Orthopedic Surgery Robot Calibration Device and Method

Abstract

The present application discloses an orthopedic surgical robot calibration device and method, including: using a position sensor to obtain the real-time position of the end effector, comparing the obtained real-time position of the end effector with the initial position of the end effector set at the time of factory shipment, and then calibrating the real-time position of the end effector to obtain calibrated position parameters; using a torque sensor to collect torque parameters received by the end effector, calibrating the collected torque parameters according to the calibrated position parameters, and the calibrated torque parameters reduce the error of surgical instrument operation; adjusting the initial position of the surgical instrument according to the calibrated position parameters, and adjusting the force condition of the surgical instrument according to the calibrated torque data. By first correcting the position parameters and then using the corrected position parameters to assist in correcting the torque parameters, the surgical accuracy and safety of the surgical robot are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of soft tissue robots, and particularly to an orthopedic surgical robot calibration device and method. Background Art

[0002] In the medical field, especially in orthopedic surgeries, surgical robots are increasingly widely used, and their high precision, high stability, and good surgical assistance effects have been widely recognized by doctors and patients. However, during the actual use of surgical robots, many technical challenges still exist. Among them, the calibration problems of position parameters and torque parameters are particularly crucial. The end effector of a surgical robot is the core component of surgical operations, and its position accuracy directly affects the surgical effect. Traditional position calibration methods mainly rely on the set parameters at the time of factory shipment. However, during actual surgeries, due to the influence of various factors, such as mechanical wear and environmental changes, the position of the end effector may shift. If this shift is not calibrated in a timely manner, it will cause the surgical instrument to fail to accurately reach the predetermined position, thereby affecting the precision and safety of the surgery. When a doctor sits in front of the console and operates the surgical robot through a remote handle, a certain amount of force needs to be applied to control the surgical instrument on the robot arm. In a specific surgical case, the doctor's goal is to remove a 5-mm thick hyperplastic tissue. The doctor applies force through the remote handle, causing the robotic arm of the surgical robot to move. This movement is achieved through the surgical instrument in the flexible channel. However, during the surgery, a problem occurred: the hyperplastic tissue was not completely removed. This usually means that there is a deviation between the actual movement distance of the surgical instrument and the movement instruction applied by the doctor through the remote handle. This deviation may stem from multiple factors, but one of the key factors is that the magnitude of the applied force affects the accuracy of the robot's movement. In a surgical robot system, the force applied by the doctor is transmitted to the surgical instrument through a series of mechanical and electronic components. There may be some non-linear factors in this transmission process, such as friction and elastic deformation, which will cause a difference between the actual movement distance and the expected movement distance. In addition, the control system of the surgical robot may also have a certain lag or error, which will further affect the surgical precision. Therefore, when the doctor applies force through the remote handle to operate the surgical instrument, although enough force has been applied to move the surgical instrument 5 mm to remove the 5-mm thick hyperplastic tissue, in fact, due to the influence of the above factors, the movement distance of the surgical instrument may not reach the expected 5 mm, resulting in incomplete removal of the hyperplastic tissue.

[0003] As disclosed in Chinese Patent Application No. 202111296911.X, a method, device, electronic device and readable storage medium for calibrating the origin position are involved in the field of soft tissue robots, including: when it is detected that the end effector and the base are engaged, obtaining the first real-time position parameter of the flexible channel of the end effector; obtaining the initial position parameter of the flexible channel of the end effector; obtaining the offset position parameter of the channel of the end effector according to the difference between the first real-time position parameter and the initial position parameter; obtaining the mean position parameter of the end effector according to the offset position parameter; obtaining the second real-time position parameter of the flexible channel; obtaining the calibration angle parameter of the end effector according to the mean position parameter and the second real-time position parameter; and calibrating the origin position of the end effector according to the calibration angle parameter. The present invention eliminates the origin position deviation problem caused by various uncertain factors by optimizing the determination logic of the origin position of the end effector.

[0004] In the prior art patents, only the position parameters of the end effector of the surgical robot are calibrated, and the torque parameters are not calibrated, which affects the accuracy of the surgery. Summary of the Invention

[0005] The present application provides an orthopedic surgical robot calibration device and method, which first corrects the position parameters and then uses the corrected position parameters to assist in correcting the torque parameters, improving the surgical accuracy and safety of the surgical robot. Through the correction process, the error of the position parameters can be significantly reduced.

[0006] The present application provides an orthopedic surgical robot calibration method, including:

[0007] S101, using a position sensor to obtain the real-time position of the end effector, comparing the obtained real-time position of the end effector with the initial position of the end effector set at the time of factory, and then calibrating the real-time position of the end effector to obtain the calibrated position parameters;

[0008] S102, using a torque sensor to collect the torque parameters received by the end effector, and calibrating the collected torque parameters according to the calibrated position parameters;

[0009] S103, adjusting the initial position of the surgical instrument according to the calibrated position parameters, and adjusting the force received by the surgical instrument according to the calibrated torque data.

[0010] Preferably, according to the obtained calibrated position parameters, a torque correction model is established, and the formula in the torque correction model is: , where is the torque collected, is the torque corrected according to the position parameters, It is the torque adjustment amount calculated based on the calibrated position parameters.

[0011] Preferably, the torque adjustment amount ΔM is a linear function of the position calibration amount , that is: ΔM = , where , are linear coefficients determined according to empirical data, and are the calibrated position parameters, and are the real-time position parameters collected.

[0012] Preferably, the method for calibrating the torque parameters further includes:

[0013] S201, according to the historical surgical data of the surgical robot, obtain the relationship between the surgical actions and the torque changes, identify the key points and the overall trend of the torque changes through the relationship between the surgical actions and the torque changes, and draw a torque change curve graph according to the relationship between the surgical actions and the torque changes, the key points of the torque changes and the overall trend;

[0014] S202, input the torque change curve graph into the dynamic torque calibrator, use the dynamic torque calibrator for simulation calibration, simulate the expected value, measure the measured value in real time with a torque sensor, compare the expected value and the measured value, and obtain the difference value;

[0015] S203, calculate the calibration coefficient according to the obtained difference value;

[0016] S204, verify the calculated calibration coefficient, and substitute the verified calibration coefficient into the torque sensor in step S102 for calibration.

[0017] Preferably, set the dynamic torque calibrator to the simulation mode, input the torque change curve graph into the dynamic torque calibrator as the calibration standard, and the calibrator simulates the change of the torque according to the set dynamic torque change curve, that is, the expected value. At the same time, use a torque sensor for measurement, record the dynamic torque value output by the calibrator measured by the torque sensor in real time, the dynamic torque value measured by the torque sensor in real time is the measured value, compare the measured value with the expected value one by one, compare the measured value and the expected value at each time point, and obtain the difference value between the measured value and the expected value.

[0018] Preferably, obtain the calibration coefficient a by calculating the linear relationship between the measured value and the expected value, and substitute the obtained calibration coefficient a into the formula y = ax + b, where y is the calibrated measured value, x is the original measured value, a is the calibration coefficient, representing the linear relationship between the measured value and the expected value, and b is the intercept.

[0019] Preferably, the method for calibrating the position parameters and torque parameters of the surgical robot according to the historical surgical data of the surgical robot further includes: when the position parameters and torque parameters are about to deviate, identifying the fluctuation states of the position parameters and torque parameters at this time, and warning and pre-calibrating the real-time measured position parameters and torque parameters according to the identified data fluctuation states. The specific method is as follows:

[0020] S301, identifying the data fluctuation states when the position parameters and torque parameters are about to deviate according to the collected historical data of the surgical robot;

[0021] S302, using a real-time monitoring system to monitor the position parameters and torque parameters in real time. When the real-time monitoring system detects that the data fluctuation states of the real-time position parameters and torque parameters meet the warning standard, give a warning and calibrate;

[0022] S303, dividing the deviation sensitive area and non-deviation sensitive area according to the historical data of the surgical robot and the identified data fluctuation states.

[0023] Preferably, the deviation state is the abnormal change of these parameters during normal operation, and the deviation state is manifested as the sudden change of the parameters, exceeding the preset normal range, or continuous unstable fluctuation.

[0024] Preferably, the method for calibrating the position parameters and torque parameters further includes calibrating the directions of the position parameters and torque parameters. Specifically:

[0025] S401, collecting surgical history data, where the surgical history data includes the change magnitudes and directions of the position parameters and torque parameters, and calculating the magnitude calibration factor and direction calibration factor according to the historical data:

[0026] S402, calculating the calibration parameters according to the calculated magnitude calibration factor and direction calibration factor, and using the calibration parameters to calibrate the position parameters and torque parameters.

[0027] The present application also provides an orthopedic surgical robot calibration device, including: a position sensor module, a data acquisition and processing module, a torque sensor module, a torque calibration module, an identification and warning module, and a calculation module. The position sensor module and the torque sensor module are arranged on the end effector of the surgical robot. The data acquisition and processing module is arranged inside both the position sensor module and the torque sensor module. The torque calibration module is electrically connected to the torque sensor module.

[0028] One or more technical solutions provided in this application have at least the following technical effects or advantages: By first correcting the position parameters and then using the corrected position parameters to assist in correcting the torque parameters, the surgical accuracy and safety of the surgical robot are improved. Through the correction process, the error of the position parameters can be significantly reduced. The corrected position parameters can be used as a reference to correct the torque parameters more quickly, and thus the estimation error of the torque parameters is also correspondingly reduced. By correcting the torque parameters, it can be ensured that the force exerted by the surgical instrument on the tissue remains within a safe range, reducing the surgical risk. Adjusting solely based on the position parameters may lead to inaccurate adjustments because other influencing factors such as torque are not considered. After adding the correction process of the torque parameters, the motion state and force condition of the robotic arm can be considered more comprehensively, thereby improving the accuracy and safety of the adjustment. This systematic correction method helps the surgical robot better adapt to complex surgical environments and improve the surgical success rate;

[0029] Improve the dynamic response ability of the torque sensor, enabling it to better adapt to the dynamic torque changes during the surgical process, improving the accuracy of the torque parameters, helping the surgical robot to more accurately sense and control the interaction force between the surgical instrument and the tissue, enhancing the stability of the surgical robot during the surgical process, reducing jitter and deviation during the surgical process, improving the measurement accuracy of the torque sensor under dynamic torque changes, and the calibrated position parameters more accurately reflect the actual motion state of the surgical robot, improving the surgical success rate and safety. By considering the influence of dynamic torque changes, the measurement accuracy of the torque sensor is significantly improved, which helps the surgical robot to more accurately control the surgical instrument and reduce errors during the surgical process. Due to the improvement of the accuracy of the torque parameters and the stability of the surgical robot, the surgical success rate is also correspondingly increased. This helps to reduce the risk of surgical complications and recurrence and improve the rehabilitation quality of patients;

[0030] Improve the calibration pertinence of the surgical robot, reduce the adjustment time caused by parameter deviation during the surgical process, improve the surgical efficiency and precision, and ensure the smooth progress of the surgical process. By pre-calibrating and focusing on the deviation-sensitive areas, the number of surgical interruptions is reduced. Assume that each adjustment in the first solution takes T minutes, the second solution reduces the number of adjustments through some improvements but still requires adjustments, and the third solution further reduces the number of adjustments to almost zero (or very low frequency), then the total surgical time can be significantly shortened. Real-time monitoring and pre-calibration ensure that the surgical robot always maintains accurate position, posture, and torque parameters, reducing surgical errors. Assume that the surgical error rate in the first solution is E1%, the second solution reduces it to E2% through some means, and the third solution further reduces it to E3% (E3 < E2 < E1) through real-time monitoring and calibration. By reducing parameter deviation and the number of adjustments, doctors can perform surgical operations more smoothly, improving the surgical experience and feel;

[0031] By introducing a direction calibration factor, the calibration of the position parameter and the torque parameter becomes more accurate and targeted. Through direction calibration, the calibration error caused by wrong direction is reduced, making the calibrated parameters closer to the true values. Assuming the original calibration error is ±5%, after introducing direction calibration, the error may be reduced to ±2% or lower. Direction calibration enables the system to better adapt to the randomness of parameter changes, especially in a dynamic environment. By introducing direction calibration, the accuracy of calibration and the overall performance of the system are further improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a schematic flowchart of the calibration method of the orthopedic surgical robot of the present invention;

[0033] Figure 2 It is a schematic flowchart of calibrating the torque parameter in an embodiment of the present invention;

[0034] Figure 3 It is a schematic flowchart of warning and pre-calibrating the position parameter and the torque parameter measured in real time according to the recognized data fluctuation state in an embodiment of the present invention;

[0035] Figure 4 It is a schematic flowchart of calibrating the directions of the position parameter and the torque parameter in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0036] To facilitate the understanding of the present invention, the present application will be described more comprehensively below with reference to the relevant drawings; the preferred embodiments of the present invention are shown in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein; on the contrary, these embodiments are provided to make the disclosure of the present invention more thorough and comprehensive.

[0037] It should be noted that the terms "vertical", "horizontal", "upper", "lower", "left", "right" and similar expressions used herein are for illustrative purposes only and do not represent the only embodiments.

[0038] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs; the terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention; the term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0039] Embodiment 1: Figure 1 It is a schematic flowchart of the calibration method of the orthopedic surgical robot in an embodiment of the present invention, including:

[0040] S101. Use a position sensor to obtain the real-time position of the end effector, compare the obtained real-time position of the end effector with the initial position of the end effector set at the time of factory shipment, and then calibrate the real-time position of the end effector to obtain the calibrated position parameters.

[0041] Specifically, a position sensor laser rangefinder is set on the end effector. Use the laser rangefinder to detect the specific positions of the end effector on the X, Y, and Z axes in real time. The end effector includes a flexible channel and a transmission mechanism. The flexible channel enables surgical instruments to pass through. Set the data acquisition system. By setting the data acquisition frequency, the set data acquisition frequency is greater than the movement frequency of the surgical robot to ensure that real-time position parameters can be obtained while avoiding data loss. Start the data acquisition system to start obtaining the position parameters of the end effector on the X, Y, and Z axes in real time, and transmit the real-time position parameters to the computer in the form of digital signals; obtain the position parameters set at the time of factory shipment from the factory settings of the surgical robot as the calibration reference, compare the real-time obtained position parameters with the position parameters set at the time of factory shipment, calculate the difference between the two, and input the calculated difference and the real-time position parameters of the end effector into the Kalman filter model. The Kalman filter model calibrates the real-time position parameters and outputs the calibrated position parameters.

[0042] S102. Use a torque sensor to collect the torque parameters received by the end effector, and calibrate the collected torque parameters according to the calibrated position parameters. The calibrated torque parameters reduce the error of surgical instrument operation.

[0043] Further, the torque parameters reflect the interaction force between the surgical instrument and the tissue. A torque sensor is set on the end effector of the surgical instrument. Use the data acquisition system to record the torque parameters received by the surgical instrument in real time. Use a moving average filter to smooth the torque parameters. According to the calibrated position parameters obtained in step S101, establish a torque correction model. The torque correction model has the formula:

[0044]

[0045] where is the collected torque, is the torque corrected according to the position parameters, is the torque adjustment amount calculated based on the calibrated position parameters. The torque adjustment amount ΔM is a linear function of the position calibration amount , that is: ΔM = where , are linear coefficients determined according to empirical data, and is the calibrated position parameter, and are the collected real-time position parameters. The calibrated position parameter and the collected torque parameter are input into the torque correction model, and the torque is calibrated based on the calibrated position parameter according to the formula in the model.

[0046] For example, when using a surgical robot to remove a piece of hyperplastic tissue with a hyperplastic thickness of 5 mm and an expected resection depth of 4 mm, that is, the surgical instrument needs to move 4 mm to completely remove the hyperplastic tissue. A laser rangefinder is installed on the end effector of the surgical robot as a position sensor. The laser rangefinder can detect the specific position of the end effector on the X, Y, and Z axes in real time. The data acquisition system is set to ensure a data acquisition frequency of 500 Hz, while the maximum movement frequency of the surgical robot is 200 Hz to obtain real-time position parameters and avoid data loss. The data acquisition system is started to obtain the position parameters of the end effector on the X, Y, and Z axes in real time. Assume that at a certain moment, the real-time position parameters detected by the laser rangefinder are: (105, 152, 198). The position parameters of the factory settings (100, 150, 200) are obtained from the factory settings of the surgical robot. The real-time obtained position parameters are compared with the position parameters of the factory settings, and the difference between the two is calculated: = - =105 - 100 = 5 mm, = - =152 - 150 = 2 mm, = - =198 - 200 = -2 mm. The calculated difference and the real-time position parameters of the end effector are input into the Kalman filter model. The Kalman filter model calibrates the real-time position parameters and outputs the calibrated position parameters: Assume the calibrated position parameters are =(102.5, 149.5, 199). A torque sensor is set on the end effector of the surgical instrument to record the torque parameters received by the surgical instrument in real time. The data acquisition system is used to record the torque parameters received by the surgical instrument in real time. Assume the torque parameter at a certain moment is = 3.95 N·m. The moving average filter is used to smooth the torque parameters, and the smoothed data is still 3.95 N·m. Based on the calibrated position parameters obtained in step S101, a torque correction model is established. The torque correction model has a formula: , where ΔM is the torque adjustment amount calculated based on the calibrated position parameter. The torque adjustment amount ΔM is a linear function of the position calibration amount, that is: ΔM = , the linear coefficients are determined according to empirical data as follows: = 0.1, = 0.05, = 0.9. The calibrated position parameters and the collected torque parameters are input into the torque correction model, and the torque adjustment amount: ΔM is calculated according to the formula in the model = 0.1×(102.5 - 105.0)+0.05×(149.5 - 152.0)+0.9×(199.0 - 198.0)= - 0.25 - 0.125 + 0.9 = 0.525 N·m. Therefore, the calibrated torque is: = 3.95 + 0.525 = 4.475 N·m. By using the calibrated 4.475 N·m, the movement deviation is reduced from 1 mm to 0.02 mm. The actual cutting depth = expected cutting depth - movement deviation = 4 mm - 0.02 mm = 3.98 mm.

[0047] S103. Adjust the initial position of the surgical instrument according to the calibrated position parameters, and adjust the force condition of the surgical instrument according to the calibration data of the torque;

[0048] Adjust the initial position of the surgical instrument according to the magnitude of the position deviation, and change the force condition of the surgical instrument by adjusting the holding method of the surgical instrument according to the torque correction data, so as to improve the accuracy and control precision of the surgery.

[0049] The technical solutions in the embodiments of the present application at least have the following technical effects or advantages: By first correcting the position parameters and then using the corrected position parameters to assist in correcting the torque parameters, the surgical accuracy and safety of the surgical robot are improved. Through the correction process, the error of the position parameters can be significantly reduced. The corrected position parameters can be used as a reference to correct the torque parameters more quickly, and then the estimation error of the torque parameters is also correspondingly reduced. By correcting the torque parameters, it can be ensured that the acting force of the surgical instrument on the tissue remains within a safe range, reducing the surgical risk. Adjusting only relying on the position parameters may lead to inaccurate adjustment because other influencing factors such as torque are not considered. After adding the correction process of the torque parameters, the movement state and force condition of the robotic arm can be considered more comprehensively, thereby improving the accuracy and safety of the adjustment. This systematic correction method helps the surgical robot better adapt to complex surgical environments and improve the surgical success rate.

[0050] Embodiment 2: Based on the calibration process of the torque parameters in Embodiment 1, only static torque is considered. In this embodiment, a dynamic torque change curve is introduced to calibrate the torque parameters, which can enhance the stability of the surgical robot during the surgery. It helps to reduce the jitter and deviation during the surgery.

[0051] As shown Figure 2 the method for calibrating torque parameters further includes:

[0052] S201. Obtain the relationship between surgical actions and torque changes based on the historical surgical data of the surgical robot. Identify the key points and overall trends of torque changes through the relationship between surgical actions and torque changes. Draw a torque change curve graph based on the relationship between surgical actions and torque changes, the key points of torque changes, and the overall trends;

[0053] Specifically, obtain complete and accurate historical data from the storage location of the historical surgical data of the surgical robot. Select cases according to the surgical type, surgical action complexity, surgical duration, and patient conditions to ensure that the selected cases can comprehensively reflect the torque change characteristics of the surgical robot in different surgical scenarios. Preprocess the selected surgical case data, including data cleaning, denoising, and alignment, to ensure the accuracy and consistency of the data. Divide the surgical process into several surgical action stages, each stage corresponding to a specific surgical action. For each surgical action stage, record the torque change data of the surgical robot, including the magnitude and change rate of the torque, etc. Input the recorded torque change data into the data analysis software MATLAB to form. Use the tools in MATLAB to identify the peaks, valleys, and turning points in the torque change data. The peak is the maximum value point in the torque change data, which represents the highest level of torque reached during the surgical process. When identifying the peak, pay attention to the prominent points in the data, and the prominent points usually correspond to specific actions during the surgery, such as actions that require a large torque like cutting and tightening screws; The valley is the minimum value point in the torque change data, which reflects the lowest level of torque during the surgical process. The valley appears at the transition point of the surgical action or during the rest period when the torque requirement of the surgical instrument decreases; The turning point is the point where the torque change trend changes significantly, from increasing to decreasing or from decreasing to increasing. The turning point usually marks the transition of the surgical action or operation stage, and the turning point is identified by using differentiation; Analyze the stationarity, periodicity, and mutability of the torque change. A stable torque change indicates that the surgical process is relatively stable, while a drastic fluctuation may reflect complex actions or abnormal conditions during the surgery. Determine whether there is periodicity in the torque change by identifying whether there are repeated peaks and valleys. If there are repeated peaks and valleys, it indicates the existence of periodicity, otherwise, there is no periodicity; Observe whether there are sudden increases or decreases in the torque change. These mutations correspond to unexpected events or operation errors during the surgery. The analysis of mutability helps to identify potential risk points during the surgical process. Draw a torque change curve graph based on the identified relationship between surgical actions and torque changes, the key points of torque changes, and the overall trends.

[0054] S202. Input the torque change curve graph into the dynamic torque calibrator, perform simulated calibration using the dynamic torque calibrator to simulate the expected value, measure the measured value in real time with a torque sensor, compare the expected value and the measured value, and obtain the difference value.

[0055] Further, set the dynamic torque calibrator to the simulation mode, input the torque change curve graph into the dynamic torque calibrator as the calibration standard, and the calibrator simulates the change of torque according to the set dynamic torque change curve, that is, the expected value. At the same time, use a torque sensor to measure and record the dynamic torque value output by the calibrator in real time. The dynamic torque value measured by the torque sensor in real time is the measured value. Compare the measured value with the expected value one by one, compare the measured value and the expected value at each time point, obtain the difference value between the measured value and the expected value, calculate the average value and standard deviation of the obtained several difference values. The average value reflects the overall level of the difference value, and the standard deviation reflects the fluctuation degree of the difference value.

[0056] S203. Calculate the calibration coefficient according to the obtained difference value.

[0057] Based on the measured value and the expected value obtained in step S202, obtain the relationship between the measured value and the expected value, obtain the calibration coefficient a by calculating the linear relationship between the measured value and the expected value, substitute the obtained calibration coefficient a into the formula y = ax + b, where y is the calibrated measured value, x is the original measured value, a is the calibration coefficient representing the linear relationship between the measured value and the expected value, b is the intercept, and b represents the calibrated measured value when the original measured value is 0. Calculate the intercept b by the least squares method; apply the calculated calibration coefficient to the output end of the torque sensor to calibrate the torque sensor.

[0058] S204. Verify the calculated calibration coefficient, and substitute the verified calibration coefficient into the torque sensor in step S102 for calibration.

[0059] Further, use the calculated calibration coefficient to repeat the simulated calibration process in S202, record the measured value of the torque sensor again, compare it with the expected value, analyze the difference between the measured value and the expected value before and after calibration, and evaluate whether the calibration effect is significant. If the calibration effect is significant, that is, the difference between the measured value and the expected value is significantly reduced, the calibration is successful; if the calibration effect is not ideal, adjust the calibration coefficient according to the evaluation result and repeat this step.

[0060] Substitute the finally obtained calibration coefficient into the torque sensor in step S102, calibrate the torque sensor through the calibration coefficient, and then calibrate the torque parameter. By performing the inverse implementation of Embodiment 1, that is, calibrating the torque parameter through the calibration coefficient, and calibrating the position parameter through the torque parameter obtained by calibration, so that the torque sensor can accurately measure the dynamic torque change, improving the surgical precision and safety.

[0061] The technical solutions in the embodiments of the present application at least have the following technical effects or advantages: improving the dynamic response ability of the torque sensor, enabling it to better adapt to the dynamic torque changes during the operation, improving the accuracy of the torque parameter, helping the surgical robot to more accurately sense and control the interaction force between the surgical instrument and the tissue, enhancing the stability of the surgical robot during the operation, reducing the jitter and deviation during the operation, improving the measurement accuracy of the torque sensor under dynamic torque changes, the calibrated position parameter more accurately reflects the actual motion state of the surgical robot, improving the success rate and safety of the operation. By considering the influence of dynamic torque changes, the measurement accuracy of the torque sensor is significantly improved, which helps the surgical robot to more accurately control the surgical instrument and reduce the errors during the operation. Since the accuracy of the torque parameter and the stability of the surgical robot are improved, the success rate of the operation is also correspondingly increased. This helps to reduce the risk of surgical complications and recurrence and improve the rehabilitation quality of patients.

[0062] Embodiment 3: On the basis of Embodiment 1 and Embodiment 2, when the surgical robot starts to be used, it is easy for the doctor to lose the initial position, resulting in the doctor losing the operating feel. At the same time, during the operation of the surgical robot, the position parameter and the torque parameter are prone to deviation. When the deviation occurs, the operation needs to be stopped to adjust the position of the position parameter and the torque parameter, which greatly affects the efficiency and precision of the operation. In this embodiment, the data fluctuation state when the position parameter and the torque parameter are about to deviate is identified, and an early warning is given for the deviation phenomenon, reducing the number of surgical interruptions caused by parameter deviation.

[0063] As Figure 3 shown, the method for calibrating the position parameter and the torque parameter of the surgical robot according to the historical surgical data of the surgical robot further includes: when the position parameter and the torque parameter are about to deviate, identifying the fluctuation state of the position parameter and the torque parameter at this time, and giving an early warning and performing early calibration on the real-time measured position parameter and torque parameter according to the identified data fluctuation state. The specific method is:

[0064] S301, according to the collected historical data of the surgical robot, identify the data fluctuation state when the position parameter and the torque parameter are about to deviate;

[0065] Furthermore, clean the historical data of the surgical robot, use the Local Outlier Factor to detect the outliers in the data, identify the data points that deviate from the normal range, remove the incorrect data caused by equipment failures, operation mistakes, etc. Finally, verify the cleaned data to ensure the consistency and integrity of the data. Classify and partition the cleaned data according to dimensions such as surgical type, operation time, and robot model.

[0066] The offset state refers to the abnormal changes of these parameters during normal operation. The offset state is manifested as sudden changes in parameters, exceeding the preset normal range, or continuous unstable fluctuations. Sudden change: It means that the parameter changes sharply within a short period of time. This change may be caused by external interference, system failure, or operation mistakes, etc. Calculate the instantaneous change rate of the parameter, that is, the ratio of the difference between the parameter values at adjacent time points to the time interval. Set an instantaneous change rate threshold. When the instantaneous change rate of the parameter exceeds the instantaneous change rate threshold, it is considered that a sudden change has occurred. The instantaneous change rate threshold is set by statistically analyzing the distribution of the instantaneous change rates of historical data or based on business experience; Exceeding the normal range: Each parameter has its normal working range. When the parameter value exceeds this range, it can be considered that an offset has occurred. The normal range can be set according to the statistical characteristics of historical data or business experience. Set a normal value range for each parameter based on historical data or business experience, and monitor the parameter value in real time. When the parameter value exceeds this normal range, it is considered that an offset has occurred; Continuous unstable fluctuation: It means that the parameter fluctuates continuously within a period of time, and the fluctuation amplitude is large and cannot remain stable. This kind of fluctuation may be caused by the instability of the system or the continuous influence of the external environment. Calculate the fluctuation amplitude of the parameter within a time window, that is, the difference between the maximum value and the minimum value of the parameter value. Set a fluctuation amplitude threshold. When the fluctuation amplitude of the parameter exceeds this threshold, it is considered that a continuous unstable fluctuation has occurred. The threshold of the fluctuation amplitude should be set based on the statistical characteristics of historical data and business requirements; For the above three cases of the offset state, as long as one condition is met, it is considered that the position parameter and the torque parameter have an offset.

[0067] Based on the recognition result of the offset state, determine the specific time points when the position parameters and torque parameters deviate. Considering the actual requirements and data characteristics comprehensively, determine the length of the time window. This length should be long enough to capture the complete process of parameter fluctuations, but not too long to include too much irrelevant information. According to the determined time window length, intercept the data segments of the position parameters and torque parameters within the time range before the offset point; The fluctuation state is a specific pattern or behavior exhibited by the parameters as they change over time, which may reflect the internal dynamic changes of the system or external environmental disturbances. According to the intercepted data segments, use clustering analysis to identify abnormal fluctuations, that is, identify the fluctuation state. Extract the characteristics of the fluctuation state based on the identified fluctuation state, find the maximum and minimum values within the fluctuation state, and then calculate the difference between the two to calculate the fluctuation amplitude. Determine the start and end time points of the fluctuation state, and calculate the time difference between these two points to extract the duration feature. Identify the frequency components of the fluctuation through spectral analysis methods, and store the data fluctuation state when the above-mentioned identified position parameters and torque parameters are about to deviate.

[0068] S302. Use a real-time monitoring system to monitor the position parameters and torque parameters in real time. When the real-time monitoring system detects that the data fluctuation state of the real-time position parameters and torque parameters meets the warning standard, give a warning and perform calibration;

[0069] Specifically, the warning standard is that the similarity between the real-time position parameters and torque parameters and the data fluctuation state when the position parameters and torque parameters are about to deviate is greater than the similarity threshold. Among them, the similarity threshold is set based on experience. The monitoring system monitors the position parameters and torque parameters of the surgical robot in real time. When the parameter changes meet the warning standard, the system immediately issues a warning signal and prepares to execute the calibration program. The calibration program is described in detail in Embodiment 1 and Embodiment 2 and will not be elaborated here.

[0070] S303. Divide the offset-sensitive area and non-offset-sensitive area according to the historical data of the surgical robot and the identified offset state;

[0071] Furthermore, based on the historical data and offset state, set the fluctuation thresholds for the position parameters and torque parameters. The setting of the fluctuation thresholds is based on statistical methods, empirical rules or expert opinions. When the fluctuation of the position parameters or torque parameters is greater than or equal to the set fluctuation threshold, divide this area or time period into the offset-sensitive area; otherwise, divide it into the non-offset-sensitive area. When the surgical robot runs into the offset-sensitive area, the system needs to pay key attention and perform calibration in advance to prevent parameter offset from affecting the surgical efficiency and accuracy.

[0072] The technical solutions in the embodiments of the present application at least have the following technical effects or advantages: improving the calibration pertinence of the surgical robot, reducing the adjustment time caused by parameter deviation during the operation, improving the operation efficiency and accuracy, ensuring the smooth progress of the operation, reducing the number of operation interruptions by pre-calibration and focusing on the offset-sensitive area. Assuming that each adjustment in the first solution takes T minutes, the second solution reduces the number of adjustments through some improvements but still requires adjustments, and the third solution further reduces the number of adjustments to almost zero (or very low frequency), then the total operation time can be significantly shortened. Real-time monitoring and pre-calibration ensure that the surgical robot always maintains accurate position, attitude and torque parameters, reducing operation errors. Assuming that the operation error rate of the first solution is E1%, the second solution reduces it to E2% through some means, and the third solution further reduces it to E3% (E3 < E2 < E1) through real-time monitoring and calibration. By reducing parameter deviation and the number of adjustments, doctors can perform surgical operations more smoothly, improving the operation experience and feel.

[0073] Embodiment 4: Based on the first three embodiments, collect and calibrate the position parameters and torque parameters and perform early warning calibration. The magnitudes and directions of the changes in the position parameters and torque parameters are random. The above three embodiments all describe the calibration of the magnitudes of the changes in the position parameters and torque parameters. In this embodiment, the calibration of the directions of the position parameters and torque parameters is added.

[0074] As Figure 4 shown, the method for calibrating the position parameters and torque parameters further includes calibrating the directions of the position parameters and torque parameters. Specifically:

[0075] S401, collect surgical historical data, where the surgical historical data includes the magnitudes and directions of the changes in the position parameters and torque parameters, and calculate the magnitude calibration factor and the direction calibration factor according to the historical data;

[0076] Furthermore, according to the calibration of the magnitudes of the position parameters and torque parameters in Embodiments 1 to 3, use statistical functions (such as mean, standard deviation adjustment functions, etc.) to calculate the mean and standard deviation of the position parameters and torque parameters in the above embodiments, and then calculate the magnitude calibration factor through the mean and standard deviation. The magnitude calibration factor is usually used to adjust the magnitude of the parameter change to ensure the accuracy of calibration. The formula is: , where is an adjustment coefficient that can be determined according to experiments, is the mean, is the standard deviation, and the mean and standard deviation are obtained by calculating the collected position parameters or torque parameters; the direction calibration factor is used to identify and adjust the direction of the parameter change. It can be calculated through a direction recognition function according to the direction characteristics of the parameter change. The formula is: , where is the average direction change amount, is the sign function, used to represent the positive or negative value of a numerical value.

[0077] S402. Calculate the calibration parameter according to the calculated size calibration factor and direction calibration factor, and use the calibration parameter to calibrate the position parameter and the torque parameter;

[0078] Calculate the calibration parameter using the size calibration factor and the direction calibration factor. The formula is: calibration parameter = (original parameter × size calibration factor) × direction calibration factor. Use the calibration parameter to calibrate the position parameter and the torque parameter, so that the calibrated parameter is closer to the true value.

[0079] The technical solution in the embodiment of the present application at least has the following technical effects or advantages: By introducing the direction calibration factor, the calibration of the position parameter and the torque parameter is made more accurate and targeted. Through direction calibration, the calibration error caused by the wrong direction is reduced, so that the calibrated parameter is closer to the true value. Assuming that the original calibration error is ±5%, after introducing direction calibration, the error may be reduced to ±2% or lower. Direction calibration enables the system to better adapt to the randomness of parameter changes, especially in a dynamic environment. By introducing direction calibration, the calibration accuracy and the overall performance of the system are further improved.

[0080] Embodiment Five: The orthopedic surgical robot calibration device includes: a position sensor module, a data acquisition and processing module, a torque sensor module, a torque calibration module, an identification and warning module, and a calculation module. The position sensor module is used to detect the specific position of the end effector of the surgical robot on the X, Y, and Z axes in real time. Usually, high-precision sensors such as laser rangefinders are used to ensure the accuracy and real-time of data acquisition; the data acquisition and processing module is used to set the data acquisition frequency to ensure that the data acquisition frequency is greater than the movement frequency of the surgical robot to avoid data loss; preprocess the original data, such as denoising, filtering, etc.; the torque sensor module is used to record the torque parameters received by the surgical instrument in real time; the torque calibration module is used to calibrate the collected torque parameters according to the calibrated position parameters and simulate the dynamic torque change, and perform dynamic calibration on the torque sensor to reduce the error of surgical instrument operation; the identification and warning module is used to identify the data fluctuation state when the position parameter and the torque parameter are about to deviate, and give a warning and perform pre-calibration; the calculation module is used to calculate the size calibration factor and the direction calibration factor according to the historical data for calibrating the position parameter and the torque parameter, and calculate the calibration parameter according to the size calibration factor and the direction calibration factor to calibrate the position parameter and the torque parameter.

[0081] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for calibrating an orthopedic surgical robot, characterized in that: include: S101, using a position sensor to obtain a real-time position of an end actuator, comparing the obtained real-time position of the end actuator with an initial position of the end actuator set at the factory, and then calibrating the real-time position of the end actuator to obtain a calibrated position parameter; S102, using a torque sensor to collect torque parameters of the end actuator, and calibrating the collected torque parameters according to the calibrated position parameters; According to the obtained calibrated position parameters, a torque correction model is established, and the torque correction model has the formula: ,in, is the acquired torque, is the torque obtained by correcting the position parameters, It is the torque adjustment calculated based on the corrected position parameters. The torque adjustment ΔM is the position calibration value. A linear function, that is: ΔM= ,in, , is the linear coefficient, determined based on empirical data, and is the position parameter after calibration, and is the real-time position parameter collected; S103, adjusting the initial position of the surgical instrument according to the calibrated position parameters, and adjusting the force condition of the surgical instrument according to the calibration data of the torque.

2. The orthopedic surgical robot calibration method according to claim 1, characterized in that: The method for calibrating the torque parameters also includes: S201, based on the historical surgical data of the surgical robot, obtain the relationship between the surgical action and the torque change, identify the key points and overall trend of the torque change through the relationship between the surgical action and the torque change, and draw a torque change curve according to the relationship between the surgical action and the torque change, the key points and overall trend of the torque change; S202, inputting the torque change curve into a dynamic torque calibrator, using the dynamic torque calibrator to perform simulation calibration, simulating an expected value, using a torque sensor to measure in real time to obtain a measured value, comparing the expected value with the measured value, and obtaining a difference value; S203, calculating a calibration coefficient according to the obtained difference value; S204, verifying the calculated calibration coefficient, and substituting the verified calibration coefficient into the torque sensor in step S102 for calibration.

3. The orthopedic surgical robot calibration method according to claim 2, characterized in that: Set the dynamic torque calibrator to simulation mode, input the torque change curve into the dynamic torque calibrator as the calibration standard, and the calibrator simulates the change of torque according to the set dynamic torque change curve, that is, the expected value. At the same time, use the torque sensor to measure, and record the dynamic torque value output by the torque sensor real-time measurement calibrator. The dynamic torque value of the torque sensor real-time measurement calibrator is the measured value. Compare the measured value with the expected value one by one, compare the measured value and the expected value at each time point, and get the difference between the measured value and the expected value.

4. The orthopedic surgical robot calibration method according to claim 2, characterized in that: The calibration coefficient a is obtained by calculating the linear relationship between the measured value and the expected value, and the obtained calibration coefficient a is substituted into the formula y=ax+b, where y is the calibrated measured value, x is the original measured value, a is the calibration coefficient, which represents the linear relationship between the measured value and the expected value, and b is the intercept.

5. The orthopedic surgical robot calibration method according to claim 2, characterized in that: The method for calibrating the position parameters and torque parameters of the surgical robot according to the historical surgical data of the surgical robot also includes: when the position parameters and torque parameters are about to deviate, the fluctuation state of the position parameters and torque parameters at this time is identified, and the real-time measured position parameters and torque parameters are warned and calibrated in advance according to the identified data fluctuation state. The specific method is: S301, identifying the data fluctuation state when the position parameter and the torque parameter are about to be offset according to the collected historical data of the surgical robot; S302, using a real-time monitoring system to monitor the position parameters and torque parameters in real time, and when the real-time monitoring system detects that the data fluctuation state of the real-time position parameters and torque parameters meets the warning standard, an early warning is issued and calibration is performed; S303, dividing the deviation-sensitive area and the non-deviation-sensitive area according to the historical data of the surgical robot and the identified data fluctuation state.

6. The orthopedic surgical robot calibration method according to claim 5, characterized in that: The offset state is an abnormal change in the parameters during normal operation. The offset state is manifested as a sudden change in the parameters, exceeding the preset normal range, or continuous unstable fluctuations.

7. The orthopedic surgical robot calibration method according to claim 5, characterized in that: The method for calibrating the position parameters and the torque parameters also includes calibrating the directions of the position parameters and the torque parameters, specifically: S401, collect surgical history data, the surgical history data includes the change size and direction of position parameters and torque parameters, and calculate the size calibration factor and direction calibration factor based on the historical data: S402, calculating calibration parameters according to the calculated size calibration factor and direction calibration factor, and using the calibration parameters to calibrate the position parameters and the torque parameters.

8. An orthopedic surgical robot calibration device, applied to the orthopedic surgical robot calibration method according to any one of claims 1 to 7, characterized in that: include: A position sensor module, a data acquisition and processing module, a torque sensor module, a torque calibration module, an identification and warning module and a calculation module. The position sensor module and the torque sensor module are arranged on the end actuator of the surgical robot. The position sensor module and the torque sensor module are both provided with a data acquisition and processing module. The torque calibration module is electrically connected to the torque sensor module.

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