A cavity obstacle avoidance navigation method and system based on self-sensing magnetic control bending catheter

Abstract

This invention relates to a method and system for obstacle avoidance navigation in a cavity based on a self-sensing magnetically controlled curved conduit. The method includes: acquiring the initial wavelength, initial azimuth angle, and position coordinates of key navigation points of sensors in the magnetically controlled curved conduit; estimating the initial values ​​of magnetic field strength, effective conduit length, and permanent magnet spacing based on the position coordinates and generating control commands; driving the magnetically controlled curved conduit to bend and deform based on the control commands; calculating the total curvature and bending direction angle based on the wavelength offset; calculating the angular velocity vector based on the total curvature and torsion; calculating the rotation matrix based on the angular velocity vector; acquiring a frame of the sensor position curve; updating the frame according to the rotation matrix, and calculating the actual position of the sensor based on the updated curve frame; and determining whether the end of the magnetically controlled curved conduit has reached the target position based on the actual position. Compared with the prior art, this invention has the advantages of good system adaptability and high navigation accuracy.

Description

Technical Field

[0001] This invention relates to the intersection of interventional medical devices, fiber optic sensing technology, and magnetic drive control technology. In particular, it relates to a cavity obstacle avoidance navigation method and system based on a self-sensing magnetically controlled curved catheter. It is suitable for intelligent interventional navigation in robotic minimally invasive surgery, especially for high-precision interventional surgery of narrow, bifurcated, and complex cavities such as cardiovascular and cerebrovascular vessels. It can also be extended to fields such as industrial narrow cavity detection and micro-robot navigation. Background Technology

[0002] Minimally invasive surgery has become the mainstream technique in clinical surgical diagnosis and treatment due to its significant advantages of less trauma, faster recovery, and fewer complications. Interventional catheters, as the core manipulators used in minimally invasive surgery to penetrate deep into human cavities, play a crucial role in determining surgical safety through precise control and real-time navigation within complex cavities. They are also key to improving treatment outcomes and reducing intraoperative collateral damage.

[0003] Magnetic drive technology, with its advantage of flexible control, has become the mainstream method for controlling the morphology of interventional catheters in minimally invasive surgery. This technology integrates magnetic elements into the catheter and, combined with external equipment, controls the strength and direction of the magnetic field to drive the catheter to perform flexible bending, turning, and other morphological changes, significantly improving the passage and operational flexibility of interventional catheters in narrow and tortuous cavities of the human body. Li et al. proposed a multi-section telescopic soft magnetic robot that can adapt to blood vessel lumens of different diameters and curvatures, achieving active stiffness adjustment (Z. Li and Q. Xu, “Multi-Section Magnetic Soft Robot with MultirobotNavigation System for Vasculature Intervention,” Cyborg Bionic Syst, vol. 5, p. 0188, Jan. 2024.). However, existing magnetically controlled interventional catheters have significant technical shortcomings. They lack real-time feedback capabilities regarding their own shape and terminal position, and surgical navigation relies entirely on external equipment such as X-rays and electromagnetic imaging. This not only exposes medical staff and patients to radiation risks, but electromagnetic imaging is also susceptible to environmental interference, leading to reduced navigation accuracy. Furthermore, it cannot achieve automatic closed-loop control of the catheter's shape. This problem severely limits its clinical application in high-precision minimally invasive surgeries such as cardiovascular and cerebrovascular surgeries.

[0004] Fiber optic shape sensing technology possesses characteristics such as miniaturization, resistance to electromagnetic interference, high detection accuracy, and fast dynamic response, making it highly adaptable to the miniaturization and high-precision application requirements of minimally invasive surgical catheters. It can be embedded within the catheter to detect deformations such as bending and torsion in real time, and reconstruct the three-dimensional morphology of the catheter with high precision. It has already been implemented in some commercial minimally invasive surgical navigation systems. PHILIPS has launched a new technology platform, FORS, which utilizes fiber optic shape sensing technology to achieve real-time three-dimensional visualization of intravascular devices (JA Van Herwaarden et al., “First in Human Clinical Feasibility Study of Endovascular Navigation with Fiber Optic RealShape (FORS) Technology,” European Journal of Vascular and Endovascular Surgery, vol. 61, no. 2, pp.317–325, Feb. 2021.). However, this technology can only passively sense the catheter morphology and lacks the ability to actively control the catheter morphology. It cannot autonomously adjust the catheter's course according to the complex cavities of the human body, making it difficult to meet the obstacle avoidance navigation requirements of complex cavities.

[0005] Currently, magneto-actuated shape control and fiber optic shape sensing technologies are still independently developed and clinically applied, and have not yet achieved technological integration and functional synergy in interventional catheters. This has created a technological barrier between the "blind-controlled" shape adjustment of magnetically controlled catheters and the "passive" detection of fiber optic sensing devices. Against this backdrop, there is an urgent clinical need for a minimally invasive surgical integrated interventional catheter system that combines magnetically driven active shape control with real-time fiber optic sensing capabilities. This system would fundamentally solve the core technological challenge of intelligent navigation for interventional catheters, further promoting the technological development and clinical application of high-precision minimally invasive surgeries in cardiovascular and cerebrovascular procedures.

[0006] The invention disclosed in CN106610273B is a shape detection device and method based on a helical fiber Bragg grating sensor array, including a helical fiber Bragg grating sensor array, a fiber Bragg grating demodulator, a data acquisition and shape reconstruction device, and a display device. This invention requires no other external auxiliary equipment, is unaffected by electromagnetic interference, has good medical compatibility, emits no radiation, and can perform long-distance remote monitoring. Through the helical configuration of the fiber Bragg grating sensor array, multi-point deformation detection of a single fiber can be achieved, forming a quasi-distributed detection system. By encapsulating the fiber on a nickel-titanium alloy wire, the grating points can be protected from wear, resulting in strong anti-interference capabilities and an expanded detection range. It can obtain the shape of flexible robots in real time with high real-time responsiveness. Simultaneously detecting curvature and torsion, the detection method is simple and can be applied to shape perception detection in gastroscopy, colonoscopy, and flexible / soft robots. It can also play an important role in flexible robots in disaster relief, medical rehabilitation, and national defense security. However, this solution does not reconstruct the complete morphology of the catheter in three-dimensional space, resulting in lower navigation accuracy. Summary of the Invention

[0007] The purpose of this invention is to overcome the shortcomings of the prior art by providing a cavity obstacle avoidance navigation method and system based on a self-sensing magnetically controlled curved conduit. This invention aims to solve the technical problems of existing magnetically controlled conduits lacking real-time shape feedback and fiber optic sensing devices being able to only passively detect and not actively control the shape.

[0008] The objective of this invention can be achieved through the following technical solutions: A cavity obstacle avoidance navigation method based on a self-sensing magnetically controlled curved catheter includes: The initial wavelength, initial azimuth angle, and position coordinates of key navigation points of the sensors in the magnetically controlled curved duct are obtained; based on the position coordinates, the initial values ​​of the magnetic field strength, the effective length of the duct, and the spacing between permanent magnets are estimated, and control commands are generated. Based on the control command, a uniform magnetic field is generated and the effective length of the conduit and the spacing between the permanent magnets are adjusted to drive the magnetically controlled curved conduit to bend and deform; based on the initial wavelength, the wavelength offset caused by the bending deformation of the magnetically controlled curved conduit is calculated; based on the wavelength offset and the initial azimuth angle, the curvature component and torsional rate of the sensor are calculated. Based on the curvature components, calculate the total curvature and bending direction angle; calculate the deflection based on the torsion and bending direction angle; calculate the angular velocity vector based on the total curvature and deflection; calculate the rotation matrix based on the angular velocity vector; obtain the frame of the sensor position curve; update the frame according to the rotation matrix, and calculate the actual position of the sensor based on the updated curve frame; determine whether the end of the magnetically controlled curved guide tube has reached the target position based on the actual position.

[0009] Furthermore, based on the actual position, it is determined whether the end of the magnetically controlled curved conduit has reached the target position. The corresponding determination process includes: Calculate the error between the actual position and the position coordinates. If the error is less than a preset threshold, it is determined that the end of the magnetically controlled curved conduit has reached the target position. Then, iteratively correct the current iteration value of the field strength, the current iteration value of the effective length of the conduit, and the current iteration value of the permanent magnet spacing until the error between the actual position and the position coordinates is less than the threshold.

[0010] Furthermore, the correction formula corresponding to the iterative correction is: in, For the first In the next iteration, the error between the target position and the actual position of the conduit tip is... Indicates the first The correction amount of the magnetic field in the next iteration. Indicates the first The correction amount for the outer tube length in the next iteration Indicates the first The amount of correction for the spacing between permanent magnets in the next iteration. The length of the outer tube. The distance between permanent magnets. Indicates the position of the catheter tip. It indicates the magnitude and direction of the applied magnetic field.

[0011] Furthermore, the initial values ​​of the magnetic field strength, the effective length of the catheter, and the spacing between the permanent magnets are estimated using a pre-constructed catheter end position model; the catheter end position model includes: in, This refers to the position of the catheter tip. For the magnitude and direction of the applied magnetic field, The length of the outer tube. The distance between permanent magnets. This represents the magnetic moment of a permanent magnet ring. The magnetic moment of a permanent magnet. Let be the Young's modulus of the magnetic ring. This is the Young's modulus of the magnet. The moment of inertia of the magnetic ring cross section, Let be the moment of inertia of the cross section of the magnet.

[0012] Furthermore, based on the wavelength offset and the initial azimuth angle, the curvature component and torsional rate of the sensor are calculated, and the corresponding calculation formulas are as follows: in, and For curvature components, For torsional rate, , , The first The azimuth angles of the 1st, 2nd, and 3rd fiber cores at each FBG measurement point. 、 These are bending and torsional sensitivities, respectively. This is the distance from the fiber core to the center of the sensing bundle. , and The first The axial strain values ​​of the 1st, 2nd, and 3rd fiber cores at the nth FBG measuring point, where n represents the axial strain value of the 1st, 2nd, and 3rd fiber cores. One FBG measurement point.

[0013] Furthermore, based on the curvature components, the total curvature and bending direction angle are calculated; based on the torsional rate and bending direction angle, the deflection is calculated, and the corresponding calculation formula is as follows: in, For total curvature, The bending direction angle, For torsion, This represents the bending direction angle at the nth grating position. Indicates the torsion rate.

[0014] Furthermore, based on the total curvature and torsion, the angular velocity vector is calculated using the following formula: in, It is the angular velocity vector. Indicates the first Axial linear increment of each FBG measuring point For the first Tangent unit vector at each FBG measurement point Let the radius of the curve spiral be the radius of the nth FBG measuring point. For the first Rotation angle per unit arc length at each FBG measuring point For the first The unit vector of the binormal at each FBG measurement point They represent the first angular velocity vector at each FBG The three components in the local coordinate system; Based on the angular velocity vector, the rotation matrix is ​​calculated using the following formula: in, Let be a rotation matrix. It is the identity matrix. The coefficient is the sine coefficient. It is a cross product matrix. This is the cosine correction factor.

[0015] Furthermore, the frame is updated according to the rotation matrix, and the corresponding update expression is: in, For the first Tangent unit vector at each FBG measurement point Indicates the first The principal normal unit vector at each FBG measurement point Indicates the first Tangent unit vector at each FBG measurement point For the first The principal normal unit vector at each FBG measurement point For the first The unit vector of the binormal at each FBG measurement point Indicates the first Unit vector of the binormal at each FBG measurement point; Based on the updated curve frame, the actual position of the sensor is calculated using the following formula: in, For the first The actual location of the sensor at each FBG measurement point. For the first The actual location of the sensor at each FBG measurement point. For the first Axial linear increment of each FBG measuring point This indicates the arc length step between adjacent FBG measurement points. This represents the cosine correction factor.

[0016] Furthermore, based on the initial wavelength, the wavelength shift caused by the bending deformation of the magnetically controlled curved conduit is calculated, and the corresponding calculation formula is as follows: in, This is the wavelength offset. The initial wavelength of FBG. The elastic coefficient is 1. The total strain generated by the FBG along with the optical fiber is denoted as FBG.

[0017] The present invention also provides a system for a cavity obstacle avoidance navigation method based on a self-sensing magnetically controlled curved duct, comprising a memory and a processor, wherein the memory stores a computer program, and the processor calls the computer program to execute the steps of any of the methods described above.

[0018] Compared with the prior art, the present invention has the following advantages: (1) This invention achieves complete morphological reconstruction of the catheter in three-dimensional space by simultaneously calculating the total curvature, bending direction angle, and torsion angle, and further calculating the angular velocity vector and rotation matrix based on these parameters to iteratively update the Frenet frame of the curve; the total curvature calculated from the FBG strain data can characterize the severity of the bending; the bending direction angle can characterize which plane the bending occurs in; at the same time, the system also independently calculates the torsion angle, which can characterize the degree of rotation of the catheter around its own axis. The total curvature tells the system how much it bends, the bending direction angle tells the system which direction it bends, and the torsion angle tells the system whether there is torsion. These three parameters together constitute a complete description of the local deformation of the catheter; By incorporating these three parameters into a unified reconstruction framework, the system can accurately distinguish between two fundamentally different mechanical behaviors: bending deformation and torsional deformation. This avoids misjudging torsion as bending or vice versa, thereby achieving precise reconstruction of the true posture of the magnetically controlled curved duct in three-dimensional space. It avoids the posture calculation errors caused by ignoring torsion or assuming planar bending in traditional methods, enabling the duct to maintain high-precision shape perception and position positioning capabilities even when passing through the complex three-dimensional bending and spiral structures in the body's natural cavities.

[0019] (2) This invention obtains the current frame of the sensor position curve, updates the frame according to the rotation matrix, and calculates the actual position of the sensor based on the updated curve frame, thus realizing the point-by-point continuous position recursion from the proximal end to the distal end of the catheter; through the rotation matrix, the system can accurately calculate the frame and position of the next point according to the frame of the current point and the bending and torsion information at that point. This process is carried out iteratively along the length of the catheter until the distal end of the catheter is reached. Unlike traditional methods that estimate shape solely through discrete point interpolation or simple geometric assumptions, the frame iterative update method of this invention strictly follows the curve evolution law in differential geometry, ensuring that the position recursion between adjacent measurement points has clear physical meaning and mathematical rigor. It achieves continuous, smooth, and error-free three-dimensional shape reconstruction from the proximal end to the distal end of the catheter, ensuring continuous changes in the tangential, normal, and subnormal directions of the reconstructed curve at each point. This avoids unreasonable shape distortion caused by blind interpolation between discrete sampling points, thereby significantly improving the accuracy and reliability of catheter distal end position calculation.

[0020] (3) This invention compares the actual position of the catheter tip obtained by FBG perception and three-dimensional reconstruction with the preset key navigation point position coordinates, and autonomously judges whether the target position has been reached based on the error between the two. If the target position has not been reached, the next round of control correction is automatically started, forming a complete perception-drive-judgment-correction closed-loop control system. This realizes fully autonomous obstacle avoidance navigation of the magnetically controlled curved catheter in complex human body cavities. The system can automatically sense the relative positional relationship between the catheter and the cavity wall, autonomously adjust the drive parameters to avoid obstacles, and accurately converge to each preset navigation point. This significantly reduces the technical threshold and workload of operators, while improving the safety and repeatability of the navigation process. Attached Figure Description

[0021] Figure 1 This is a flowchart of a cavity obstacle avoidance navigation method based on a self-sensing magnetically controlled curved duct provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of a cavity obstacle avoidance navigation system based on a self-sensing magnetically controlled curved duct provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of a self-sensing magnetically controlled curved conduit, which is part of a cavity obstacle avoidance navigation system based on a self-sensing magnetically controlled curved conduit provided in an embodiment of the present invention. Figure 4 This is a schematic diagram of the fiber optic sensing bundle in a cavity obstacle avoidance navigation system based on a self-sensing magnetically controlled curved conduit provided in an embodiment of the present invention. Figure 5 This is a schematic diagram of the fiber optic sensing bundle end face of a cavity obstacle avoidance navigation system based on a self-sensing magnetically controlled curved conduit provided in an embodiment of the present invention. Figure 6 This is a schematic diagram of the experimental steps of a cavity obstacle avoidance navigation system based on a self-sensing magnetically controlled curved duct provided in an embodiment of the present invention during an obstacle avoidance experiment; Figure 7 This is a schematic diagram of an experimental image of a cavity obstacle avoidance navigation system based on a self-sensing magnetically controlled curved conduit provided in an embodiment of the present invention during an obstacle avoidance experiment.

[0022] In the figure: 1-Computer, 2-Fiber optic sensing demodulation system, 3-Displacement stage, 4-Self-sensing magnetic control guide tube, 5-Magnetic field range generated by Helmholtz coil, 6-Outer tube, 7-Miniature magnetic ring, 8-Helical fiber bundle, 9-Miniature magnet, 10-Adhesive, 11-Single-mode fiber, 12-Fiber core, 13-Cladding, 14-Coating layer. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0024] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0025] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0026] Definitions: OFDR (Optical Frequency Reduction) system is a distributed fiber optic sensing technology. Its core principle involves incident a linearly swept continuous laser beam into the fiber. By measuring the interference signal between the backscattered light and the reference light, and performing a Fourier transform on this interference signal, the information in the frequency domain is mapped to information in the fiber's axial distance domain, thus obtaining the scattering intensity distribution at various locations along the fiber. Unlike FBG (Fiber Optic Grating), which can only measure strain or temperature at discrete points with pre-written gratings, OFDR technology utilizes the natural, continuous Rayleigh scattering signal in the fiber as the sensing information carrier. It achieves fully distributed measurement along the entire fiber without the need for any structures written on the fiber, resulting in extremely high spatial resolution (down to millimeter or even sub-millimeter level) and strain measurement accuracy.

[0027] The Frenet-Serret framework is a standard tool in differential geometry used to describe the local geometric properties of a space curve at each point. It consists of three mutually orthogonal unit vectors: the tangent vector T, the principal normal vector N, and the binormal vector B.

[0028] Example 1 like Figure 1 As shown, this embodiment provides a cavity obstacle avoidance navigation method based on a self-sensing magnetically controlled curved duct, the method including the following steps: S1: Obtain the initial wavelength, initial azimuth angle, and position coordinates of key navigation points of the sensors in the magnetically controlled curved duct; based on the position coordinates, estimate the initial values ​​of magnetic field strength, effective duct length, and permanent magnet spacing, and generate control commands; Preferred, Using a pre-built catheter tip position model, the initial values ​​of the magnetic field strength, effective catheter length, and permanent magnet spacing are estimated. The catheter tip position model includes: in, This refers to the position of the catheter tip. For the magnitude and direction of the applied magnetic field, The length of the outer tube. The distance between permanent magnets. This represents the magnetic moment of a permanent magnet ring. The magnetic moment of a permanent magnet. Let be the Young's modulus of the magnetic ring. This is the Young's modulus of the magnet. The moment of inertia of the magnetic ring cross section, Moment of inertia of the cross section of the magnet S2: Based on control commands, a uniform magnetic field is generated and the effective length of the conduit and the spacing between permanent magnets are adjusted to drive the magnetically controlled bending conduit to bend and deform; based on the initial wavelength, the wavelength offset caused by the bending deformation of the magnetically controlled bending conduit is calculated; based on the wavelength offset and the initial azimuth angle, the curvature component and torsional rate of the sensor are calculated. Preferred, Based on the wavelength offset and initial azimuth angle, the curvature component and torsional rate of the sensor are calculated, and the corresponding calculation formulas are as follows: in, and For curvature components, For torsional rate, , , The first The azimuth angles of the 1st, 2nd, and 3rd fiber cores at each FBG measurement point. 、 These are bending and torsional sensitivities, respectively. This is the distance from the fiber core to the center of the sensing bundle. , and The first The axial strain values ​​of the 1st, 2nd, and 3rd fiber cores at the nth FBG measuring point, where n represents the axial strain value of the 1st, 2nd, and 3rd fiber cores. One FBG measurement point.

[0029] Specifically, The axial strain of each fiber core is calculated based on the wavelength offset. Combined with the initial azimuth angle, the curvature component and torsion ratio at the nth FBG measuring point are calculated using the strain-curvature-torsion decoupling formula. The cumulative torsion angle is obtained by integrating the torsion ratio along the arc length. Combined with the initial azimuth angle, the real-time azimuth angle of each fiber core is calculated.

[0030] The total curvature and bending direction angle are calculated based on the curvature components, and the angular velocity vector is constructed based on the total curvature and deflection. The rotation matrix is ​​obtained through the Rodriguez formula, and the Frenet frame of the sensor position curve is iteratively updated. The actual position of the sensor is recursively calculated based on the updated frame, thereby realizing the reconstruction of the three-dimensional morphology of the duct.

[0031] Preferred, Based on the initial wavelength, the wavelength shift caused by the bending deformation of the magnetically controlled curved conduit is calculated using the following formula: in, This is the wavelength offset. The initial wavelength of FBG. The elastic coefficient is 1. The total strain generated by the FBG along with the optical fiber is denoted as FBG.

[0032] S3: Calculate the total curvature and bending direction angle based on the curvature components; calculate the deflection based on the torsional rate and bending direction angle; calculate the angular velocity vector based on the total curvature and deflection; calculate the rotation matrix based on the angular velocity vector; obtain the frame of the sensor position curve; update the frame according to the rotation matrix, and calculate the actual position of the sensor based on the updated curve frame; determine whether the end of the magnetically controlled curved guide tube has reached the target position based on the actual position.

[0033] Preferred, Based on the curvature components, the total curvature and bending direction angle are calculated; based on the torsional rate and bending direction angle, the deflection is calculated, and the corresponding calculation formulas are as follows: in, For total curvature, The bending direction angle, For torsion, This represents the bending direction angle at the nth grating position. Indicates the torsion rate.

[0034] Preferred, Based on the total curvature and torsion, the angular velocity vector is calculated using the following formula: in, ; in, It is the angular velocity vector. Indicates the first Axial linear increment of each FBG measuring point For the first Tangent unit vector at each FBG measurement point For the first The curve helix radius of each FBG measuring point For the first Rotation angle per unit arc length at each FBG measuring point For the first The unit vector of the binormal at each FBG measurement point They represent the first angular velocity vector at each FBG The three components in the local coordinate system; The Rodriguez rotation matrix is ​​calculated based on the angular velocity vector, and the corresponding formula is as follows: in, For the Rodriguez rotation matrix, It is the identity matrix. The coefficient is the sine coefficient. It is a cross product matrix. This is the cosine correction factor.

[0035] Preferred, The frame is updated based on the rotation matrix, and the corresponding update expression is: in, For the first Tangent unit vector at each FBG measurement point Indicates the first The principal normal unit vector at each FBG measurement point Indicates the first Tangent unit vector at each FBG measurement point For the first The principal normal unit vector at each FBG measurement point For the first The unit vector of the binormal at each FBG measurement point Indicates the first Unit vector of the binormal at each FBG measurement point; Based on the updated curve frame, the actual position of the sensor is calculated using the following formula: in, For the first The actual location of the sensor at each FBG measurement point. For the first The actual location of the sensor at each FBG measurement point. For the first Axial linear increment of each FBG measuring point This indicates the arc length step between adjacent FBG measurement points. This represents the cosine correction factor.

[0036] Preferred, The judgment process includes: The error between the actual position and the position coordinates is calculated. If the error is less than a preset threshold, it is determined that the end of the magnetically controlled curved duct has reached the target position. If it is greater than or equal to the threshold, the initial values ​​of the field strength, the effective length of the duct, and the spacing between the permanent magnets are iteratively corrected until the error between the actual position and the position coordinates is less than the threshold.

[0037] The correction formula corresponding to the iterative correction is: in, For the first In the next iteration, the error between the target position and the actual position of the conduit tip is... Indicates the first The correction amount of the magnetic field in the next iteration. Indicates the first The correction amount for the outer tube length in the next iteration Indicates the first The amount of correction for the spacing between permanent magnets in the next iteration. The length of the outer tube. The distance between permanent magnets. Indicates the position of the catheter tip. It indicates the magnitude and direction of the applied magnetic field.

[0038] Example 2 This embodiment provides a self-sensing magnetically controlled bending conduit system, including a control computer, an optical fiber sensing demodulation system, a self-sensing magnetically controlled bending conduit, a magnetic field driving device, and a structural adjustment device.

[0039] The control computer serves as the core control terminal of the system, incorporating closed-loop control algorithms, 3D morphology reconstruction algorithms, and navigation point path planning logic. It enables real-time reception of sensor data, catheter morphology calculation, tip position deviation analysis, and control command output, supporting full-process decision-making and precise control. Overcoming the limitations of traditional magnetic control systems that separate "shape control" from "sensing" data, it achieves fully automated closed-loop control, enabling navigation of complex cavities without manual intervention and enhancing the intelligence level of interventional surgery.

[0040] The fiber optic sensing demodulation system has a sampling frequency of 1kHz-10kHz, enabling real-time acquisition of wavelength shift signals from fiber optic gratings and the completion of optical-to-electrical signal conversion and data transmission. The demodulation system supports multi-channel parallel acquisition, detecting multiple fiber optic sensing signals to ensure comprehensive and reliable deformation detection, providing high-precision raw data for duct 3D morphology reconstruction. This system integrates two core devices: a grating demodulator and an OFDR system. It can flexibly switch operating modes according to actual sensing needs, achieving high-precision acquisition and demodulation processing of fiber optic sensing signals.

[0041] The self-sensing magnetically controlled bending conduit serves as the core carrier at the end of the system. Its overall outer diameter is adapted to the miniaturized operation requirements of human body cavities, integrating a reverse-magnetized permanent magnet array and a fiber optic sensing bundle. The reverse-magnetized permanent magnet array uses high magnetic energy product materials, which can generate sufficient magnetic torque under low-intensity magnetic fields. The spacing between the permanent magnets can be adaptively adjusted within a certain range, allowing for flexible switching of various bending shapes of the conduit by changing the spacing, adapting to the obstacle avoidance and navigation requirements of different cavities. The fiber optic sensing bundle is composed of multiple single-mode optical fibers spirally wound and bonded with adhesive. The sensing bundle is uniformly embedded in the conduit along the conduit axis, ensuring no blind spots in deformation detection and realizing the integration of magnetically driven active deformation and real-time deformation sensing functions.

[0042] The magnetic field drive device consists of a one-dimensional Helmholtz coil and a high-precision current drive module. It can generate a uniform magnetic field with precise and controllable direction and magnitude according to control commands, providing stable magnetic torque for the catheter. The working area of ​​the Helmholtz coil can cover the entire control section of the catheter, ensuring the uniformity of the magnetic field and avoiding uneven deformation of the catheter due to magnetic field gradient.

[0043] The structural adjustment device is the core of the system's mechanical adjustment. It is compatible with the self-sensing magnetically controlled bending catheter and can precisely adjust the spacing between the permanent magnet arrays according to the instructions of the control computer. Together with the magnetic field drive device, it can flexibly adjust the bending shape of the catheter to meet the operational needs of cavity environments with different curvature requirements.

[0044] Furthermore, the self-sensing magnetically controlled curved catheter system can achieve flexible adaptation and functional expansion of various devices. The control computer, magnetic field drive device, fiber optic sensing demodulation system, structural adjustment device and self-sensing magnetically controlled curved catheter are connected through standardized interfaces. Different specifications of self-sensing magnetically controlled curved catheters, magnetic field drive devices or structural adjustment devices can be replaced according to the needs of clinical scenarios to adapt to the operation requirements of different minimally invasive interventional surgeries such as cardiovascular and bronchial procedures.

[0045] This system innovatively adopts an integrated design of a reverse magnetized concentric structure and a helical fiber optic sensing bundle, combining magnetically driven active shape control with real-time fiber optic shape sensing. It integrates five major components: a self-sensing magnetically controlled bending catheter, a magnetic field drive device, a fiber optic sensing demodulation system, a structural control device, and a control computer. This enables precise control of the catheter's morphology, real-time deformation sensing, and closed-loop error correction. It can flexibly switch between complex bending shapes such as S-shapes and C-shapes. The overall structure is compact, highly resistant to electromagnetic interference, and highly integrated with shape control and sensing. It has demonstrated strong potential in simulated obstacle avoidance experiments, providing a core solution for intelligent interventional navigation in robotic minimally invasive surgery, particularly suitable for high-precision interventional procedures in cardiovascular and cerebrovascular diseases.

[0046] Example 3 This embodiment uses obstacle avoidance in complex human cavities as an application scenario, and builds a self-sensing magnetically controlled bending catheter system, such as... Figure 2 As shown, this is used to conduct obstacle avoidance experiments. The experiment follows a closed-loop process: system initialization and calibration, navigation point parameter estimation, magnetic control and structural adjustment, real-time duct deformation detection, duct 3D shape reconstruction, error calculation, threshold judgment, and iterative correction / continuous navigation.

[0047] To verify the applicability and performance differences of the system under different fiber optic demodulation technologies, comparative experiments were conducted using two typical sensing demodulation schemes: a grating demodulator and an OFDR system. The former uses a fiber Bragg grating array to achieve discrete-point strain acquisition, while the latter utilizes Rayleigh scattering to achieve continuous distributed strain sensing. Both have their advantages in terms of spatial resolution, sampling rate, and system complexity, and can comprehensively evaluate the system's deformation sensing capability and control accuracy in different application scenarios.

[0048] This embodiment provides a self-sensing magnetically controlled bending duct system that uses a grating demodulator as a fiber optic sensing demodulation system to verify the obstacle avoidance and navigation performance of the self-sensing magnetically controlled bending duct system in simulating complex cavities of the human body.

[0049] like Figure 3 As shown, the effective total length of the self-sensing magnetically controlled bending conduit is fixed at 18.5cm. The outer flexible support tube is made of highly flexible silicone material, and the internal structure contains an optical fiber sensing bundle engraved with FBG. A reverse-magnetized permanent magnet array is integrated at the distal end of the conduit.

[0050] like Figure 4 As shown, the fiber optic sensing bundle is made of three G.652 single-mode fibers tightly wound in a spiral structure and bonded tightly with adhesive. Each single-mode fiber has 10 FBG arrays with a length of 5mm and a spacing of 2cm. Figure 5 This is a schematic diagram of the end face of the fiber optic sensing bundle.

[0051] The magnetic field drive device used in the system can generate a uniform magnetic field of 0-30 mT, and the magnetic field strength exhibits a good linear relationship with the current. The structural control device employs a precision electric displacement stage to control the length of the external conduit. Distance to magnet array Precise adjustments are achieved through the computer's built-in closed-loop control algorithm, 3D morphology reconstruction algorithm, and navigation point path planning logic, supporting full-process decision-making and control.

[0052] The working steps of the entire system are as follows Figure 6 As shown.

[0053] Step 1: System initialization calibration.

[0054] The fiber optic sensing demodulation system calibrates the initial wavelength and initial twist angle of the FBG (core sensing element), records the position coordinates of key navigation points, and sets a threshold error. =5mm.

[0055] Step 2, Navigation point parameter estimation.

[0056] Based on the magnetic drive shaping principle of the reverse magnetized permanent magnet array and Euler-Bernoulli beam theory, the two magnets generate magnetic torque respectively: The catheter body is modeled as two cascaded cantilever beams, and the catheter tip position model is constructed based on Euler-Bernoulli beam theory: Estimate the initial value of the magnetic field strength Initial value of effective catheter length Initial value of permanent magnet spacing To generate control commands.

[0057] Step 3, Magnetically controlled shaping and structural regulation.

[0058] The control computer synchronously outputs commands to the magnetic field drive device and the structural parameter control device. The magnetic field drive device adjusts the input current to generate a uniform magnetic field, causing the array of reverse-magnetized permanent magnets inside the conduit to deform under the action of magnetic torque; simultaneously, the structural parameter control device precisely adjusts... and The two work together to drive the catheter to bend and deform.

[0059] Step 4: Perform catheter deformation monitoring.

[0060] During the duct deformation process, real-time fiber optic deformation detection is performed simultaneously. A grating demodulator acquires the wavelength offset of the FBG array at a preset sampling frequency of 5kHz. When the conduit undergoes bending or torsional deformation, the FBG generates a total strain along with the optical fiber. The wavelength shift satisfies: in, The initial wavelength of the FBG. The optical-elastic coefficient is denoted as . The demodulator converts the optical signal into an electrical signal, which is transmitted to the control computer. Based on the wavelength offset, the computer calculates the strain distribution of the FBG in the three fiber cores. .

[0061] Step 5: Reconstruct the three-dimensional shape of the catheter.

[0062] Adopting the Frenet-Serret framework Perform three-dimensional morphological reconstruction of the catheter to obtain the actual position of the catheter tip. After receiving the strain data, the computer uses a strain-curvature-torsional conversion model to solve for the curvature components of each FBG in the duct. , and torsion rate : in, For the first One FBG measurement point This is the azimuth angle of the optical fiber. , These are bending and torsional sensitivities, respectively. This is the distance from the fiber core to the center of the sensing bundle. Then, the total curvature is solved from the curvature components. , bending direction and torsion: Discretize the space curve into several segments of constant curvature spirals. ( It is the arc length of the spiral. Where is the helix radius. The linear increment is in the Z-axis direction. (The angle of rotation per unit arc length). Based on curvature in differential geometry... Harmony rate The basic definition of a spiral, and its three core parameters. , , It can be represented as: Based on rigid body kinematic constraints, the angular velocity vector of the spiral... Distributed only along the axis of rotation, it is represented under the Frenet-Serret frame as follows: The Rodriguez rotation formula is used to achieve iterative updates of adjacent measuring point frames. The rotation matrix S is defined as: in, It is the identity matrix. , , .

[0063] Curve Frame It can be updated via the Rhodes matrix as follows: Therefore, the actual position of the sensor can be calculated as follows: Step 6: Error calculation and threshold determination.

[0064] Calculate the actual position Location of key navigation points error : If error Determine if the catheter tip has reached the target position; if The magnetic field strength correction is solved by the damped least squares method. , , The corrected formula is: Iterative update parameters Repeat steps 3-5 until the deviation meets the threshold requirement.

[0065] Step 7: Navigate continuously until the experiment ends.

[0066] Repeat steps 2-5 until the catheter passes through all the set key navigation points, at which point the experiment ends.

[0067] The experiment used a transparent silicone blood vessel model with an inner diameter of 8mm to simulate narrow cavities in the human body. Four key navigation points were set within the model for forced passage, and the waypoint positioning error threshold was set. Set to 5mm.

[0068] The results are as follows Figure 7As shown, the catheter successfully navigated within an 8mm diameter vascular model without colliding with the model boundaries, precisely passing through four pre-set key navigation points. The deviation between the actual and target positions at each waypoint was less than 4mm, with an average end-point deviation of 2.0mm at the final target waypoint. These deviations primarily stemmed from sensor manufacturing processes, minor magnetic field control offsets, and calculation errors in the fiber optic morphology reconstruction algorithm. The average number of waypoint deviation correction iterations was 2-3, with a single waypoint navigation adjustment time ≤10s and a total vascular navigation time ≤50s. The results validate the functional synergy between the system's magnetically driven active shape control and real-time fiber optic grating sensing, as well as the effectiveness of the integrated "magnetically controlled shape-fiber optic sensing-closed-loop correction" control, fully demonstrating the practicality and stability of this invention in complex cavity navigation scenarios.

[0069] Example 4 This embodiment provides a self-sensing magnetically controlled bending duct system that uses an OFDR system as an optical fiber sensing demodulation scheme to verify the obstacle avoidance and navigation performance of the self-sensing magnetically controlled bending duct system in simulating complex cavities of the human body.

[0070] This embodiment uses the same self-sensing magnetically controlled bending conduit system structure as Embodiment 3, the difference being that the fiber optic sensing demodulation system is replaced with an OFDR system to verify its deformation sensing capability at high spatial resolution.

[0071] like Figure 3 As shown, the effective total length of the self-sensing magnetically controlled bending conduit is fixed at 20cm. The outer layer is a highly flexible silicone support tube, and the inner layer contains a spirally wound fiber optic sensing bundle. Unlike Example 3, this example uses ordinary single-mode fiber, eliminating the need for FBG array writing and utilizing the natural Rayleigh scattering within the fiber as a distributed sensing signal. A reverse-magnetized permanent magnet array is integrated at the distal end of the conduit. The magnetic field driving device, structural control device, and control computer configuration are consistent with Example 3.

[0072] The experimental environment was the same as in Example 3: a human blood vessel model with a diameter of 8mm was simulated, four key navigation points were set, and an error threshold was set. =5mm. The experiment followed... Figure 6 The closed-loop process shown is carried out.

[0073] Step 1: System initialization calibration.

[0074] The OFDR system performs a baseline scan of the duct's initial state, acquires Rayleigh scattering spectra at various points along the fiber optic cable as reference spectra, and records the coordinates of key navigation points. Set error threshold =5mm.

[0075] Step 2, Navigation point parameter estimation.

[0076] Based on the magnetic drive shaping principle of the reverse magnetized permanent magnet array and Euler-Bernoulli beam theory, the initial value of the magnetic field strength is estimated. Initial value of effective catheter length Initial value of permanent magnet spacing To generate control commands.

[0077] Step 3, Magnetically controlled shaping and structural regulation.

[0078] The control computer synchronously outputs commands to the magnetic field drive device and the structural control device, driving the conduit to bend and deform.

[0079] Step 4: Perform catheter deformation monitoring.

[0080] During the deformation of the fiber optic cable, the OFDR system acquires the wavelength shift of the Rayleigh scattering signal within the fiber in real time using a high-frequency scanning method. By comparing the cross-correlation peak shift between the current spectrum and the reference spectrum, the continuous strain distribution at each point along the fiber is calculated. The spatial resolution reaches sub-millimeter level. Compared to the FBG discrete point detection in Example 3, the OFDR system can capture more refined local deformation features.

[0081] Step 5: Reconstruct the three-dimensional shape of the catheter.

[0082] After receiving the strain data, the computer uses the same Frenet-Serret framework and curvature-torsion conversion model as in Example 3 to reconstruct the three-dimensional morphology of the catheter and obtain the actual position of the catheter tip. Thanks to continuous strain input, the interpolation error in morphological reconstruction is effectively suppressed.

[0083] Step 6: Error calculation and threshold determination.

[0084] Calculation error .like The magnetic field strength correction is solved by the damped least squares method. , , Iteratively update the parameters and repeat steps 3-5 until the deviation meets the threshold requirement.

[0085] Step 7: Navigate continuously until the experiment ends.

[0086] Repeat steps 2-5 until the catheter passes through all the set key navigation points, at which point the experiment ends.

[0087] The results are as follows Figure 7As shown, the OFDR system exhibits higher spatial resolution and signal-to-noise ratio in deformation detection. The catheter did not collide with the vessel boundary throughout the entire process and accurately reached the four key navigation points. The deviation between the actual position and the target position of each waypoint was ≤3.5mm, and the average end deviation of the final target waypoint was 1.5mm, which is better than the 2.0mm in Example 1; the average number of waypoint deviation correction iterations was 2, the navigation control time per waypoint was ≤8s, and the total obstacle avoidance navigation time was ≤45s.

[0088] It should be noted that, Figure 7 This method is applicable to both Example 3 (grating demodulator) and Example 4 (OFDR system). The duct path trajectory is basically the same under the two demodulation schemes, with no significant difference in the macroscopic path. The only difference is in the end-positioning accuracy: the end deviation is 2.0 mm in Example 1 and 1.5 mm in Example 2.

[0089] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A cavity obstacle avoidance navigation method based on a self-sensing magnetically controlled curved duct, characterized in that, include: The initial wavelength, initial azimuth angle, and position coordinates of key navigation points of the sensors in the magnetically controlled curved duct are obtained; based on the position coordinates, the initial values ​​of the magnetic field strength, the effective length of the duct, and the spacing between permanent magnets are estimated, and control commands are generated. Based on the control command, a uniform magnetic field is generated and the effective length of the conduit and the spacing between the permanent magnets are adjusted to drive the magnetically controlled bending conduit to bend and deform. Based on the initial wavelength, calculate the wavelength offset caused by the bending deformation of the magnetically controlled curved conduit; Based on the wavelength offset and the initial azimuth angle, the curvature component and torsional rate of the sensor are calculated; Based on the curvature components, calculate the total curvature and bending direction angle; calculate the deflection based on the torsional rate and bending direction angle; calculate the angular velocity vector based on the total curvature and deflection; calculate the rotation matrix based on the angular velocity vector; obtain the frame of the sensor position curve; The frame is updated according to the rotation matrix, and the actual position of the sensor is calculated based on the updated curved frame; based on the actual position, it is determined whether the end of the magnetically controlled curved guide tube has reached the target position.

2. The cavity obstacle avoidance navigation method based on a self-sensing magnetically controlled curved conduit according to claim 1, characterized in that, Based on the actual position, it is determined whether the end of the magnetically controlled curved conduit has reached the target position. The corresponding determination process includes: Calculate the error between the actual position and the position coordinates. If the error is less than a preset threshold, it is determined that the end of the magnetically controlled curved conduit has reached the target position. Then, iteratively correct the current iteration value of the field strength, the current iteration value of the effective length of the conduit, and the current iteration value of the permanent magnet spacing until the error between the actual position and the position coordinates is less than the threshold.

3. The cavity obstacle avoidance navigation method based on a self-sensing magnetically controlled curved duct according to claim 2, characterized in that, The correction formula corresponding to the iterative correction is: in, For the first In the next iteration, the error between the target position and the actual position of the conduit tip is... Indicates the first The correction amount of the magnetic field in the next iteration. Indicates the first The correction amount for the outer tube length in the next iteration Indicates the first The amount of correction for the spacing between permanent magnets in the next iteration. The length of the outer tube. The distance between permanent magnets. Indicates the position of the catheter tip. It indicates the magnitude and direction of the applied magnetic field.

4. The cavity obstacle avoidance navigation method based on a self-sensing magnetically controlled curved duct according to claim 1, characterized in that, The initial values ​​for estimating the magnetic field strength, the effective length of the catheter, and the spacing between the permanent magnets are achieved using a pre-constructed catheter end position model; the catheter end position model includes: in, This refers to the position of the catheter tip. For the magnitude and direction of the applied magnetic field, The length of the outer tube. The distance between permanent magnets. This represents the magnetic moment of a permanent magnet ring. The magnetic moment of a permanent magnet. Let be the Young's modulus of the magnetic ring. This is the Young's modulus of the magnet. The moment of inertia of the magnetic ring cross section, Let be the moment of inertia of the cross section of the magnet.

5. A cavity obstacle avoidance navigation method based on a self-sensing magnetically controlled curved duct according to claim 1, characterized in that, Based on the wavelength offset and initial azimuth angle, the curvature component and torsional rate of the sensor are calculated, and the corresponding calculation formulas are as follows: in, and For curvature components, For torsional rate, , , The first The azimuth angles of the 1st, 2nd, and 3rd fiber cores at each FBG measurement point. 、 These are bending and torsional sensitivities, respectively. This is the distance from the fiber core to the center of the sensing bundle. , and The first The axial strain values ​​of the 1st, 2nd, and 3rd fiber cores at the nth FBG measuring point, where n represents the axial strain value of the 1st, 2nd, and 3rd fiber cores. One FBG measurement point.

6. A cavity obstacle avoidance navigation method based on a self-sensing magnetically controlled curved duct according to claim 5, characterized in that, Based on the curvature components, the total curvature and bending direction angle are calculated; based on the torsional rate and bending direction angle, the deflection is calculated using the following formula: in, For total curvature, The bending direction angle, For torsion, This represents the bending direction angle at the nth grating position. Indicates the torsion rate.

7. A cavity obstacle avoidance navigation method based on a self-sensing magnetically controlled curved conduit according to claim 6, characterized in that, Based on the total curvature and torsion, the angular velocity vector is calculated using the following formula: in, It is the angular velocity vector. Indicates the first Axial linear increment of each FBG measuring point For the first Tangent unit vector at each FBG measurement point Let the radius of the curve spiral be the radius of the nth FBG measuring point. For the first Rotation angle per unit arc length at each FBG measuring point For the first The unit vector of the binormal at each FBG measurement point They represent the first angular velocity vector at each FBG The three components in the local coordinate system; Based on the angular velocity vector, the rotation matrix is ​​calculated using the following formula: in, For rotation matrix, It is the identity matrix. The coefficient is the sine coefficient. It is a cross product matrix. This is the cosine correction factor.

8. A cavity obstacle avoidance navigation method based on a self-sensing magnetically controlled curved conduit according to claim 7, characterized in that, The frame is updated based on the rotation matrix, and the corresponding update expression is: in, For the first Tangent unit vector at each FBG measurement point Indicates the first The principal normal unit vector at each FBG measurement point Indicates the first Tangent unit vector at each FBG measurement point For the first The principal normal unit vector at each FBG measurement point For the first The unit vector of the binormal at each FBG measurement point Indicates the first Unit vector of the binormal at each FBG measurement point; Based on the updated curve frame, the actual position of the sensor is calculated using the following formula: in, For the first The actual location of the sensor at each FBG measurement point. For the first The actual location of the sensor at each FBG measurement point. For the first Axial linear increment of each FBG measuring point This indicates the arc length step between adjacent FBG measurement points. This represents the cosine correction factor.

9. A cavity obstacle avoidance navigation method based on a self-sensing magnetically controlled curved duct according to claim 1, characterized in that, Based on the initial wavelength, the wavelength shift caused by the bending deformation of the magnetically controlled curved conduit is calculated using the following formula: in, This is the wavelength offset. The initial wavelength of FBG. The elastic coefficient is 1. The total strain generated by the FBG along with the optical fiber is denoted as FBG.

10. A system for a cavity obstacle avoidance navigation method based on a self-sensing magnetically controlled curved duct, characterized in that, It includes a memory and a processor, the memory storing a computer program, the processor invoking the computer program to perform the steps of the method as described in any one of claims 1 to 9.

Images