Transcutaneous puncture surgery robot system based on quantum multi-dimensional sensor and control method

Abstract

The application relates to the technical field of medical control, in particular to a transcutaneous puncture operation robot system and a control method based on a quantum multidimensional sensor. The method comprises the following steps: a magnetic field change detection and a puncture needle position determination are performed on a puncture process by using a magnetic field sensor based on a superconducting quantum interference device, and a transcutaneous puncture operation puncture needle position distribution is obtained. Meanwhile, the system is based on an advanced technical architecture, and can provide accurate support for various transcutaneous puncture operation modes, which cover the fields of transcutaneous puncture tumor minimally invasive operation, spine minimally invasive operation, neurosurgery minimally invasive operation and the like. The system has wide indications, and can be used for soft tissue, spine and brain related diseases, and can cope with various operations such as tumor ablation, spine scoliosis screw implantation, Alzheimer's disease and epilepsy electrode implantation, brain hemorrhage drainage and the like. The application can ensure the accuracy and safety of puncture.

Description

Technical Field

[0001] This invention relates to the field of medical control technology, and in particular to a percutaneous puncture surgical robot system and control method based on quantum multidimensional sensors. Background Technology

[0002] In recent years, percutaneous puncture surgical robots have gradually become a research hotspot. Existing percutaneous puncture robot technologies include magnetic navigation, near-infrared navigation, and the more advanced structured light navigation. These devices still have significant room for improvement in terms of risk control, surgical precision, and real-time operation. Quantum multidimensional sensors, however, are greatly improving many problems in the medical field by providing unprecedented precision and functionality. These sensors utilize principles of quantum mechanics, such as superposition and entanglement, to achieve previously unattainable high sensitivity, high precision, high resolution, high response rate, high transparency, and non-invasive measurement methods. These characteristics provide new possibilities for the development of percutaneous puncture surgical robots. Currently, traditional percutaneous puncture surgical navigation technology mainly relies on imaging methods such as ultrasound, CT, and X-ray fluoroscopy to guide the puncture needle. While these methods can improve puncture precision to some extent, they also suffer from difficulties in localization, weak anti-interference capabilities, and the inability to quantify operations during surgery. This hinders the standardization, homogenization, and normalization of percutaneous puncture surgery, resulting in a long learning curve for doctors. Summary of the Invention

[0003] Therefore, it is necessary for the present invention to provide a percutaneous puncture surgical robot system and control method based on quantum multidimensional sensors to solve at least one of the above-mentioned technical problems.

[0004] To achieve the above objectives, a control method for a percutaneous puncture surgical robot system based on quantum multidimensional sensors includes the following steps:

[0005] Step S1: Detect the change in the puncture magnetic field during the percutaneous puncture procedure using a magnetic field sensor based on a superconducting quantum interference device placed near the patient's body surface, so as to obtain the distribution field of the percutaneous puncture magnetic field change; determine the position of the puncture needle during the percutaneous puncture procedure based on the distribution field of the percutaneous puncture magnetic field change, so as to obtain the distribution of the position of the percutaneous puncture needle.

[0006] Step S2: By real-time monitoring of the patient's respiratory movement changes and human body displacement changes during the percutaneous puncture surgery robot, and based on the changes in the patient's respiratory movement changes and human body displacement changes, the percutaneous puncture needle position distribution is analyzed to correct the puncture depth, and the percutaneous puncture needle depth distribution is obtained.

[0007] Step S3: Using a magnetic resonance imaging sensor based on nitrogen vacancy centers placed near the puncture needle, the tumor displacement distribution during the percutaneous puncture surgical robot is detected to obtain the tumor displacement distribution of the percutaneous puncture patient; the location distribution of the percutaneous puncture needle reaching the target area is determined based on the tumor displacement distribution of the percutaneous puncture patient.

[0008] Step S4: Based on the distribution of the percutaneous needle position in the target area, perform needle insertion depth distribution control for percutaneous puncture surgery to generate percutaneous puncture surgery needle insertion navigation path, so as to perform corresponding percutaneous puncture surgery robot puncture navigation adjustment work.

[0009] Furthermore, step S1 includes the following steps:

[0010] Step S11: Using a magnetic field sensor based on a superconducting quantum interference device placed near the patient's body surface, the magnetic field fluctuations of the percutaneous puncture surgical robot are collected during the puncture process, and the weak magnetic field distribution fluctuations at each moment during the percutaneous puncture are obtained.

[0011] Step S12: Perform magnetic field spatial gradient analysis on the weak magnetic field distribution fluctuations at each moment during the percutaneous puncture process to obtain the magnetic field spatial distribution gradient corresponding to each spatial distribution position during the percutaneous puncture process.

[0012] Step S13: Perform puncture space distribution analysis on the puncture process corresponding to the percutaneous puncture surgical robot to obtain the puncture space distribution between the puncture needle and the surrounding tissues during the percutaneous puncture process;

[0013] Step S14: Based on the magnetic field spatial distribution gradient corresponding to each spatial distribution position during the percutaneous puncture process, the magnetic field change distribution coupling processing is performed on the puncture spatial distribution between the puncture needle and the surrounding tissues during the percutaneous puncture process to obtain the magnetic field change distribution field of the percutaneous puncture surgery.

[0014] Step S15: Determine the position of the puncture needle in the percutaneous puncture surgery robot based on the distribution of the magnetic field change in the percutaneous puncture surgery, and obtain the distribution of the position of the percutaneous puncture needle.

[0015] Furthermore, step S15 includes the following steps:

[0016] Step S151: Perform electromagnetic property analysis on the tissue surrounding the surgical area during the percutaneous puncture procedure of the percutaneous puncture surgical robot to obtain the electromagnetic properties of the tissue surrounding the percutaneous puncture surgical area, including the conductivity and dielectric constant of the surrounding tissue.

[0017] Step S152: Perform temporal decomposition of magnetic field perturbation on the distribution field of magnetic field changes during percutaneous puncture surgery to obtain the distribution of magnetic field perturbation at each time point during percutaneous puncture.

[0018] Step S153: Based on the electromagnetic properties of the tissue surrounding the percutaneous puncture surgical area, the relative position of the puncture is calculated by analyzing the distribution of magnetic field changes and disturbances generated at each time point during the percutaneous puncture, thus obtaining the relative position distribution of the puncture needle tip in the percutaneous puncture surgery.

[0019] Step S154: Obtain the stress response between the puncture needle tip and the surrounding tissue and the puncture force through the puncture process corresponding to the percutaneous puncture surgical robot;

[0020] Step S155: Based on the stress response between the puncture needle tip and the surrounding tissue and the puncture force, the relative position distribution of the percutaneous puncture needle tip is corrected for puncture position deviation, and the position distribution of the percutaneous puncture needle is obtained.

[0021] Furthermore, step S153 includes the following steps:

[0022] Electromagnetic flow and dielectric effect of the puncture needle were analyzed to obtain the electromagnetic flow and dielectric effect between the percutaneous puncture needle and the tissue surrounding the surgical area, based on the electrical conductivity and dielectric coefficient of the tissues surrounding the percutaneous puncture area.

[0023] The distribution of magnetic field changes and disturbances generated at each time point during percutaneous puncture was analyzed in the time domain and frequency domain to extract the relative position feature points of the percutaneous puncture needle tip at each time point, thus obtaining the set of relative position feature points of the magnetic field caused by the movement of the percutaneous puncture needle tip.

[0024] Based on the electromagnetic flow and dielectric effect between the percutaneous puncture needle and the surrounding tissue of the surgical area, the relative position of each relative position feature point in the set of magnetic field relative position feature points caused by the movement of the percutaneous puncture needle tip is calculated to obtain the distribution of the relative position of the percutaneous puncture needle tip.

[0025] Furthermore, step S155 includes the following steps:

[0026] Stress field modeling is performed on the stress response between the puncture needle tip and the surrounding tissue to simulate the local stress distribution generated when the puncture needle tip comes into contact with the surrounding tissue during puncture, and to generate the corresponding stress coupling distribution model between the puncture needle tip and the surrounding tissue.

[0027] Stress gradient analysis was performed on the stress coupling distribution model between the puncture needle tip and the surrounding tissue to obtain the stress change gradient between the puncture needle tip and the surrounding tissue.

[0028] Based on the puncture force between the puncture needle tip and the surrounding tissue, the corresponding puncture process is analyzed by tissue puncture elastic modulus to obtain the corresponding tissue puncture elastic modulus between the puncture needle tip and the surrounding tissue.

[0029] Based on the stress gradient between the puncture needle tip and the surrounding tissue and the elastic modulus of the tissue puncture, the relative position distribution of the puncture needle tip in percutaneous puncture surgery is corrected for puncture position deviation, and the position distribution of the puncture needle in percutaneous puncture surgery is obtained.

[0030] Furthermore, step S2 includes the following steps:

[0031] Step S21: The patient's respiratory motion changes are monitored in real time during the percutaneous puncture procedure by a preset pressure sensor array. The body surface pressure change signal generated by the patient's respiratory motion is converted into an electrical signal, and the electrical signal is statistically analyzed to obtain the patient's respiratory motion changes, including the patient's respiratory cycle, tidal volume, respiratory rate, and respiratory phase change parameters.

[0032] Step S22: By performing a three-dimensional reconstruction of the patient's human body contour in a preoperative static state with the operating table as the coordinate origin, a human body displacement reference map is generated.

[0033] Step S23: By synchronously activating the preset laser radar scanning device, the percutaneous puncture surgical robot performs real-time monitoring of the human body's three-dimensional point cloud during the puncture process to obtain real-time three-dimensional point cloud data of the human body during the percutaneous puncture process; based on the human body displacement reference map and through the iterative nearest point algorithm, the relative displacement change of the human body is calculated for the corresponding three-dimensional feature points in the real-time three-dimensional point cloud data of the human body during the percutaneous puncture process to obtain the patient's human body displacement change.

[0034] Step S24: Based on the changes in the patient's respiratory movements and the changes in the patient's body displacement, the puncture path deviation is calculated using the puncture needle tip path deviation calculation formula to estimate the puncture path deviation of the percutaneous puncture surgical robot, so as to obtain the puncture path deviation vector between the puncture needle tip and the ideal target point at each time.

[0035] Step S25: Based on the puncture path deviation vector between the puncture needle tip and the ideal target point at each time point, perform a puncture depth correction analysis on the percutaneous puncture needle position distribution to obtain the percutaneous puncture needle depth distribution.

[0036] Furthermore, the specific formula for calculating the deviation of the puncture needle tip path in step S24 is as follows:

[0037]

[0038] In the formula, Let be the puncture path deviation vector between the needle tip and the ideal target point at time t, where t0 is the initial puncture time, T is the patient's corresponding respiratory cycle, and i is the item index of the coordinate axis direction, where 1 represents the x-axis direction in the Cartesian coordinate system, 2 represents the y-axis direction in the Cartesian coordinate system, and 3 represents the z-axis direction in the Cartesian coordinate system. Let k be the change in human body displacement of the patient along the i-th coordinate axis at time t. i c represents the second-order nonlinear deviation weight corresponding to the i-th coordinate axis direction. i Let m be the first-order nonlinear deviation weight corresponding to the i-th coordinate axis direction. i α is the linear deviation weight corresponding to the i-th coordinate axis direction. i Let ω be the attenuation coefficient corresponding to the i-th coordinate axis, and ω be the patient's respiratory rate. The patient's corresponding respiratory phase. Let t be the tidal unit direction vector corresponding to the patient at time t.

[0039] Furthermore, step S3 includes the following steps:

[0040] Step S31: Use the magnetic resonance imaging sensor based on nitrogen vacancy center placed near the puncture needle to perform magnetic resonance measurement of the puncture needle during the puncture process corresponding to the percutaneous puncture surgical robot, so as to generate the change of magnetic resonance signal of nitrogen vacancy center of percutaneous puncture needle.

[0041] Step S32: Based on the change of the magnetic resonance signal of the nitrogen vacancy center of the percutaneous puncture needle, perform micro-displacement tracking analysis of the puncture process corresponding to the percutaneous puncture surgical robot to obtain the micro-dynamic displacement trajectory of the percutaneous puncture needle.

[0042] Step S33: Obtain the magnetic resonance image of the tumor tissue corresponding to the percutaneous puncture needle during the puncture process using a magnetic resonance imaging sensor based on nitrogen vacancy centers, and perform spatial distribution analysis of the puncture needle and tumor based on the magnetic resonance image of the tumor tissue corresponding to the percutaneous puncture needle during the puncture process to generate the spatial distribution relationship between the percutaneous puncture needle and the tumor tissue location during the puncture process.

[0043] Step S34: Based on the micro-dynamic displacement trajectory of the percutaneous puncture needle and combined with dynamic simulation and physical modeling, the spatial distribution relationship between the percutaneous puncture needle and the tumor tissue position during the puncture process is detected to eliminate the mechanical influence of different puncture angles, speeds and local tissue deformation caused by needle puncture on tumor displacement, and obtain the tumor displacement distribution of percutaneous puncture patients.

[0044] Step S35: Determine the location distribution of the percutaneous puncture needle reaching the target area based on the tumor displacement distribution of the percutaneous puncture patient.

[0045] Furthermore, step S4 includes the following steps:

[0046] Step S41: Based on the distribution of the percutaneous needle insertion depth in the target area, the distribution difference between the needle insertion depth and the target area is quantified to obtain the difference in the distribution distance between the percutaneous needle insertion depth and the target area reached by the needle.

[0047] Step S42: Based on the difference in the distribution distance between the percutaneous puncture needle depth and the target area reached by the puncture, perform needle insertion navigation control on the needle insertion path of the percutaneous puncture surgical robot during the corresponding puncture process to generate a percutaneous puncture surgical needle insertion navigation path.

[0048] Step S43: Generate corresponding percutaneous puncture surgery navigation control commands based on the percutaneous puncture needle insertion navigation path response, and apply them to the percutaneous puncture surgery robot to perform the corresponding percutaneous puncture surgery robot puncture navigation adjustment work.

[0049] Furthermore, the present invention also provides a percutaneous puncture surgical robot system based on quantum multidimensional sensors, for executing the control method of the percutaneous puncture surgical robot system based on quantum multidimensional sensors as described above. The percutaneous puncture surgical robot system based on quantum multidimensional sensors includes:

[0050] The percutaneous puncture needle position determination module is used to detect changes in the puncture magnetic field during the puncture process of the percutaneous puncture surgical robot by using a magnetic field sensor based on a superconducting quantum interference device placed near the patient's body surface, so as to obtain the distribution field of the percutaneous puncture surgical magnetic field change; based on the distribution field of the percutaneous puncture surgical magnetic field change, the puncture needle position is determined during the puncture process of the percutaneous puncture surgical robot, thereby obtaining the percutaneous puncture needle position distribution;

[0051] The percutaneous puncture needle depth correction module is used to monitor the changes in the patient's respiratory movements and body displacement during the puncture process corresponding to the percutaneous puncture surgical robot in real time, and to perform puncture needle depth correction analysis on the percutaneous puncture needle position distribution based on the changes in the patient's respiratory movements and body displacement, thereby obtaining the percutaneous puncture needle depth distribution.

[0052] The target area location determination module is used to detect tumor displacement distribution during the percutaneous puncture procedure using a nitrogen-vacancy-centered magnetic resonance imaging sensor placed near the puncture needle, thereby obtaining the tumor displacement distribution of the percutaneous puncture patient; and to determine the corresponding percutaneous puncture needle location distribution in the target area based on the tumor displacement distribution of the percutaneous puncture patient.

[0053] The percutaneous needle insertion navigation control module is used to control the needle insertion depth distribution of percutaneous puncture surgery based on the distribution of the percutaneous puncture needle's position in the target area, generate the percutaneous puncture needle insertion navigation path, and perform corresponding percutaneous puncture robot puncture navigation adjustment work.

[0054] The beneficial effects of this invention are:

[0055] 1. The control method of the percutaneous puncture surgical robot system based on quantum multidimensional sensors proposed in this invention has the following advantages compared with the prior art: By utilizing a magnetic field sensor based on a superconducting quantum interference device placed near the patient's body surface to detect changes in the puncture magnetic field, this high-precision magnetic field sensor can sensitively capture extremely subtle magnetic field fluctuations. Its detection accuracy can reach the picotesla level, far exceeding traditional magnetic field detection methods. When the puncture needle is advanced in the body, due to the magnetic properties of the puncture needle material and the weak influence of the surrounding tissue environment on the magnetic field, a unique magnetic field change pattern will be generated. By monitoring these changes in real time, the distribution field of the percutaneous puncture surgical magnetic field change is constructed as if drawing a detailed "magnetic field map" for the surgical area, accurately presenting the strength of each magnetic field. The technology leverages the penetrability and stability of the magnetic field to determine the location of the puncture needle. Previous methods were limited by tissue obstruction and human movement, leading to some inaccuracies. This new technique overcomes these limitations. The puncture needle acts as a traceable "magnetic marker" within the magnetic field; regardless of its movement or direction, the magnetic field sensor can quickly calculate its three-dimensional coordinates based on the changing magnetic field, resulting in an accurate distribution of the percutaneous puncture needle location. This significantly improves the first-time success rate of punctures, reduces unnecessary trauma to patients from repeated punctures, shortens the overall surgical time, lowers surgical risks, and lays a solid foundation for subsequent puncture positioning, thus solving the problem of difficult positioning during percutaneous puncture surgery. Secondly, real-time monitoring of the patient's respiratory movements and body displacement during the puncture process is crucial for ensuring the accuracy of needle insertion. In a natural state, respiratory movements cause minute rises and falls and displacements in the chest cavity, abdominal cavity, and even the entire body. In percutaneous puncture surgery, even millimeter-level changes can cause the needle to deviate from its intended path. By employing advanced monitoring technologies, such as high-precision optical tracking and inertial measurement units, comprehensive monitoring of respiratory movements can be achieved. This allows for precise recording of dynamic parameters such as respiratory rate, depth, and duration of inhalation and exhalation, as well as the real-time displacement vectors of various body parts in three-dimensional space. Based on these changes, the puncture procedure can be precisely adjusted. When performing puncture depth correction analysis based on needle position distribution, it's like equipping the surgical procedure with an intelligent "navigator." It fully considers the dynamic changes in the human body and uses complex mathematical models and algorithms to convert respiratory movements and human displacement data into adjustment instructions for the puncture needle depth. For example, when the patient inhales, the chest cavity expands, causing organs such as the liver to move upwards. At this time, the puncture depth of the lesion near the liver needs to be adjusted accordingly to avoid punctures that are too deep or too shallow. This process effectively compensates for puncture errors caused by the dynamic changes in the patient's body, ensuring that the puncture needle always accurately reaches the target along the ideal trajectory, thereby making percutaneous puncture surgery standardized, homogenized, and regulated.Then, by using a nitrogen-vacancy center-based magnetic resonance imaging (MRI) sensor placed near the puncture needle to detect tumor displacement distribution, nitrogen-vacancy center MRI technology has ultra-high spatial resolution, which can clearly distinguish the boundary, morphology, and internal structural changes of tumor tissue and surrounding normal tissue at the microscopic scale. During the puncture, the position of the tumor is not fixed due to its own physiological characteristics, changes in the force on the surrounding tissue, and the slight movement of the patient's body. The real-time acquisition of the tumor displacement distribution of the percutaneous puncture patient by this sensor is like giving the surgeon a pair of "X-ray glasses" to accurately observe the tumor's every move. This real-time dynamic positioning method greatly improves the targeting of the puncture. It allows the puncture needle to respond instantly when the tumor shifts, adjust its path, and accurately hit the core area of ​​the tumor or specific treatment targets, thereby improving the anti-interference ability of the percutaneous puncture surgical robot during the puncture process. Finally, by using the distribution of the percutaneous needle's position relative to the target area to perform percutaneous puncture depth distribution for navigation control, once the current position of the needle relative to the target area is determined, it is combined with the pre-planned needle depth distribution. Utilizing advanced navigation algorithms and intelligent control systems, the generated percutaneous puncture navigation path is like a "highway" tailor-made for the needle. This navigation path fully considers various variables during the puncture process, such as tissue elastic deformation, respiratory movements monitored in previous steps, human body displacement, and tumor displacement, optimizing the needle direction and depth in real time. When performing corresponding percutaneous puncture robot puncture navigation adjustments, the robot can quickly and accurately move the needle according to the navigation path instructions, ensuring that each puncture operation is accurate. This not only improves the precision and efficiency of the surgery but also reduces errors caused by factors such as hand tremors and fatigue from human operation, thereby improving the puncture precision of the percutaneous puncture robot.

[0056] 2. The percutaneous puncture surgical robot system based on quantum multidimensional sensors proposed in this invention operates with the help of quantum multidimensional sensors. These sensors can acquire multidimensional data of the target tissue under the guidance of imaging equipment such as CT, MRI, and ultrasound, specifically covering key information such as the tissue's three-dimensional spatial location, elastic properties, and density distribution. Subsequently, the data is processed using a high-precision quantum algorithm to generate an accurate tissue model, which is also updated synchronously in real time. The system consists of a percutaneous needle position determination module, a percutaneous needle insertion depth correction module, a target area location determination module, and a percutaneous needle insertion navigation control module. This system enables the control method of any percutaneous puncture surgical robot system based on quantum multidimensional sensors as described in this invention. It is used to coordinate the operations between computer programs running on various modules to achieve the control method of any percutaneous puncture surgical robot system based on quantum multidimensional sensors. The internal structure of the system cooperates with each other, which can greatly reduce repetitive work and manpower input, and can quickly and effectively provide a more accurate and efficient control process for the percutaneous puncture surgical robot system based on quantum multidimensional sensors, thereby simplifying the operation process of the percutaneous puncture surgical robot system based on quantum multidimensional sensors. Attached Figure Description

[0057] Other features, objects, and advantages of the invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0058] Figure 1 This is a flowchart illustrating the steps of the control method for the percutaneous puncture surgical robot system based on quantum multidimensional sensors according to the present invention.

[0059] Figure 2 for Figure 1 A detailed flowchart of step S1;

[0060] Figure 3 for Figure 2 A detailed flowchart of step S15. Detailed Implementation

[0061] The technical method of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0062] To achieve the above objectives, please refer to Figures 1 to 3 This invention provides a control method for a percutaneous puncture surgical robot system based on quantum multidimensional sensors, the method comprising the following steps:

[0063] Step S1: Detect the change in the puncture magnetic field during the percutaneous puncture procedure using a magnetic field sensor based on a superconducting quantum interference device placed near the patient's body surface, so as to obtain the distribution field of the percutaneous puncture magnetic field change; determine the position of the puncture needle during the percutaneous puncture procedure based on the distribution field of the percutaneous puncture magnetic field change, so as to obtain the distribution of the position of the percutaneous puncture needle.

[0064] Step S2: By real-time monitoring of the patient's respiratory movement changes and human body displacement changes during the percutaneous puncture surgery robot, and based on the changes in the patient's respiratory movement changes and human body displacement changes, the percutaneous puncture needle position distribution is analyzed to correct the puncture depth, and the percutaneous puncture needle depth distribution is obtained.

[0065] Step S3: Using a magnetic resonance imaging sensor based on nitrogen vacancy centers placed near the puncture needle, the tumor displacement distribution during the percutaneous puncture surgical robot is detected to obtain the tumor displacement distribution of the percutaneous puncture patient; the location distribution of the percutaneous puncture needle reaching the target area is determined based on the tumor displacement distribution of the percutaneous puncture patient.

[0066] Step S4: Based on the distribution of the percutaneous needle position in the target area, perform needle insertion depth distribution control for percutaneous puncture surgery to generate percutaneous puncture surgery needle insertion navigation path, so as to perform corresponding percutaneous puncture surgery robot puncture navigation adjustment work.

[0067] In the embodiments of this invention, please refer to Figure 1 The diagram shown is a flowchart illustrating the steps of the control method for the percutaneous puncture surgical robot system based on quantum multidimensional sensors according to the present invention. In this example, the control method for the percutaneous puncture surgical robot system based on quantum multidimensional sensors includes the following steps:

[0068] Step S1: Detect the change in the puncture magnetic field during the percutaneous puncture procedure using a magnetic field sensor based on a superconducting quantum interference device placed near the patient's body surface, so as to obtain the distribution field of the percutaneous puncture magnetic field change; determine the position of the puncture needle during the percutaneous puncture procedure based on the distribution field of the percutaneous puncture magnetic field change, so as to obtain the distribution of the position of the percutaneous puncture needle.

[0069] In this embodiment of the invention, a magnetic field sensor based on a superconducting quantum interference device (SQUID) is placed at a specific location on the patient's body surface to monitor weak magnetic field fluctuations during the puncture process. These sensors can accurately sense magnetic field fluctuations caused by the interaction between the puncture needle and the surrounding tissues. To ensure that the sensor can accurately capture the required data, the sensor should be located at a certain distance from the puncture point. The sensitivity of the sensor is set to be able to detect weak magnetic field changes between the skin surface and deep tissues. Typically, the resolution of the sensor is in the nanoterrestrial (nT) to petater (pT) range, allowing the detection of weak magnetic field distribution fluctuations at each moment during the percutaneous puncture process. By performing spatial gradient analysis on the previously acquired magnetic field distribution fluctuations (magnetic field gradient refers to the rate of change of magnetic field strength in space, reflecting the spatial distribution of magnetic field changes), and analyzing the spatial distribution during the puncture process, the needle position and its trajectory are first obtained based on the real-time control information of the surgical robot. Simultaneously, combined with the previously obtained magnetic field spatial gradient data, the relative positional relationship between the puncture needle and the patient's tissue is determined. A precise kinematic model is used to analyze the spatial positional distribution of the puncture needle along the entire puncture path. Furthermore, based on the previously analyzed magnetic field spatial gradient information, the spatial positional distribution of the puncture needle along the entire puncture path is coupled. First, a mathematical model is established between the magnetic field changes during puncture and the contact relationship between the puncture needle and surrounding tissue. By simulating the magnetic field changes generated when the puncture needle contacts the tissue, and combining actual magnetic field gradient data, the influence of magnetic field changes on the contact between the needle and tissue is calculated. Finite element analysis (FEA) or computational fluid dynamics (CFD) methods can be used to simulate the magnetic field changes during puncture, and model inversion is used to accurately estimate the spatial distribution relationship between the needle and surrounding tissue, thus obtaining the magnetic field distribution field of percutaneous puncture surgery. Then, the position of the puncture needle is accurately determined based on the previously obtained magnetic field change distribution field. First, based on the previously analyzed puncture spatial distribution data and the magnetic field change distribution field, a reverse calculation algorithm or optimization algorithm is used to determine the position of the puncture needle at each moment during the puncture process. Specifically, based on the spatial distribution characteristics of the magnetic field change distribution field, a global optimization model is constructed. This model optimizes the spatial positioning of the puncture needle by minimizing the magnetic field error during the puncture process. At this time, the position of the needle can be continuously adjusted by combining the current motion state of the puncture robot and the target trajectory through the position feedback control algorithm to ensure that the needle accurately enters the target tissue without deviating from the trajectory and is displayed on the surgical interface in real time, thus obtaining the puncture needle position distribution for percutaneous puncture surgery.

[0070] Step S2: By real-time monitoring of the patient's respiratory movement changes and human body displacement changes during the percutaneous puncture surgery robot, and based on the changes in the patient's respiratory movement changes and human body displacement changes, the percutaneous puncture needle position distribution is analyzed to correct the puncture depth, and the percutaneous puncture needle depth distribution is obtained.

[0071] In this embodiment of the invention, an array of 16 high-precision piezoresistive pressure sensors is used. These sensors are closely fitted to the patient's body surface according to the anatomical distribution of key respiratory motion sensing areas in the chest and abdomen, ensuring seamless contact between the sensors and the skin. When the patient breathes, the rise and fall of the chest and abdomen causes changes in air pressure. The piezoresistive sensitive element of the sensor deforms under pressure, and the piezoresistive effect converts the change in body surface pressure into an electrical signal. After preprocessing by amplification and filtering circuits, the electrical signal is transmitted to a hardware module with a built-in dedicated statistical analysis algorithm. This module uses a sampling frequency of 100Hz. Electrical signals are collected, and peak detection and cycle recognition algorithms are used to accurately calculate the patient's respiratory cycle with an accuracy of 0.1 seconds. Tidal volume is calculated using an integral algorithm, with an error controlled within 5%. Respiratory rate is derived from the reciprocal of the cycle, and respiratory phase change parameters are extracted using a phase comparison algorithm, thus obtaining changes in respiratory motion and body displacement. Before surgery, when the patient is in a static, lying position, a scanning device based on structured light 3D scanning technology is activated. This device evenly distributes four high-precision projectors and eight high-resolution cameras around the operating table, constructing a coordinate system with the operating table as the origin. A three-dimensional measurement coordinate system is used. A projector projects a specifically coded structured light stripe pattern onto the patient's body surface. A camera simultaneously captures stripe deformation images from different angles. Feature extraction, matching, and triangulation calculations are performed on the acquired multi-view images to construct a human body displacement reference map with an accuracy of 1 millimeter. This map fully presents the patient's body contour and spatial position information in a preoperative static state. Simultaneously, three LiDAR scanning devices, installed at 120-degree angles to each other and fixed to an adjustable bracket above the operating table, are activated to ensure that the scanning field of view covers the entire patient. The LiDAR pulses at a frequency of 1000 times per second. The system emits a laser beam, which is reflected off the human body surface. The reflected light is received, converted into photoelectric signals, and processed to generate real-time three-dimensional point cloud data of the human body during the percutaneous puncture process. Simultaneously, a pre-constructed human body displacement reference map is input. The chip uses an algorithm to accurately match and compare the coordinates of three-dimensional feature points of the human body in the two sets of data, such as key joints like the shoulder, elbow, and hip. It calculates the relative displacement of each feature point in three-dimensional space and calculates the puncture path deviation for the percutaneous puncture surgical robot, accurately obtaining the puncture path deviation vector between the puncture needle tip and the ideal target point at each moment.Then, by utilizing a needle insertion depth correction model based on finite element analysis, the model is constructed based on a large amount of clinical puncture case data and a human tissue biomechanical property database. The puncture path deviation vector between the puncture needle tip and the ideal target point at each time point, which was previously quantitatively calculated, is input into the model. Based on the principle of tissue biomechanical transmission, the model simulates the force situation of the puncture needle when encountering tissue resistance and elastic deformation, and considers the influence of the direction and magnitude of the deviation vector on the needle insertion depth. For example, when the deviation vector points to a harder tissue area, the model will appropriately reduce the needle insertion depth to avoid puncture difficulties; conversely, if it points to loose tissue, the needle insertion depth will be reasonably increased. The puncture needle insertion depth correction analysis is performed on the distribution of puncture needle positions in percutaneous puncture surgery with a correction accuracy of 0.05 mm, and finally the needle insertion depth distribution of percutaneous puncture surgery is obtained.

[0072] Step S3: Using a magnetic resonance imaging sensor based on nitrogen vacancy centers placed near the puncture needle, the tumor displacement distribution during the percutaneous puncture surgical robot is detected to obtain the tumor displacement distribution of the percutaneous puncture patient; the location distribution of the percutaneous puncture needle reaching the target area is determined based on the tumor displacement distribution of the percutaneous puncture patient.

[0073] In this embodiment of the invention, a magnetic resonance imaging (MRI) sensor based on nitrogen-vacancy centers (NV centers) installed near the puncture needle monitors the movement of the puncture needle in real time during percutaneous puncture. The NV centers have high magnetic sensitivity and can respond to minute changes in the external magnetic field. The sensor detects minute changes in the magnetic field around the puncture needle to obtain the NV center MRI signal, generating an MRI signal related to the positional change of the puncture needle. Based on the previously acquired NV center MRI signal changes, the sensor performs real-time tracking and analysis of the minute displacement of the puncture needle. Specifically, this is achieved by performing time-domain and frequency-domain analysis on the MRI signal to identify the positional change of the puncture needle during puncture. This analysis process uses high-precision signal processing algorithms, including Fast Fourier Transform (FFT) and Kalman filtering, to process and denoise the sensor signal. By comparing MRI signal data acquired at different time points, the displacement trajectory of the puncture needle is tracked, obtaining the dynamic displacement information of the puncture needle during puncture. Simultaneously, the NV center-based MRI sensor acquires the positional change of the puncture needle during puncture. The process involves obtaining magnetic resonance imaging (MRI) images of the corresponding tumor tissue. Specifically, the sensor not only monitors the movement of the puncture needle but also generates high-resolution MRI images of the puncture needle and its surrounding area through its highly sensitive MRI capabilities. This results in clear spatial distribution information of the tumor tissue, the relative positional relationship between the tumor tissue and the puncture needle, and the path of the puncture needle within the tumor tissue. Furthermore, by combining the minute dynamic displacement trajectory of the puncture needle with dynamic simulation and physical modeling, tumor displacement is detected. Specifically, firstly, based on the previously obtained dynamic displacement trajectory data of the puncture needle and the physical effects of the puncture needle on the tissue during the puncture process, tumor displacement is simulated. Numerical simulation methods such as finite element analysis (FEA) and computational fluid dynamics (CFD) are used to physically model the angle, velocity, and puncture depth of the puncture needle, simulating the mechanical effects of the puncture needle's movement on the surrounding tumor tissue. This simulation takes into account the local tissue deformation caused by the puncture needle during the puncture process to analyze the possible displacement range of the tumor tissue under different puncture angles and velocities, thereby obtaining the tumor displacement distribution of percutaneous puncture patients. Then, based on the previously obtained tumor displacement distribution, the positional distribution of the puncture needle reaching the target area is further analyzed. Specifically, firstly, based on the tumor displacement distribution map, the changing trend of tumor tissue during the puncture process is analyzed. Combining the current position and puncture direction of the puncture needle, multiple target positions that the puncture needle may reach during the puncture process are determined. Through optimization algorithms, such as particle swarm optimization (PSO) or genetic algorithm (GA), the optimal path and final target position of the puncture needle are determined based on the positional relationship between the puncture needle and the tumor. During this process, the puncture angle and puncture speed also need to be adjusted in real time to ensure that the puncture needle can accurately reach the target area, and finally the positional distribution of the percutaneous puncture needle reaching the target area is obtained.

[0074] Step S4: Based on the distribution of the percutaneous needle position in the target area, perform needle insertion depth distribution control for percutaneous puncture surgery to generate percutaneous puncture surgery needle insertion navigation path, so as to perform corresponding percutaneous puncture surgery robot puncture navigation adjustment work.

[0075] In this embodiment of the invention, a percutaneous puncture needle is precisely positioned to reach a predetermined target area. A quantum sensor is used to monitor the state of the puncture needle at different depths in real time. By comparing the spatial distribution of the current puncture needle depth with that of the target area, the spatial difference between the puncture depth and the target area is calculated. The multidimensional measurement capability of the quantum multidimensional sensor allows the acquisition of data including, but not limited to, needle insertion depth, lateral displacement, longitudinal displacement, and angular changes, forming a high-dimensional target area position distribution. Based on this data, a specific algorithm (e.g., least squares method or Bayesian inference method) is used to quantify the distance difference between the current position of the puncture needle and the target area. The difference is then calculated based on the previously obtained puncture depth and target area... The next step after quantifying the differences in the distribution of the regions is to perform precise navigation control of the needle insertion path during percutaneous puncture. Specifically, the system uses the data on the differences in the distribution of the target region, combined with robot control algorithms (such as path planning methods based on genetic algorithms, artificial neural networks, or PID control), to generate the optimal puncture path. This path not only takes into account the spatial distribution of the target region, but also the operational stability, flexibility, and accuracy of the puncture needle. Quantum sensors provide real-time feedback on minute displacements between the puncture needle and the target region, generating real-time adjustment commands for the puncture needle insertion path to ensure precise control of the needle depth, angle, and direction during the puncture process, thereby generating a percutaneous puncture needle insertion navigation path. Based on the previously generated percutaneous puncture surgical navigation path, the system accurately calculates the control commands for each step of the operation, generates specific navigation control commands, and applies them to the percutaneous puncture surgical robot. In the specific implementation process, after receiving the navigation path, the robot control system generates specific motion commands through the built-in kinematic and dynamic models. These control commands include, but are not limited to, the needle insertion rate, needle insertion angle, needle insertion depth, and needle rotation angle, and are accurately executed by the robot drive system. Real-time data feedback provided by quantum multidimensional sensors (such as the real-time position of the puncture needle, the reflection signal of the target area, etc.) continuously corrects the navigation path in real time and adjusts the control commands to ensure that the puncture needle can accurately reach the target area and correct path deviations in real time. When the deviation of the puncture needle exceeds the predetermined tolerance range, the robot control system automatically adjusts the needle insertion path, recalculates the motion commands, and further corrects the error. The surgical robot completes the precise puncture of the target area by continuously adjusting the direction and depth of needle insertion, and finally performs the corresponding percutaneous puncture surgical robot puncture navigation adjustment work.

[0076] Furthermore, as an embodiment of the present invention, reference is made to... Figure 2 As shown, Figure 1 A detailed flowchart of step S1 is shown below. In this embodiment, step S1 includes the following steps:

[0077] Step S11: Using a magnetic field sensor based on a superconducting quantum interference device placed near the patient's body surface, the magnetic field fluctuations of the percutaneous puncture surgical robot are collected during the puncture process, and the weak magnetic field distribution fluctuations at each moment during the percutaneous puncture are obtained.

[0078] In this embodiment of the invention, a magnetic field sensor based on a superconducting quantum interference device (SQUID) is placed at a specific location on the patient's body surface to monitor weak magnetic field fluctuations during the puncture process. These sensors can accurately sense magnetic field fluctuations caused by the interaction between the puncture needle and the surrounding tissues. To ensure that the sensor can accurately capture the required data, the sensor should be located at a certain distance from the puncture point. The specific distance can be determined according to factors such as the surgical site and puncture depth. The sensitivity of the sensor is set to detect weak magnetic field changes between the skin surface and deep tissues. Typically, the resolution of the sensor is in the nanoterrestrial (nT) to petater (pT) range. At every moment during the entire puncture process, the magnetic field sensor continuously records the changes in the magnetic field, obtaining time-stamped magnetic field fluctuation data, forming a sequence of magnetic field strength changes over time during the puncture process, and finally obtaining the weak magnetic field distribution fluctuations corresponding to each moment during the percutaneous puncture process.

[0079] Step S12: Perform magnetic field spatial gradient analysis on the weak magnetic field distribution fluctuations at each moment during the percutaneous puncture process to obtain the magnetic field spatial distribution gradient corresponding to each spatial distribution position during the percutaneous puncture process.

[0080] In this embodiment of the invention, spatial gradient analysis is performed on the previously acquired magnetic field fluctuation data. The magnetic field gradient refers to the rate of change of magnetic field strength in space, reflecting the spatial distribution of magnetic field changes. First, the magnetic field distribution data at each moment is spatially sampled, and the gradient of the magnetic field at different locations is calculated using numerical calculation methods (such as the finite difference method or gradient calculation method). Specifically, the rate of change of magnetic field strength along different directions is calculated using the measurement data of the magnetic field sensor at different locations in space. For this purpose, the sensor position needs to be accurately calibrated, and the magnetic field gradient distribution at each location is inferred based on the characteristics of magnetic field changes during the puncture process and the geometric structure of human tissue. A set of spatiotemporal distribution data of magnetic field gradient at each spatial location during the puncture process is obtained, reflecting the magnetic field changes generated when the puncture needle interacts with the surrounding tissue. Finally, the spatial distribution gradient of the magnetic field at each spatial location during the percutaneous puncture process is obtained.

[0081] Step S13: Perform puncture space distribution analysis on the puncture process corresponding to the percutaneous puncture surgical robot to obtain the puncture space distribution between the puncture needle and the surrounding tissues during the percutaneous puncture process;

[0082] In this embodiment of the invention, by analyzing the spatial distribution during the puncture process, the position and trajectory of the needle during the puncture process are first obtained based on the real-time control information of the surgical robot. At the same time, combined with the previously obtained magnetic field spatial gradient data, the relative positional relationship between the puncture needle and the patient's tissue is determined. Through a precise kinematic model, the spatial positional distribution of the puncture needle along the entire puncture path is analyzed. At this time, not only the change of the puncture needle in the depth direction (such as the X-axis direction) is considered, but also the distance and relative position between the puncture needle and surrounding tissues (such as muscles, fat, blood vessels, etc.) need to be considered. In addition, the contact relationship between the puncture needle and different tissue interfaces is modeled to accurately predict the spatial distribution of the contact between the needle and surrounding tissues during the puncture process. Finally, the puncture spatial distribution between the puncture needle and the surrounding tissues of the human body during percutaneous puncture is obtained.

[0083] Step S14: Based on the magnetic field spatial distribution gradient corresponding to each spatial distribution position during the percutaneous puncture process, the magnetic field change distribution coupling processing is performed on the puncture spatial distribution between the puncture needle and the surrounding tissues during the percutaneous puncture process to obtain the magnetic field change distribution field of the percutaneous puncture surgery.

[0084] In this embodiment of the invention, based on the previously obtained magnetic field spatial gradient information, the relationship between magnetic field changes during puncture and the interaction between the puncture needle and human tissue is coupled. First, a mathematical model is established between the magnetic field changes during puncture and the contact relationship between the puncture needle and surrounding tissue. By simulating the magnetic field changes generated when the puncture needle contacts the tissue, and combining actual magnetic field gradient data, the influence of magnetic field changes on the contact between the needle and tissue is calculated. To complete the coupling process, the magnetic field change field needs to be weighted and averaged to ensure that the response characteristics of different tissues to magnetic field changes (such as differences in tissue conductivity, magnetism, etc.) are taken into account. In this process, finite element analysis (FEA) or computational fluid dynamics (CFD) methods can be used to simulate the magnetic field changes during puncture, and the spatial distribution relationship between the needle and surrounding tissue is accurately estimated through model inversion. Through this coupling process, a complete magnetic field change distribution field during puncture is obtained, and finally, the magnetic field change distribution field of percutaneous puncture surgery is obtained.

[0085] Step S15: Determine the position of the puncture needle in the percutaneous puncture surgery robot based on the distribution of the magnetic field change in the percutaneous puncture surgery, and obtain the distribution of the position of the percutaneous puncture needle.

[0086] In this embodiment of the invention, the position of the puncture needle is accurately determined based on the previously obtained magnetic field variation distribution field. First, based on the previously analyzed puncture spatial distribution data and the magnetic field variation distribution field, a reverse calculation algorithm or optimization algorithm is used to determine the position of the puncture needle at each moment during the puncture process. Specifically, based on the spatial distribution characteristics of the magnetic field variation distribution field, a global optimization model is constructed. This model optimizes the spatial positioning of the puncture needle by minimizing the magnetic field error during the puncture process. At this time, the position of the needle can be continuously adjusted by combining the current motion state of the puncture robot and the target trajectory through a position feedback control algorithm to ensure that the needle accurately enters the target tissue without deviating from the trajectory. In order to ensure position accuracy, during the algorithm implementation process, real-time data from sensors is also used to dynamically correct the position of the needle to compensate for possible errors. The position distribution of the puncture needle can be accurately determined and displayed on the surgical interface in real time, thus obtaining the position distribution of the percutaneous puncture needle.

[0087] Furthermore, as an embodiment of the present invention, reference is made to... Figure 3 As shown, Figure 2 A detailed flowchart of step S15 is shown below. In this embodiment, step S15 includes the following steps:

[0088] Step S151: Perform electromagnetic property analysis on the tissue surrounding the surgical area during the percutaneous puncture procedure of the percutaneous puncture surgical robot to obtain the electromagnetic properties of the tissue surrounding the percutaneous puncture surgical area, including the conductivity and dielectric constant of the surrounding tissue.

[0089] In this embodiment of the invention, electromagnetic properties of tissues surrounding the surgical area are analyzed using high-frequency electromagnetic field detection technology. Specifically, a multi-band electromagnetic sensor is used to perform a non-invasive scan of the surgical area, measuring the conductivity and dielectric constant at different locations within the area. The electromagnetic sensor interacts with the surrounding tissue through high-frequency electromagnetic waves, detecting the characteristics of electromagnetic wave reflection or transmission. This information reflects the conductivity and dielectric constant of the tissue. By modeling the electromagnetic responses of different tissue types (such as skin, fat, muscle, and blood vessels), the electromagnetic properties of each tissue can be accurately obtained. These data are then processed and inverted. The algorithm obtains the specific conductivity and dielectric constant of each tissue. Taking liver tissue as an example, in the frequency range of 100kHz-10MHz, the dielectric constant is approximately between 40 and 60, which means that liver tissue can store relatively more electrical energy under electromagnetic fields at this frequency. This is related to its complex cell structure, intracellular components, and the electrical properties of intercellular fluid. The dielectric constant of skin tissue varies depending on the different layers of the epidermis and dermis. The dielectric constant of the epidermis is generally between 20 and 30, while the dielectric constant of the dermis is approximately 30 to 40 due to the influence of water content, collagen, and other components. Finally, the electromagnetic properties of the tissue surrounding the percutaneous puncture surgical area are obtained.

[0090] Step S152: Perform temporal decomposition of magnetic field perturbation on the distribution field of magnetic field changes during percutaneous puncture surgery to obtain the distribution of magnetic field perturbation at each time point during percutaneous puncture.

[0091] In this embodiment of the invention, a quantum multidimensional sensor or a high-precision magnetic field sensor is used to monitor the changes in the magnetic field of the surgical area during the puncture process in real time. The sensor records the changes in the magnetic field strength and direction of the puncture area at different time points. After digital processing, these changes are extracted by a time-series decomposition algorithm to extract magnetic field disturbances at different frequencies and time scales. For example, a fast Fourier transform (FFT) is used to perform frequency domain analysis on the time domain signal to obtain the magnetic field change characteristics at each moment. Through this decomposition process, a dynamic magnetic field change distribution map is obtained, which can show in detail the magnetic field disturbances generated at different time points during the puncture process. Finally, the distribution of magnetic field change disturbances generated at each time point during the percutaneous puncture process is obtained.

[0092] Step S153: Based on the electromagnetic properties of the tissue surrounding the percutaneous puncture surgical area, the relative position of the puncture is calculated by analyzing the distribution of magnetic field changes and disturbances generated at each time point during the percutaneous puncture, thus obtaining the relative position distribution of the puncture needle tip in the percutaneous puncture surgery.

[0093] In this embodiment of the invention, the precise position of the puncture needle tip during the operation is calculated by combining electromagnetic properties and magnetic field disturbance data. First, based on the previously obtained tissue electromagnetic properties and combined with the obtained magnetic field disturbance data, the relative position of the puncture needle tip is calculated using an inversion algorithm or mathematical model (such as finite element analysis or orthogonal analysis). By modeling the correspondence between electromagnetic response and magnetic field change, the position change of the puncture needle tip during the operation can be calculated. At this time, through multiple calculations and iterative optimization, the position of the puncture needle is gradually corrected to ensure that it can be accurately guided to the target area during the operation, reducing the influence of errors and deviations. The result is the distribution of the relative position of the puncture needle tip at each time point, and finally the distribution of the relative position of the puncture needle tip in percutaneous puncture surgery.

[0094] Step S154: Obtain the stress response between the puncture needle tip and the surrounding tissue and the puncture force through the puncture process corresponding to the percutaneous puncture surgical robot;

[0095] In this embodiment of the invention, sensors are used to monitor the interaction force between the puncture needle tip and the surrounding tissue in real time. Specifically, force sensors and strain sensors are installed near the puncture needle tip. These sensors can measure the stress and puncture force generated when the needle tip contacts the tissue during the puncture process. The stress sensor detects the deformation and stress on the tissue surface during the puncture process, while the puncture force sensor can sense the resistance when the puncture needle enters the tissue. This real-time data is collected and processed by the robot control system to generate dynamic stress response curves and puncture force time series diagrams. During the puncture process, the changing trends of these data can reflect the contact between the puncture needle and the surrounding tissue, whether the puncture force is within a reasonable range, and whether the puncture is performed smoothly. Finally, the stress response and puncture force between the puncture needle tip and the surrounding tissue are obtained.

[0096] Step S155: Based on the stress response between the puncture needle tip and the surrounding tissue and the puncture force, the relative position distribution of the percutaneous puncture needle tip is corrected for puncture position deviation, and the position distribution of the percutaneous puncture needle is obtained.

[0097] In this embodiment of the invention, by integrating previously acquired stress response and puncture force data and combining them with the obtained relative position distribution of the puncture needle tip, the robot system first analyzes whether there is a positional deviation of the puncture needle based on the puncture force and stress response data. If the sensor detects that the puncture force is too large or too small, or that the stress distribution differs from the expectation, it indicates that the puncture needle has shifted position. By comparing the error between the current puncture needle tip position and the target position, the system uses an error correction algorithm (such as a PID control algorithm or a Kalman filter algorithm) to dynamically adjust the relative position of the puncture needle. This correction process takes into account different time points during the puncture process, the electromagnetic characteristics of different tissues, and the corresponding mechanical feedback. It can adjust the position of the puncture needle in real time during the puncture process to ensure that the puncture needle can accurately reach the target area and effectively puncture the target tissue during the operation, thereby improving the success rate and accuracy of the puncture surgery. The corrected puncture needle position distribution map is then presented, and the final percutaneous puncture needle position distribution is obtained.

[0098] Furthermore, step S153 includes the following steps:

[0099] Electromagnetic flow and dielectric effect of the puncture needle were analyzed to obtain the electromagnetic flow and dielectric effect between the percutaneous puncture needle and the tissue surrounding the surgical area, based on the electrical conductivity and dielectric coefficient of the tissues surrounding the percutaneous puncture area.

[0100] In this embodiment of the invention, the conductivity and dielectric constant of the percutaneous puncture surgical area and its surrounding tissues are measured using quantum multidimensional sensors. These sensors employ advanced quantum sensing technology, enabling them to capture the electrical properties of the tissues with high precision. Specifically, the sensors transmit electromagnetic wave signals within the puncture needle area to the sensors for real-time analysis, thereby obtaining conductivity and dielectric constant data for that area. This data is not only used to assess the differences in electromagnetic properties between the puncture needle and the surrounding tissues but also reflects the physical properties of different tissues, such as the conductivity differences between soft tissues like muscle, fat, or blood vessels. Based on these parameters, numerical simulation methods are used to model the electromagnetic flow and dielectric effect between the puncture needle and the surgical area. Specifically, electromagnetic field simulation tools (such as COMSOL Multiphysics) are used to solve for the electromagnetic interaction between the puncture needle and the target tissue, obtaining a complete distribution map of electromagnetic flow and dielectric effect. This map shows how electromagnetic flow propagates within the tissue during puncture needle insertion and how different tissues affect the electric and magnetic field distributions around the puncture needle, ultimately yielding the electromagnetic flow and dielectric effect between the percutaneous puncture needle and the tissues surrounding the surgical area.

[0101] Preferably, time-domain and frequency-domain analysis is performed on the distribution of magnetic field changes and disturbances generated at each time point during percutaneous puncture to extract the relative position feature points of the percutaneous puncture needle tip at each time point, thereby obtaining the set of relative position feature points of the magnetic field caused by the movement of the percutaneous puncture needle tip.

[0102] In this embodiment of the invention, the magnetic field changes of the puncture needle tip are recorded at each time point. For this purpose, a quantum multidimensional sensor can measure the local magnetic field disturbance during the movement of the puncture needle tip in real time and collect magnetic field data at each time point. These data include the time-domain fluctuations of the magnetic field strength. After time-domain analysis, the time-varying characteristics of the magnetic field disturbance caused by the change in the position of the puncture needle tip can be obtained. Using frequency domain analysis methods such as Fourier transform, frequency spectrum analysis of the magnetic field disturbance is performed to extract frequency feature points related to the relative position change of the puncture needle tip. These feature points represent the relative position of the puncture needle at different time points, especially the region where the magnetic field change is most significant when the puncture needle interacts with the surrounding tissue. By analyzing the magnetic field disturbance pattern at each moment, the spatial position experienced by the puncture needle tip during the movement and its corresponding electromagnetic effect can be effectively extracted. Furthermore, by using data fitting methods, combined with known electromagnetic field models and tissue dielectric properties, the magnetic field disturbance at each moment is matched with the precise relative position of the puncture needle, and finally, the set of magnetic field relative position feature points caused by the movement of the percutaneous puncture needle tip is obtained.

[0103] Preferably, the relative position of the percutaneous puncture needle tip is calculated by estimating the relative position of each relative position feature point in the set of magnetic field relative position feature points caused by the movement of the percutaneous puncture needle tip based on the electromagnetic flow and dielectric effect between the percutaneous puncture needle and the surrounding tissue of the surgical area, thus obtaining the distribution of the relative position of the percutaneous puncture needle tip.

[0104] In this embodiment of the invention, based on the aforementioned analysis of electromagnetic flow and dielectric effect, the relative position of the puncture needle tip at each moment is further calculated. Utilizing the previously obtained information on electromagnetic flow and dielectric effect, an interaction model of the electric and magnetic fields between the puncture needle and various tissues within the surgical area can be obtained. Through numerical calculations at each time point within the feature point set, combined with the tissue electrical properties and the puncture needle position, an inverse problem-solving technique (such as the least squares optimization algorithm) is used to obtain the distribution of the relative position of the puncture needle tip. This calculation process is repeated at certain time intervals, thereby updating the accuracy of the puncture needle tip in real time. Accurate positioning is crucial in this process, which relies on real-time sensor data feedback and computational modeling of the puncture needle's trajectory. By adjusting the calculated position of the puncture needle using a precise electromagnetic model, consistency with the actual situation can be ensured. In this way, the relative position distribution of the puncture needle can be precisely corrected at every moment, further improving the accuracy and safety of the surgical procedure. The relative position information of the puncture needle tip is fused with the positioning data of the surgical target area to obtain a complete puncture process path, ensuring that the puncture needle can be precisely inserted into the target area according to the predetermined trajectory. Finally, the relative position distribution of the puncture needle tip in percutaneous puncture surgery is calculated.

[0105] Furthermore, step S155 includes the following steps:

[0106] Stress field modeling is performed on the stress response between the puncture needle tip and the surrounding tissue to simulate the local stress distribution generated when the puncture needle tip comes into contact with the surrounding tissue during puncture, and to generate the corresponding stress coupling distribution model between the puncture needle tip and the surrounding tissue.

[0107] In this embodiment of the invention, a contact model between the puncture needle tip and the surrounding tissue is established. Specifically, the stress distribution between the puncture needle tip and the surrounding tissue is modeled using the finite element analysis (FEA) method. First, the geometric model of the puncture needle is constructed and the physical properties of the needle tip are defined, such as the shape of the needle tip, the material (usually stainless steel or alloy), and the initial position of the needle tip in contact with the tissue. Then, the geometric model of the surrounding tissue is extracted using medical imaging data (such as CT or MRI images). Based on the different properties of the tissue (such as soft tissue, muscle, fat, blood vessels, etc.), corresponding physical parameters such as elastic modulus and Poisson's ratio are assigned. Through numerical simulation, the stress distribution when the needle tip contacts the tissue is calculated, including local stress concentration at the needle tip and stress diffusion in the surrounding tissue. In this process, the contact mechanical behavior between the needle tip and the tissue must be accurately modeled, taking into account contact friction, nonlinear elastic response of the tissue, and strain gradient, and finally generating a stress coupling distribution model between the puncture needle tip and the surrounding tissue.

[0108] Preferably, stress gradient analysis is performed on the stress coupling distribution model between the puncture needle tip and the surrounding tissue to obtain the stress change gradient between the puncture needle tip and the surrounding tissue.

[0109] In this embodiment of the invention, after completing the stress field modeling, stress gradient analysis is performed. The key to this step is to analyze the stress change between the puncture needle tip and the surrounding tissue using numerical simulation methods (such as the finite difference method or the finite element method). First, the local stress distribution map when the needle tip contacts the surrounding tissue is calculated using the model, including the stress response of the needle tip and the surrounding tissue. Then, the stress distribution map is processed using a gradient analysis algorithm to calculate the stress gradient as a function of distance. Specifically, the rate of change of stress at each point around the needle tip can be calculated using numerical differentiation methods, thereby obtaining the stress gradient in the needle tip contact area. This analysis result helps to understand the tissue deformation during puncture, so as to avoid tissue damage or needle displacement errors during puncture due to excessive or insufficient local stress. Finally, the corresponding stress gradient between the puncture needle tip and the surrounding tissue is obtained.

[0110] Preferably, the tissue puncture elastic modulus is analyzed based on the puncture force between the puncture needle tip and the surrounding tissue to obtain the corresponding tissue puncture elastic modulus between the puncture needle tip and the surrounding tissue.

[0111] In this embodiment of the invention, by analyzing the puncture force during the puncture process and combining it with the aforementioned stress gradient, the puncture elastic modulus of the surrounding tissue is further calculated. First, during the puncture operation, the puncture force changes with the increase of the needle tip insertion depth. A high-precision force sensor (such as a pressure sensor or torque sensor) monitors the puncture force on the needle tip in real time during the puncture process. Second, through numerical modeling, based on the relationship between the measured puncture force and the needle tip insertion depth, and combined with the stress distribution at the contact between the needle tip and the tissue, the local elastic modulus of the tissue is calculated using mechanical formulas (such as Hooke's law). Specifically, there is a linear or nonlinear relationship between the puncture force and the degree of tissue deformation. Therefore, iterative calculations of the puncture force and the tissue elastic modulus are required at different depth points to obtain an accurate elastic modulus value. This value reflects the resistance characteristics of the surrounding tissue to the puncture needle during the puncture process. Finally, the corresponding tissue puncture elastic modulus between the puncture needle tip and the surrounding tissue is obtained.

[0112] Preferably, the relative position distribution of the percutaneous puncture needle tip is corrected for puncture position deviation based on the stress gradient between the puncture needle tip and the surrounding tissue and the elastic modulus of the tissue puncture, so as to obtain the position distribution of the percutaneous puncture needle.

[0113] In this embodiment of the invention, by combining the results of the aforementioned stress gradient and puncture force analysis, puncture position deviation correction is performed. First, by analyzing the real-time position and direction of the puncture needle during the puncture process, and based on the feedback signal from the quantum multidimensional sensor, the deviation of the needle tip relative to the target tissue is calculated. On this basis, by combining the stress gradient between the needle tip and the tissue and the elastic modulus of the tissue, possible sources of deviation during the puncture process are identified, such as local unbalanced forces in contact between the needle tip and the tissue, incorrect needle tip insertion angle, etc. To correct these deviations, firstly, an adaptive algorithm (such as a PID control algorithm or model predictive control) is used to adjust the position and angle of the puncture needle according to real-time feedback to ensure that the needle tip accurately reaches the target position. Secondly, the magnitude of the puncture force is adjusted according to the elastic characteristics of the tissue to avoid further deviation of the puncture position due to excessive or insufficient puncture force. Through this correction method, it is ensured that the puncture needle can maintain accurate positioning throughout the puncture process, reducing surgical errors and improving surgical precision and safety. This step also requires real-time monitoring of the stress response between the needle tip and the tissue to ensure that there is no excessive stress concentration or tissue damage during the puncture process, ultimately obtaining the puncture needle position distribution for percutaneous puncture surgery.

[0114] Furthermore, step S2 includes the following steps:

[0115] Step S21: The patient's respiratory motion changes are monitored in real time during the percutaneous puncture procedure by a preset pressure sensor array. The body surface pressure change signal generated by the patient's respiratory motion is converted into an electrical signal, and the electrical signal is statistically analyzed to obtain the patient's respiratory motion changes, including the patient's respiratory cycle, tidal volume, respiratory rate, and respiratory phase change parameters.

[0116] In this embodiment of the invention, an array of 16 high-precision piezoresistive pressure sensors is used. These sensors are closely fitted to the patient's body surface according to the anatomical distribution of key respiratory motion sensing areas in the human chest and abdomen, ensuring seamless contact between the sensors and the skin. When the patient breathes, the rise and fall of the chest and abdomen causes changes in air pressure. The piezoresistive sensitive element of the sensor deforms under force, and the change in body surface pressure is converted into an electrical signal based on the piezoresistive effect. After preprocessing by amplification and filtering circuits, the electrical signal is transmitted to a hardware module with a built-in dedicated statistical analysis algorithm. This module collects the electrical signal at a sampling frequency of 100Hz, and accurately calculates the patient's corresponding respiratory cycle through peak detection and cycle recognition algorithms, with an accuracy of up to 0.1 seconds. The tidal volume is calculated using an integral algorithm, with an error controlled within 5%. The respiratory rate is obtained based on the reciprocal of the cycle, and the respiratory phase change parameters are extracted through a phase comparison algorithm. Finally, the changes in the patient's respiratory motion are obtained, including the patient's corresponding respiratory cycle, tidal volume, respiratory rate, and respiratory phase change parameters.

[0117] Step S22: By performing a three-dimensional reconstruction of the patient's human body contour in a preoperative static state with the operating table as the coordinate origin, a human body displacement reference map is generated.

[0118] In this embodiment of the invention, before the surgery begins, when the patient is in a static, lying position, a scanning device based on structured light 3D scanning technology is activated. This device has four high-precision projectors and eight high-resolution cameras evenly arranged around the operating table. A 3D measurement coordinate system is constructed with the operating table as the origin. The projectors project a specially coded structured light stripe pattern onto the patient's body surface. The cameras simultaneously capture stripe deformation images from different angles. The image data is transmitted in real time via a high-speed data transmission line to a workstation equipped with powerful graphics processing capabilities. The workstation runs a 3D reconstruction algorithm based on stereo vision principles to extract features, match, and perform triangulation calculations on the acquired multi-view images. A human displacement reference map is constructed with an accuracy of 1 millimeter, fully presenting the patient's human body contour and spatial position information in a static state before surgery. Finally, a human displacement reference map is constructed.

[0119] Step S23: By synchronously activating the preset laser radar scanning device, the percutaneous puncture surgical robot performs real-time monitoring of the human body's three-dimensional point cloud during the puncture process to obtain real-time three-dimensional point cloud data of the human body during the percutaneous puncture process; based on the human body displacement reference map and through the iterative nearest point algorithm, the relative displacement change of the human body is calculated for the corresponding three-dimensional feature points in the real-time three-dimensional point cloud data of the human body during the percutaneous puncture process to obtain the patient's human body displacement change.

[0120] In this embodiment of the invention, three lidar scanning devices, each mounted at a 120-degree angle to the other, are simultaneously activated. These devices are fixed to an adjustable bracket above the operating table to ensure that the scanning field of view covers the entire patient's body. The lidar emits laser beams at a pulse frequency of 1000 times per second. The laser beams are reflected off the human body surface. After being received, the reflected light is converted into photoelectric signals and processed to generate real-time three-dimensional point cloud data of the human body during the percutaneous puncture process. The point cloud data accuracy can reach 0.5 mm. This data is transmitted to a dedicated computing chip that runs an iterative nearest point algorithm. At the same time, a pre-constructed human body displacement reference map is input. The chip uses the algorithm to accurately match and compare the coordinates of three-dimensional feature points of the human body in the two sets of data, such as key joints like the shoulder, elbow, and hip, to calculate the relative displacement of each feature point in three-dimensional space. This yields the patient's human body displacement change with a displacement calculation accuracy of 0.2 mm.

[0121] Step S24: Based on the changes in the patient's respiratory movements and the changes in the patient's body displacement, the puncture path deviation is calculated using the puncture needle tip path deviation calculation formula to estimate the puncture path deviation of the percutaneous puncture surgical robot, so as to obtain the puncture path deviation vector between the puncture needle tip and the ideal target point at each time.

[0122] In this embodiment of the invention, a suitable formula for calculating the puncture needle tip path deviation is constructed by combining the initial puncture time, the patient's corresponding respiratory cycle, the patient's corresponding human body displacement change, the second-order nonlinear deviation weight, the first-order nonlinear deviation weight, the linear deviation weight, the attenuation coefficient, the patient's corresponding respiratory rate, respiratory phase, and the tidal unit direction vector. The puncture path deviation is calculated for the puncture process corresponding to the percutaneous puncture surgical robot, and the puncture path deviation vector between the puncture needle tip and the ideal target point at each time point is accurately obtained. Finally, the puncture path deviation vector between the puncture needle tip and the ideal target point at each time point is obtained.

[0123] Step S25: Based on the puncture path deviation vector between the puncture needle tip and the ideal target point at each time point, perform a puncture depth correction analysis on the percutaneous puncture needle position distribution to obtain the percutaneous puncture needle depth distribution.

[0124] In this embodiment of the invention, a needle insertion depth correction model based on finite element analysis is used. The model is constructed based on a large amount of clinical puncture case data and a human tissue biomechanical property database. The puncture path deviation vector between the puncture needle tip and the ideal target point at each time point, which was previously quantitatively calculated, is input into the model. Based on the principle of tissue biomechanical transmission, the model simulates the force situation of the puncture needle when it encounters tissue resistance and elastic deformation. The influence of the direction and magnitude of the deviation vector on the needle insertion depth is considered. For example, when the deviation vector points to a harder tissue area, the model will appropriately reduce the needle insertion depth to avoid puncture difficulties; conversely, if it points to loose tissue, the needle insertion depth will be reasonably increased. The puncture needle insertion depth correction analysis is performed on the distribution of puncture needle positions in percutaneous puncture surgery with a correction accuracy of 0.05 mm, and finally the needle insertion depth distribution of percutaneous puncture surgery is obtained.

[0125] Furthermore, the specific formula for calculating the deviation of the puncture needle tip path in step S24 is as follows:

[0126]

[0127] In the formula, Let be the puncture path deviation vector between the needle tip and the ideal target point at time t, where t0 is the initial puncture time, T is the patient's corresponding respiratory cycle, and i is the item index of the coordinate axis direction, where 1 represents the x-axis direction in the Cartesian coordinate system, 2 represents the y-axis direction in the Cartesian coordinate system, and 3 represents the z-axis direction in the Cartesian coordinate system. Let k be the change in human body displacement of the patient along the i-th coordinate axis at time t. i c represents the second-order nonlinear deviation weight corresponding to the i-th coordinate axis direction. i Let m be the first-order nonlinear deviation weight corresponding to the i-th coordinate axis direction. i α is the linear deviation weight corresponding to the i-th coordinate axis direction. i Let ω be the attenuation coefficient corresponding to the i-th coordinate axis, and ω be the patient's respiratory rate. The patient's corresponding respiratory phase. Let t be the tidal unit direction vector corresponding to the patient at time t.

[0128] This invention, through the use of a specific mathematical model and verification, derives a formula for calculating the puncture needle tip path deviation. This formula is used to estimate the puncture path deviation for percutaneous puncture surgical robots. It fully considers the puncture path deviation vector between the needle tip and the ideal target point at time t. The initial time of puncture is t0, the patient's corresponding respiratory cycle is T, and the item index of the coordinate axis is i, where 1 represents the x-axis direction in the Cartesian coordinate system, 2 represents the y-axis direction in the Cartesian coordinate system, 3 represents the z-axis direction in the Cartesian coordinate system, and the change in the patient's body displacement in the i-th coordinate axis direction at time t. The second-order nonlinear deviation weight k corresponding to the i-th coordinate axis direction i The first-order nonlinear deviation weight c corresponding to the i-th coordinate axis direction i The linear deviation weight m corresponding to the i-th coordinate axis direction i The attenuation coefficient α corresponding to the i-th coordinate axis direction i The patient's corresponding respiratory rate ω, the patient's corresponding respiratory phase The tidal unit direction vector of the patient at time t Based on the puncture path deviation vector between the puncture needle tip and the ideal target point at time t The interrelationships between the above parameters constitute a functional relationship:

[0129]

[0130] This formula enables the calculation of puncture path deviation for percutaneous puncture surgical robots. Furthermore, the formula calculates the needle tip path deviation by considering the changes in patient displacement along the x, y, and z axes (corresponding to i = 1, 2, and 3, respectively) in a Cartesian coordinate system. This approach comprehensively reflects the human body's positional changes in different spatial directions, avoiding the problem of focusing only on a single direction while ignoring the impact of displacement in other directions on puncture path deviation. This makes the calculation of puncture path deviation more closely reflect the complex spatial motion of the actual human body. This is achieved by incorporating the patient's corresponding respiratory cycle T, respiratory rate ω, and respiratory phase. and the unit direction vector of moisture Respiratory motion-related parameters are incorporated into the formula. During percutaneous puncture surgery, the patient's breathing inevitably causes body fluctuations and micro-movements, affecting the puncture path. This allows for accurate capture of the deviations caused by respiratory motion, leading to more precise calculations of puncture path deviations. Furthermore, by setting second-order nonlinear deviation weights, first-order nonlinear deviation weights, and linear deviation weights, the formula considers the influence of different types of deviations along different coordinate axes (x, y, and z axes corresponding to i). This means it can finely distinguish the role of different types of deviations in the formation of puncture path deviations. For example, nonlinear deviations have a more significant impact in some directions, while linear deviations dominate in others, helping to more accurately quantify and analyze the root causes of puncture path deviations. In addition, the formula includes an attenuation coefficient, corresponding to different coordinate axes, considering the attenuation of deviations over time. In actual puncture procedures, deviations caused by some factors gradually weaken over time. The introduction of this coefficient more realistically simulates this dynamic process, making the calculation results of puncture path deviations more reasonable and accurate over time.

[0131] Furthermore, step S3 includes the following steps:

[0132] Step S31: Use the magnetic resonance imaging sensor based on nitrogen vacancy center placed near the puncture needle to perform magnetic resonance measurement of the puncture needle during the puncture process corresponding to the percutaneous puncture surgical robot, so as to generate the change of magnetic resonance signal of nitrogen vacancy center of percutaneous puncture needle.

[0133] In this embodiment of the invention, a magnetic resonance imaging sensor based on nitrogen-vacancy centers (NV centers) installed near the puncture needle monitors the movement of the puncture needle in real time during percutaneous puncture. NV centers have high magnetic sensitivity and can respond to minute changes in the external magnetic field. The sensor obtains the NV center magnetic resonance signal by detecting minute changes in the magnetic field around the puncture needle. Specifically, the NV center magnetic resonance imaging sensor is first installed on a dedicated support near the puncture needle. During the puncture, the sensor senses the magnetic field disturbance of the puncture needle, generating a magnetic resonance signal related to the positional change of the puncture needle. High-precision magnetic resonance imaging technology is used to sample and analyze the displacement of the puncture needle each time, thereby capturing minute changes in the magnetic resonance signal during the puncture process, ultimately generating the percutaneous puncture needle NV center magnetic resonance signal change.

[0134] Step S32: Based on the change of the magnetic resonance signal of the nitrogen vacancy center of the percutaneous puncture needle, perform micro-displacement tracking analysis of the puncture process corresponding to the percutaneous puncture surgical robot to obtain the micro-dynamic displacement trajectory of the percutaneous puncture needle.

[0135] In this embodiment of the invention, the minute displacement of the puncture needle is tracked and analyzed in real time based on the previously acquired changes in the magnetic resonance signal of the nitrogen vacancy center. Specifically, this is achieved by performing time-domain and frequency-domain analysis on the magnetic resonance signal to identify the positional changes of the puncture needle during the puncture process. This analysis process uses high-precision signal processing algorithms, including techniques such as Fast Fourier Transform (FFT) and Kalman filtering, to process and denoise the sensor signal. By comparing the magnetic resonance signal data acquired at different time points, the displacement trajectory of the puncture needle is tracked to obtain the dynamic displacement information of the puncture needle during the puncture process. This dynamic displacement trajectory can accurately reflect the motion changes of the puncture needle in space, and finally, the minute dynamic displacement trajectory of the percutaneous puncture needle is obtained.

[0136] Step S33: Obtain the magnetic resonance image of the tumor tissue corresponding to the percutaneous puncture needle during the puncture process using a magnetic resonance imaging sensor based on nitrogen vacancy centers, and perform spatial distribution analysis of the puncture needle and tumor based on the magnetic resonance image of the tumor tissue corresponding to the percutaneous puncture needle during the puncture process to generate the spatial distribution relationship between the percutaneous puncture needle and the tumor tissue location during the puncture process.

[0137] In this embodiment of the invention, a magnetic resonance imaging (MRI) sensor based on nitrogen vacancy centers is used to acquire MRI images of the tumor tissue corresponding to the puncture needle during the puncture process. Specifically, the sensor not only monitors the movement of the puncture needle but also generates high-resolution MRI images of the puncture needle and its surrounding area through its highly sensitive MRI capabilities. To accurately locate the tumor tissue, a three-dimensional spatial distribution image of the puncture needle and tumor tissue is obtained along the path of the puncture needle using high magnetic field excitation and induction technology. By using a specific scanning protocol, the sensor can dynamically acquire real-time MRI images of the tumor tissue during the puncture process. These images are processed by an image reconstruction algorithm to form clear spatial distribution information of the tumor tissue, the relative positional relationship between the tumor tissue and the puncture needle, and the path of the puncture needle in the tumor tissue. Finally, the spatial distribution relationship between the percutaneous puncture needle and the tumor tissue position during the puncture process is generated.

[0138] Step S34: Based on the micro-dynamic displacement trajectory of the percutaneous puncture needle and combined with dynamic simulation and physical modeling, the spatial distribution relationship between the percutaneous puncture needle and the tumor tissue position during the puncture process is detected to eliminate the mechanical influence of different puncture angles, speeds and local tissue deformation caused by needle puncture on tumor displacement, and obtain the tumor displacement distribution of percutaneous puncture patients.

[0139] In this embodiment of the invention, tumor displacement is detected by combining the micro-dynamic displacement trajectory of the puncture needle with dynamic simulation and physical modeling. Specifically, the operation is as follows: First, based on the previously obtained dynamic displacement trajectory data of the puncture needle, combined with the physical effects of the puncture needle on the tissue during the puncture process, the tumor displacement is simulated. Then, using numerical simulation methods such as finite element analysis (FEA) and computational fluid dynamics (CFD), the angle, speed, and puncture depth of the puncture needle are physically modeled to simulate the mechanical effects of the puncture needle's movement on the surrounding tumor tissue. This simulation takes into account the local tissue deformation caused by the puncture needle during the puncture process, thereby analyzing the possible displacement range of the tumor tissue under different puncture angles and speeds. Through multiple simulations, a tumor displacement distribution map is generated, thereby predicting the overall displacement of the tumor during the puncture process, and finally obtaining the tumor displacement distribution of the percutaneous puncture patient.

[0140] Step S35: Determine the location distribution of the percutaneous puncture needle reaching the target area based on the tumor displacement distribution of the percutaneous puncture patient.

[0141] In this embodiment of the invention, the location distribution of the puncture needle reaching the target area is further analyzed based on the previously obtained tumor displacement distribution. Specifically, firstly, based on the tumor displacement distribution map, the changing trend of the tumor tissue during the puncture process is analyzed. Combining the current position and puncture direction of the puncture needle, multiple target positions that the puncture needle may reach during the puncture process are determined. Through optimization algorithms, such as particle swarm optimization (PSO) or genetic algorithm (GA), the optimal path and final target position of the puncture needle are determined based on the relationship between the puncture needle and the tumor position. During this process, the puncture angle and puncture speed also need to be adjusted in real time to ensure that the puncture needle can accurately reach the target area, and finally the location distribution of the percutaneous puncture needle reaching the target area is obtained.

[0142] Furthermore, step S4 includes the following steps:

[0143] Step S41: Based on the distribution of the percutaneous needle insertion depth in the target area, the distribution difference between the needle insertion depth and the target area is quantified to obtain the difference in the distribution distance between the percutaneous needle insertion depth and the target area reached by the needle.

[0144] In this embodiment of the invention, in a percutaneous puncture surgical robot system based on quantum multidimensional sensors, the percutaneous puncture needle is first precisely positioned to reach the predetermined target area. The state of the puncture needle at different depths is monitored in real time using quantum sensors. By comparing the spatial distribution of the current depth of the puncture needle with that of the target area, the spatial difference between the puncture depth and the target area is calculated. The multidimensional measurement capability of the quantum multidimensional sensor allows the acquisition of data including but not limited to needle insertion depth, lateral displacement, longitudinal displacement, and angle changes, forming a high-dimensional target area position distribution. Based on this data, the distance difference between the current position of the puncture needle and the target area is quantified using a specific algorithm (e.g., least squares method or Bayesian inference method). The error between the needle insertion path and the target position is derived through spatial coordinates and time changes, and the statistical distribution of this error is obtained, forming a quantitative result of the positional difference between the needle insertion depth and the target area. This difference quantification process can help further optimize the needle insertion path of the percutaneous puncture surgery, ultimately obtaining the distributional positional distance difference between the percutaneous puncture needle insertion depth and the puncture reaching the target area.

[0145] Step S42: Based on the difference in the distribution distance between the percutaneous puncture needle depth and the target area reached by the puncture, perform needle insertion navigation control on the needle insertion path of the percutaneous puncture surgical robot during the corresponding puncture process to generate a percutaneous puncture surgical needle insertion navigation path.

[0146] In this embodiment of the invention, based on the quantitative results of the previously obtained puncture depth and target area distribution difference, the next step is to perform precise navigation control on the needle insertion path during percutaneous puncture. Specifically, the system utilizes the target area distribution difference data and combines it with robot control algorithms (such as path planning methods based on genetic algorithms, artificial neural networks, or PID control) to generate the optimal puncture path. This path not only considers the spatial distribution of the target area but also the operational stability, flexibility, and accuracy of the puncture needle. Quantum sensors provide real-time feedback on minute displacements between the puncture needle and the target area, generating real-time adjustment commands for the puncture needle insertion path to ensure precise control of the needle insertion depth, angle, and direction during the puncture process. Specifically, the robot system corrects the needle insertion path in real time based on the calculated needle-target area distribution difference to ensure that the puncture needle enters the target area along the shortest and most accurate path. During this process, the surgical system adjusts the angle of the robot joints, controls the advancement speed of the puncture needle, and adjusts the needle insertion direction to ultimately generate the percutaneous puncture needle insertion navigation path.

[0147] Step S43: Generate corresponding percutaneous puncture surgery navigation control commands based on the percutaneous puncture needle insertion navigation path response, and apply them to the percutaneous puncture surgery robot to perform the corresponding percutaneous puncture surgery robot puncture navigation adjustment work.

[0148] In this embodiment of the invention, based on the previously generated percutaneous puncture surgical navigation path, the system accurately calculates the control commands for each step of the operation, generates specific navigation control commands, and applies them to the percutaneous puncture surgical robot. In the specific implementation process, after receiving the navigation path, the robot control system generates specific motion commands through the built-in kinematic and dynamic models. These control commands include, but are not limited to, the needle insertion rate, needle insertion angle, needle insertion depth, and needle rotation angle, etc., and are accurately executed by the robot drive system. Real-time data feedback provided by quantum multidimensional sensors (such as the real-time position of the puncture needle, the reflection signal of the target area, etc.) continuously corrects the navigation path in real time and adjusts the control commands to ensure that the puncture needle can accurately reach the target area and correct path deviations in real time. When the deviation of the puncture needle exceeds the predetermined tolerance range, the robot control system automatically adjusts the needle insertion path, recalculates the motion commands, and further corrects the error. The surgical robot completes the precise puncture of the target area by continuously adjusting the direction and depth of the needle insertion, and finally performs the corresponding percutaneous puncture surgical robot puncture navigation adjustment work.

[0149] Furthermore, the present invention also provides a percutaneous puncture surgical robot system based on quantum multidimensional sensors, for executing the control method of the percutaneous puncture surgical robot system based on quantum multidimensional sensors as described above. The percutaneous puncture surgical robot system based on quantum multidimensional sensors includes:

[0150] The percutaneous puncture needle position determination module is used to detect changes in the puncture magnetic field during the puncture process of the percutaneous puncture surgical robot by using a magnetic field sensor based on a superconducting quantum interference device placed near the patient's body surface, so as to obtain the distribution field of the percutaneous puncture surgical magnetic field change; based on the distribution field of the percutaneous puncture surgical magnetic field change, the puncture needle position is determined during the puncture process of the percutaneous puncture surgical robot, thereby obtaining the percutaneous puncture needle position distribution;

[0151] The percutaneous puncture needle depth correction module is used to monitor the changes in the patient's respiratory movements and body displacement during the puncture process corresponding to the percutaneous puncture surgical robot in real time, and to perform puncture needle depth correction analysis on the percutaneous puncture needle position distribution based on the changes in the patient's respiratory movements and body displacement, thereby obtaining the percutaneous puncture needle depth distribution.

[0152] The target area location determination module is used to detect tumor displacement distribution during the percutaneous puncture procedure using a nitrogen-vacancy-centered magnetic resonance imaging sensor placed near the puncture needle, thereby obtaining the tumor displacement distribution of the percutaneous puncture patient; and to determine the corresponding percutaneous puncture needle location distribution in the target area based on the tumor displacement distribution of the percutaneous puncture patient.

[0153] The percutaneous needle insertion navigation control module is used to control the needle insertion depth distribution of percutaneous puncture surgery based on the distribution of the percutaneous puncture needle's position in the target area, generate the percutaneous puncture needle insertion navigation path, and perform corresponding percutaneous puncture robot puncture navigation adjustment work.

[0154] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A transcutaneous puncture surgery robot system based on a quantum multidimensional sensor, characterized by, Comprise: Percutaneous puncture needle position determination module for detecting puncture magnetic field changes of the puncture process corresponding to the percutaneous puncture surgery robot by using the superconducting quantum interference device based magnetic field sensor placed near the patient's body surface to obtain the percutaneous puncture surgery magnetic field change distribution field; determine the puncture needle position of the puncture process corresponding to the percutaneous puncture surgery robot based on the percutaneous puncture surgery magnetic field change distribution field, so as to obtain the percutaneous puncture surgery puncture needle position distribution; Percutaneous puncture needle depth correction module for analyzing the puncture needle depth correction of the percutaneous puncture surgery puncture needle position distribution based on the respiratory motion changes and body displacement changes of the patient during the puncture process corresponding to the percutaneous puncture surgery robot, and obtaining the percutaneous puncture surgery needle depth distribution; Arrive target area position determination module for detecting tumor displacement distribution of the puncture process corresponding to the percutaneous puncture surgery robot by using the nitrogen vacancy center based magnetic resonance imaging sensor placed near the puncture needle to obtain the percutaneous puncture patient tumor displacement distribution; determine the puncture needle to reach the target area position distribution corresponding to the percutaneous puncture based on the percutaneous puncture patient tumor displacement distribution; Percutaneous needle puncture navigation control module for controlling the needle puncture navigation of the percutaneous puncture surgery needle depth distribution based on the percutaneous puncture needle to reach the target area position distribution, generating the percutaneous puncture surgery needle puncture navigation path, and executing the corresponding percutaneous puncture surgery robot puncture navigation adjustment work; The control method of the percutaneous puncture surgery robot system based on quantum multidimensional sensor comprises the following steps: Step S1: detecting the puncture magnetic field changes of the puncture process corresponding to the percutaneous puncture surgery robot by using the superconducting quantum interference device based magnetic field sensor placed near the patient's body surface to obtain the percutaneous puncture surgery magnetic field change distribution field; determine the puncture needle position of the puncture process corresponding to the percutaneous puncture surgery robot based on the percutaneous puncture surgery magnetic field change distribution field, so as to obtain the percutaneous puncture surgery puncture needle position distribution; Step S2: by real-time monitoring the respiratory motion changes and body displacement changes of the patient during the puncture process corresponding to the percutaneous puncture surgery robot, and based on the respiratory motion changes and body displacement changes of the patient, the percutaneous puncture surgery puncture needle position distribution is analyzed to correct the puncture needle depth, and the percutaneous puncture surgery needle depth distribution is obtained; Step S3: detecting the tumor displacement distribution of the puncture process corresponding to the percutaneous puncture surgery robot by using the nitrogen vacancy center based magnetic resonance imaging sensor placed near the puncture needle to obtain the percutaneous puncture patient tumor displacement distribution; determine the puncture needle to reach the target area position distribution corresponding to the percutaneous puncture based on the percutaneous puncture patient tumor displacement distribution; Step S4: control the needle puncture navigation of the percutaneous puncture surgery needle depth distribution based on the percutaneous puncture needle to reach the target area position distribution, generate the percutaneous puncture surgery needle puncture navigation path, and execute the corresponding percutaneous puncture surgery robot puncture navigation adjustment work.

2. The quantum multi-dimensional sensor based transcutaneous puncture surgery robot system according to claim 1, wherein, Step S1 comprises the following steps: Step S11: Collecting the fluctuation of the magnetic field of the puncture process corresponding to the percutaneous puncture robot by using the magnetic field sensor based on superconducting quantum interference device placed near the surface of the patient, to obtain the fluctuation of the weak magnetic field distribution corresponding to each time point in the percutaneous puncture process; Step S12: Analyzing the magnetic field spatial gradient of the fluctuation of the weak magnetic field distribution corresponding to each time point in the percutaneous puncture process, to obtain the magnetic field spatial distribution gradient corresponding to each spatial distribution position in the percutaneous puncture process; Step S13: Analyzing the puncture spatial distribution of the puncture process corresponding to the percutaneous puncture robot, to obtain the puncture spatial distribution between the puncture needle and the surrounding tissue of the human body in the percutaneous puncture process; Step S14: Processing the puncture spatial distribution between the puncture needle and the surrounding tissue of the human body in the percutaneous puncture process based on the magnetic field spatial distribution gradient corresponding to each spatial distribution position in the percutaneous puncture process, to obtain the magnetic field change distribution field of the percutaneous puncture operation; Step S15: Determining the puncture needle position of the puncture process corresponding to the percutaneous puncture robot based on the magnetic field change distribution field of the percutaneous puncture operation, to obtain the puncture needle position distribution of the percutaneous puncture operation.

3. The quantum multi-dimensional sensor based transcutaneous puncture surgery robot system according to claim 2, wherein, Step S15 includes the following steps: Step S151: Analyzing the electromagnetic characteristics of the surrounding tissue of the operation area of the percutaneous puncture robot corresponding to the puncture process, to obtain the electromagnetic characteristics of the surrounding tissue of the percutaneous operation area, including the conductivity and dielectric coefficient corresponding to the surrounding tissue; Step S152: Decomposing the magnetic field disturbance of the magnetic field change distribution field of the percutaneous puncture operation in time sequence, to obtain the magnetic field change disturbance distribution generated at each time point in the percutaneous puncture process; Step S153: Calculating the relative position of the puncture needle tip based on the electromagnetic characteristics of the surrounding tissue of the percutaneous operation area, to obtain the relative position distribution of the puncture needle tip of the percutaneous puncture operation; Step S154: Obtaining the stress reaction and puncture force between the puncture needle tip and the surrounding tissue through the puncture process corresponding to the percutaneous puncture robot; Step S155: Correcting the puncture position deviation of the relative position distribution of the puncture needle tip of the percutaneous puncture operation based on the stress reaction and puncture force between the puncture needle tip and the surrounding tissue, to obtain the puncture needle position distribution of the percutaneous puncture operation.

4. The quantum multi-dimensional sensor based transcutaneous puncture surgery robot system according to claim 3, wherein, Step S153 includes the following steps: Analyzing the electromagnetic flow and dielectric effect between the percutaneous puncture needle and the surrounding tissue of the operation area based on the conductivity and dielectric coefficient corresponding to the surrounding tissue of the percutaneous puncture robot, to obtain the electromagnetic flow and dielectric effect between the percutaneous puncture needle and the surrounding tissue of the operation area; Analyzing the magnetic field change disturbance distribution generated at each time point in the percutaneous puncture process in time domain and frequency domain, to extract the relative position feature points corresponding to the percutaneous puncture needle tip at each time point, to obtain the magnetic field relative position feature point set caused by the movement of the percutaneous puncture needle tip; The relative position of each relative position feature point in the set of relative position feature points caused by the movement of the percutaneous puncture needle tip is calculated based on the electromagnetic flow and dielectric effect between the percutaneous puncture needle and the tissue around the surgical area, and the relative position distribution of the percutaneous puncture needle tip in the percutaneous puncture surgery is obtained.

5. The quantum multi-dimensional sensor based transdermal puncturing surgery robot system according to claim 3, wherein, Step S155 includes the following steps: The stress reaction between the puncture needle tip and the surrounding tissue is modeled to simulate the local stress distribution generated when the puncture needle tip contacts the surrounding tissue during the puncture process, and a corresponding stress coupling distribution model between the puncture needle tip and the surrounding tissue is generated; The stress coupling distribution model between the puncture needle tip and the surrounding tissue is analyzed to obtain the stress change gradient between the puncture needle tip and the surrounding tissue; The puncture elastic modulus of the tissue between the puncture needle tip and the surrounding tissue is analyzed based on the puncture force between the puncture needle tip and the surrounding tissue, and the puncture elastic modulus of the tissue between the puncture needle tip and the surrounding tissue is obtained; The puncture position deviation of the percutaneous puncture surgery puncture needle tip relative position distribution is corrected based on the stress change gradient and the puncture elastic modulus of the tissue between the puncture needle tip and the surrounding tissue, and the puncture needle position distribution in the percutaneous puncture surgery is obtained.

6. The quantum multi-dimensional sensor based transdermal puncturing surgery robot system according to claim 1, wherein, Step S2 includes the following steps: Step S21: The patient's respiratory motion changes are monitored in real time during the puncture process of the percutaneous puncture surgery robot by using a pre-set pressure sensor array to convert the body surface pressure change signal generated by the patient's respiratory motion into an electrical signal, and the electrical signal is analyzed to obtain the patient's respiratory motion changes, including the patient's corresponding respiratory cycle, tidal volume, respiratory rate, and respiratory phase change parameters; Step S22: The patient's body contour is scanned and three-dimensionally reconstructed in all directions under the preoperative static state with the operating table as the coordinate origin to construct a human body displacement benchmark atlas; Step S23: The human body three-dimensional point cloud data in the percutaneous puncture process is obtained by synchronously starting a pre-set laser radar scanning device to monitor the human body three-dimensional point cloud in real time during the puncture process of the percutaneous puncture surgery robot; the relative displacement change of the corresponding human body three-dimensional feature points in the human body three-dimensional real-time point cloud data in the percutaneous puncture process is calculated based on the human body displacement benchmark atlas and by using the iterative closest point algorithm to obtain the patient's human body displacement change; Step S24: The puncture path deviation of the percutaneous puncture surgery robot is calculated based on the patient's respiratory motion changes and the patient's human body displacement changes using the puncture needle tip path deviation calculation formula to obtain the puncture path deviation vector between the puncture needle tip and the ideal target point at each time; Step S25: The puncture depth of the percutaneous puncture surgery puncture needle position distribution is corrected and analyzed based on the puncture path deviation vector between the puncture needle tip and the ideal target point at each time to obtain the percutaneous puncture surgery needle depth distribution.

7. The quantum multi-dimensional sensor based transcutaneous puncture surgery robot system according to claim 6, wherein, The puncture needle tip path deviation calculation formula in step S24 is as follows: ； In the formula, In order to be in The vector of puncture path deviation between the puncture needle tip and the ideal target point at any given time. At the initial moment of puncture, For the patient's corresponding respiratory cycle, This represents the item index along the coordinate axis, where 1 indicates the x-axis direction in Cartesian coordinates, 2 indicates the y-axis direction, and 3 indicates the z-axis direction. In order to be in At this moment The changes in human body displacement corresponding to the patient along each coordinate axis. For the first The second-order nonlinear deviation weights corresponding to each coordinate axis direction For the first The first-order nonlinear deviation weights corresponding to each coordinate axis direction For the first The linear deviation weights corresponding to each coordinate axis direction For the first The attenuation coefficients corresponding to each coordinate axis direction The patient's corresponding respiratory rate, The patient's corresponding respiratory phase. In order to be in The tidal unit direction vector corresponding to the patient at that moment.

8. The quantum multi-dimensional sensor based transdermal puncturing surgery robot system according to claim 1, wherein, Step S3 includes the following steps: Step S31: performing a percutaneous puncture needle magnetic resonance measurement on the corresponding puncture process of the percutaneous puncture surgery robot by using a corresponding nitrogen vacancy center based magnetic resonance imaging sensor placed near the puncture needle to generate a percutaneous puncture needle nitrogen vacancy center magnetic resonance signal change; Step S32: performing a percutaneous puncture needle micro-displacement tracking analysis on the corresponding puncture process of the percutaneous puncture surgery robot based on the percutaneous puncture needle nitrogen vacancy center magnetic resonance signal change, to obtain a percutaneous puncture needle micro-dynamic displacement trajectory; Step S33: obtaining a corresponding tumor tissue magnetic resonance image of the percutaneous puncture needle in the puncture process by the nitrogen vacancy center based magnetic resonance imaging sensor, and performing a puncture needle and tumor spatial distribution analysis according to the corresponding tumor tissue magnetic resonance image of the percutaneous puncture needle in the puncture process, to generate a spatial distribution relationship between the percutaneous puncture needle and the tumor tissue position in the puncture process; Step S34: based on the percutaneous puncture needle micro-dynamic displacement trajectory and combined with dynamic simulation and physical modeling, detecting the tumor displacement distribution of the spatial distribution relationship between the percutaneous puncture needle and the tumor tissue position in the puncture process, to eliminate the mechanical influence of the percutaneous puncture needle different puncture angles, speed and needle puncture generated local tissue deformation on the tumor displacement, to obtain a percutaneous puncture patient tumor displacement distribution; Step S35: determining a corresponding percutaneous puncture needle target region position distribution according to the percutaneous puncture patient tumor displacement distribution.

9. The quantum multi-dimensional sensor based transdermal puncturing surgery robot system according to claim 1, wherein, Step S4 includes the following steps: Step S41: quantifying the needle depth distribution difference between the needle depth distribution and the target region distribution of the percutaneous puncture surgery based on the percutaneous puncture needle target region position distribution, to obtain the distribution position distance difference between the percutaneous puncture needle depth and the puncture target region; Step S42: performing a needle path puncture navigation control on the corresponding puncture process of the percutaneous puncture surgery robot according to the distribution position distance difference between the percutaneous puncture needle depth and the puncture target region, to generate a percutaneous puncture surgery needle puncture navigation path; Step S43: generating a corresponding percutaneous puncture surgery navigation control instruction through the percutaneous puncture surgery needle puncture navigation path response and acting on the percutaneous puncture surgery robot to perform corresponding percutaneous puncture surgery robot puncture navigation adjustment work.

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