An operating table position adjustment optimization control method for CT puncture operating platform

Abstract

The present invention provides an operating table position adjustment optimization control method for a CT puncture operating platform, which relates to the field of intelligent control technology. The method comprises performing a sensor scan on an operator, determining a three-dimensional posture point cloud, constructing an analog regulator in a coaxial coordinate system, performing a simulated decision analysis on the three-dimensional posture point cloud under a double-step adjustment, determining an objective adjustment strategy, determining a feed amount of a micro-motor group based on a control mode of the CT puncture operating platform, and performing position control on the operating table. The method is used to solve the technical problems in the prior art of insufficient intelligence in operating table control and adjustment, inability to realize personalized adjustment of operators and adaptive adjustment of operation processes, resulting in poor real-time and accuracy of operating table adjustment, and can effectively improve the personalization and personnel adaptability of operating table position adjustment, and ensure the immediacy of adjustment response and adjustment effect.

Description

Technical Field

[0001] The present invention relates to the field of intelligent control technology, and in particular to a method for optimizing the position adjustment of an operating table for a CT puncture operating platform. Background Art

[0002] As an important auxiliary equipment, CT puncture operation platform is widely used in the medical field. Traditional CT puncture operation platform mostly relies on manual adjustment and lacks flexibility and precision, which may cause operators to have uncomfortable posture, low operating efficiency and even affect operating accuracy during long operations.

[0003] At present, with the introduction of intelligent operating table adjustment systems, improvements have been made to a certain extent, but existing methods mostly rely on simple preset adjustment algorithms and are mostly limited to static body shapes or simple coordinate systems. Especially in high-precision CT puncture operations, any slight error may affect the effect.

[0004] In summary, the existing technology still has the problem of insufficient intelligence in the control and adjustment of the operating console, and is unable to achieve personalized adjustment of operators and adaptive adjustment of the operation process, resulting in technical problems such as poor real-time and accuracy of the operating console adjustment. Summary of the invention

[0005] The present application provides an operating table position adjustment optimization control method for a CT puncture operating platform, which is used to solve the technical problems in the prior art of insufficient intelligence of operating table control adjustment, inability to achieve operator personalized adjustment and adaptive adjustment of the operation process, resulting in poor real-time and accuracy of operating table adjustment.

[0006] In view of the above problems, the present application provides an operating table position adjustment optimization control method for a CT puncture operating platform.

[0007] The present application provides an operating table position adjustment optimization control method for a CT puncture operating platform, which specifically includes: performing a sensor scan on an operator to determine a three-dimensional posture point cloud, wherein the three-dimensional posture point cloud is a key position point cloud; calling historical adjustment records, mining posture adjustment relationships under ergonomics, and constructing an analog regulator under a coaxial coordinate system, wherein the posture adjustment relationship includes a first fixed relationship based on the operator's body shape and a second linear relationship based on the operator's posture; receiving the three-dimensional posture point cloud, combining the analog regulator to perform simulated decision analysis under double-step adjustment, and determining an objective adjustment strategy; obtaining a control mode of the CT puncture operating platform, identifying the objective adjustment strategy and performing motion process decomposition to determine the feed amount of a micromotor group, wherein the control mode is cooperative control of the micromotor group; and adjusting the position of the operating table based on the feed amount of the micromotor group.

[0008] Furthermore, the simulated decision analysis under two-step adjustment is performed in combination with the simulated regulator, including: identifying the three-dimensional posture point cloud to determine the body characteristics of the operator; based on the body characteristics, overall adjustment is performed based on the first fixed relationship to define implicit adjustment standards, wherein the implicit adjustment standard is the baseline standard of the operator under the operation cycle, which is the relative state of the operator's position with the operating table under the standard posture; fixing the implicit adjustment standard under the operation cycle, performing three-dimensional posture point cloud restoration and simulated adjustment based on the second linear relationship for the key position point cloud, and determining the objective adjustment strategy.

[0009] Furthermore, the three-dimensional posture point cloud restoration and simulation adjustment based on the second linear relationship include: identifying the three-dimensional posture point cloud and performing simulation restoration, measuring posture variables, wherein the posture variables include the spatial migration amount of each key position point cloud; based on the second linear relationship, calculating the adjusted spatial position and adjustment angle of the operating console under the posture variables and performing simulation verification; integrating the spatial position and adjustment angle as the objective adjustment strategy.

[0010] Furthermore, after measuring the posture variables, it includes: setting a posture trend change threshold, which is a critical constraint value for measuring the posture variables; identifying the posture variables, and if the posture variables are greater than or equal to the posture trend change threshold, generating a position adjustment instruction; if the posture variables are less than the posture trend change threshold, performing superimposed supervision of the posture variables.

[0011] Furthermore, determining the feed amount of the micromotor group includes: identifying the control mode and determining the motor control logic, wherein the motor control logic includes the relative amplitude modulation relationship between the rotation speed of each micromotor and the control target; based on the control target, disassembling the objective adjustment strategy and determining the sub-control strategy, wherein each sub-control strategy corresponds to the micromotor group one by one; based on the motor control logic, calculating the feed amount of each micromotor under the sub-control strategy, and performing collaborative identification of the time dimension and the space dimension.

[0012] Furthermore, after determining the feed amount of the micromotor group, it includes: based on a digital-to-analog conversion interface, converting the feed amount to determine analog adjustment information, wherein the digital-to-analog conversion interface performs bidirectional conversion between digital quantity and analog quantity; the micromotor group responds to the analog adjustment information to perform position control of the operating table.

[0013] Furthermore, after determining the objective adjustment strategy, it includes: triggering a subjective feature library by identifying the operator's number, and the subjective feature library is built into the simulation regulator; traversing the subjective feature library, matching the three-dimensional posture point cloud, and determining the operating habit characteristics; based on the operating habit characteristics, compensating the objective adjustment strategy.

[0014] Furthermore, a subjective feature library is constructed, including: obtaining the adjustment records of the operator and storing them in a temporary database, which is periodically updated; mining the operator's operating habits based on the temporary database; and performing incremental learning on the analog regulator based on the operator's operating habits to generate a subjective feature library, wherein the subjective feature library is marked with an operator number.

[0015] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0016] The embodiment of the present application provides an operating table position adjustment optimization control method for a CT puncture operating platform, which performs a sensor scan on an operator, determines a three-dimensional posture point cloud, calls historical adjustment records, mines an ergonomic posture adjustment relationship, and constructs an analog regulator in a coaxial coordinate system, wherein the posture adjustment relationship includes a first fixed relationship based on the operator's body shape and a second linear relationship based on the operator's posture; receives the three-dimensional posture point cloud, and performs a simulated decision analysis under a two-step adjustment in combination with the analog regulator to determine an objective adjustment strategy; obtains a control mode of the CT puncture operating platform, identifies the objective adjustment strategy and performs motion process decomposition, determines the feed amount of a micro-motor group, and performs position control of the operating table, which is used to solve the technical problems of insufficient intelligence of operating table control and adjustment in the prior art, inability to realize personalized adjustment of operators and adaptive adjustment of operation processes, resulting in poor real-time and accuracy of operating table adjustment, and can effectively improve the personalization and personnel adaptability of operating table position adjustment, and ensure the immediacy of adjustment response and adjustment effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A schematic diagram of a process flow of an operating table position adjustment optimization control method for a CT puncture operating platform is provided for this application;

[0018] Figure 2 A schematic diagram of a simulation decision analysis process under double-step adjustment in a method for optimizing control of operating table position adjustment for a CT puncture operating platform is provided for this application. DETAILED DESCRIPTION

[0019] The present application provides an operating table position adjustment optimization control method for a CT puncture operating platform, performs sensor scanning on the operator, determines a three-dimensional posture point cloud, constructs a simulation regulator in a coaxial coordinate system, performs simulated decision analysis on the three-dimensional posture point cloud under double-step adjustment, determines an objective adjustment strategy, determines the feed amount of a micromotor group based on a control mode of the CT puncture operating platform, and performs position control of the operating table. The method is used to solve the technical problems existing in the prior art of insufficient intelligence in operating table control and adjustment, inability to achieve personalized adjustment of the operator and adaptive adjustment of the operation process, resulting in poor real-time and accuracy of operating table adjustment.

[0020] Example: Figure 1 As shown, the present application provides an operating table position adjustment optimization control method for a CT puncture operating platform, the method comprising:

[0021] S1: Performing a sensor scan on the operator to determine a three-dimensional posture point cloud, wherein the three-dimensional posture point cloud is a key position point cloud;

[0022] In the embodiment of the present application, sensors installed around the operating table, such as infrared sensors, depth cameras, etc., are used to scan the operator's body in real time. The sensors capture the operator's posture and convert it into three-dimensional point cloud data to collect the position data of key parts in three-dimensional space.

[0023] Specifically, a spatial distribution consisting of multiple three-dimensional coordinate points that can measure the operator's posture is used as the three-dimensional posture point cloud, wherein each point cloud represents the position of a key part of the operator's body in the three-dimensional space. Preferably, in order to improve the calculation speed, invalid point cloud distribution is screened out, and the point cloud distribution of the parts related to the working posture during the operation is retained, specifically the position data of the parts that have an important impact on the operation accuracy, comfort or safety during the operation, as the key position point cloud. For example, the key positions may include the head, shoulders, hands, waist and other positions.

[0024] Through sensor scanning, the actual working posture of the operator can be accurately acquired and converted into a spatial point position distribution based on key positions as the three-dimensional posture point cloud.

[0025] Preferably, the three-dimensional posture point cloud contains the static and dynamic position information of the operator, and the three-dimensional posture point cloud is used as the basis for subsequent personalized adjustment of the operating console. The determination of the key position point cloud lays a solid foundation for the personalization and precision of the entire adjustment process.

[0026] S2: calling historical adjustment records, mining the posture adjustment relationship under ergonomics, and constructing a simulation regulator under a coaxial coordinate system, wherein the posture adjustment relationship includes a first fixed relationship based on the operator's body shape and a second linear relationship based on the operator's posture;

[0027] Specifically, the historical adjustment record includes adjustment data between the position of the operating console and the posture of the operator in scenarios such as operators of different body sizes and different postures and operating tasks.

[0028] In an embodiment of the present application, the position adjustment of the CT puncture operating platform is divided into two stages, including a first fixed relationship based on the operator's body shape and a second linear relationship based on the operator's posture. Specifically, the first fixed relationship refers to the relative position relationship between the operating table and the operator under a specific body shape. For example, for operators with taller or shorter bodies, the adjustment standard of the operating table is different, that is, no matter how the posture changes, the position adjustment of the operating table will maintain a predetermined fixed ratio, wherein the first fixed relationship includes adjustment standards under a variety of personnel body shapes.

[0029] The second linear relationship refers to the linear change relationship between the position of the console and the dynamic posture of the operator when the operator's posture changes. For example, when the operator's shoulder position changes, the adjustment amount of the console also changes linearly. The adjustment amount of the console can be accurately calculated based on the angle and coordinates of the posture change.

[0030] For example, for a taller operator, the first fixed relationship may require the basic height of the operating table to be increased, and the fixed adjustment ratio to be increased. On this basis, the second linear relationship will linearly calculate the adjustment requirements for the height and angle of the operating table when the upper limbs move or turn. That is, the analog regulator can automatically adjust the height and angle of the operating table in real time according to the operator's body shape and posture changes.

[0031] Next, the coaxial coordinate system refers to combining the posture data of the operating table and the operator in a unified coordinate system, which usually includes three axes (X, Y, and Z axes), which respectively represent the horizontal position, vertical position, and depth position in space. Based on the coaxial coordinate system, the simulation regulator is constructed based on the first fixed relationship and the second linear relationship as the adjustment basis, and the simulation regulator is further supervised and trained based on the historical adjustment records to improve the convergence of the adjustment decision. The simulation regulator can accurately reflect the operator's demand changes for the position of the operating table under different postures, generate an adjustment strategy based on the above relationship, and provide a decision-making basis for the precise adjustment of the operating table.

[0032] S3: receiving the three-dimensional posture point cloud, and performing simulation decision analysis under double-step adjustment in combination with the simulation regulator to determine an objective adjustment strategy;

[0033] First, the three-dimensional posture point cloud is received, that is, obtained by sensor scanning, representing the distribution of key position points of the operator in the three-dimensional space. The three-dimensional posture point cloud is input into the simulation regulator for analysis and processing. The two-step adjustment is an operation standard adjustment based on the first fixed relationship and a posture point cloud migration adjustment based on the second linear relationship.

[0034] Specifically, the body features of the operator are determined by identifying the three-dimensional posture point cloud, and matching is performed based on the first fixed relationship to determine the adjustment standard of the operating table during the entire operation cycle of the current operator. For example, the adjustment standard of the operating table is different for operators with taller or shorter bodies, that is, no matter how the posture changes, the position adjustment of the operating table for operators of different body sizes will be maintained at a predetermined fixed ratio corresponding to the body size.

[0035] Furthermore, on the basis of the above adjustment, that is, based on the results of the first step analysis, the second step of the two-step adjustment is performed. Specifically, according to the three-dimensional posture point cloud of the operator, that is, the specific data of the posture change, the adjustment direction and adjustment scale of the operating table are decided in combination with the second linear relationship, and the objective adjustment strategy is determined, that is, the adjustment strategy determined based on the operator's body shape standard and posture change, that is, the adjustment strategy including parameters such as the position coordinates, angle and movement amount of the operating table. Among them, the second step of the two-step adjustment emphasizes real-time and adaptability. The system can quickly respond to slight changes in the operator's posture and automatically adjust the position, angle and height of the operating table, thereby ensuring that the operator always maintains a comfortable and ergonomic working posture.

[0036] Based on this objective adjustment strategy, the operating table is automatically adjusted to ensure that the operator is in the best working posture, thereby ensuring operating accuracy and comfort.

[0037] Further, such as Figure 2 As shown, in combination with the analog regulator, the analog decision analysis under the double-step adjustment is performed, and step S3 includes:

[0038] Identify the three-dimensional posture point cloud and determine the body features of the operator; based on the body features, make overall adjustments based on the first fixed relationship and define implicit adjustment standards, wherein the implicit adjustment standard is the baseline standard of the operator during the operation cycle, which is the relative position of the operator with respect to the operating table in the standard posture; fix the implicit adjustment standard during the operation cycle, perform three-dimensional posture point cloud restoration and simulated adjustment based on the second linear relationship for the key position point cloud, and determine the objective adjustment strategy.

[0039] In an embodiment of the present application, the three-dimensional posture point cloud is identified to determine the physical characteristics of the operator, such as body parameters such as height, shoulder width, and arm length. Then, based on the physical characteristics, the operating table is adjusted as a whole through the first fixed relationship. For example, if the operator is taller, the initial position of the operating table may need to be raised accordingly, and the proportion of the adjustment scale under the same posture migration degree under shoulder width and arm length is correspondingly larger. The adjustment standard based on the first fixed relationship is used as the implicit adjustment standard, and the subsequent posture adjustment is the adjustment based on the implicit adjustment standard.

[0040] Exemplarily, a reference posture, such as standing, sitting or a specific operating posture, can be determined as the standard posture, and the relative position of the standard posture and the operating table can be used as the baseline, and the adjustment ratio under different posture migration degrees can be determined, such as, the joint migrates a first spatial distance, and the operating table correspondingly adjusts a second spatial distance, and the ratio of the first distance to the second distance is used as the baseline adjustment standard.

[0041] Furthermore, the implicit adjustment standard is fixed, and under this adjustment standard, an adjustment decision of posture change is made to ensure that the position of the operating table always remains in a relatively ideal position during the entire operation cycle. Specifically, after that, the system will perform point cloud posture restoration and simulation adjustment for the data of the key position point cloud. Point cloud posture restoration refers to the distributed simulation of the three-dimensional posture point cloud in the simulation regulator, based on the migration amount of each posture point cloud, based on the second linear relationship, that is, the linear mapping relationship between the operator's posture change and the operating table position adjustment, that is, adjusting the constraints in units of the baseline adjustment standard, and determining the operating table adjustment strategy under the migration amount, that is, under the personalized standard of body shape characteristics, an objective adjustment strategy for real-time posture changes, including the adjustment of parameters such as the height and angle of the operating table, to ensure that the operating table always remains in the optimal position during the entire operation process.

[0042] Furthermore, the three-dimensional posture point cloud restoration and the simulation adjustment based on the second linear relationship, step S3 includes:

[0043] Identify the three-dimensional posture point cloud and perform simulation restoration to measure posture variables, wherein the posture variables include the spatial migration amount of each key position point cloud; based on the second linear relationship, calculate the adjusted spatial position and adjustment angle of the operating table under the posture variable and perform simulation verification; integrate the spatial position and adjustment angle as the objective adjustment strategy.

[0044] The three-dimensional posture point cloud refers to the point cloud data of the operator's key position in space obtained by the sensor. These data contain the positions of the operator's body parts in the three-dimensional space, and identify the operator's current posture, including the spatial relationship between the body parts and the relative position based on the console. Based on the three-dimensional posture point cloud, point cloud distribution simulation is performed, that is, the posture in the actual operation process, which is convenient for simulation analysis.

[0045] Among them, the posture variable is the spatial migration amount of each key position point cloud in the three-dimensional posture point cloud relative to the previous moment. The spatial migration amount refers to the spatial offset of a certain part of the operator's body (such as shoulders, hands, etc.) compared to the posture at the previous moment.

[0046] The posture variable is used as the adjustment target, and based on the second linear relationship, the adjustment spatial position and adjustment angle of the operating table are calculated. The second linear relationship refers to the linear relationship between the posture change of the operator and the adjustment of the operating table. Based on the implicit adjustment standard based on the first fixed relationship, the posture variable of the operator, that is, the spatial migration amount, is converted into a specific operating table adjustment requirement. For example, for shoulder tilt, the unit amplitude modulation is determined by the implicit adjustment standard, and the specific parameters that the operating table needs to adjust in the tilt direction are calculated according to the second linear relationship to adapt to the new working posture.

[0047] After calculating the adjustment space position and adjustment angle, simulation verification is performed. That is, the relative position of the adjusted console position and the three-dimensional posture point cloud in the coaxial coordinate system is verified to determine whether the console adjustment plan meets the actual needs. If it is determined to be the best adjustment position, the adjustment strategy will be considered valid, and the currently determined adjustment space position and adjustment angle will be used as the objective adjustment strategy.

[0048] The operating console can dynamically respond to the operator's posture changes, ensuring that it is always in the optimal working state, reducing operator fatigue, and improving operator comfort and efficiency.

[0049] Further, after measuring the posture variables, step S3 includes:

[0050] A posture trend change threshold is set, where the posture trend change threshold is a critical constraint value for measuring posture variables; the posture variable is identified, and if the posture variable is greater than or equal to the posture trend change threshold, a position adjustment instruction is generated; if the posture variable is less than the posture trend change threshold, superimposed supervision of the posture variable is performed.

[0051] In the embodiment of the present application, the posture trend change threshold refers to the critical constraint value used to measure the change of posture variables, and is mainly used to determine whether the posture change of the operator has reached the degree that requires adjustment. Specifically, the posture trend change threshold is a preset numerical value, which is used as a judgment standard to mark what degree of posture change is significant and requires adjustment of the operating table. For example, if the displacement of key parts such as shoulders and arms of the operator exceeds the threshold during the operation, it means that his working posture has changed significantly, and the operating table should be adjusted accordingly. Through the constraint of the posture trend change threshold, frequent redundant adjustments are avoided, so that the position adjustment of the operating table meets the compound demand.

[0052] The posture variable is checked against the posture trend threshold, and if the posture variable is greater than or equal to the set trend threshold, the system will generate a position adjustment instruction. Specifically, when the operator's posture change reaches or exceeds the threshold, it means that the operating table needs to be adjusted accordingly to ensure that the operator can continue to maintain a comfortable and ergonomic working posture. For example, if the operator raises his arm to a certain height and this change exceeds the set threshold, a position adjustment instruction is automatically generated, instructing the operating table to make corresponding adjustments in the vertical direction, such as raising or rotating, so that the operator can continue to operate in the new posture.

[0053] If the posture variable is less than the posture change threshold, the system enters the superposition supervision mode. In this case, although the change of the posture variable has not reached the level that requires immediate adjustment of the console, that is, no adjustment is made at present, the operator's posture change will continue to be monitored and superimposed supervision will be performed on it, that is, the next multiple small posture changes will be cumulatively monitored until the total posture change reaches the set threshold, and then the position of the console will be adjusted. This helps to avoid frequent small adjustments and ensure the timeliness and effectiveness of the adjustments.

[0054] In summary, the timing and frequency of operating table adjustment are optimized, unnecessary operating table adjustments are reduced, and at the same time, it is ensured that the operator always maintains the best ergonomic working state.

[0055] Further, after determining the objective adjustment strategy, step S3 includes:

[0056] By identifying the operator's number, a subjective feature library is triggered, and the subjective feature library is built into the simulation regulator; the subjective feature library is traversed to match the three-dimensional posture point cloud to determine the operating habit characteristics; based on the operating habit characteristics, the objective adjustment strategy is compensated.

[0057] Specifically, by identifying the operator's number, determining and activating the subjective feature library that conforms to the operator's operating habits, and making targeted adjustments based on the operator's habits, the user's adaptability is improved. The operator's number refers to a unique identifier assigned to each operator, such as a combination of numbers or letters, which is used to distinguish different operators so that personalized operating data related to them can be accurately called.

[0058] The subjective feature library is a database that stores the individual habits and preference characteristics of operators. One operator corresponds to one subjective feature library, which is built into the analog regulator. By identifying the operator's number, the personalized habits of the operator are found and obtained, such as the preferred initial position, adjustment frequency, and operation angle of the console, so as to optimize the console adjustment strategy according to personal characteristics.

[0059] The operation habit characteristics, that is, the personalized operation characteristics of the operator in the current posture, are determined by traversing the subjective feature library and matching the three-dimensional posture point cloud.

[0060] Once the operating habit characteristics are determined, the objective adjustment strategy is compensated. Each operator's habits and preferences may be different from the universal adjustment solution. Through habit compensation, the control station adjustment solution is ensured to match the operator's personalized needs. For example, if the system finds that an operator is accustomed to a lower operating table height when working, the control station is set to a position more suitable for the operator based on the objective adjustment strategy, thereby improving comfort and operating accuracy.

[0061] Furthermore, a subjective feature library is constructed, and step S3 includes:

[0062] The adjustment record of the operator is obtained and stored in a temporary database, which is updated periodically; based on the temporary database, the operator's operating habits are mined; based on the operator's operating habits, the analog regulator is incrementally learned to generate a subjective feature library, wherein the subjective feature library is marked with the operator number.

[0063] Specifically, the adjustment record refers to all adjustment operations made by the operator in the process of using the operating platform, including the position adjustment, angle adjustment and other changes that may affect the working posture of the operating platform, and is stored in a temporary database. The temporary database will regularly update the adjustment record to adapt to the operator's habitual adjustments, ensuring that the data in the database reflects the latest operating habits and preferences.

[0064] Furthermore, based on the temporary database, the system will mine the operating habits of personnel, that is, the regular operating behaviors formed by operators in the process of using the operating platform, and through record identification, extract the operating methods and operating characteristics frequently performed by operators within a period of time as the operating habits of the personnel.

[0065] Based on the operator's operating habits, the analog regulator is incrementally learned so that the analog regulator can gradually adjust and improve its adjustment strategy to adapt to the operator's changing operating habits. For example, if the operator's adjustment records show that they gradually get used to adjusting the angle of the console more frequently, incremental learning will enable the analog regulator to understand this change and automatically increase the frequency of angle adjustment, thereby responding to the operator's needs more accurately.

[0066] For different operators, corresponding subjective feature libraries are constructed. And the association between the subjective feature library and the operator code is established to ensure that the personalized needs of different operators can be accurately distinguished. In summary, by continuously learning and adapting to the personalized needs of operators, the adjustment plan of the operating console can be optimized according to the behavioral habits of operators.

[0067] S4: acquiring the control mode of the CT puncture operation platform, identifying the objective adjustment strategy and performing motion process decomposition, and determining the feeding amount of the micro-motor group, wherein the control mode is the coordinated control of the micro-motor group;

[0068] S5: Based on the feed amount of the micro-motor group, the position of the operating table is controlled.

[0069] In the embodiment of the present application, the control mode is the coordinated control of the micro-motor group, that is, multiple micro-motors work in coordination to achieve precise motion control of the operating table position. For example, the position adjustment of the operating table may require multiple micro-motors to control different parts of the platform separately, such as lifting, rotating, etc.

[0070] Identify the objective adjustment strategy and decompose the motion process. Determine the target position, target angle, and required motion mode of the operating table according to the objective adjustment strategy. Decompose the motion process of the operating table, specifically decompose the overall operating table adjustment requirements into multiple sub-processes. Each sub-process involves the adjustment of a certain part or dimension of the operating table. For example, depending on the control type of the micromotor, the height, angle, etc. of the operating table need to be considered separately and accurately adjusted one by one.

[0071] According to the disassembled motion process, the feed amount of each micromotor is determined. The feed amount refers to the specific measurement that each micromotor needs to adjust when performing adjustments, such as speed adjustment. For example, if the operating table needs to rise 10 centimeters, the corresponding type of micromotor needs to provide a certain feed amount to enable the platform to complete the 10-centimeter rise and fall. That is, the objective adjustment strategy for adjusting the position of the operating table is converted into a corresponding control structure, that is, the motion control parameters of the micromotor group, and based on the coordinated control of the micromotor group, the position adjustment control of the operating table is realized.

[0072] Furthermore, the step S4 of determining the feeding amount of the micro-motor group includes:

[0073] The control mode is identified and the motor control logic is determined, wherein the motor control logic includes the relative amplitude modulation relationship between the rotation speed of each micromotor and the control target; based on the control target, the objective adjustment strategy is disassembled to determine the sub-control strategy, wherein each sub-control strategy corresponds to a micromotor group one by one; based on the motor control logic, the feed amount of each micromotor under the sub-control strategy is calculated, and the time dimension and the space dimension are collaboratively identified.

[0074] In the embodiment of the present application, the control mode is the coordinated control of the micro-motor group, that is, multiple micro-motors cooperate to complete various adjustment tasks of the operating platform. The motor control logic describes how each micro-motor is precisely controlled according to a specific target, especially the relative amplitude modulation relationship between the speed of each micro-motor and the control target. The control target is the control element of each micro-motor, such as height, angle, and the control of each micro-motor may be different.

[0075] The relative amplitude modulation relationship between speed and control target refers to the speed change amplitude that each micromotor needs to adjust when the control target (such as the height, angle or position of the operating table) changes. For example, when the operating table needs to be raised, the micromotor with height adjustment function may need to speed up.

[0076] Next, the objective adjustment strategy is disassembled based on the control objectives of different micromotors. That is, the overall control panel adjustment strategy is decomposed into multiple sub-control strategies based on the control objectives. For example, the adjustment of the control panel may require multiple micromotors to control different movement directions, such as lifting, rotating, tilting, etc. Each subtask corresponds to a specific micromotor control objective, ensuring that each micromotor accurately performs the task according to its own control objective.

[0077] At the same time, the corresponding relationship between each sub-control strategy and the micro-motor group is determined. Each sub-control strategy specifies the adjustment target of a micro-motor. For example, the height adjustment of the console may be assigned to one micro-motor, while the rotation angle adjustment is assigned to another micro-motor, ensuring that each micro-motor can perform operations according to the predetermined target and avoid control conflicts or coordination failures.

[0078] Based on the motor control logic, the feed amount of each micromotor under the sub-control strategy is calculated. For example, if the height of the operating table needs to be increased by 10 cm, the precise feed amount that the related micromotor needs to provide in completing this height adjustment process is calculated based on the linear relationship between the rotational speed and the control target.

[0079] The feed amount of each micromotor is co-identified from the time dimension and the space dimension to ensure that the adjustment action of each micromotor is synchronized in space and time, avoiding adjustment errors caused by time lag or space deviation. For example, if multiple micromotors need to complete multiple directions of movement at the same time, that is, the coordination of these movements in time and their coordination in space to ensure the adjustment effect.

[0080] Furthermore, after determining the feed amount of the micro-motor group, step S4 includes:

[0081] Based on the digital-to-analog conversion interface, the feed amount is converted to determine analog adjustment information, wherein the digital-to-analog conversion interface performs bidirectional conversion between digital quantity and analog quantity; the micromotor group responds to the analog adjustment information to control the position of the operating table.

[0082] Specifically, the digital-to-analog conversion interface is a plug-in that converts digital signals into analog signals, or converts analog signals into digital signals. In the decision analysis process, digital signals are generally used to handle complex calculations and decision-making processes, while the actuator, i.e., the micro-motor group in the embodiment of the present application, can only recognize analog signals for precise control.

[0083] Therefore, based on the digital-to-analog conversion interface, the digital feed amount, that is, the specific amount of movement that each micromotor needs to perform, is converted into an analog signal suitable for micromotor control, so that the micromotor can make precise adjustment responses based on these signals.

[0084] After completing the digital-to-analog conversion, the analog adjustment information is determined, including the specific control instructions converted according to the feed amount, and sent to the micro-motor group to drive the micro-motor regulation. The micro-motor group responds to the analog adjustment information to perform position regulation of the operating table.

[0085] The present application provides an operating table position adjustment optimization control method for a CT puncture operating platform, which has the following technical effects:

[0086] 1. Taking the key position point cloud related to posture adjustment as the analysis standard, the position adjustment analysis of the operating console under posture changes is carried out to screen out invalid point clouds, reduce the amount of calculation on the basis of ensuring the adjustment effect, and improve processing efficiency.

[0087] 2. Based on the first fixed relationship of body shape and the second linear relationship based on posture variables, a two-step adjustment decision is made by building an analog regulator to improve the accuracy and stability of the console adjustment, ensure that each adjustment can be accurate and in place, and avoid errors caused by posture changes. At the same time, the introduction of posture trend change thresholds improves the effectiveness of the adjustment response, responds to the needs of operators in a timely manner, and ensures the stability and flexibility of the console. Through personalized learning of operating habits, the adjustment of the console can be automatically adjusted according to the preferences of each operator, improving comfort and work efficiency.

[0088] 3. Based on the motor control logic, the micromotor feed amount is calculated, and coordinated control in space and time dimensions is performed to achieve precise coordinated movement of the micromotor, ensuring that the operating platform can accurately complete complex motion tasks with the cooperation of multiple micromotors, reduce errors, and improve the adjustment efficiency of the operating platform.

[0089] Through the above-mentioned detailed description of the operating table position adjustment optimization control method for a CT puncture operating platform in this specification, those skilled in the art can clearly know the operating table position adjustment optimization control method for a CT puncture operating platform in this embodiment. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0090] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be 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 present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for optimizing the position adjustment of an operating table for a CT puncture operating platform, characterized in that: The method comprises: Performing a sensor scan on the operator to determine a three-dimensional posture point cloud, wherein the three-dimensional posture point cloud is a key position point cloud; Recall historical adjustment records, explore ergonomic posture adjustment relationships, and construct a simulated adjuster in a coaxial coordinate system, wherein the posture adjustment relationship includes a first fixed relationship based on the operator's body shape and a second linear relationship based on the operator's posture; receiving the three-dimensional posture point cloud, performing a simulated decision analysis under a two-step adjustment in combination with the simulated regulator, and determining an objective adjustment strategy; Obtaining a control mode of the CT puncture operating platform, identifying the objective adjustment strategy and performing motion process decomposition, and determining the feed amount of the micro-motor group, wherein the control mode is cooperative control of the micro-motor group; Based on the feed amount of the micro-motor group, the position of the operating table is controlled; The analog decision analysis under the dual-step adjustment is performed in combination with the analog regulator, including: Identifying the three-dimensional posture point cloud to determine the operator's body shape characteristics; Based on the body shape characteristics, the overall adjustment is performed based on the first fixed relationship to define an implicit adjustment standard, wherein the implicit adjustment standard is the baseline standard of the operator during the operation cycle, which is the relative position of the operator to the operating table in a standard posture; The implicit adjustment standard under the operation cycle is fixed, and three-dimensional posture point cloud restoration and simulation adjustment based on the second linear relationship are performed on the key position point cloud to determine the objective adjustment strategy.

2. The method for optimizing the position adjustment of an operating table for a CT puncture operating platform according to claim 1, characterized in that: The performing of three-dimensional posture point cloud restoration and simulation adjustment based on the second linear relationship includes: Identify the three-dimensional posture point cloud and perform simulation restoration to measure posture variables, wherein the posture variables include the spatial migration amount of each key position point cloud; Based on the second linear relationship, calculating the adjusted spatial position and adjustment angle of the operating console under the posture variable and performing simulation verification; The spatial position and the adjustment angle are integrated as the objective adjustment strategy.

3. The method for optimizing the position adjustment of an operating table for a CT puncture operating platform according to claim 2, characterized in that: After measuring posture variables, including: Setting a posture change threshold, wherein the posture change threshold is a critical constraint value for measuring posture variables; Identifying the posture variable, and generating a position adjustment instruction if the posture variable is greater than or equal to the posture trend change threshold; If the posture variable is less than the posture trend change threshold, superposition supervision of the posture variable is performed.

4. The method for optimizing the position adjustment of an operating table for a CT puncture operating platform according to claim 1, wherein: Determining the feed amount of the micro-motor group includes: Identifying the control mode and determining the motor control logic, wherein the motor control logic includes a relative amplitude modulation relationship between the rotation speed of each micromotor and the control target; Based on the control target, the objective adjustment strategy is disassembled to determine sub-control strategies, wherein each sub-control strategy corresponds to a micro-motor group; Based on the motor control logic, the feed amount of each micromotor under the sub-control strategy is calculated, and the time dimension and the space dimension are collaboratively identified.

5. The method for optimizing the position adjustment of an operating table for a CT puncture operating platform according to claim 4, characterized in that: After determining the feed amount of the micro-motor group, the method includes: Based on a digital-to-analog conversion interface, the feed amount is converted to determine analog adjustment information, wherein the digital-to-analog conversion interface performs bidirectional conversion between digital and analog quantities; The micro-motor group responds to the analog adjustment information to adjust the position of the operating table.

6. The method for optimizing the position adjustment of an operating table for a CT puncture operating platform according to claim 1, characterized in that: After determining the objective adjustment strategy, including: By identifying the operator's number, a subjective feature library is triggered, and the subjective feature library is built into the analog regulator; Traversing the subjective feature library, matching the three-dimensional posture point cloud, and determining the operation habit characteristics; Based on the operating habit characteristics, the objective adjustment strategy is compensated.

7. The method for optimizing the position adjustment of an operating table for a CT puncture operating platform according to claim 6, characterized in that: Build a subjective feature library, including: Obtaining the operator's adjustment record and storing it in a temporary database, which is periodically updated; Mining personnel operation habits based on the temporary database; Based on the operator's operating habits, incremental learning is performed on the analog regulator to generate a subjective feature library, wherein the subjective feature library is marked with an operator number.

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