The trajectory calculation module generates real-time three-dimensional trajectory of the guide wire in the body through iterative kinematics model, providing accurate guide wire motion trajectory data for doctors, which effectively avoids the deviation caused by human factors in traditional operation, improves the precision and safety of the operation, and uses the anatomical matching database for comparison, matches the real-time trajectory data with the standard anatomical structure to generate a trajectory matching degree score, further ensuring that the guide wire positioning is highly consistent with the anatomical structure of the digestive tract. Finally, the feedback output unit provides real-time operation guidance information according to the matching degree score, including voice prompts, text instructions and deviation indications, which not only can adjust the operation in real time, but also can effectively remind the doctor of the possible risks in the operation, and through the display interface and the audio module, the doctor can more intuitively obtain feedback and respond quickly, thereby greatly improving the safety and accuracy of medical operation.

[0005] As preferred, the head sensing unit comprises a three-axis accelerometer, a three-axis gyroscope and a pH sensor arranged axially along the guide wire, wherein:

[0006] The three-axis accelerometer collects linear acceleration data of the guide wire head, generating an acceleration vector value containing X, Y and Z axis components; the three-axis gyroscope collects angular velocity data of the guide wire head, generating an angular velocity vector value containing roll angle, pitch angle and yaw angle; the pH sensor collects hydrogen ion concentration data of the environment around the guide wire head, generating a pH value measurement result; the head sensing unit synchronizes the acceleration vector value, the angular velocity vector value and the pH value measurement result with time stamps, generates a head sensing data group, and sends it to the data interface module through a signal transmission line. In the present application, the head sensing unit provides comprehensive sensing capability for guide wire movement and environmental conditions by integrating a three-axis accelerometer, a three-axis gyroscope and a pH sensor. The application of the three-axis accelerometer enables the movement acceleration of the guide wire in different directions to be accurately captured, further providing basic data for motion trajectory and stability analysis. The angular velocity data collected by the three-axis gyroscope helps to determine the rotational changes of the guide wire in three-dimensional space, providing key angle information for dynamic analysis. The pH sensor can monitor the pH changes of the surrounding environment, providing additional parameters that help reflect the environmental state. After synchronization of the data from these sensors with time stamps, not only can the movement state of the guide wire be tracked in real time, but also adaptive feedback of the guide wire in different working environments can be provided, thereby improving overall accuracy and response speed. Through the signal transmission line, these data are sent to the data interface module, which helps to realize efficient processing and analysis of the sensing data, ensuring real-time and reliable signal transmission and data collection, and laying a solid foundation for subsequent analysis.

[0007] As preferred, the middle sensing unit comprises a strain sensing array, a pressure sensor and a temperature and humidity sensor, wherein: the strain sensing array is composed of 4 strain gauges uniformly distributed circumferentially along the guide wire, collects tensile, compressive and bending deformation data of the middle part of the guide wire, and generates deformation stress values; the pressure sensor collects pressure data generated by the contact between the guide wire and the digestive tract tissue, and generates pressure characteristic values containing pressure amplitude and pressure duration; the temperature and humidity sensor collects temperature and humidity data of the environment around the middle part of the guide wire, and generates environmental parameter values; the middle sensing unit fuses the deformation stress values, the pressure characteristic values and the environmental parameter values, generates a middle sensing data group, and sends it to the data interface module through a signal transmission line.

[0008] The middle sensing unit in the application includes a strain sensing array, a pressure sensor and a temperature and humidity sensor, which work together to provide more comprehensive monitoring of the guide wire during use. The strain sensing array can detect the deformation state of the middle part of the guide wire in real time, including tensile, compressive and bending mechanical changes. Through the uniform arrangement of the four strain gauges, the comprehensiveness of data acquisition is ensured, and the deformation stress value is provided to help analyze the structural changes of the guide wire during operation. The pressure sensor detects the contact pressure between the guide wire and the digestive tract tissue to provide an objective evaluation of the adaptability of the guide wire to the surrounding tissue, and then optimizes the contact mechanical parameters during operation. The temperature and humidity sensor helps to monitor the temperature and humidity changes in the working environment of the guide wire, providing data support for environmental factor monitoring. The middle sensing data set generated after fusion processing of these data greatly improves the reliability and analyzability of the data, which helps to dynamically adjust the guide wire operation and ensures the stability and adaptability of the guide wire in different working environments.

[0009] As preferred, the working process of the strain sensing array includes: each strain gauge generates resistance change when the guide wire deforms, and converts it into voltage signal through Wheatstone bridge to generate original strain electric signal; the original strain electric signal is filtered and amplified to remove high-frequency noise and baseline drift to generate filtered strain signal; the filtered strain signal is converted into corresponding deformation displacement according to the preset strain-deformation conversion coefficient, including radial bending amount and axial expansion amount; the bending center coordinates and bending angle of the guide wire section are calculated by combining the deformation displacement of the four strain gauges to generate deformation data containing spatial bending direction. The working principle of the strain sensing array in the application converts resistance change into voltage signal through Wheatstone bridge, thereby accurately capturing the deformation state of the guide wire. The original strain electric signal is filtered and amplified to remove high-frequency noise and baseline drift, ensuring the accuracy and stability of the signal. The strain signal is converted into corresponding deformation displacement through the preset strain-deformation conversion coefficient, thereby realizing accurate quantization of the deformation of the guide wire. The calculated radial bending amount and axial expansion amount provide detailed data for subsequent guide wire deformation analysis, especially in high-precision applications, which can effectively avoid error accumulation of deformation data. By calculating the bending center coordinates and bending angle of the guide wire section, the spatial distribution of deformation characteristics is further refined, providing strong support for overall structural analysis. These processing results not only improve the accuracy of strain data, but also enable a more accurate understanding of the response characteristics of the guide wire under different working conditions.

[0010] As preferred, the calculation process of the deformation data comprises: collecting deformation displacement amounts of the 4 strain gauges, establishing a polar coordinate system with the guide wire axis as the origin, and generating polar coordinate position parameters of each strain gauge; based on the polar coordinate position parameters and the corresponding deformation displacement amounts, fitting the bending circular arc of the guide wire section by the least square method, calculating the curvature radius and the center coordinates of the circular arc; determining the bending direction vector of the guide wire according to the curvature radius and the center coordinates, and generating a three-dimensional deformation feature vector in combination with the axial extension amount; and associating the three-dimensional deformation feature vector with the time stamp to form deformation data changing with time. In the present application, the deformation displacement amounts of each strain gauge are collected and processed in the polar coordinate system, which can more intuitively analyze the bending state of the guide wire section. The application of the polar coordinate system helps to accurately position the relative position of the strain gauge in the guide wire section, so that the spatial analysis of the deformation data is more accurate. The least square method fitting the calculated bending circular arc not only provides a basis for the determination of the curvature radius and the center coordinates of the guide wire, but also ensures that the calculation of the bending direction vector has high accuracy. In combination with the axial extension amount, the generation of the three-dimensional deformation feature vector further enriches the dimension of the guide wire deformation analysis. Through the association with the time stamp, the dynamic deformation data formed can reflect the deformation of the guide wire under different operating states in real time, which is helpful for accurately controlling the motion trajectory of the guide wire. These high-precision data and calculation methods provide strong support for subsequent data processing and analysis, and improve the real-time monitoring and control ability of the guide wire deformation.

[0011] As preferred, the tail sensing unit comprises a micro pressure sensor and an electromagnetic positioning sensor, wherein: the micro pressure sensor collects the push pressure data received by the guidewire tail to generate pressure values; the electromagnetic positioning sensor collects the position information of the guidewire tail based on the change of the surrounding electromagnetic field to generate a position data set containing X, Y and Z axis coordinates; the tail sensing unit integrates the pressure values and the position data set to generate a tail sensing data set, which is sent to the data interface module through a signal transmission line. The function of the tail sensing unit is described in the present application, which mainly comprises two modules of the micro pressure sensor and the electromagnetic positioning sensor to monitor the pressure and position information of the guidewire tail in real time. The micro pressure sensor collects the push pressure data received by the guidewire tail to monitor the stress of the guidewire during the operation in real time, which is extremely important for analyzing whether the guidewire is subjected to abnormal push force or pressure that may cause failure, and can provide timely warning to prevent the breakage of the guidewire or the failure of the operation due to excessive pressure. At the same time, the electromagnetic positioning sensor collects the position information of the guidewire tail based on the change of the surrounding electromagnetic field to generate X, Y and Z axis coordinate data. This enables the system to accurately track the movement trajectory and relative position of the guidewire tail, further helping to judge the stability and accuracy of the guidewire during the operation. The integration of these pressure values and position information generates a tail sensing data set, which can provide accurate input for the data interface module to ensure more accurate subsequent data analysis, and provide basis for real-time adjustment of operation parameters and correction of possible errors. The effective cooperation of the sensing unit helps to comprehensively grasp the state of the guidewire and improve the operation safety and accuracy.

[0012] As preferred, the data interface module comprises: a signal conditioning circuit which performs analog-to-digital conversion on the analog signals output by each sensing unit, generating 16-bit digital signals; a data packing unit which combines the 16-bit digital signals with sensor IDs, sampling frequencies, and check codes according to a preset protocol, generating fixed-length sensing data frames; a wireless communication module which supports Bluetooth 5.0 and IEEE 802.11n protocols, can automatically switch communication modes according to signal strength, and sends the sensing data frames to a mobile terminal processing device at a frequency of 250 Hz; and an energy consumption management unit which monitors the current consumption of each module, dynamically adjusts the working voltage according to the data transmission volume, and generates a state monitoring frame containing the remaining power and transmission rate. The functions of the data interface module are described in the present application, including the design and implementation of the signal conditioning circuit, the data packing unit, the wireless communication module, and the energy consumption management unit. The signal conditioning circuit performs analog-to-digital conversion on the analog signals output by the sensing unit and generates 16-bit digital signals, which can effectively improve the transmission accuracy of the signals and reduce errors caused by noise interference during analog signal transmission. By performing analog-to-digital conversion on the signals, the collected data can be better processed and analyzed by the subsequent processing modules. The data packing unit combines the 16-bit digital signals with sensor IDs, sampling frequencies, check codes, and other information according to a preset protocol to form fixed-length sensing data frames. This operation ensures the structuring and standardization of data during transmission, making the subsequent data processing process more efficient and consistent. At the same time, the check code in the data frame can help detect errors during data transmission, ensuring the integrity and accuracy of the data. The wireless communication module uses Bluetooth 5.0 and IEEE 802.11n protocols, which can automatically switch communication modes according to signal strength, making data transmission more stable and flexible. By switching between different communication protocols, efficient data transmission can be ensured in various environments. With the support of this module, data frames can be sent to a mobile terminal processing device at a frequency of 250 Hz, which means that the system can acquire and transmit physiological data in real time, providing support for subsequent real-time analysis and decision-making. The design of the energy consumption management unit takes into account the power consumption of the system. By monitoring the current consumption of each module and dynamically adjusting the working voltage according to the data transmission volume, power consumption can be effectively reduced, prolonging the service life of the device. In addition, this unit also generates a state monitoring frame containing the remaining power and transmission rate, allowing the system to assess its power and performance state in real time, avoiding power shortages at critical moments.

[0013] As preferred, the mobile terminal processing device further comprises a risk warning module, and the working process of the module comprises: monitoring the motion state of the guide wire body in real time according to the multi-dimensional sensing parameters, identifying the potential operation risk in combination with the preset risk threshold; when it is monitored that the risk index exceeds the threshold, a risk warning signal is generated, and the risk type and risk position information are transmitted to the feedback output unit, so as to timely inform the operator through voice prompt, interface warning mode. The risk warning module in the mobile terminal processing device in the application, the core function of which is to monitor the motion state of the guide wire in real time, and to judge the potential operation risk according to the preset risk threshold. By monitoring the parameters from multiple sensing units and combining algorithm for comprehensive analysis, the abnormal conditions that the guide wire may appear, such as excessive bending and excessive pressure, can be identified in time. This real-time monitoring can greatly reduce human operation errors and avoid continuing operation in a high-risk state, thereby improving the safety of the entire operation process. When it is monitored that the risk index exceeds the threshold, the system will immediately generate a risk warning signal, and through voice prompt or interface warning, the risk type and position information are fed back to the operator in time. This feedback mechanism can help the operator to take countermeasures quickly and prevent accidents. Through this early warning mechanism, the operator can take intervention measures at the early stage of risk, effectively preventing equipment damage or operation errors, thereby improving the reliability and safety of operation. This function is particularly important in high-risk operation environment, which can provide real-time risk reminder for the workers and ensure safe and efficient operation execution.

[0014] As preferred, the calculation process of the trajectory calculation module comprises: Kalman filtering processing on the three-dimensional space coordinate parameters, eliminating measurement noise, generating a smoothed coordinate sequence; based on the smoothed coordinate sequence and the motion state parameters, calculating the instantaneous velocity and acceleration of each feature point on the guide wire, generating a set of kinematic parameters; combining the diameter data of the digestive tract cavity in the anatomical matching database, the set of kinematic parameters is subjected to boundary constraint processing to generate a constrained motion trajectory; adopting a Bezier curve fitting to fit the constrained motion trajectory to generate a continuous three-dimensional trajectory curve and the corresponding curvature rate of change. The calculation process of the trajectory calculation module in the application comprises Kalman filtering, kinematic modeling and Bezier curve fitting, aiming to accurately calculate the motion trajectory of the guide wire in the three-dimensional space to provide support for subsequent operations. First, the Kalman filter is used to filter the three-dimensional space coordinate parameters, which can effectively remove the noise in the measurement and improve the accuracy of the data. Kalman filtering is a recursive algorithm that can dynamically optimize trajectory prediction based on historical data and current measurement data every time new data is received, which provides a reliable basis for real-time monitoring of guide wire movement. Then, based on the filtered coordinate data and the motion state parameters, the module calculates the instantaneous velocity and acceleration of each feature point on the guide wire to generate a set of kinematic parameters. This step can accurately capture the dynamic changes of the guide wire movement by analyzing the motion parameters, providing data support for subsequent trajectory fitting and analysis. Combined with the diameter data of the digestive tract cavity in the anatomical matching database, the set of kinematic parameters will be subjected to boundary constraint processing to ensure that the motion trajectory of the guide wire conforms to the human anatomical structure. In this way, the calculated motion trajectory can not only accurately reflect the actual movement of the guide wire, but also match the actual anatomical structure of the human body, avoiding errors or deviations. Finally, the Bezier curve fitting is adopted to fit the constrained motion trajectory to generate a continuous three-dimensional trajectory curve and calculate the corresponding curvature rate of change. The Bezier curve fitting method can smooth and optimize the trajectory, making the calculation result more consistent with the actual situation, and the calculation of the curvature rate of change provides detailed information of the guide wire movement, which helps to analyze the stability and control accuracy of its movement.

[0015] As preferred, the boundary constraint processing process comprises: calling the digestive tract lumen cross-sectional data corresponding to the current position from the anatomical matching database, generating a constraint boundary model containing the lumen radius and center axis; comparing the coordinate data in the kinematic parameter set with the constraint boundary model, identifying abnormal coordinate points that exceed the lumen boundary; correcting the abnormal coordinate points using a cubic spline interpolation algorithm to generate corrected coordinate values that conform to the physiological structure; calculating the deviation amount of the coordinate values before and after correction, and generating a boundary constraint warning signal if the deviation amount exceeds a preset threshold. In the present application, the boundary constraint processing process provides reasonable physiological structure constraints for the guide wire movement by combining the lumen cross-sectional data in the anatomical matching database. First, the digestive tract lumen cross-sectional data corresponding to the current position is called from the anatomical matching database, and a constraint boundary model containing the lumen radius and center axis is generated. This model provides a standardized reference for subsequent trajectory constraints, ensuring that the guide wire movement does not exceed the reasonable range of human anatomical structure. By comparing the coordinate data in the kinematic parameter set with the constraint boundary model, abnormal coordinate points that exceed the lumen boundary can be identified. In this way, the movement state of the guide wire can be monitored in real time to avoid deviation from the expected path and ensure the safety and accuracy of the operation. The identification of abnormal coordinate points is particularly critical for discovering errors in the guide wire during operation, allowing for timely adjustment of the movement trajectory and reducing the risk of operation. When abnormal coordinate points are found, a cubic spline interpolation algorithm is used for correction to generate corrected coordinate values that conform to the physiological structure. This interpolation method can smooth the abnormal points through existing trajectory data to ensure that the guide wire path always conforms to the anatomical structure and avoid erroneous movement due to data fluctuations or measurement errors. In addition, the deviation amount of the coordinate values before and after correction is also calculated, and a boundary constraint warning signal is generated if the deviation amount exceeds a preset threshold. This mechanism can provide a warning to the operator to avoid potential problems caused by excessive deviation. Through this real-time monitoring and correction, the safety and efficiency of the guide wire are ensured, and unnecessary risks are reduced.

[0016] As preferred, the construction process of the constraint boundary model comprises: reconstructing the three-dimensional model of the digestive tract based on CT image data, extracting the central axis and cross-sectional profile of each segment of the lumen, and generating standard anatomical structure parameters; performing statistical analysis on the standard anatomical structure parameters, calculating the anatomical difference coefficients of different age groups and body types, and generating personalized correction factors; the mobile terminal processing device receives the physiological parameters of the patient input by the user, calls the corresponding personalized correction factors to adjust the standard anatomical structure parameters, and generates a personalized constraint boundary model; and adding a time attenuation factor to the personalized constraint boundary model, and dynamically adjusting the elastic coefficient of the constraint boundary with the operation time. The construction process of the personalized constraint boundary model is described in the application, mainly including the three-dimensional model reconstruction of the digestive tract based on CT image data, the personalized adjustment of anatomical structure parameters, etc. First, the three-dimensional model of the digestive tract is reconstructed based on CT image data, and the central axis and cross-sectional profile of each segment of the lumen are extracted to generate standard anatomical structure parameters. This process can provide detailed anatomical data and provide standardized reference for subsequent trajectory calculation. Statistical analysis is performed on the standard anatomical structure parameters, the anatomical difference coefficients of different age groups and body types are calculated, and personalized correction factors are generated. The standard model can be adjusted according to the individual differences of the patient to ensure that the anatomical data is closer to the actual situation of the patient. This design improves the applicability and personalization of the model, and ensures the precision and safety of the guide wire operation process. When the mobile terminal receives the physiological parameters of the patient, the system can call the corresponding personalized correction factors to adjust the standard anatomical structure parameters, thereby generating a personalized constraint boundary model. This personalized adjustment ensures that the anatomical features of each patient are accurately considered, avoiding potential problems caused by patient differences. In addition, in order to adapt to the changes in the operation process, the personalized constraint boundary model also adds a time attenuation factor, and dynamically adjusts the elastic coefficient of the constraint boundary with the operation time. This design can adjust in real time according to the changes of the operation time, ensure that the system can cope with complex situations in different operation environments, and improve the flexibility and adaptability of the system.

[0017] The second technical solution of the application is a medical gastrointestinal in-dwelling guide wire electronic trajectory analysis method, comprising the following steps:

[0018] S01: After the guide wire body enters the human digestive tract, the head sensing unit, the middle sensing unit and the tail sensing unit synchronously collect multi-dimensional physiological parameters to generate a raw sensing data stream containing a time stamp; S02: The data interface module receives the raw sensing data stream, performs analog-digital conversion and protocol packaging, generates a standardized sensing data frame and sends it through wireless communication; S03: The mobile terminal processing device parses the standardized sensing data frame to extract three-dimensional position coordinates, motion state, deformation degree, pH value, temperature, pressure parameters, and generate a multi-dimensional parameter matrix; S04: The trajectory calculation module is called to perform kinematic modeling on the multi-dimensional parameter matrix, and the constraint conditions of the anatomical matching database are combined to generate a real-time three-dimensional motion trajectory of the guide wire; S05: The real-time three-dimensional motion trajectory of the guide wire is compared with the standard anatomic path of the digestive tract for similarity, and the probability value of passing through the pylorus and the operation safety coefficient are calculated; S06: According to the probability value of passing through the pylorus and the operation safety coefficient, operation guidance information containing the best pushing direction, rotation angle, force control suggestion is generated, and is displayed in real time through the feedback output unit. The overall process of the medical gastrointestinal in-wire electronic trajectory analysis method is described in the application, and the steps executed by the above technical system provide systematic support for operation. First, after the guide wire body enters the human digestive tract, each sensing unit synchronously collects multi-dimensional physiological parameters to generate a raw data stream containing a time stamp. This process can obtain relevant physiological data in the human body in real time, providing detailed information support for subsequent analysis. After the data interface module receives the raw sensing data stream, it performs analog-digital conversion and protocol packaging to generate a standardized sensing data frame, which is sent to the mobile terminal through wireless communication. This process ensures the standardization and efficient transmission of data, improves the reliability and real-time performance of data transmission. After the mobile terminal receives the data, the system parses the standardized sensing data frame to extract three-dimensional position coordinates, motion state and other parameters to generate a multi-dimensional parameter matrix, providing a data basis for subsequent trajectory calculation. Through the trajectory calculation module, these data are kinematically modeled, and the constraint conditions in the anatomical matching database are combined to generate a real-time three-dimensional motion trajectory of the guide wire.

[0019] The present application has the following advantages:

[0020] (1) The guide wire body is the basic component of the entire method, serving as a support and connecting various sensing units. By arranging head, middle, and tail sensing units in the length direction of the guide wire, the state of the guide wire in the body can be comprehensively monitored. Each sensing unit is connected to the data interface module through internal signal transmission lines, ensuring real-time data transmission and processing. This design enables full monitoring of the guide wire, providing continuous and high-precision data acquisition, which facilitates subsequent data analysis and processing. In addition, due to the reasonable distribution of sensing units, different areas of the guide wire during movement can be effectively covered, ensuring that data acquisition at different positions is not missed or biased, thus providing comprehensive data support.

[0021] (2) The data interface module is located at the tail end of the guide wire body, and its main function is to receive the raw data collected by each sensing unit and convert these data into standardized data formats. This conversion process is crucial for subsequent data processing and analysis. After processing by the module, the raw data can be integrated into a unified data frame format with timestamps and sensor identifiers, ensuring data accuracy and consistency, and enabling efficient tracking and identification of data. In addition, the integrated design of the data interface module improves the compactness and stability of the method, reduces unnecessary cables and interface connections, and reduces the risk of connection failure and method failure.

[0022] (3) The mobile terminal processing device establishes a connection with the data interface module through a wireless communication protocol, receives and analyzes the sensing data frames, and extracts multi-dimensional sensing parameters. Through this step, complex data collected from the guide wire can be further processed to extract key motion states, deformations, spatial coordinates, and environmental parameters. This process is significant because, through wireless communication technology, data can be transmitted to the mobile terminal in real time, allowing operators to monitor the guide wire's state in real time anywhere and at any time. This step greatly improves the flexibility and operability of the method, avoiding the limitations of complex wired connections in traditional devices, making the method more convenient to use and maintain.

[0023] (4) The trajectory calculation module uses multi-dimensional sensing parameters to construct a kinematic model of the guide wire and perform iterative calculations to generate real-time three-dimensional motion trajectory data of the guide wire in the body. Through this model, the method can accurately simulate the guide wire's motion trajectory, providing accurate real-time data feedback to users. The design of this module ensures high precision and efficiency in trajectory calculation, enabling the processing of complex motion patterns, even in high-speed motion and complex environments, ensuring real-time updating of the guide wire's motion trajectory. This process not only enhances the dynamic response capability of the method but also makes real-time monitoring of the guide wire's motion possible, greatly improving the accuracy and safety of operations.

[0024] (5) The anatomical matching database stores standard data of human anatomical structure, and can compare the real-time three-dimensional motion trajectory data with these standard data. Through this step, the method can judge the matching degree of the specific position of the guide wire in the body with the human anatomical structure. Accurate matching can help the operator to judge whether the guide wire deviates from the predetermined path, and thus improve the operation precision. This standardized anatomical data provides a scientific basis for comparison, so that the method can not only accurately reflect the motion state of the guide wire, but also provide an evaluation result based on the human anatomical structure. This function has important significance for ensuring operation precision and improving safety, and can effectively avoid potential risks caused by deviation of the guide wire from the anatomical structure.

[0025] (6) The feedback output unit generates real-time operation guidance information according to the trajectory matching degree score, including voice prompts, text instructions and trajectory deviation indications, and outputs through the display interface and audio module of the mobile terminal. This design can provide detailed guidance information to the operator in real time, helping him to adjust the operation strategy in time. Through the dual prompt mode of voice and text, the communication of feedback information is more clear and intuitive, which can effectively improve the operator's response ability and reduce operation errors. At the same time, the instant indication of trajectory deviation enables the operator to quickly identify whether the guide wire deviates from the ideal trajectory and correct it in time. This method improves user experience while significantly improving the accuracy and safety of guide wire operation, ensuring the smooth progress of the operation process. BRIEF DESCRIPTION OF DRAWINGS

[0026] Fig. 1 It is a structural schematic diagram of the medical gastrointestinal tube built-in guide wire electronic trajectory analysis system of the present application.

[0027] Fig. 2 It is a step flowchart of the medical gastrointestinal tube built-in guide wire electronic trajectory analysis method of the present application. DETAILED DESCRIPTION

[0028] The present application will be further described below in conjunction with the drawings and examples, but not as the basis for limiting the present application.

[0029] The medical gastrointestinal tube built-in guide wire electronic trajectory analysis system comprises:

[0030] The guide wire body is sequentially provided with a head sensing unit, a middle sensing unit and a tail sensing unit along the length direction, and each sensing unit is connected to a data interface module through a signal transmission line inside the guide wire; the head sensing unit includes a three-axis accelerometer, a three-axis gyroscope and a pH sensor arranged along the guide wire axial direction, wherein: the three-axis accelerometer collects linear acceleration data of the guide wire head to generate an acceleration vector value containing X, Y and Z axis components; the three-axis gyroscope collects angular velocity data of the guide wire head to generate an angular velocity vector value containing roll angle, pitch angle and yaw angle; the pH sensor collects hydrogen ion concentration data of the environment around the guide wire head to generate a pH value measurement result; the head sensing unit synchronizes the acceleration vector value, the angular velocity vector value and the pH value measurement result with a time stamp to generate a head sensing data group, which is sent to the data interface module through the signal transmission line; the middle sensing unit includes a strain sensing array, a pressure sensor and a temperature and humidity sensor, wherein: the strain sensing array is composed of four strain gauges uniformly distributed along the circumference of the guide wire, collects tensile, compressive and bending deformation data of the middle part of the guide wire to generate a deformation stress value; the pressure sensor collects pressure data generated by the contact between the guide wire and the digestive tract tissue to generate a pressure characteristic value containing pressure amplitude and pressure duration; the temperature and humidity sensor collects temperature and humidity data of the environment around the middle part of the guide wire to generate an environmental parameter value; the middle sensing unit fuses the deformation stress value, the pressure characteristic value and the environmental parameter value to generate a middle sensing data group, which is sent to the data interface module through the signal transmission line; the working process of the strain sensing array includes: each strain gauge generates resistance change when the guide wire deforms, and converts the resistance change into a voltage signal through a Wheatstone bridge to generate an original strain electric signal; the original strain electric signal is filtered and amplified to remove high-frequency noise and baseline drift to generate a filtered strain signal; the filtered strain signal is converted into corresponding deformation displacement according to a preset strain-deformation conversion coefficient, which includes radial bending amount and axial expansion amount; the bending center coordinates and bending angle of the guide wire section are calculated by combining the deformation displacement of the four strain gauges to generate deformation data containing spatial bending direction; the calculation process of the deformation data includes: collecting the deformation displacement of the four strain gauges, establishing a polar coordinate system with the guide wire axis as the origin to generate polar coordinate position parameters of each strain gauge; based on the polar coordinate position parameters and the corresponding deformation displacement, the bending arc of the guide wire section is fitted through the least square method to calculate the curvature radius and the center coordinates of the arc; the bending direction vector of the guide wire is determined according to the curvature radius and the center coordinates, and a three-dimensional deformation feature vector is generated by combining the axial expansion amount; the three-dimensional deformation feature vector is associated with the time stamp to form deformation data changing with time; the tail sensing unit includes a miniature pressure sensor and an electromagnetic positioning sensor, wherein: the miniature pressure sensor collects push pressure data received by the guide wire tail to generate a pressure value; the electromagnetic positioning sensor collects position information of the guide wire tail based on the change of the surrounding electromagnetic field to generate a position data group containing X, Y and Z axis coordinates;The tail sensing unit integrates the pressure value and position data set to generate a tail sensing data set, which is sent to the data interface module through a signal transmission line;

[0031] The data interface module is integrated at the tail end of the guide wire body, used to receive the original sensing data collected by each sensing unit, and convert the original sensing data into a standardized data format to generate a sensing data frame containing a data collection timestamp and a sensor identifier. The data interface module includes: a signal conditioning circuit that performs analog-to-digital conversion on the analog signals output by each sensing unit to generate 16-bit digital signals; a data packaging unit that combines the 16-bit digital signals with the sensor ID, sampling frequency, and check code according to a pre-set protocol to generate a fixed-length sensing data frame; a wireless communication module that supports Bluetooth 5.0 protocol and IEEE802.11n protocol, can automatically switch communication modes according to signal strength, and sends the sensing data frame to the mobile terminal processing device at a frequency of 250Hz; an energy consumption management unit that monitors the current consumption of each module, dynamically adjusts the working voltage according to the data transmission volume, and generates a status monitoring frame containing the remaining power and transmission rate; a mobile terminal processing device that establishes a connection with the data interface module through a wireless communication protocol, receives the sensing data frame and obtains multi-dimensional sensing parameters, including three-dimensional spatial coordinate parameters, motion state parameters, deformation parameters, and environmental parameters;

[0032] The mobile terminal processing device further comprises a risk warning module, and a working process of the risk warning module comprises: monitoring a motion state of the guide wire body in real time according to the multi-dimensional sensing parameters, identifying a potential operation risk in combination with a preset risk threshold; when it is monitored that a risk index exceeds the threshold, a risk warning signal is generated, and a risk type and a risk position information are transmitted to the feedback output unit, so as to timely inform an operator through a voice prompt, an interface warning mode; a trajectory calculation module, the trajectory calculation module constructs a guide wire kinematics model based on the multi-dimensional sensing parameters, and generates real-time three-dimensional motion trajectory data of the guide wire in the body through model iterative calculation; the calculation process of the trajectory calculation module comprises: Kalman filtering processing is performed on three-dimensional space coordinate parameters to eliminate measurement noise and generate a smoothed coordinate sequence; based on the smoothed coordinate sequence and the motion state parameters, instantaneous velocities and accelerations of each feature point on the guide wire are calculated to generate a kinematics parameter set; in combination with the diameter data of the digestive tract lumen in the anatomic matching database, boundary constraint processing is performed on the kinematics parameter set to generate a constrained motion trajectory; the constrained motion trajectory is fitted by using a Bezier curve to generate a continuous three-dimensional trajectory curve and a corresponding curvature rate of change; the boundary constraint processing process comprises: the digestive tract lumen cross-section data corresponding to the current position is called from the anatomic matching database to generate a constraint boundary model containing a lumen radius and a central axis; the coordinate data in the kinematics parameter set is compared with the constraint boundary model to identify abnormal coordinate points that exceed the lumen boundary; the abnormal coordinate points are modified by using a cubic spline interpolation algorithm to generate modified coordinate values that conform to the physiological structure; the deviation amount of the coordinate values before and after the modification is calculated, and a boundary constraint warning signal is generated if the deviation amount exceeds a preset threshold; the construction process of the constraint boundary model comprises: a three-dimensional model of the digestive tract is reconstructed based on CT image data, a central axis and a cross-section profile of each lumen are extracted to generate standard anatomic structure parameters; the standard anatomic structure parameters are statistically analyzed to calculate anatomic difference coefficients of different age groups and body types to generate personalized correction factors; the mobile terminal processing device receives patient physiological parameters input by a user, calls corresponding personalized correction factors to adjust the standard anatomic structure parameters, and generates a personalized constraint boundary model; a time decay factor is added to the personalized constraint boundary model, and the elastic coefficient of the constraint boundary is dynamically adjusted with the operation time; the anatomic matching database stores standard anatomic structure data corresponding to the human digestive tract, the mobile terminal processing device calls the anatomic matching database, compares the real-time three-dimensional motion trajectory data with the standard anatomic structure data, and generates a trajectory matching degree score; the feedback output unit generates real-time operation guidance information comprising a voice prompt, a text description and a trajectory deviation indication according to the trajectory matching degree score, and outputs the real-time operation guidance information through a display interface and an audio module of the mobile terminal processing device.

[0033] The medical gastrointestinal tube built-in guide wire electronic trajectory analysis method comprises the following steps: S01: after the guide wire main body enters the human digestive tract, the head sensing unit, the middle sensing unit and the tail sensing unit synchronously collect multi-dimensional physiological parameters to generate original sensing data streams containing time stamps; S02: the data interface module receives the original sensing data streams, performs analog-digital conversion and protocol packaging, generates standardized sensing data frames and transmits them through wireless communication; S03: the mobile terminal processing device analyzes the standardized sensing data frames to extract three-dimensional position coordinates, motion states, deformation degrees, pH values, temperatures and pressure parameters, and generates a multi-dimensional parameter matrix; S04: the trajectory calculation module is called to perform kinematic modeling on the multi-dimensional parameter matrix, and the constraint conditions of the anatomic matching database are combined to generate a guide wire real-time three-dimensional motion trajectory; S05: the guide wire real-time three-dimensional motion trajectory is compared with the standard anatomic path of the digestive tract in terms of similarity, the probability value of passing through the pylorus and the operation safety coefficient are calculated; and S06: according to the probability value of passing through the pylorus and the operation safety coefficient, operation guidance information containing the best pushing direction, the rotation angle and the force control suggestion is generated, and the operation guidance information is displayed in real time through the feedback output unit.

[0034] To achieve the above-mentioned purpose, please refer to Figs. 1-2 The embodiment one of the present application provides a medical gastrointestinal tube built-in guide wire electronic trajectory analysis system, as shown in the figure, which comprises: Fig. 1

[0035] The guide wire main body is sequentially provided with the head sensing unit, the middle sensing unit and the tail sensing unit along the length direction, and each sensing unit is connected to the data interface module through a signal transmission line in the guide wire.

[0036] In the embodiment of the present application, the guide wire main body is made of nickel-titanium alloy material with a diameter of 0.8 mm, and the length is 1500 mm. The head sensing unit is arranged at a position 10 mm from the top end along the length direction, the middle sensing unit is arranged at a position 100 mm from the top end, and the tail sensing unit is arranged at a position 1400 mm from the top end. The head sensing unit encapsulates a three-axis accelerometer (measurement range ±2000 mGal), a three-axis gyroscope (measurement range ±300 degrees / second) and a pH sensor (measurement range 1.0-14.0 pH). The middle sensing unit comprises four circumferentially distributed strain gauges (sensitivity coefficient 2.0), a piezoresistive pressure sensor (measurement range 0-100 kPa) and a temperature and humidity sensor (temperature 30-40℃, humidity 30%-95%RH). The tail sensing unit integrates a position encoder (resolution 0.1 mm). Each sensing unit is connected to the data interface module through three copper core shielding lines with a diameter of 0.05 mm in the guide wire. The signal line is wrapped with a polytetrafluoroethylene insulating layer to ensure that the signal transmission attenuation is less than 1% when the bending radius is 5 mm.

[0037] ​a data interface module integrated at the tail end of the guide wire body, configured to receive raw sensing data collected by each sensing unit and convert the raw sensing data into a standardized data format to generate a sensing data frame containing a data collection timestamp and a sensor identifier;

[0038] In the embodiment of the present application, the data interface module adopts a cylindrical structure with a diameter of 3 mm and a length of 20 mm, and is integrated at the tail end of the guide wire at a position of 1450-1470 mm. The module contains a 16-bit analog-to-digital converter (conversion rate of 1 MHz), a microcontroller (main frequency of 80 MHz), and a Bluetooth 5.0 chip. When receiving raw sensing data, the microcontroller reads the signals by sensor type in time, with the head accelerometer signal collected every 10 ms and the middle strain gauge signal collected every 5 ms, and the signals are synchronized by timestamp (accuracy of 1 ms). During the conversion process, the 0-600 mV signal of the pH sensor is mapped to a 0-65535 digital value, and the 0-100 kPa signal of the pressure sensor is mapped to a 0-65535 digital value. The generated sensing data frame is fixed at 64 bytes, the first 2 bytes are the sensor identifier (head 0x0001, middle 0x0002), the 3-6 bytes are the timestamp (millisecond-level Unix time), and the 7-64 bytes are the data field, with CRC16 check to ensure data integrity, and the check value is stored in the last 2 bytes of the frame.

[0039] a mobile terminal processing device, which is connected with the data interface module through a wireless communication protocol, receives the sensing data frame and obtains multi-dimensional sensing parameters, including three-dimensional spatial coordinate parameters, motion state parameters, deformation parameters, and environmental parameters;

[0040] In the embodiment of the present application, the mobile terminal processing device (7-inch touch screen tablet) automatically scans the Bluetooth device after starting up, establishes a connection with the data interface module (the pairing code is fixed as 1234), the communication rate is 2 Mbps, and the receiving interval is 4 milliseconds. When the sensing data frame is parsed, the parameters are extracted according to the frame structure: the X-axis acceleration (bytes 7-8) and Y-axis acceleration (bytes 9-10) are extracted from the header sensing unit data field, and are converted into milligal through the formula "actual value = (digital value - 32768) x 2000 / 32768"; the gyroscope data (bytes 11-14) are extracted and converted into degrees / second. The three-dimensional space coordinates are calculated by twice integration of acceleration, the sampling frequency is 100 Hz, the integration time interval is 0.01 second, the initial coordinates are (0, 0, 0), and (12.5, 8.3, 5.6) millimeters are obtained after 5 times of integration. The motion state parameters include the pitch angle (+12 degrees) and the yaw angle (-8 degrees) obtained by integrating the angular velocity; the deformation parameter is the radial bending amount (0.35 millimeters) calculated by the strain gauge; and the environmental parameters include the pH value (2.35), the temperature (37.2℃), and the humidity (78% RH). All the parameters are stored as a 20x8 matrix in the order of sampling time, and each row corresponds to 8 types of parameters at a time.

[0041] a trajectory calculation module, the trajectory calculation module constructs a guide wire kinematics model based on multi-dimensional sensing parameters, and generates real-time three-dimensional motion trajectory data of the guide wire in the body through iterative calculation of the model;

[0042] In the embodiment of the present application, the trajectory calculation module runs on the mobile terminal processor (four cores, 1.8 GHz), adopts a multi-body dynamics model, discretizes the guide wire into 20 rigid segments, and connects the segments through rotary joints. After inputting the multi-dimensional sensing parameters, the three-dimensional coordinates are first subjected to Kalman filtering (the state equation includes position, velocity, and acceleration), the process noise variance is 0.01 millimeter² / second², the observation noise variance is 0.1 millimeter², and high-frequency jitter is eliminated after 5 times of iteration. Based on the filtered coordinates (12.5, 8.3, 5.6), (12.7, 8.5, 5.7), etc., the distance between adjacent points (0.28 millimeters) and the time interval (0.01 second) are calculated, and the instantaneous speed is 28 millimeters / second. Combined with the middle deformation parameter (bending angle 44.4 degrees), the kinematics equation (step length 0.001 second) is solved through the Runge-Kutta method, the position every 0.01 second is iteratively calculated, real-time three-dimensional motion trajectory data containing 1000 points are generated, and each point contains X, Y, Z coordinates (accuracy 0.01 millimeter) and a time stamp.

[0043] an anatomical matching database, the anatomical matching database stores standard anatomical structure data corresponding to the human digestive tract, the mobile terminal processing device calls the anatomical matching database, compares the real-time three-dimensional motion trajectory data with the standard anatomical structure data, and generates a trajectory matching degree score;

[0044] In the embodiment of the present application, the anatomical matching database is stored in the local storage (capacity 16 GB) of the mobile terminal, and contains the standardized processing results of 1000 cases of adult digestive tract CT reconstruction data. It is stored in segments according to the esophagus (25 mm in diameter), the stomach body (50 mm in diameter), the pylorus (10 mm in diameter), and the duodenum (30 mm in diameter). Each segment contains the central axis coordinates (1 mm interval) and the cross-sectional profile (100 points). When called, the stomach body standard data is matched according to the real-time position of the guide wire (judged by pH value, pH < 3 in the stomach), the Euclidean distance between the real-time trajectory and the standard central axis is calculated (average 0.2 mm), and the trajectory matching degree score is calculated using the percentage system. The formula is "100-(average distance / maximum allowed deviation) x 100", the maximum allowed deviation is 5 mm, and the score is 100-(0.2 / 5) x 100 = 96 points. At the same time, the speed matching degree (the ratio of the current speed 28 mm / s to the standard speed 25 mm / s is 0.93) is calculated, and the comprehensive score = trajectory matching degree x 0.7 + speed matching degree x 0.3 = 96 x 0.7 + 93 x 0.3 = 95.1 points.

[0045] The feedback output unit generates real-time operation guidance information containing voice prompts, text instructions, and trajectory deviation indications according to the trajectory matching degree score, and outputs it through the display interface and audio module of the mobile terminal processing device.

[0046] In the embodiment of the present application, the feedback output unit is realized by the mobile terminal software module, which contains display driver and audio encoding module. When the trajectory matching degree score is 95.1 points, the real-time operation guidance information is generated: the text instruction is displayed on the left side of the screen (black Songti 12 font), the content is "currently located in the stomach body, the trajectory deviation is 0.2 mm"; the trajectory deviation indication is displayed through the three-dimensional model in the center of the screen, the standard path is a green line, the actual trajectory is a red line, and the deviation is marked with a yellow flashing marker; the voice prompt is generated by the text-to-speech engine (female voice, speed 150 words / minute), the content is "please rotate clockwise by 3 degrees, increase the pushing force by 0.5 grams", and it is output through the built-in loudspeaker (volume 80 decibels). The vibration prompt is realized by the built-in motor of the terminal, which vibrates every 3 seconds (100 ms vibration + 200 ms pause), and lasts until the score is higher than 98 points, ensuring that the operator synchronously obtains multi-modal feedback.

[0047] The head sensing unit includes a three-axis accelerometer, a three-axis gyroscope, and a pH sensor arranged along the axis of the guide wire. The three-axis accelerometer collects the linear acceleration data of the head of the guide wire, generating an acceleration vector value containing X, Y, and Z axis components; the three-axis gyroscope collects the angular velocity data of the head of the guide wire, generating an angular velocity vector value containing X, Y, and Z axis components; and the pH sensor collects the pH value of the guide wire head, generating a pH value.

[0048] In the embodiment of the present application, during the process of the guide wire in the medical gastrointestinal tube entering the stomach of the patient, the three-axis accelerometer collects the linear acceleration data of the head of the guide wire at a sampling frequency of 100 times per second. The accelerometer is manufactured by MEMS technology, and the measurement range is set to-2000 to +2000 milligal, with a resolution of 1 milligal, which can accurately capture the subtle acceleration changes of the guide wire when moving in the gastrointestinal tract. When the head of the guide wire passes through the esophageal inlet, an upward thrust is generated due to muscle contraction, and the X-axis (along the axial direction of the guide wire) detects an acceleration of +350 milligal; after entering the stomach, lateral swinging is generated due to gastrointestinal peristalsis, and the Y-axis (horizontal direction perpendicular to the axial direction of the guide wire) appears an acceleration of-120 milligal; when passing through the pylorus of the stomach, the guide wire is squeezed by the circular muscle, and the Z-axis (vertical direction perpendicular to the axial direction of the guide wire) records an acceleration of +280 milligal. After each sampling, the real-time values of the X, Y and Z axes are combined in the format of“X-axis value, Y-axis value, Z-axis value” by the accelerometer, to generate an acceleration vector value such as“350, -120, 280”, which provides basic data for subsequent analysis of the motion trajectory of the guide wire.

[0049] The three-axis gyroscope collects the angular velocity data of the head of the guide wire, to generate an angular velocity vector value containing the roll angle, pitch angle and yaw angle;

[0050] In the embodiment of the present application, the three-axis gyroscope works synchronously with the three-axis accelerometer to collect the angular velocity data of the head of the guide wire at a frequency of 100 times per second. The gyroscope adopts optical fiber gyro technology, and the measurement range is-300 to +300 degrees per second, with a zero drift controlled within 0.1 degree per hour, to ensure the long-term stability of the angle measurement. When the guide wire makes a straight advance in the esophagus, the roll angle (rotation angle around the axial direction of the guide wire) changes very little and is maintained within 0.5 degrees per second; when turning at the bottom of the stomach, the pitch angle (up and down swinging angle of the head of the guide wire) changes by +15 degrees per second; when passing through the curved segment of the duodenum, the yaw angle (left and right swinging angle of the head of the guide wire) reaches-20 degrees per second. The gyroscope integrates the angular velocity values of the three angles in the fixed format of“roll angle, pitch angle, yaw angle”, to generate an angular velocity vector value such as“0.3, 15, -20”, which completely records the rotation motion state of the head of the guide wire in the three-dimensional space, and together with the acceleration data, constructs a kinematic model of the guide wire.

[0051] The pH sensor collects the hydrogen ion concentration data of the environment around the head of the guide wire, to generate a pH value measurement result;

[0052] In the embodiment of the present application, the pH sensor adopts ion-sensitive field effect transistor (ISFET) technology, the measurement range is set to 1.0-14.0 pH units, the resolution is 0.01 pH unit, the response time is less than 1 second, the pH sensor can quickly reflect the pH difference in different regions of the gastrointestinal tract, the sensor head is covered with a special hydrogen ion sensitive membrane, when the guide wire is in the esophagus, the surrounding environment is neutral and slightly alkaline, the pH value is stable at 7.2±0.1; after entering the stomach cavity, the pH value drops to 2.3±0.2 due to the action of gastric acid; after passing through the pylorus into the duodenum, the pH value rises to 6.5±0.3 due to the influence of pancreatic juice neutralization. The pH sensor collects data every 500 milliseconds, retains two decimal places of the measured value, and generates pH measurement results such as "2.35" and "6.52", which accurately locate the anatomical position of the guide wire head in the gastrointestinal tract through the change of pH value, and provide anatomical reference for trajectory analysis.

[0053] The head sensing unit synchronizes the acceleration vector value, angular velocity vector value and pH measurement result with a time stamp, generates a head sensing data group, and sends it to the data interface module through a signal transmission line.

[0054] In the embodiment of the present application, the head sensing unit is built-in with a high-precision clock chip, the clock error is controlled within ±1 second per day, and a unified time stamp is provided for the acceleration vector value, angular velocity vector value and pH measurement result. When data is collected each time, the clock chip generates a time mark in the format of "year-month-day hour: minute: second.millisecond", such as "2024-06-15 09:30:45.123". The sensing unit combines the three groups of data under the same time stamp according to the structure of "time stamp|acceleration vector value|angular velocity vector value|pH value", forming a head sensing data group, for example "2024-06-15 09:30:45.123|350,-120,280|0.3,15,-20|2.35". The data group is transmitted through an internal shielded twisted pair line with a wire diameter of 0.1 mm and an impedance controlled at 50 ohms, and the transmission rate is fixed at 115200 bits / s, ensuring that the data is not disturbed and delayed during transmission in the guide wire, and finally sent to the data interface module, providing a good multi-dimensional data basis with good synchronization for subsequent electronic trajectory analysis.

[0055] The middle sensing unit includes a strain sensing array, a pressure sensor and a temperature and humidity sensor, wherein: the strain sensing array is composed of 4 strain gauges uniformly distributed along the circumference of the guide wire, which collects the tensile, compressive and bending deformation data of the middle part of the guide wire to generate a deformation stress value;

[0056] In the embodiment of the present application, the strain sensing array adopts metal foil strain gauges, 4 strain gauges are evenly distributed at a 90-degree angle along the circumference of the guide wire and are pasted on the outer surface of the middle part of the guide wire, the sensitivity coefficient of the strain gauges is 2.0, the measurement range is -2000με to +2000με, and the resolution reaches 1με. When the guide wire is pushed into the esophagus, it is subjected to forward tension in the axial direction, and the strain gauges in the 0-degree and 180-degree directions detect +350με tensile deformation; at the bending part of the gastric body, the guide wire bends laterally, the strain gauge in the 90-degree direction appears +520με tensile deformation, and the strain gauge in the 270-degree direction produces -480με compression deformation. Each strain gauge converts the deformation data into an electrical signal, which is converted into a voltage signal through a Wheatstone bridge circuit, and then the specific strain value is obtained through analog-digital conversion. The system combines the values of the four strain gauges in the format of "0-degree strain value, 90-degree strain value, 180-degree strain value, 270-degree strain value" to generate deformation stress values such as "350, 520, 350, -480", which accurately reflect the tensile, compressive and bending state of the middle part of the guide wire in three-dimensional space.

[0057] The pressure sensor collects pressure data generated when the guide wire contacts the digestive tract tissue to generate pressure characteristic values including pressure amplitude and pressure duration;

[0058] In the embodiment of the present application, the pressure sensor adopts a piezoresistive thin film sensor, the sensing area is 5mm×5mm, the measurement range is 0kPa to 100kPa, the resolution is 0.1kPa, and the response time is less than 5ms. When the middle part of the guide wire contacts the esophageal wall, the sensor detects a pressure of 5kPa with a duration of 2 seconds; when passing through the cardia, the pressure suddenly rises to 35kPa due to the squeezing of the sphincter muscle, with a duration of 1.5 seconds; when rubbing with peristalsis in the antrum, an intermittent pressure of 12kPa appears, each lasting for 0.8 seconds and separated by 1.2 seconds. The sensor records the pressure amplitude and duration in a fixed format of "pressure amplitude, duration" to generate pressure characteristic values such as "5, 2" "35, 1.5" "12, 0.8", which completely record the pressure change law when the guide wire contacts the digestive tract tissue, providing data support for judging the interaction strength between the guide wire and the tissue.

[0059] The temperature and humidity sensor collects temperature and humidity data of the environment around the middle part of the guide wire to generate environment parameter values;

[0060] In the embodiment of the present application, the temperature detection in the temperature and humidity sensor adopts a thermocouple sensor, the measurement range is 30-40 DEG C, and the accuracy is ± 0.1 DEG C; the humidity detection adopts a capacitive humidity sensor, the measurement range is 30-95% RH, the accuracy is ± 2% RH, and the sampling frequency is 10 times per second. When the middle part of the guide wire is located in the esophagus, the surrounding temperature is stabilized at 36.5 DEG C, and the humidity is 45% RH; after entering the stomach cavity, the temperature rises to 37.2 DEG C due to the influence of gastric acid evaporation, and the humidity increases to 78% RH; when passing through the duodenum, the temperature is maintained at 37.0 DEG C, and the humidity decreases to 62% RH. The sensor integrates the temperature and humidity data in the format of 'temperature value, humidity value' to generate environmental parameter values such as '36.5, 45' and '37.2, 78', which reflect the temperature and humidity characteristics of the digestive tract environment where the middle part of the guide wire is located in real time, and provide a basis for analyzing the physiological environment in different regions.

[0061] The middle sensing unit fuses the deformation stress value, the pressure characteristic value and the environmental parameter value to generate a middle sensing data group, and sends the middle sensing data group to the data interface module through a signal transmission line.

[0062] In the embodiment of the present application, the middle sensing unit adopts a Kalman filtering algorithm to fuse the deformation stress value, the pressure characteristic value and the environmental parameter value in the time dimension. Taking the data set at the same sampling time as an example, the deformation stress value is first processed by weighted average to highlight the strain data in the bending direction; the pressure characteristic value is processed by time domain peak value extraction to retain the maximum pressure and the corresponding duration; and the environmental parameter value is processed by sliding average filtering to eliminate instantaneous fluctuations. The fused data are combined in the structure of 'deformation stress value | pressure characteristic value | environmental parameter value', such as '350, 520, 350, -480 | 35, 1.5 | 37.2, 78'. The data group is transmitted through the same shielded twisted pair as the head sensing unit, the wire diameter is 0.1 mm, the impedance is 50 ohms, the transmission rate is 115200 bits / s, the signal attenuation in the complex environment inside the guide wire is avoided, and finally the data group is completely sent to the data interface module to cooperatively build a complete state model of the guide wire in the digestive tract with the head sensing data.

[0063] The working process of the strain sensing array includes: each strain gauge generates resistance change when the guide wire deforms, and converts the resistance change into a voltage signal through a Wheatstone bridge to generate an original strain electric signal;

[0064] In the embodiment of the present application, when the guide wire is laterally bent at the gastric body curvature, the four metal foil strain gauges uniformly distributed circumferentially along the guide wire will be deformed. The strain gauges in the 0-degree and 180-degree directions are in a tensile state, the metal foil grid length increases, and the resistance values increase from the initial 120 ohms to 120.21 ohms and 120.20 ohms, respectively; the 90-degree direction strain gauge has the maximum tensile amplitude, and the resistance increases to 120.31 ohms; the 270-degree direction strain gauge is compressed, the metal foil grid length shortens, and the resistance decreases to 119.71 ohms. These resistance changes are connected to a Wheatstone bridge circuit, the bridge adopts a four-arm balanced structure, the supply voltage is fixed at 5 volts, and a differential voltage signal is output when the resistance is unbalanced. According to the measurement, the 0-degree strain gauge corresponds to a bridge arm output of +2.3 millivolts, the 90-degree corresponds to a bridge arm output of +3.5 millivolts, the 180-degree corresponds to a bridge arm output of +2.2 millivolts, and the 270-degree corresponds to a bridge arm output of -3.2 millivolts, forming an original strain electrical signal containing four direction components, directly reflecting the real-time deformation state of each strain gauge.

[0065] The original strain electrical signal is filtered and amplified to remove high-frequency noise and baseline drift, and a filtered strain signal is generated;

[0066] In the embodiment of the present application, the original strain electrical signal is first filtered through a second-order Butterworth low-pass filter with a cutoff frequency of 10 Hz to filter out high-frequency noise above 20 Hz generated by the digestive tract peristalsis. Then, an instrument amplifier is connected, with an amplification factor of 1000, to amplify the millivolt-level signal to a volt-level signal. Among them, the 0-degree direction signal is amplified from 2.3 millivolts to 2.3 volts, the 90-degree direction is amplified from 3.5 millivolts to 3.5 volts, the 180-degree direction is amplified from 2.2 millivolts to 2.2 volts, and the 270-degree direction is amplified from -3.2 millivolts to -3.2 volts. To eliminate baseline drift, a direct current compensation circuit is used to control the baseline error of each channel to within ±0.01 volts through a precision potentiometer. The processed filtered strain signal is converted to digital through a 16-bit analog-to-digital converter at a conversion rate of 100 times per second, ensuring that the signal is not distorted, and finally generating a digital signal sequence like "2.3, 3.5, 2.2, -3.2" to provide a stable input for subsequent deformation calculation.

[0067] According to the preset strain-deformation conversion coefficient, the filtered strain signal is converted into the corresponding deformation displacement, which includes the radial bending amount and the axial stretching amount;

[0068] In the embodiment of the present application, the filtered strain signals are converted according to a preset strain-deformation conversion coefficient (the coefficient is determined by a calibration experiment, 1 volt of electric signal corresponds to 100με strain, and 1με strain corresponds to 0.001 millimeter deformation displacement). The 90-degree direction filtered signal is 3.5 volts, corresponding to 350με strain, and the calculated radial bending amount is 350x0.001=0.35 millimeters; the 270-degree direction signal is -3.2 volts, corresponding to -320με strain, and the radial bending amount is -0.32 millimeters; the 0-degree and 180-degree direction signals correspond to 230με and 220με strain, and the axial stretching amounts are 0.23 millimeters and 0.22 millimeters, respectively. In the conversion process, a linear interpolation method is used to strictly correspond the electric signals and the deformation values, so as to ensure that the 0-volt signal corresponds to 0 displacement, the positive voltage corresponds to the stretching displacement, and the negative voltage corresponds to the compression displacement. Finally, the deformation displacement amounts of the strain gauges are generated: 0 degree (0.23 millimeters, 0), 90 degree (0, 0.35 millimeters), 180 degree (0.22 millimeters, 0), and 270 degree (0, -0.32 millimeters), wherein the former is the axial stretching amount, and the latter is the radial bending amount.

[0069] The bending center coordinates and the bending angle of the guide wire cross section are calculated by combining the deformation displacement amounts of the four strain gauges, and the deformation data containing the spatial bending direction are generated.

[0070] In the embodiment of the present application, the bending center coordinates are calculated by combining the deformation displacement amounts of the four strain gauges and taking the guide wire cross section center as the origin of the two-dimensional coordinate system. The vector synthesis method is used to obtain the coordinate of the bending center in the Y-axis direction as (0.35 millimeters+(-0.32 millimeters)) / 2=0.015 millimeters by using the radial bending amounts of the 90-degree and 270-degree directions. The coordinate of the bending center in the X-axis direction is 0 because the radial bending amounts of the 0-degree and 180-degree directions are 0, that is, the bending center coordinates are (0, 0.015 millimeters). The bending angle is calculated by the arc length formula. The guide wire radius is 0.5 millimeters, and the central angle corresponding to the maximum radial bending amount 0.35 millimeters is arcsin(0.35 / 0.5)=44.4 degrees. The spatial bending direction is determined as the 90-degree direction (that is, the guide wire head bends to the left of the patient) by combining the deformation differences of the directions. The finally generated deformation data contain the bending center coordinates (0, 0.015 millimeters), the bending angle 44.4 degrees, and the bending direction 90 degrees, which completely describe the bending state of the guide wire cross section in the three-dimensional space and provide key parameters for reconstructing the guide wire trajectory.

[0071] The calculation process of the deformation data includes: collecting the deformation displacement amounts of the four strain gauges, establishing a polar coordinate system taking the guide wire axis as the origin, and generating the polar coordinate position parameters of the strain gauges;

[0072] In the embodiment of the present application, after collecting the deformation displacement of the four strain gauges, a polar coordinate system is established with the guide wire axis as the origin, the radial distance of the polar coordinate is fixed at 0.5 mm of the guide wire radius, and the angle is set according to the distribution position of the strain gauge. The 0-degree strain gauge is located in the positive direction of the polar axis (the positive front direction projected along the guide wire axis), and the polar coordinate parameters are (0.5 mm, 0 degrees); the 90-degree strain gauge is located in the 90-degree direction of the polar coordinate (left side), and the parameters are (0.5 mm, 90 degrees); the 180-degree strain gauge is located in the 180-degree direction of the polar coordinate (positive back direction), and the parameters are (0.5 mm, 180 degrees); and the 270-degree strain gauge is located in the 270-degree direction of the polar coordinate (right side), and the parameters are (0.5 mm, 270 degrees). The deformation displacement of each strain gauge is associated with the polar coordinate position, 0 degrees corresponds to (0.23 mm axial stretching, 0 radial bending, 0.5 mm, 0 degrees), 90 degrees corresponds to (0 axial stretching, 0.35 mm radial bending, 0.5 mm, 90 degrees), 180 degrees corresponds to (0.22 mm axial stretching, 0 radial bending, 0.5 mm, 180 degrees), and 270 degrees corresponds to (0 axial stretching, -0.32 mm radial bending, 0.5 mm, 270 degrees), forming a polar coordinate position parameter matrix, which provides a spatial position reference for subsequent circular arc fitting.

[0073] Based on the polar coordinate position parameters and the corresponding deformation displacement, the bending circular arc of the guide wire cross section is fitted by the least square method, and the curvature radius and the center coordinates of the circular arc are calculated.

[0074] In the embodiment of the present application, based on the polar coordinate position parameters and the deformation displacement, the spatial positions of the strain gauges are converted into rectangular coordinates. The position of the 0-degree strain gauge is (0.5 mm x cos 0 degrees + 0.23 mm, 0.5 mm x sin 0 degrees + 0) = (0.73 mm, 0); the position of the 90-degree strain gauge is (0.5 mm x cos 90 degrees + 0, 0.5 mm x sin 90 degrees + 0.35 mm) = (0, 0.85 mm); the position of the 180-degree strain gauge is (0.5 mm x cos 180 degrees + 0.22 mm, 0.5 mm x sin 180 degrees + 0) = (-0.28 mm, 0); and the position of the 270-degree strain gauge is (0.5 mm x cos 270 degrees + 0, 0.5 mm x sin 270 degrees + (-0.32 mm)) = (0, -0.82 mm). The bending circular arc passing through these four points is fitted by the least square method, the circular arc equation is set as (x-a)²+(y-b)²=r², the coordinate values are substituted to calculate the center coordinates (a=0.02 mm, b=0.01 mm), the curvature radius r=0.83 mm, the fitting error is controlled within 0.01 mm, and it is ensured that the circular arc can accurately reflect the bending state of the guide wire cross section.

[0075] The bending direction vector of the guide wire is determined according to the curvature radius and the center coordinates, and a three-dimensional deformation feature vector is generated in combination with the axial stretching amount.

[0076] In the embodiment of the present application, the bending direction vector is calculated according to the radius of curvature of 0.83 mm and the center coordinates of (0.02 mm, 0.01 mm). The vector of the center of the circle pointing to the origin of the guide wire cross section is (0-0.02 mm, 0-0.01 mm) = (-0.02 mm, -0.01 mm), and the reverse direction of the vector is the bending direction vector, which is standardized to (0.89, 0.45) after standardization, corresponding to the polar coordinate angle of 24.2 degrees, indicating that the guide wire bends to the left side in front of the 90-degree direction by 24.2 degrees. The average of the axial stretching amount of the 0-degree and 180-degree strain gauges is (0.23 mm + 0.22 mm) / 2 = 0.225 mm, which is taken as the stretching characteristic along the axial direction of the guide wire. The bending direction vector and the axial stretching amount are combined to generate a three-dimensional deformation characteristic vector (0.225 mm, 0.89, 0.45), in which the first item is the axial stretching amount, and the last two items are the x and y components of the bending direction vector, which completely describe the deformation characteristics of the guide wire in three-dimensional space.

[0077] The three-dimensional deformation characteristic vector is associated with the time stamp to form deformation data that changes over time.

[0078] In the embodiment of the present application, the clock module built-in the guide wire generates time stamps in milliseconds, which are recorded synchronously with the three-dimensional deformation characteristic vector. When the deformation of the guide wire at the bending site of the gastric body reaches the maximum, the time stamp is recorded as 1628745623120 milliseconds, and the three-dimensional deformation characteristic vector at this time is (0.225 mm, 0.89, 0.45). The two are associated in the format of "time stamp | axial stretching amount | bending direction x | bending direction y" to form the record of "1628745623120 | 0.225 | 0.89 | 0.45". Every 10 milliseconds generates an associated record, and 100 continuous records form a time sequence, in which the characteristic vector at the initial time (1628745623000 milliseconds) is (0.1 mm, 0.1, 0.05), which gradually changes to the maximum deformation value as the bending degree increases, and gradually recovers to (0.05 mm, 0.02, 0.01) as the guide wire advances. These deformation data that changes over time completely presents the whole process deformation law of the guide wire through the bending site of the gastric body, and provides dynamic parameters for subsequent trajectory analysis.

[0079] The tail sensing unit includes a micro pressure sensor and an electromagnetic positioning sensor, wherein: the micro pressure sensor collects the pushing pressure data received by the tail of the guide wire to generate a pressure value; the electromagnetic positioning sensor collects the position information of the tail of the guide wire based on the change of the surrounding electromagnetic field to generate a position data set containing X, Y and Z axis coordinates; the tail sensing unit integrates the pressure value and the position data set to generate a tail sensing data set, which is sent to the data interface module through a signal transmission line.

[0080] In the embodiment of the present application, the tail sensing unit includes a micro pressure sensor and an electromagnetic positioning sensor. The micro pressure sensor adopts a piezoresistive principle, has a measurement range of 0-500 grams, a resolution of 1 gram, and a sampling frequency of 100 Hz, is installed on the force receiving surface of the guide wire tail pushing handle, and directly senses the pushing force applied by the operator's thumb. When the pushing force is 300 grams, the corresponding electrical signal output by the sensor is converted into an analog-digital signal to generate a pressure value of 300. When the pushing force changes, the value is updated synchronously, and the value is recorded every 0.01 seconds. The electromagnetic positioning sensor is composed of three orthogonal coils, receives the induction signal of an external fixed magnetic field (magnetic field strength of 0.5 Tesla and frequency of 10 kHz), calculates the spatial coordinates through the coil voltage change, has an X-axis measurement range of -500 to 500 mm, a Y-axis measurement range of -500 to 500 mm, and a Z-axis measurement range of -1000 to 1000 mm, a resolution of 0.1 mm, and a sampling frequency of 50 Hz. When the tail of the guide wire is located at a certain position in the gastrointestinal tract, the output position data group is X=150.2 mm, Y=-30.5 mm, and Z=450.8 mm. The tail sensing unit integrates the pressure value and the position data group with the same timestamp to form a tail sensing data group, such as (300, 150.2, -30.5, 450.8), which is transmitted in the form of a differential signal through a coaxial cable with a diameter of 0.3 mm at a transmission rate of 1 Mbps, ensuring continuous data transmission without loss.

[0081] The data interface module includes a signal conditioning circuit that converts the analog signals output by each sensing unit into 16-bit digital signals.

[0082] In the embodiment of the present application, the signal conditioning circuit receives analog signals from the head sensing unit and the middle sensing unit. These signals include voltage signals of a three-axis accelerometer (range -5 to +5 volts), current signals of a three-axis gyroscope (range 4 to 20 milliamperes), millivolt-level signals of a pH sensor (range 0 to 600 millivolts), and microvolt-level signals of a strain gauge (range -100 to +100 microvolts). The circuit first amplifies the weak signals through operational amplifiers. The strain gauge signal is amplified by 1000 times to -100 to +100 millivolts, and the pH sensor signal is amplified by 10 times to 0 to 6 volts. Subsequently, the signals are converted into 16-bit digital signals by a 16-bit analog-to-digital converter with a fixed conversion clock frequency of 1 megahertz. The analog signals are quantized into 65536 discrete levels, where -5 volts corresponds to 0, 0 volts corresponds to 32768, and +5 volts corresponds to 65535. For example, a +2.5 volt signal of the accelerometer is converted to 49152, and a +50 microvolt signal of the strain gauge is amplified to +50 millivolts, corresponding to 32768+(50 / 1000*32768)=34406. The converted 16-bit digital signals are stored according to the sensor type, with each signal occupying 2 bytes of storage space, ensuring that the accuracy loss of the original signal is controlled within 0.0015%.

[0083] The data packaging unit combines the 16-bit digital signal, the sensor ID, the sampling frequency and the check code according to a preset protocol to generate a fixed-length sensor data frame.

[0084] In the embodiment of the application, the data packaging unit starts a preset protocol, which stipulates that the length of the sensor data frame is fixed at 64 bytes, including a sensor ID (2 bytes), a sampling frequency (1 byte), a data field (58 bytes) and a check code (3 bytes). The sensor ID adopts unique coding, the head accelerometer is 0x0001, and the middle strain gauge is 0x0002. The sampling frequency is coded in binary, 250 Hz corresponds to 0x01, and 500 Hz corresponds to 0x02. Here, 250 Hz is uniformly used, and the code is 0x01. The data field is sequentially filled with 16-bit digital signals according to the sensor type, each signal occupies 2 bytes, and 58 bytes can accommodate 29 signal values. For example, the X-axis value of the head accelerometer is 49152 (0xC000), and the Y-axis value is 32768 (0x8000), which are arranged in sequence. The check code adopts a cyclic redundancy check (CRC) algorithm, and the CRC32 value of the first 61 bytes of data is calculated and the last 3 bytes are intercepted. For example, the first 61 bytes of the data frame containing the accelerometer and strain gauge signals are calculated by the CRC to be 0x12345678, the check code is 0x345678, and the final generated sensor data frame is "000101C0008000...345678" (hexadecimal representation), which ensures the integrity of data transmission.

[0085] The wireless communication module supports Bluetooth 5.0 protocol and IEEE802.11n protocol, can automatically switch the communication mode according to the signal strength, and sends the sensor data frame to the mobile terminal processing device at a frequency of 250 Hz.

[0086] In the embodiment of the present application, the wireless communication module simultaneously activates the Bluetooth 5.0 and IEEE802.11n protocol stacks, the Bluetooth module has a fixed transmission power of 0dBm (1mW), the communication distance is 0-10m, the IEEE802.11n module has a transmission power of 15dBm (32mW), and the communication distance is 0-50m. The module is built-in with a signal strength detection circuit, which monitors the RSSI (Received Signal Strength Indication) value of the receiving end in real time. When RSSI≥-70dBm, the Bluetooth 5.0 mode is adopted, and the data transmission rate is fixed at 2Mbps; when RSSI<-70dBm, the IEEE802.11n mode is automatically switched to, and the rate is increased to 150Mbps. When the guide wire is in the patient's body, the distance from the mobile terminal outside the body is usually 0.5-2m, and the RSSI value is stable at-55dBm, so the Bluetooth 5.0 mode is adopted, and the sensor data frame is transmitted at a frequency of 250Hz, that is, one frame is transmitted every 4ms, each frame has 64 bytes, and the transmission rate is 250*64=128000 bits / s (128kbps), which ensures real-time and avoids channel congestion.

[0087] The energy consumption management unit monitors the current consumption of each module, dynamically adjusts the working voltage according to the data transmission volume, and generates a state monitoring frame containing the remaining power and transmission rate.

[0088] In the embodiment of the present application, the energy consumption management unit monitors the current consumption through a precision resistor (1 ohm) connected in series in the power supply circuit of each module, uses a differential amplifier to measure the voltage drop across the resistor, calculates that the working current of the signal conditioning circuit is 20mA, the working current of the data packaging unit is 15mA, and the working current of the wireless communication module is 30mA in Bluetooth mode and 80mA in IEEE802.11n mode. The output voltage of the built-in DC-DC converter can be adjusted in the range of 3.0-3.6V. When the data transmission volume is 128kbps (64 bytes per frame, 250Hz), the working voltage is set to 3.3V; when the transmission volume decreases to 64kbps, the voltage decreases to 3.0V. The battery uses a 3.7V lithium polymer battery with a capacity of 200mAh, the energy consumption management unit measures the remaining power every 10 seconds, and the initial power is calculated to be 200mAh, and the remaining power is 145mAh after working for 1 hour by a coulomb meter. The state monitoring frame is generated in the format of "remaining power (mAh)|transmission rate (kbps)|working voltage (V)", such as "145|128|3.3", and is sent synchronously with the sensor data frame, so that the mobile terminal can master the energy consumption state of the guide wire in real time.

[0089] The mobile terminal processing device further comprises a risk warning module, and a working process of the module comprises: monitoring a motion state of the guide wire body in real time according to multi-dimensional sensing parameters, identifying a potential operation risk in combination with a preset risk threshold; when it is monitored that a risk index exceeds the threshold, a risk warning signal is generated, and risk type and risk position information are transmitted to a feedback output unit, so as to timely inform an operator through voice prompt and interface warning.

[0090] In the embodiment of the application, the multi-dimensional sensing parameters of the risk warning module comprise guide wire tail pressure (0-500 grams), three-dimensional coordinates (X / Y / Z axes), bending angle (0-90 degrees) and moving speed (0-50 mm / s), and the preset risk threshold is: pressure > 400 grams (excessive pushing), speed > 30 mm / s (moving too fast), bending angle > 70 degrees (excessive bending), and coordinates exceeding a preset path range of the gastrointestinal tract (X±50 mm, Y±50 mm, Z±100 mm). The module compares parameters and the threshold in real time. When the guide wire tail pressure rises to 420 grams and lasts for 0.5 seconds, it is determined that there is an excessive pushing risk; when the moving speed reaches 35 mm / s, it is determined that there is a moving too fast risk; and when the coordinates deviate to X=210 mm (exceeding +50 mm), it is determined that there is a path deviation risk. The generated risk warning signal comprises risk type coding (01 for excessive pushing, 02 for moving too fast, and 03 for path deviation) and three-dimensional coordinates of the risk position, such as (01, 155.3, -28.7, 460.2), and the signal is transmitted to the feedback output unit, triggering voice prompt (“excessive pushing risk, current pressure 420 grams”) and displaying a red warning box in the operation interface, and the box is marked with risk type, position coordinates and real-time parameters. The warning lasts until the parameters return to the threshold, ensuring that the operator can immediately adjust the operation.

[0091] The calculation process of the trajectory calculation module comprises: performing Kalman filtering processing on the three-dimensional space coordinate parameters to eliminate measurement noise and generate a smoothed coordinate sequence.

[0092] In the embodiment of the present application, when Kalman filtering is performed on the three-dimensional space coordinate parameters of the guide wire head and middle part, first, a state equation and an observation equation are established. The state equation contains six state variables of position (x, y, z) and velocity (vx, vy, vz), and the observation equation takes the coordinate parameters collected by the sensor as input, and the noise variance matrix is determined by experiment: the position measurement noise standard deviation is 0.1 mm, and the velocity noise standard deviation is 0.05 mm / ms. Taking the coordinate data of the guide wire passing through the stomach pylorus as an example, the original measurement value has a random fluctuation of ±0.08 mm, such as the x coordinates of the consecutive 5 sampling points are 5.23 mm, 5.31 mm, 5.19 mm, 5.35 mm and 5.27 mm. Kalman filtering eliminates noise through prediction-update iteration, the prediction step estimates the current position according to the previous time state and motion model, and the update step corrects the prediction result combined with the observation value, and the smoothed coordinate sequence is obtained after processing: 5.25 mm, 5.27 mm, 5.26 mm, 5.28 mm and 5.27 mm, the difference between adjacent points is controlled within 0.02 mm, ensuring the continuous and smooth trajectory, and providing stable input for subsequent kinematic analysis.

[0093] Based on the smoothed coordinate sequence and motion state parameters, the instantaneous velocity and acceleration of each feature point on the guide wire are calculated, and a kinematic parameter set is generated;

[0094] In the embodiment of the present application, based on the smoothed coordinate sequence, the central difference method is used to calculate the instantaneous velocity and acceleration of the guide wire feature points. In the case of time interval Δt=4 ms (corresponding to sampling frequency 250 Hz), the velocity component vx is calculated by (x(i+1)-x(i-1)) / (2Δt), and the acceleration component ax is calculated by (vx(i+1)-vx(i-1)) / (2Δt). Taking the motion of the guide wire head in the descending duodenum as an example, the smoothed x coordinate sequence is 10.20 mm, 10.28 mm, 10.37 mm and 10.46 mm (corresponding to i-1 to i+2 time), and vx=(10.37-10.20) / (2×4)=0.021 mm / ms is calculated, and vy=0.015 mm / ms and vz=0.008 mm / ms are calculated in the same way, and the synthesized velocity is 0.026 mm / ms. In the acceleration calculation, ax=(0.023-0.019) / (2×4)=0.0005 mm / ms², and the kinematic parameter set containing the velocity and acceleration components in x, y and z directions is generated, which completely describes the motion state of the guide wire in three-dimensional space.

[0095] Combined with the diameter data of the digestive tract cavity in the anatomical matching database, the boundary constraint processing is performed on the kinematic parameter set, and a constrained motion trajectory is generated;

[0096] In the embodiment of the present application, the anatomically matched database stores the diameter data of the digestive tract lumen of patients of different ages and body types, such as the upper esophageal diameter of 25 mm, the gastric body diameter of 50 mm, and the descending duodenal diameter of 30 mm, and the data accuracy is ±1 mm. The position coordinates in the kinematic parameter set are compared with the corresponding lumen diameter, and when the radial distance of the guide wire feature point exceeds the lumen radius, the boundary constraint processing is triggered. For example, when the guide wire moves in the middle segment of the esophagus, the x coordinate calculation value at a certain moment is 13.0 mm, and the lumen radius of this segment is 12.5 mm, which exceeds the boundary by 0.5 mm. The system corrects the position coordinates by proportional scaling, adjusts the x value to 12.5 mm, and at the same time corrects the speed and acceleration parameters by the same proportion, to ensure that the corrected kinematic parameter set satisfies: x²+y²+z²≤(lumen radius)². After the constraint processing, the guide wire trajectory is strictly limited within the digestive tract lumen, eliminating the virtual out-of-bound caused by measurement errors and ensuring the anatomical rationality of the trajectory.

[0097] The constrained motion trajectory is fitted by using a Bezier curve to generate a continuous three-dimensional trajectory curve and a corresponding curvature rate of change.

[0098] In the embodiment of the present application, a third-order Bezier curve is used to fit the constrained motion trajectory, and the curve equation is P(t)=P0(1-t)³+3P1t(1-t)²+3P2t²(1-t)+P3t³, where t∈[0, 1], P0 to P3 are control vertices selected from the constrained trajectory by the least square method. Taking the curved segment of the guide wire through the gastric fundus to the gastric body as an example, five key coordinate points are selected as the fitting reference: (8.2, 3.5, 2.1) mm, (9.1, 4.2, 2.3) mm, (10.3, 5.0, 2.5) mm, (11.5, 5.7, 2.7) mm, and (12.8, 6.3, 2.9) mm, and the control vertices P0=(8.2, 3.5, 2.1), P1=(8.8, 3.9, 2.2), P2=(11.0, 5.4, 2.6), and P3=(12.8, 6.3, 2.9) are calculated. The deviation between the fitted Bezier curve and the original trajectory is less than 0.1 mm, and the curvature rate of change is calculated by taking the second derivative of the curve. The results show that the curvature rate of change is 0.05 mm⁻¹ / ms at the gastric fundus bend and decreases to 0.02 mm⁻¹ / ms after entering the gastric body, fully presenting the bending change characteristics of the guide wire in the digestive tract and providing an intuitive trajectory reference for clinical operation.

[0099] The boundary constraint processing process includes: retrieving the digestive tract lumen cross-sectional data corresponding to the current position from the anatomically matched database to generate a constraint boundary model containing the lumen radius and the center axis;

[0100] In the embodiment of the present application, the cross-section data of the current position of the guide wire corresponding to the digestive tract cavity is retrieved from the anatomically matched database, the database stores three-dimensional model parameters according to the digestive tract segments, the esophageal middle segment data contains a cavity radius of 12.5 mm, a central axis coordinate of (0, 0, 0) to (0, 0, 100) mm (in the length direction), and a circular cross-section with a center located on the central axis. According to the three-dimensional coordinates (5.2, 10.1, 35.6) mm of the head of the guide wire, the system determines that it is located at the cross-section of the middle segment of the esophagus at 35.6 mm, extracts the constraint boundary model parameters of this position: a cavity radius of 12.5 mm, a cross-section center coordinate of (0, 0, 35.6) mm, and a central axis normal vector of (0, 0, 1) at the cross-section. The constraint boundary model is described in a mathematical expression as: (x-0)²+(y-0)²≤12.5²(z=35.6 mm plane), which ensures that the model completely matches the anatomical structure and provides an accurate reference for subsequent boundary comparison.

[0101] Compare the coordinate data in the kinematic parameter set with the constraint boundary model to identify abnormal coordinate points that exceed the cavity boundary;

[0102] In the embodiment of the present application, the coordinate data in the kinematic parameter set is compared with the constraint boundary model point by point, the comparison formula is the Euclidean distance of the coordinate point to the center of the cross-section: √(x²+y²), and it is compared with the cavity radius of 12.5 mm. Taking the continuous 5 sampling points of the guide wire in the middle segment of the esophagus as an example, the coordinates are (5.2, 10.1, 35.6), (5.5, 10.5, 35.7), (5.8, 11.0, 35.8), (6.1, 11.5, 35.9), (6.4, 12.0, 36.0) mm, and the distances of each point to the center are calculated as 11.3 mm, 11.8 mm, 12.3 mm, 12.8 mm, and 13.3 mm, respectively. The distances of the last two points exceed 12.5 mm, which are determined as abnormal coordinate points that exceed the cavity boundary, and their position index and specific coordinate values are recorded to provide a clear target for subsequent correction.

[0103] The abnormal coordinate points are corrected using a cubic spline interpolation algorithm to generate corrected coordinate values that conform to the physiological structure;

[0104] In the embodiment of the present application, the abnormal coordinate points (6.1, 11.5, 35.9) mm and (6.4, 12.0, 36.0) mm are corrected by using a cubic spline interpolation algorithm. The algorithm takes each two normal points before and after the abnormal point as a reference, i.e. (5.5, 10.5, 35.7), (5.8, 11.0, 35.8), and (the next normal point is preset as (6.7, 11.2, 36.1)), to construct a cubic spline function. For the x coordinate, the interpolation function is x(t) = at3 + bt2 + ct + d, and the coefficients are solved by substituting the known points, i.e. a = -0.2, b = 1.5, c = -2.3, and d = 6.8. The corrected x value at t = 3 (the position of the abnormal point) is 6.2 mm. Similarly, the corrected y value is 11.4 mm, ensuring that the distance from the corrected coordinate (6.2, 11.4, 35.9) mm to the center is 12.4 mm, which is less than 12.5 mm. The second abnormal point is corrected to (6.5, 11.6, 36.0) mm, which is 12.5 mm away from the center, fully meeting the constraint boundary model, and the corrected coordinate value forms a continuous and smooth sequence with the normal points before and after.

[0105] The deviation amount of the coordinate values before and after correction is calculated, and if the deviation amount exceeds the preset threshold, a boundary constraint warning signal is generated.

[0106] In the embodiment of the present application, the deviation amount of the coordinate values before and after correction is calculated by using the Euclidean distance formula: deviation amount = √[(x corrected - x original)2 + (y corrected - y original)2 + (z corrected - z original)2]. The original coordinate of the first abnormal point is (6.1, 11.5, 35.9) mm, and after correction, it is (6.2, 11.4, 35.9) mm, with a deviation amount of 0.14 mm = √[(0.1)2 + (-0.1)2 + 02]. The original coordinate of the second abnormal point is (6.4, 12.0, 36.0) mm, and after correction, it is (6.5, 11.6, 36.0) mm, with a deviation amount of 0.41 mm = √[(0.1)2 + (-0.4)2 + 02]. The preset threshold is 0.3 mm, and the deviation amount of the second abnormal point 0.41 mm exceeds the threshold, so the system immediately generates a boundary constraint warning signal, which contains information such as the position of the abnormal point (36.0 mm), the deviation amount 0.41 mm, and the corrected coordinate, and is synchronously sent to the mobile terminal in the form of a red flashing icon and numerical prompt, prompting the operator to adjust the pushing force as the guide wire may approach the cavity wall.

[0107] The construction process of the constraint boundary model includes: reconstructing the three-dimensional model of the digestive tract based on the CT image data, extracting the center axis and cross-sectional profile of each segment of the cavity, and generating standard anatomical structure parameters;

[0108] In the embodiment of the present application, a healthy volunteer group is scanned by using a 64-slice spiral CT device, the layer thickness is set to 0.625 mm, the scanning range is from the oropharynx to the duodenal bulb, and continuous cross-sectional image data is obtained. The CT image is processed by using three-dimensional reconstruction software, the digestive tract cavity area is extracted by using a threshold segmentation algorithm (HU value range: -100 to 200), the internal gap of the cavity is filled by using a region growing method, and a complete three-dimensional model of the digestive tract is generated. The center axis of each segment of the cavity is extracted from the three-dimensional model, and the center axis of the esophageal segment is calculated by using a skeleton extraction algorithm as a spatial curve from the lower edge of the C6 vertebra to the cardia, with a length of about 250 mm, and the segmented curvature radius is: 300 mm for the upper segment, 250 mm for the middle segment, and 200 mm for the lower segment. The cross-sectional profile is obtained by cross-sectioning perpendicular to the center axis, the cross-section of the upper esophageal segment is circular with a diameter of 23±1 mm, and the body of the stomach is elliptical with a major axis of 55±3 mm and a minor axis of 40±2 mm. The center axis coordinates (x, y, z) and the diameter and shape parameters (ellipse major axis / minor axis ratio) of the cross-sectional profile are arranged as standard anatomical structure parameters and stored as a structured data set.

[0109] The standard anatomical structure parameters are statistically analyzed, the anatomical difference coefficients of different age groups and body types are calculated, and personalized correction factors are generated;

[0110] In the embodiment of the present application, 1000 cases of standard anatomical structure parameters of different age groups (20-30 years old, 31-50 years old, 51-70 years old) and body types (BMI <18.5, 18.5-23.9, ≥24) are collected, and the anatomical difference coefficients are calculated by using one-way analysis of variance. The esophageal diameter in the 20-30 year old group is 23 mm, and the 51-70 year old group is 25 mm, and the difference coefficient is (25-23) / 23=0.087; the major axis of the body of the stomach in the BMI≥24 group is 58 mm, which is 3 mm larger than that of the normal BMI group, and the difference coefficient is 3 / 55=0.054. The difference coefficients are grouped according to age and BMI to fit personalized correction factors, and the formula is: correction factor=1+(age group coefficient×0.4+BMI coefficient×0.6). For a patient of 31-50 years old and BMI=25, the age group coefficient is 0.03, the BMI coefficient is 0.04, and the correction factor is 1+(0.03×0.4+0.04×0.6)=1.036, that is, the diameter of the cavity of the patient is 1.036 times of the standard value. All the correction factors are stored according to the groups to form a personalized correction factor library covering the entire population.

[0111] The mobile terminal processing device receives the physiological parameters of the patient input by the user, calls the corresponding personalized correction factor to adjust the standard anatomical structure parameters, and generates a personalized constraint boundary model;

[0112] In the embodiment of the present application, the input interface of the mobile terminal processing device sets the patient physiological parameter input item, including age (accurate to years), height (accurate to centimeters), weight (accurate to 0.1 kg), and automatically calculates BMI = weight (kg) / [height (m)] 2. When the patient is 35 years old, 175 cm tall, and 78 kg, the BMI = 78 / (1.75) 2 = 25.4, which matches the 31-50 years old, BMI ≥ 24 group. The system calls the correction factor corresponding to this group from the correction factor library, which is 1.036, and adjusts the standard anatomic structure parameters: the esophageal middle segment diameter is 12.5 mm x 1.036 = 12.95 mm, the gastric body axis curvature radius is 250 mm x 1.036 = 259 mm, and the cross-sectional ellipse long axis is 55 mm x 1.036 = 56.98 mm. The adjusted parameters are reconstructed according to the mathematical expression of step S41 to generate a personalized constraint boundary model, in which the esophageal middle segment constraint formula is x 2 + y 2 ≤ 12.95 2, which ensures that the model matches the actual anatomic structure of the patient.

[0113] A time decay factor is added to the personalized constraint boundary model, and the elastic coefficient of the constraint boundary is dynamically adjusted with the operation time.

[0114] In the embodiment of the present application, a time decay factor is added to the personalized constraint boundary model, and the formula is: decay factor = 1 - 0.001 x operation time (min), elastic coefficient = basic elastic coefficient x decay factor, and the basic elastic coefficient is set to 0.02 mm / gf. At the beginning of the operation (0 min), the elastic coefficient = 0.02 x 1 = 0.02 mm / gf, which allows a 0.02 mm / gf deformation buffer when the guide wire contacts the boundary; after 30 minutes of operation, the decay factor = 1 - 0.001 x 30 = 0.97, and the elastic coefficient = 0.02 x 0.97 = 0.0194 mm / gf, and the buffer deformation is reduced. When the guide wire approaches the gastric antrum boundary at 30 minutes of operation, the diameter of the personalized constraint boundary model is dynamically adjusted to 56.98 mm x 0.97 = 55.27 mm, and the elastic coefficient is 0.0194 mm / gf, that is, when the guide wire exerts 5 gf, the maximum boundary invasion allowed is 5 x 0.0194 = 0.097 mm, which is reduced by 3% compared to the initial state, thereby improving the operation safety by gradually tightening the constraint boundary and adapting to the change in tissue elasticity after a long time of operation.

[0115] The second embodiment of the present application also provides a medical gastrointestinal tube-embedded guide wire electronic trajectory analysis method, as shown in Fig. 2 The method is implemented based on the medical gastrointestinal tube-embedded guide wire electronic trajectory analysis system as above, and includes the following steps:

[0116] S01: After the guide wire body enters the human digestive tract, the head sensor unit, the middle sensor unit and the tail sensor unit synchronously collect multi-dimensional physiological parameters to generate a raw sensor data stream containing a time stamp;

[0117] In the embodiment of the application, the guide wire body is made of nickel-titanium alloy with a diameter of 0.8 mm. After entering the human digestive tract, the head sensor unit, the middle sensor unit and the tail sensor unit synchronously collect data at a frequency of 100 times per second. The three-axis accelerometer of the head sensor unit records linear acceleration of X axis +320 mg, Y axis -150 mg and Z axis +210 mg. The three-axis gyroscope records angular velocity of roll angle 0.3 degrees per second, pitch angle +12 degrees per second and yaw angle -8 degrees per second. The pH sensor measures the pH value of the gastric acid environment as 2.35. All the data are marked with the same time stamp 1628745623000 milliseconds. The four strain gauges of the middle sensor unit respectively collect deformation data of 0 degree direction +350 με, 90 degree direction +520 με, 180 degree direction +350 με and 270 degree direction -480 με. The pressure sensor records the contact pressure of 35 kPa and lasts for 1.5 seconds. The temperature and humidity sensor measures the environmental parameters of 37.2°C and 78% RH. The time stamp is also 1628745623000 milliseconds. The position encoder of the tail sensor unit records the guide wire advancing length of 150 mm. The head data and the middle data are integrated into the raw sensor data stream. Each piece of data contains 12 parameters and is arranged in chronological order to form continuous records.

[0118] S02: The data interface module receives the raw sensor data stream, performs analog-to-digital conversion and protocol packaging, generates standardized sensor data frames and sends them through wireless communication;

[0119] In the embodiment of the application, the signal conditioning circuit of the data interface module receives the raw sensor data stream. The microvolt-level strain signal is amplified by 1000 times through the operational amplifier. The millivolt-level pH signal is amplified by 10 times. All the analog signals are connected to the 16-bit analog-to-digital converter with a conversion clock frequency of 1 megahertz. The acceleration of +320 mg is converted into a digital value of 49152. The pH value of 2.35 is converted into a digital value of 2350. The converted digital signals are packaged according to the preset protocol. The protocol specifies that each frame of data has a length of 64 bytes, contains 2 bytes of sensor ID (0x0001 for the head and 0x0002 for the middle), 1 byte of sampling frequency (0x64 corresponding to 100 Hz), 58 bytes of data field (storing digital values of 12 parameters), and 3 bytes of CRC check code (calculated for the previous 61 bytes). The packaged standardized sensor data frames are sent through the Bluetooth 5.0 module with a transmission power of 0 dBm and a transmission rate of 2 Mbps. Each frame is sent every 4 milliseconds, ensuring that the delay from data collection to wireless transmission is controlled within 10 milliseconds. Each frame of data is checked for errors before being received, avoiding the impact of transmission errors on subsequent analysis.

[0120] S03: The mobile terminal processing device parses the standardized sensor data frame to extract three-dimensional position coordinates, motion state, deformation degree, pH value, temperature, and pressure parameters, and generates a multi-dimensional parameter matrix;

[0121] In the embodiment of the application, the mobile terminal processing device receives the standardized sensor data frame through Bluetooth, and a parsing program extracts each parameter according to a protocol format: the first and second bytes of the data field are extracted to obtain the head X-axis acceleration 49152, which is converted into an actual value +320 milligal; the third and fourth bytes are extracted to obtain the Y-axis acceleration 32768-(150*32768 / 500)=22938, which corresponds to-150 milligal. Three-dimensional position coordinates are calculated by integrating acceleration, and the acceleration data of five consecutive sampling points are accumulated to obtain the current coordinates (12.5, 8.3, 5.6) millimeters in combination with the initial position (0, 0, 0). The motion state parameter is obtained by integrating the angular velocity to obtain the guide wire head pitch angle +12 degrees. The deformation degree is calculated by the strain value to obtain the radial bending amount 0.35 millimeters. The pH value, temperature, and pressure parameters are directly converted into physical quantities. All parameters are arranged in the structure of “three-dimensional coordinates | motion state | deformation degree | pH value | temperature | pressure” to form a 10*10 multi-dimensional parameter matrix, each row representing a sampling time, and each column representing a type of parameter.

[0122] S04: A trajectory calculation module is called to kinematically model the multi-dimensional parameter matrix, and a constraint condition in an anatomic matching database is combined to generate a guide wire real-time three-dimensional motion trajectory;

[0123] In the embodiment of the application, the trajectory calculation module calls a Kalman filter to process the three-dimensional coordinates in the multi-dimensional parameter matrix, the state equation contains position and velocity variables, the observation noise variance is 0.1 millimeter, and the measurement noise of ±0.08 millimeter is eliminated after prediction-update iteration to generate the smooth coordinate sequence (12.5, 8.3, 5.6), (12.7, 8.5, 5.7), (12.9, 8.7, 5.8) millimeters. In combination with the constraint condition of the lumen diameter 50 millimeters in the anatomic matching database of the gastric body, it is ensured that the distance from the coordinate value to the center of the lumen is not more than 25 millimeters, and the coordinates exceeding the distance are proportionally corrected. The coordinate sequence after correction is fitted by using a Bezier curve, the control points are set to (12.5, 8.3, 5.6), (12.6, 8.4, 5.65), (12.8, 8.6, 5.75), (12.9, 8.7, 5.8), the deviation between the fitted curve and the original coordinates is less than 0.1 millimeter, a guide wire real-time three-dimensional motion trajectory of 25 frames per second is generated, and the bending path of the guide wire in the gastric body is clearly displayed.

[0124] S05: The guide wire real-time three-dimensional motion trajectory is compared with the standard anatomic path of the digestive tract for similarity, and the probability value of passing through the pylorus and the operation safety coefficient are calculated;

[0125] In the embodiment of the present application, by comparing the real-time three-dimensional motion trajectory of the guide wire with the standard anatomic path in the anatomic matching database of the digestive tract, the coordinate sequence of the standard path in the pylorus region is (20.0, 15.0, 10.0), (20.5, 15.3, 10.2), (21.0, 15.6, 10.4) mm, and the current trajectory coordinates of the guide wire are (19.8, 14.9, 9.9), (20.3, 15.2, 10.1), (20.8, 15.5, 10.3) mm. The Euclidean distance of each pair of corresponding points is calculated, and the average distance is 0.2 mm, and the similarity is (1-0.2 / 5) x 100% = 96% (5 mm is the maximum allowed deviation). The pylorus passing probability value is calculated based on the similarity, and the formula is probability value = similarity x 0.8 + speed matching degree x 0.2, the speed matching degree is the ratio of the current speed of the guide wire 0.026 mm / ms to the standard path speed 0.025 mm / ms, which is 0.96, and the probability value is 96% x 0.8 + 96% x 0.2 = 96%. The operation safety coefficient is calculated by the pressure parameter, and the ratio of the current pressure 35 kPa to the safety threshold 50 kPa is 0.7, and the safety coefficient is 0.7 x 100 = 70.

[0126] S06: According to the pylorus passing probability value and the operation safety coefficient, operation guidance information containing the best pushing direction, rotation angle and force control suggestion is generated, and is displayed in real time through the feedback output unit.

[0127] In the embodiment of the present application, according to the pylorus passing probability value 96% and the operation safety coefficient 70, the system starts the decision algorithm to generate the operation guidance information. The best pushing direction is calculated according to the trajectory deviation, the current position of the guide wire is 0.1 mm left of the standard path, and it is suggested to adjust 2 degrees to the right; the rotation angle is determined according to the gyroscope data, the yaw angle -8 degrees needs to be corrected to -5 degrees, that is, to rotate 3 degrees clockwise; the force control is based on the pressure sensor data, and there is still a 15 kPa margin from the 50 kPa threshold, and it is suggested to increase the pushing force by 0.5 grams (1 gram corresponds to a 10 kPa pressure change). The guidance information is generated in the format of "pushing direction: right 2 degrees | rotation angle: clockwise 3 degrees | force: +0.5 grams", and the mobile terminal screen of the feedback output unit displays the expected trajectory after adjustment in a three-dimensional animation, and at the same time, the vibration module sends 3 short vibrations, each vibration lasts for 100 milliseconds, and the interval is 200 milliseconds, to ensure that the operator can obtain accurate operation suggestions in real time.

[0128] Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting, the scope of the present application is defined by the appended claims rather than the above description, and therefore all changes falling within the meaning and scope of the equivalent elements of the application file are intended to be included in the present application.

[0129] The foregoing is considered as illustrative of the principles of the application. Numerous modifications and changes will readily occur to those skilled in the art, and it is intended to embody these modifications and changes into the scope of the application insofar as they do not depart from the spirit and scope of the claims. It is therefore intended that the application not be limited to the described embodiments, but that the application be able to extend to all aspects within the scope of the claims, be they presently known or become available in the future.

Claims

1. A medical gastrointestinal tube guide wire electronic trajectory analysis system, characterized by comprising: a guide wire body, the guide wire body sequentially provides a head sensing unit, a middle sensing unit and a tail sensing unit along the length direction, each sensing unit is connected to a data interface module through a signal transmission line inside the guide wire; a data interface module, the data interface module is integrated at the tail end of the guide wire body, used for receiving original sensing data collected by each sensing unit, and converting the original sensing data into a standardized data format, generating a sensing data frame containing a data collection time stamp and a sensor identifier; a mobile terminal processing device, the mobile terminal processing device establishes a connection with the data interface module through a wireless communication protocol, receives the sensing data frame and obtains multi-dimensional sensing parameters including three-dimensional space coordinate parameters, motion state parameters, deformation parameters and environmental parameters by analysis; a trajectory calculation module, the trajectory calculation module constructs a guide wire kinematics model based on the multi-dimensional sensing parameters, and generates real-time three-dimensional motion trajectory data of the guide wire in the body through model iterative calculation; an anatomical matching database, the anatomical matching database stores standard anatomical structure data corresponding to the human digestive tract, the mobile terminal processing device calls the anatomical matching database, compares the real-time three-dimensional motion trajectory data with the standard anatomical structure data, and generates a trajectory matching degree score; a feedback output unit, the feedback output unit generates real-time operation guidance information containing voice prompts, text instructions and trajectory deviation indications according to the trajectory matching degree score, and outputs through the display interface and audio module of the mobile terminal processing device.

2. The medical gastrointestinal tube-insertion guide wire electronic trajectory analysis system according to claim 1, characterized by, The head sensing unit includes a three-axis accelerometer, a three-axis gyroscope and a pH sensor arranged along the axial direction of the guide wire, wherein: the three-axis accelerometer collects linear acceleration data of the guide wire head, and generates acceleration vector values containing X, Y and Z axis components; the three-axis gyroscope collects angular velocity data of the guide wire head, and generates angular velocity vector values containing roll angle, pitch angle and yaw angle; the pH sensor collects hydrogen ion concentration data of the environment around the guide wire head, and generates pH value measurement results; the head sensing unit synchronizes the acceleration vector values, angular velocity vector values and pH value measurement results with time stamps, generates a head sensing data group, and sends it to the data interface module through the signal transmission line.

3. The medical gastrointestinal tube-insertion guide wire electronic trajectory analysis system according to claim 1, characterized by, The middle sensing unit includes a strain sensing array, a pressure sensor and a temperature and humidity sensor, wherein: the strain sensing array is composed of four strain gauges uniformly distributed along the circumference of the guide wire, which collects tensile, compressive and bending deformation data of the middle part of the guide wire, and generates deformation stress values; the pressure sensor collects pressure data generated by the contact between the guide wire and the digestive tract tissue, and generates pressure characteristic values containing pressure amplitude and pressure duration; the temperature and humidity sensor collects temperature and humidity data of the environment around the middle part of the guide wire, and generates environmental parameter values; the middle sensing unit fuses the deformation stress values, pressure characteristic values and environmental parameter values to generate a middle sensing data group, which is sent to the data interface module through the signal transmission line.

4. The medical gastrointestinal tube-insertion guide wire electronic trajectory analysis system according to claim 3, characterized by The working process of the strain sensing array includes: Each strain gauge generates resistance change when the guide wire is deformed, and converts the resistance change into voltage signal through a Wheatstone bridge, to generate an original strain electric signal; The original strain electric signal is filtered and amplified to remove high-frequency noise and baseline drift, to generate a filtered strain signal; The filtered strain signal is converted into corresponding deformation displacement according to a preset strain-deformation conversion coefficient, which includes radial bending amount and axial stretching amount; The bending center coordinates and bending angle of the guide wire cross section are calculated by combining the deformation displacement of the four strain gauges, to generate deformation data containing spatial bending direction.

5. The medical gastrointestinal tube-insertion guide wire electronic trajectory analysis system according to claim 4, characterized by The calculation process of the deformation data includes: The deformation displacement of the four strain gauges is collected, and a polar coordinate system with the guide wire axis as the origin is established, to generate polar coordinate position parameters of each strain gauge; Based on the polar coordinate position parameters and corresponding deformation displacement, the bending arc of the guide wire cross section is fitted through least squares method, to calculate the curvature radius and center coordinates of the arc; The bending direction vector of the guide wire is determined according to the curvature radius and center coordinates, and a three-dimensional deformation feature vector is generated in combination with the axial stretching amount; The three-dimensional deformation feature vector is associated with a time stamp to form deformation data changing over time.

6. The medical gastrointestinal tube-insertion guide wire electronic trajectory analysis system according to claim 1, wherein The tail sensing unit includes a micro pressure sensor and an electromagnetic positioning sensor, wherein: the micro pressure sensor collects push pressure data received by the tail of the guide wire to generate a pressure value; the electromagnetic positioning sensor collects position information of the tail of the guide wire based on changes in the surrounding electromagnetic field to generate a position data set containing X, Y and Z axis coordinates; the tail sensing unit integrates the pressure value and the position data set to generate a tail sensing data set, which is sent to the data interface module through a signal transmission line.

7. The medical gastrointestinal tube-insertion guide wire electronic trajectory analysis system according to claim 1, wherein The data interface module includes: A signal conditioning circuit that performs analog-to-digital conversion on the analog signals output by each sensing unit to generate 16-bit digital signals; A data packing unit that combines the 16-bit digital signals with sensor ID, sampling frequency and check code according to a preset protocol to generate a fixed-length sensing data frame; A wireless communication module that supports Bluetooth 5.0 protocol and IEEE802.11n protocol, can automatically switch communication modes according to signal strength, and sends the sensing data frame to the mobile terminal processing device at a frequency of 250Hz; An energy consumption management unit that monitors the current consumption of each module, dynamically adjusts the working voltage according to the data transmission volume, and generates a status monitoring frame containing remaining power and transmission rate.

8. The medical gastrointestinal tube-insertion guide wire electronic trajectory analysis system according to claim 1, wherein The mobile terminal processing device further includes a risk warning module, and the working process of the module includes: monitoring the motion state of the guide wire body in real time according to multi-dimensional sensing parameters, identifying potential operation risks in combination with preset risk thresholds; when it is monitored that the risk indicators exceed the thresholds, a risk warning signal is generated, and the risk type and risk location information are transmitted to the feedback output unit, so as to timely inform the operator through voice prompt and interface warning.

9. The medical gastrointestinal tube-insertion guide wire electronic trajectory analysis system according to claim 1, wherein The calculation process of the trajectory calculation module includes: Kalman filtering is performed on the three-dimensional space coordinate parameters to eliminate measurement noise and generate a smoothed coordinate sequence; Based on the smoothed coordinate sequence and motion state parameters, the instantaneous velocity and acceleration of each feature point on the guide wire are calculated, and a kinematics parameter set is generated; Combined with the diameter data of the digestive tract lumen in the anatomical matching database, boundary constraint processing is performed on the kinematics parameter set to generate a constrained motion trajectory; A Bezier curve is used to fit the constrained motion trajectory to generate a continuous three-dimensional trajectory curve and the corresponding curvature rate of change.

10. A medical gastrointestinal tube guide wire electronic trajectory analysis method, characterized by, The method is implemented based on the medical gastrointestinal tube-embedded guide wire electronic trajectory analysis system according to any one of claims 1-9, and includes the following steps: S01: After the guide wire body enters the human digestive tract, the head sensing unit, the middle sensing unit, and the tail sensing unit synchronously collect multi-dimensional physiological parameters to generate an original sensing data stream containing a time stamp; S02: The data interface module receives the original sensing data stream, performs analog-to-digital conversion and protocol packaging, generates a standardized sensing data frame, and transmits it through wireless communication; S03: The mobile terminal processing device analyzes the standardized sensing data frame to extract three-dimensional position coordinates, motion states, deformation degrees, pH values, temperatures, and pressure parameters, and generates a multi-dimensional parameter matrix; S04: The trajectory calculation module is called to perform kinematics modeling on the multi-dimensional parameter matrix, and a real-time three-dimensional motion trajectory of the guide wire is generated in combination with the constraint conditions of the anatomical matching database; S05: The real-time three-dimensional motion trajectory of the guide wire is compared with the standard anatomical path of the digestive tract for similarity, and a probability value of passing through the pylorus and an operation safety coefficient are calculated; S06: According to the probability value of passing through the pylorus and the operation safety coefficient, operation guidance information containing suggestions for the best pushing direction, rotation angle, and force control is generated, and is displayed in real time through the feedback output unit.

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