Body position adjusting method, system and equipment applied to prone position operation and medium

Abstract

The invention discloses a body position adjusting method, system and equipment applied to prone position surgery and a medium, and relates to the field of medical equipment control, the method is applied to a body position management system, and the body position management system comprises a head frame and a body position pad; the method comprises the following steps: acquiring pressure sensing data of a body position management device based on a pressure sensor array; according to the pressure sensing data, a to-be-adjusted part of the body position management device is determined, and according to analysis of the pressure sensing data, the adjusting action of the to-be-adjusted part is determined; based on the initial posture of the to-be-adjusted component, according to the adjusting action of the to-be-adjusted component, posture adjustment is conducted on the to-be-adjusted component, so that the user completes posture adjustment according to the guidance of the posture management device; wherein the initial posture is obtained by modeling simulation analysis based on physiological feature data of the user. The prone position operation body position management system can solve the problem that existing prone position operation body position management is lack of efficiency and accuracy.

Description

Technical Field

[0001] This application relates to the field of medical device control, and more particularly to a method, system, device, and medium for adjusting body position during prone surgery. Background Technology

[0002] Proper surgical positioning is crucial for the success of any surgery. A good surgical position requires ease of operation for medical staff and ensures that the patient's vital signs do not fluctuate significantly due to the position. This is especially important in prone surgery, where the patient must maintain this position for an extended period, increasing the risk of complications such as pressure injuries and nerve compression compared to non-prone positions. To maintain a good surgical position and prevent complications, medical staff typically use assistive devices for surgical positioning management. These devices include traditional adjustable instruments, such as modular positioning pads and mechanical head frames, which can be manually adjusted to suit different patients, as well as intelligent monitoring systems, such as pressure-sensing pads, which display real-time pressure zone heat maps to guide medical staff in adjusting the patient's position.

[0003] In current prone surgery, position management using positioning pads relies solely on medical staff manually guiding the patient's position based on visual inspection and their own experience. This method lacks pre-set parameters based on individual patient characteristics, leading to repeated confirmation and manual adjustments during surgery, consuming valuable surgical time and negatively impacting comfort and safety. While position management using pressure-sensing pads only provides a thermal map of the pressure area, it lacks shape analysis for precise positioning of the adjustable components. Furthermore, it doesn't provide pre-operative modeling and simulation pre-set parameters based on individual patient skeletal and surface data. In practice, medical staff still need to manually adjust the position using the thermal map and their experience, with an error rate not significantly different from the traditional method of manually adjusting the positioning pad based on visual inspection and experience. Neither method provides precise position adjustment instructions or suggestions. Therefore, improving the efficiency and accuracy of position management in prone surgery remains a pressing technical problem that needs to be solved. Summary of the Invention

[0004] This application provides a method, system, device, and medium for position adjustment in prone surgery, to solve the technical problems of inefficiency and inaccuracy in existing prone surgery position management.

[0005] According to a first aspect of the embodiments of this application, a method for adjusting body position during prone surgery is provided, which is applied to a body position management device, the body position management device including a headrest and a body position pad; the method includes: Pressure sensor data of the body positioning management device is collected based on a pressure sensor array; wherein the pressure sensor array is respectively installed at preset locations on the head frame and the body positioning pad; Based on the pressure sensing data, the component to be adjusted in the body position management device is determined, and based on the analysis of the pressure sensing data, the adjustment action of the component to be adjusted is determined. Based on the initial posture of the component to be adjusted, the posture of the component to be adjusted is adjusted according to the adjustment action of the component to be adjusted, so that the user can complete the posture adjustment according to the guidance of the posture management device; wherein, the initial posture is obtained by modeling and simulation analysis based on the user's physiological characteristic data.

[0006] This application first collects pressure sensing data from a position management device based on a pressure sensor array, then determines the component to be adjusted based on the pressure sensing data, and subsequently determines the adjustment action of the component. Compared to existing pressure sensing pads that can only provide a thermal map of the pressure area and cannot provide precise data, still requiring adjustment based on experience, this application determines the component to be adjusted and then the adjustment action based on pressure sensing data. This allows for data quantification, and the accuracy of determining the component to be adjusted and its adjustment action can be improved based on the quantified precise data, thereby improving the accuracy of prone surgical position management. Furthermore, based on the initial posture of the component to be adjusted and its adjustment action, the posture is adjusted. Compared to existing manual position management using position pads, which cannot be pre-set and requires multiple manual adjustments during surgery, this application uses modeling and simulation based on the user's physiological characteristic data to pre-set the initial posture of the component to be adjusted. This allows for pre-setting an initial posture that matches the user's physiological characteristics before surgery, ensuring user comfort while reducing or even avoiding intraoperative position adjustments, thereby improving the efficiency of prone surgical position management.

[0007] In some embodiments of this application, the pressure sensing data includes first pressure sensing data of the headrest and second pressure sensing data of the positioning pad; the step of determining the adjustable component of the positioning management device based on the pressure sensing data specifically includes: Regional pressure analysis was performed on the first pressure sensing data and the second pressure sensing data respectively to obtain the first pressure region distribution and the second pressure region distribution. Based on a preset pressure threshold, a first region and a second region are obtained from the first pressure region distribution and the second pressure region distribution, respectively; wherein, the first region is the region in the first pressure region distribution where the pressure value is greater than the preset pressure threshold; and the second region is the region in the second pressure region distribution where the pressure value is greater than the preset pressure threshold. Shape analysis is performed on the first region and the second region respectively to identify the shape distribution of the first region and the second region, and the adjustment component of the body position management device is determined based on the shape distribution of the first region and the second region.

[0008] This application first performs regional pressure analysis on the first pressure sensor data of the head frame and the second pressure sensor data of the positioning pad, respectively, to intuitively represent the regional distribution of pressure. Then, by using a preset pressure threshold, a first region and a second region are divided, which can quickly and accurately divide the regional distribution of pressure and identify the first and second regions with abnormal pressure. Furthermore, by identifying the shape distribution of the first and second regions, the component to be adjusted can be determined. Based on the correlation between the shape distribution of the first or second region and the corresponding component to be adjusted, the component to be adjusted can be accurately determined, thereby improving the accuracy of prone surgical positioning management.

[0009] In some embodiments of this application, determining the adjustable component of the body position management device based on the shape distribution of the first region and the second region specifically includes: If the shape of the first region is a strip-shaped distribution, then the head frame is used as the component to be adjusted; If the shape of the second region is elliptical, then the positioning pad is used as the component to be adjusted.

[0010] When the shape distribution of the first region is a strip, the head frame is used as the adjustable component; when the shape distribution of the second region is an elliptical distribution, the positioning pad is used as the adjustable component. By identifying the shape distribution of the first and second regions, the system can accurately determine whether the corresponding component is the adjustable component based on the correlation between the shape distribution of pressure in different regions and the corresponding adjustable component, thereby improving the accuracy of prone surgical positioning management.

[0011] In some embodiments of this application, determining the adjustment action of the component to be adjusted based on the analysis of the pressure sensing data specifically includes: If the component to be adjusted is the head frame, then the rotation angle of the head frame is calculated and determined based on the average pressure difference and average pressure change rate obtained by analyzing the pressure sensing data, and the adjustment action of the head frame is determined based on the rotation angle of the head frame. If the component to be adjusted is the positioning pad, then the pressure adjustment amount of the positioning pad is calculated and determined based on the pressure area obtained by analyzing the pressure sensing data, and the adjustment action of the positioning pad is determined based on the pressure adjustment amount of the positioning pad.

[0012] When the head frame is the adjustable component, this application calculates and determines the rotation angle of the head frame based on the average pressure difference and average pressure change rate obtained from pressure sensing data, thereby determining the adjustment action of the head frame. When the positioning pad is the adjustable component, the pressure adjustment amount of the positioning pad is calculated and determined based on the pressure-bearing area obtained from pressure sensing data, thereby determining the adjustment action of the positioning pad. By quantitatively analyzing the pressure sensing data, an intuitive and calculable data basis can be provided for the adjustment parameters of the adjustable component, thereby determining the corresponding adjustment action of the adjustable component. This can improve the matching degree between the adjustment action and the current needs, thereby improving the accuracy of prone surgical positioning management.

[0013] In some embodiments of this application, the initial posture is obtained based on modeling and simulation analysis of the user's physiological characteristic data, specifically including: Acquire the user's physiological characteristic data; wherein, the physiological characteristic data includes body surface topology data, image scan data, and individual characteristic indicators; The user's skeletal model is reconstructed based on the image scan data; Based on the body surface topology data and the skeletal model, biomechanical simulation analysis is performed, and corrections are made in conjunction with the individual characteristic indicators to obtain the initial posture of the head frame and the positioning pad in the positioning management device.

[0014] This application first acquires physiological characteristic data of the user, including body surface topology data, image scan data, and individual characteristic indicators. Then, it reconstructs the user's skeletal model based on the image scan data and performs biomechanical simulation analysis based on the body surface topology data. Combined with individual characteristic indicators for correction, the initial posture of the head frame and positioning pad in the positioning management device is obtained. By using the user's physiological characteristic data for model reconstruction and biomechanical simulation analysis, the user's physiological characteristic data can be fully utilized to construct a simulation model that fits the user's individual characteristics. This results in an initial posture of the positioning management device that is more suitable for the current user's positioning management needs, thereby ensuring user comfort and reducing or even avoiding the negative impact of multiple manual positioning adjustments during surgery, as is currently required, thus improving the efficiency of positioning management in prone surgery.

[0015] In some embodiments of this application, the step of performing biomechanical simulation analysis based on the body surface topology data and the skeletal model, and then correcting it using the individual characteristic indicators to obtain the initial posture of the head frame and the positioning pad in the positioning management device, specifically includes: Biomechanical simulation analysis is performed based on the body surface topology data and the skeletal model. During the simulation, a multi-level finite element model is constructed based on the skeletal model, and the constraints of the multi-level finite element model are determined by combining the body surface topology data and the skeletal model. The initial support parameters of the body position management device are obtained through simulation analysis. Based on the individual characteristic indicators, the initial support parameters are corrected to obtain the initial posture of the head frame and the positioning pad in the positioning management device.

[0016] This application first performs biomechanical simulation analysis based on body surface topology data and skeletal models. During the simulation, a multi-level finite element model is constructed, and the constraints of the multi-level finite element model are determined. Then, the initial support parameters of the positioning management device are obtained through simulation. Through the multi-level finite element model, the overall human body structure of the current user is fully characterized, and the initial support parameters that are more suitable for the current user can be obtained. Then, the initial support parameters are corrected by combining the individual characteristic indicators that represent the most significant physiological indicators of the current user, so as to obtain the initial posture of the positioning management device that is more matched to the positioning management needs of the current user, thereby ensuring user comfort and reducing or even avoiding the negative impact of having to manually adjust the position multiple times during the operation, as is the case with existing methods, thereby improving the efficiency of positioning management in prone surgery.

[0017] In some embodiments of this application, it further includes: Collect postoperative complication data from the user; Based on a machine learning model, the postoperative complication data, pressure sensing data, adjustment actions of the adjustable component, and initial posture are correlated and analyzed. Based on the correlation analysis results, the initial posture of the adjustable component is optimized.

[0018] This application first collects postoperative complication data from users, and then, based on a machine learning model, conducts correlation analysis on postoperative complication data, pressure sensor data, adjustment actions of the adjustable component, and initial posture. This optimizes the initial posture of the adjustable component. By combining intraoperative data and postoperative feedback data from users, the initial posture of the adjustable component can be optimized in a feedback manner, further improving user comfort. At the same time, the correlation analysis based on the machine learning model ensures the accuracy of the correlation analysis and the accuracy of the feedback optimization of the initial posture of the adjustable component.

[0019] According to a second aspect of the embodiments of this application, a body position adjustment system for prone surgery is provided, which is applied to a body position management device, the body position management device including a head frame and a body position pad; the system includes a pressure data acquisition module, a component motion determination module and a component posture adjustment module; The pressure data acquisition module is used to acquire pressure sensing data of the body position management device based on the pressure sensor array; wherein the pressure sensor array is respectively installed at preset positions on the head frame and the body position pad; The component action determination module is used to determine the component to be adjusted in the body position management device based on the pressure sensing data, and to determine the adjustment action of the component to be adjusted based on the analysis of the pressure sensing data. The component posture adjustment module is used to adjust the posture of the component to be adjusted based on its initial posture and the adjustment action of the component, so that the user can complete the posture adjustment according to the guidance of the posture management device; wherein, the initial posture is obtained by modeling and simulation analysis based on the user's physiological characteristic data.

[0020] In some embodiments of this application, the pressure sensing data includes first pressure sensing data of the head frame and second pressure sensing data of the positioning pad; the component action determination module includes an adjustment component determination submodule; the adjustment component determination submodule includes a pressure data analysis unit, a pressure region division unit, and an adjustment component determination unit; The pressure data analysis unit is used to perform regional pressure analysis on the first pressure sensing data and the second pressure sensing data respectively to obtain the first pressure region distribution and the second pressure region distribution. The pressure region division unit is used to divide a first region and a second region from the first pressure region distribution and the second pressure region distribution respectively according to a preset pressure threshold; wherein, the first region is the region in the first pressure region distribution where the pressure value is greater than the preset pressure threshold; and the second region is the region in the second pressure region distribution where the pressure value is greater than the preset pressure threshold. The adjustment component determination unit is used to perform shape analysis on the first region and the second region respectively, identify the shape distribution of the first region and the second region, and determine the adjustment component of the body position management device based on the shape distribution of the first region and the second region.

[0021] In some embodiments of this application, the adjustment component determining unit includes a first component determining subunit and a second component determining subunit; The first component determines the subunit, which is used to treat the head frame as the component to be adjusted if the shape distribution of the first region is a strip distribution; The second component determines the subunit, which is used to treat the positioning pad as the component to be adjusted if the shape distribution of the second region is elliptical.

[0022] In some embodiments of this application, the component action determination module includes an adjustment action determination submodule; the adjustment action determination submodule includes a first action determination unit and a second action determination unit; The first action determination unit is used to, if the component to be adjusted is the head frame, calculate and determine the rotation angle of the head frame based on the average pressure difference and average pressure change rate obtained by analyzing the pressure sensing data, and determine the adjustment action of the head frame based on the rotation angle of the head frame. The second action determination unit is used to, if the component to be adjusted is the positioning pad, calculate and determine the pressure adjustment amount of the positioning pad based on the pressure area obtained by analyzing the pressure sensing data, and determine the adjustment action of the positioning pad based on the pressure adjustment amount of the positioning pad.

[0023] In some embodiments of this application, the initial posture is obtained based on modeling and simulation analysis of the user's physiological characteristic data, specifically including: Acquire the user's physiological characteristic data; wherein, the physiological characteristic data includes body surface topology data, image scan data, and individual characteristic indicators; The user's skeletal model is reconstructed based on the image scan data; Based on the body surface topology data and the skeletal model, biomechanical simulation analysis is performed, and corrections are made in conjunction with the individual characteristic indicators to obtain the initial posture of the head frame and the positioning pad in the positioning management device.

[0024] In some embodiments of this application, the step of performing biomechanical simulation analysis based on the body surface topology data and the skeletal model, and then correcting it using the individual characteristic indicators to obtain the initial posture of the head frame and the positioning pad in the positioning management device, specifically includes: Biomechanical simulation analysis is performed based on the body surface topology data and the skeletal model. During the simulation, a multi-level finite element model is constructed based on the skeletal model, and the constraints of the multi-level finite element model are determined by combining the body surface topology data and the skeletal model. The initial support parameters of the body position management device are obtained through simulation analysis. Based on the individual characteristic indicators, the initial support parameters are corrected to obtain the initial posture of the head frame and the positioning pad in the positioning management device.

[0025] This application first collects pressure sensing data from a position management device based on a pressure sensor array, then determines the component to be adjusted based on the pressure sensing data, and subsequently determines the adjustment action of the component. Compared to existing pressure sensing pads that can only provide a thermal map of the pressure area and cannot provide precise data, still requiring adjustment based on experience, this application determines the component to be adjusted and then the adjustment action based on pressure sensing data. This allows for data quantification, and the accuracy of determining the component to be adjusted and its adjustment action can be improved based on the quantified precise data, thereby improving the accuracy of prone surgical position management. Furthermore, based on the initial posture of the component to be adjusted and its adjustment action, the posture is adjusted. Compared to existing manual position management using position pads, which cannot be pre-set and requires multiple manual adjustments during surgery, this application uses modeling and simulation based on the user's physiological characteristic data to pre-set the initial posture of the component to be adjusted. This allows for pre-setting an initial posture that matches the user's physiological characteristics before surgery, ensuring user comfort while reducing or even avoiding intraoperative position adjustments, thereby improving the efficiency of prone surgical position management. Attached Figure Description

[0026] Figure 1 This is a flowchart illustrating a method for adjusting body position during prone surgery, as shown in certain embodiments of this application. Figure 2 This is a modular structure diagram of a body position adjustment system for prone surgery, as shown in certain embodiments of this application. Detailed Implementation

[0027] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below in conjunction with the accompanying drawings are exemplary and are only used to explain some embodiments of this application, and should not be construed as limiting the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments shown in this application without inventive effort are within the protection scope of this application.

[0028] In the description of this application, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, unless otherwise explicitly specified, "a plurality of" or "several" means two or more.

[0029] In current prone surgery, position management using positioning pads relies solely on medical staff manually guiding the patient's position based on visual inspection and their own experience. This method cannot be pre-set according to the patient's individual characteristics, leading to repeated confirmation and manual adjustments during surgery, consuming valuable surgical time and negatively impacting surgical comfort and safety. While position management using pressure-sensing pads only provides a thermal map of the pressure area, it still requires medical staff to manually adjust the position based on the thermal map and their own experience. The error rate is not significantly different from the traditional method of manually adjusting the positioning pad based on visual inspection and experience; neither method provides precise position adjustment instructions or suggestions. Therefore, improving the efficiency and accuracy of position management in prone surgery remains a pressing technical problem that needs to be solved.

[0030] Based on the above technical background, please refer to Figure 1 This application provides a method for adjusting body position during prone surgery, using a body position management device. The body position management device includes a head frame and a body position pad, and can automatically execute the body position adjustment method provided in this application. The method includes steps S101 to S103, each step as follows: Step S101: Based on the pressure sensor array, collect pressure sensing data of the body position management device; wherein, the pressure sensor array is respectively installed at preset positions of the head frame and the body position pad.

[0031] Specifically, the pressure sensor array installed in the head frame is located in the fulcrum contact area of ​​the head frame, specifically distributed in the forehead and bilateral zygomatic support modules. The sensor type is a miniature piezoresistive sensor, with an installation density of no less than 4 sensors per square centimeter. The data acquisition area includes the skull-cervical spine connection, covering the occipital bone and the first to seventh cervical vertebrae (C1-C7). The pressure sensor array installed in the positioning pad is located in the surface covering layer of the positioning pad, specifically distributed in bony prominences and major force-bearing support modules such as the chest (thoracic cage), pelvis (iliac crest), or knees. The sensor type is a flexible thin-film pressure sensor network, with an installation density of no less than 3 sensors per square centimeter. The data acquisition area covers the major bony prominences and weight-bearing areas of the trunk, including but not limited to key support parts such as the thoracic cage, iliac crest, and knees.

[0032] Step S102: Based on the pressure sensing data, determine the component to be adjusted in the body position management device, and based on the analysis of the pressure sensing data, determine the adjustment action of the component to be adjusted.

[0033] In some embodiments of this application, the pressure sensing data includes first pressure sensing data of the headrest and second pressure sensing data of the positioning pad; the step of determining the adjustable component of the positioning management device based on the pressure sensing data specifically includes: Regional pressure analysis was performed on the first pressure sensing data and the second pressure sensing data respectively to obtain the first pressure region distribution and the second pressure region distribution. Based on a preset pressure threshold, a first region and a second region are obtained from the first pressure region distribution and the second pressure region distribution, respectively; wherein, the first region is the region in the first pressure region distribution where the pressure value is greater than the preset pressure threshold; and the second region is the region in the second pressure region distribution where the pressure value is greater than the preset pressure threshold. Shape analysis is performed on the first region and the second region respectively to identify the shape distribution of the first region and the second region, and the adjustment component of the body position management device is determined based on the shape distribution of the first region and the second region.

[0034] Specifically, when performing regional pressure analysis on pressure sensing data, a preferred implementation method is to first convert discrete pressure sensing data into continuous pressure region sensing data through interpolation, and then convert the pressure region sensing data into the corresponding pressure region distribution through visualization. More specifically, bilinear interpolation, kriging interpolation, or finite element interpolation can be selected for interpolation, while 2D heat maps or 3D surface plots can be selected for visualization.

[0035] Specifically, the preferred value of the preset pressure threshold is 32 mmHg. As can be easily understood by those skilled in the art, the preferred value of the preset pressure threshold is obtained through clinical trial data. Obviously, different clinical trial data may yield different other values. Therefore, this preferred value is not actually a fixed value that limits the scope of this application, but should be regarded as an example of an implementable implementation method of this application.

[0036] Specifically, when performing shape analysis on the first region and the second region to identify the shape distribution of the first region and the second region, morphological analysis, neural network model recognition, or machine learning model recognition can be used, and this application does not impose any restrictions on these methods.

[0037] This application first performs regional pressure analysis on the first pressure sensor data of the head frame and the second pressure sensor data of the positioning pad, respectively, to intuitively represent the regional distribution of pressure. Then, by using a preset pressure threshold, a first region and a second region are divided, which can quickly and accurately divide the regional distribution of pressure and identify the first and second regions with abnormal pressure. Furthermore, by identifying the shape distribution of the first and second regions, the component to be adjusted can be determined. Based on the correlation between the shape distribution of the first or second region and the corresponding component to be adjusted, the component to be adjusted can be accurately determined, thereby improving the accuracy of prone surgical positioning management.

[0038] In some embodiments of this application, determining the adjustable component of the body position management device based on the shape distribution of the first region and the second region specifically includes: If the shape of the first region is a strip-shaped distribution, then the head frame is used as the component to be adjusted; If the shape of the second region is elliptical, then the positioning pad is used as the component to be adjusted.

[0039] Generally, a banded distribution refers to elements exhibiting a regional arrangement or layering phenomenon on a plane or in space. In this application, the distribution corresponding to pressure exhibits regional characteristics, specifically forming a continuous whole. An elliptical distribution refers to elements exhibiting an elliptical or near-elliptical shape on a plane or in space. In this application, the characteristic region formed by the distribution corresponding to pressure is elliptical or near-elliptical. Compared to a banded distribution, it requires the element to have an elliptical or near-elliptical shape. In some embodiments of this application, when the regional characteristic of an element is that the aspect ratio of its smallest bounding rectangle is greater than a first threshold, the element is determined to be a banded distribution. The preferred first threshold is 3:1. When the regional characteristic of an element is that the similarity between its outline and the best-fitting ellipse is higher than a second threshold, the element is determined to be an elliptical distribution. The preferred second threshold is 0.7. Those skilled in the art will readily understand that the first threshold for determining a banded distribution and the second threshold for determining an elliptical distribution are obtained through corresponding clinical trial data. Obviously, different clinical trial data may yield different other values. Therefore, these preferred values ​​are not actually fixed values ​​that limit the scope of this application, but rather examples illustrating one possible implementation method of this application.

[0040] It is easy to understand that the first region and the second region are derived from the pressure sensing data of two different components, the head frame and the positioning pad, in the positioning management device. That is, the shape distribution of the first region and the shape distribution of the second region do not interfere with each other. Therefore, it is possible that the head frame and the positioning pad simultaneously meet the conditions of being adjustable components. In this case, the shape distribution of the first region is a strip distribution and the shape distribution of the second region is an elliptical distribution. The head frame and the positioning pad are both adjustable components.

[0041] When the shape distribution of the first region is a strip, the head frame is used as the adjustable component; when the shape distribution of the second region is an elliptical distribution, the positioning pad is used as the adjustable component. By identifying the shape distribution of the first and second regions, the system can accurately determine whether the corresponding component is the adjustable component based on the correlation between the shape distribution of pressure in different regions and the corresponding adjustable component, thereby improving the accuracy of prone surgical positioning management.

[0042] In some embodiments of this application, determining the adjustment action of the component to be adjusted based on the analysis of the pressure sensing data specifically includes: If the component to be adjusted is the head frame, then the rotation angle of the head frame is calculated and determined based on the average pressure difference and average pressure change rate obtained by analyzing the pressure sensing data, and the adjustment action of the head frame is determined based on the rotation angle of the head frame. If the component to be adjusted is the positioning pad, then the pressure adjustment amount of the positioning pad is calculated and determined based on the pressure area obtained by analyzing the pressure sensing data, and the adjustment action of the positioning pad is determined based on the pressure adjustment amount of the positioning pad.

[0043] Specifically, when calculating the rotation angle of the headframe, it is based on the average pressure difference. With average pressure change rate The compensation coefficients are weighted and calculated to determine the rotation angle of the headframe. ,in This is the pressure difference compensation coefficient, in units of... , This is the pressure change rate compensation coefficient, in units of... When calculating the pressure regulation of the positioning pad, it is based on the pressure-bearing area. Compensation calculations are performed, and the pressure adjustment of the positioning pad is determined at this time. ,in This is the compressive compensation coefficient, in units of... More specifically, after obtaining the rotation angle of the head frame and the pressure adjustment amount of the positioning pad, the rotation angle of the head frame is directly used as the adjustment action of the head frame, and the pressure adjustment amount of the positioning pad is used as the adjustment action of the positioning pad.

[0044] When the head frame is the adjustable component, this application calculates and determines the rotation angle of the head frame based on the average pressure difference and average pressure change rate obtained from pressure sensing data, thereby determining the adjustment action of the head frame. When the positioning pad is the adjustable component, the pressure adjustment amount of the positioning pad is calculated and determined based on the pressure-bearing area obtained from pressure sensing data, thereby determining the adjustment action of the positioning pad. By quantitatively analyzing the pressure sensing data, an intuitive and calculable data basis can be provided for the adjustment parameters of the adjustable component, thereby determining the corresponding adjustment action of the adjustable component. This can improve the matching degree between the adjustment action and the current needs, thereby improving the accuracy of prone surgical positioning management.

[0045] Step S103: Based on the initial posture of the component to be adjusted, the posture of the component to be adjusted is adjusted according to the adjustment action of the component to be adjusted, so that the user can complete the posture adjustment according to the guidance of the posture management device; wherein, the initial posture is obtained by modeling and simulation analysis based on the user's physiological characteristic data.

[0046] In some embodiments of this application, the initial posture is obtained based on modeling and simulation analysis of the user's physiological characteristic data, specifically including: Acquire the user's physiological characteristic data; wherein, the physiological characteristic data includes body surface topology data, image scan data, and individual characteristic indicators; The user's skeletal model is reconstructed based on the image scan data; Based on the body surface topology data and the skeletal model, biomechanical simulation analysis is performed, and corrections are made in conjunction with the individual characteristic indicators to obtain the initial posture of the head frame and the positioning pad in the positioning management device.

[0047] This application first acquires physiological characteristic data of the user, including body surface topology data, image scan data, and individual characteristic indicators. Then, it reconstructs the user's skeletal model based on the image scan data and performs biomechanical simulation analysis based on the body surface topology data. Combined with individual characteristic indicators for correction, the initial posture of the head frame and positioning pad in the positioning management device is obtained. By using the user's physiological characteristic data for model reconstruction and biomechanical simulation analysis, the user's physiological characteristic data can be fully utilized to construct a simulation model that fits the user's individual characteristics. This results in an initial posture of the positioning management device that is more suitable for the current user's positioning management needs, thereby ensuring user comfort and reducing or even avoiding the negative impact of multiple manual positioning adjustments during surgery, as is currently required, thus improving the efficiency of positioning management in prone surgery.

[0048] In some embodiments of this application, the step of performing biomechanical simulation analysis based on the body surface topology data and the skeletal model, and then correcting it using the individual characteristic indicators to obtain the initial posture of the head frame and the positioning pad in the positioning management device, specifically includes: Biomechanical simulation analysis is performed based on the body surface topology data and the skeletal model. During the simulation, a multi-level finite element model is constructed based on the skeletal model, and the constraints of the multi-level finite element model are determined by combining the body surface topology data and the skeletal model. The initial support parameters of the body position management device are obtained through simulation analysis. Based on the individual characteristic indicators, the initial support parameters are corrected to obtain the initial posture of the head frame and the positioning pad in the positioning management device.

[0049] Specifically, when performing biomechanical simulations based on a skeletal model, the coordinates of the user's bony landmarks, spinal curvature, and spinal deformity parameters are obtained through the skeletal model, and these coordinates, along with the body surface topology data, are used as inputs to a multi-level finite element model.

[0050] Specifically, after simulating the multi-level finite element model, a physiological characteristic model of the user is obtained. Based on this model, the initial support parameters of the positioning management device are determined. These parameters include the head frame tilt angle and the shape of the air chambers in the positioning cushion. More specifically, when determining the head frame tilt angle based on the physiological characteristic model, the occipital protuberance obtained from the model is first used as the origin, and the apexes of the two zygomatic arches are used as support points to determine the coronal plane of the head. Then, the angle between the cervical spine physiological arc obtained from the model and the coronal plane is used as the cervical curvature angle. Through formula Determine the headframe tilt angle ,in The curvature-tilt conversion coefficient, determined based on biomechanical experiments, is preferably 0.6. For safe adjustment of normal values, the preferred value is -5°. When determining the shape of the air chamber of the positioning cushion based on the physiological characteristic model, the following compensation algorithm is activated only when the lumbar scoliosis angle Cobb angle is greater than 20°: Based on the T12-L5 segment of the spine obtained from the physiological characteristic model, the user's lumbar scoliosis direction and lumbar scoliosis angle Cobb angle are measured. and lumbar spine torsion angle Then through the formula Determine the first position pad Air chamber pressure in each air chamber ,in Based on the basic air chamber pressure, The preferred value for the angle compensation coefficient, determined based on biomechanical experiments, is 0.6 mmHg / °. The torsional compensation coefficient, determined based on biomechanical experiments, is preferably 0.4 mmHg / °. For the first The position coefficient of each air chamber (1 when it is on the same side as the lumbar scoliosis direction, indicating pressure on the lumbar scoliosis direction; -1 otherwise). For the first The distance of each air chamber from the center of the spine was used to characterize the air chamber morphology of the positioning pad, which was ultimately determined by the direction of lumbar lateral curvature and the air chamber pressure in each air chamber. Those skilled in the art will readily understand that the curvature-tilt conversion factor... Safety correction amount Angle compensation coefficient and torsional compensation coefficient The preferred values ​​are all obtained through corresponding clinical trial data. Obviously, different clinical trial data may yield different other values. Therefore, these preferred values ​​are not actually fixed values ​​that limit the scope of this application, but should be regarded as examples of one implementable implementation method of this application.

[0051] Specifically, individual characteristic indicators include the BMI index; if a user's BMI is greater than 30, the headframe support density in the initial support parameters will be increased to 150 points per square decimeter when revising the initial support parameters.

[0052] This application first performs biomechanical simulation analysis based on body surface topology data and skeletal models. During the simulation, a multi-level finite element model is constructed, and the constraints of the multi-level finite element model are determined. Then, the initial support parameters of the positioning management device are obtained through simulation. Through the multi-level finite element model, the overall human body structure of the current user is fully characterized, and the initial support parameters that are more suitable for the current user can be obtained. Then, the initial support parameters are corrected by combining the individual characteristic indicators that represent the most significant physiological indicators of the current user, so as to obtain the initial posture of the positioning management device that is more matched to the positioning management needs of the current user, thereby ensuring user comfort and reducing or even avoiding the negative impact of having to manually adjust the position multiple times during the operation, as is the case with existing methods, thereby improving the efficiency of positioning management in prone surgery.

[0053] In some embodiments of this application, it further includes: Collect postoperative complication data from the user; Based on a machine learning model, the postoperative complication data, pressure sensing data, adjustment actions of the adjustable component, and initial posture are correlated and analyzed. Based on the correlation analysis results, the initial posture of the adjustable component is optimized.

[0054] Specifically, the machine learning model is used to perform correlation analysis on postoperative complication data, pressure sensing data, adjustment actions of the adjustable component, and initial posture. During the correlation analysis, initial posture parameters, adjustment action parameters, and statistical values ​​of pressure sensing data are used as input features, and the probability of postoperative complications is used as the output label. The model is trained to obtain a mapping relationship between the input features and the output label, and the initial posture parameters are adjusted in reverse based on this relationship. The input features of the machine learning model include: initial posture parameters (headrest tilt angle, positioning cushion air chamber pressure), adjustment action parameters (headrest rotation angle, positioning cushion pressure adjustment amount), and statistical values ​​of pressure sensing data (average pressure in the first / second region, pressure area). The output feature is the probability of postoperative complications (such as the risk of pressure injury or nerve compression). During the correlation analysis, the "mapping relationship between input features and output features" is obtained through model training, and the initial posture parameters are adjusted in reverse based on this relationship. A preferred implementation of the machine learning model is a model suitable for regression analysis, correlation analysis, or parameter optimization, including but not limited to linear regression models, decision tree models, random forest models, or neural network models.

[0055] This application first collects postoperative complication data from users, and then, based on a machine learning model, conducts correlation analysis on postoperative complication data, pressure sensor data, adjustment actions of the adjustable component, and initial posture. This optimizes the initial posture of the adjustable component. By combining intraoperative data and postoperative feedback data from users, the initial posture of the adjustable component can be optimized in a feedback manner, further improving user comfort. At the same time, the correlation analysis based on the machine learning model ensures the accuracy of the correlation analysis and the accuracy of the feedback optimization of the initial posture of the adjustable component.

[0056] Compared to existing technologies, this application first collects pressure sensing data from the positioning management device based on a pressure sensor array, then determines the component to be adjusted based on the pressure sensing data, and subsequently determines the adjustment action of the component to be adjusted. Compared to existing pressure sensing pads that can only provide a thermal map of the pressure area and cannot provide precise data, still requiring adjustment based on experience, this application determines the component to be adjusted and then the adjustment action based on pressure sensing data. This allows for data quantification, and the accuracy of determining the component to be adjusted and its adjustment action can be improved based on the quantified precise data, thereby improving the accuracy of prone surgical positioning management. Furthermore, based on the initial posture of the component to be adjusted and its adjustment action, the posture is adjusted. Compared to existing solutions that use positioning pads for manual positioning management, which cannot be pre-set before surgery and require multiple manual adjustments during surgery, this application uses modeling and simulation based on the user's physiological characteristic data to pre-set the initial posture of the component to be adjusted. This allows for pre-setting an initial posture that matches the user's physiological characteristics before surgery, ensuring user comfort while reducing or even avoiding intraoperative positioning adjustments, thereby improving the efficiency of prone surgical positioning management.

[0057] For a method corresponding to the one described above, please refer to [link / reference]. Figure 2 This application provides a body position adjustment system for prone surgery, which is applied to a body position management device. The body position management device includes a head frame and a body position pad. The system includes a pressure data acquisition module 210, a component motion determination module 220, and a component posture adjustment module 230. The pressure data acquisition module 210 is used to acquire pressure sensing data of the body position management device based on the pressure sensor array; wherein the pressure sensor array is respectively installed at preset positions on the head frame and the body position pad; The component action determination module 220 is used to determine the component to be adjusted in the body position management device based on the pressure sensing data, and to determine the adjustment action of the component to be adjusted based on the analysis of the pressure sensing data. The component posture adjustment module 230 is used to adjust the posture of the component to be adjusted based on its initial posture and the adjustment action of the component to be adjusted, so that the user can complete the posture adjustment according to the guidance of the posture management device; wherein, the initial posture is obtained by modeling and simulation analysis based on the user's physiological characteristic data.

[0058] In some embodiments of this application, the pressure sensing data includes first pressure sensing data of the head frame and second pressure sensing data of the positioning pad; the component action determination module 220 includes an adjustment component determination submodule; the adjustment component determination submodule includes a pressure data analysis unit, a pressure area division unit, and an adjustment component determination unit; The pressure data analysis unit is used to perform regional pressure analysis on the first pressure sensing data and the second pressure sensing data respectively to obtain the first pressure region distribution and the second pressure region distribution. The pressure region division unit is used to divide a first region and a second region from the first pressure region distribution and the second pressure region distribution respectively according to a preset pressure threshold; wherein, the first region is the region in the first pressure region distribution where the pressure value is greater than the preset pressure threshold; and the second region is the region in the second pressure region distribution where the pressure value is greater than the preset pressure threshold. The adjustment component determination unit is used to perform shape analysis on the first region and the second region respectively, identify the shape distribution of the first region and the second region, and determine the adjustment component of the body position management device based on the shape distribution of the first region and the second region.

[0059] In some embodiments of this application, the adjustment component determining unit includes a first component determining subunit and a second component determining subunit; The first component determines the subunit, which is used to treat the head frame as the component to be adjusted if the shape distribution of the first region is a strip distribution; The second component determines the subunit, which is used to treat the positioning pad as the component to be adjusted if the shape distribution of the second region is elliptical.

[0060] In some embodiments of this application, the component action determination module 220 includes an adjustment action determination submodule; the adjustment action determination submodule includes a first action determination unit and a second action determination unit; The first action determination unit is used to, if the component to be adjusted is the head frame, calculate and determine the rotation angle of the head frame based on the average pressure difference and average pressure change rate obtained by analyzing the pressure sensing data, and determine the adjustment action of the head frame based on the rotation angle of the head frame. The second action determination unit is used to, if the component to be adjusted is the positioning pad, calculate and determine the pressure adjustment amount of the positioning pad based on the pressure area obtained by analyzing the pressure sensing data, and determine the adjustment action of the positioning pad based on the pressure adjustment amount of the positioning pad.

[0061] In some embodiments of this application, the initial posture is obtained based on modeling and simulation analysis of the user's physiological characteristic data, specifically including: Acquire the user's physiological characteristic data; wherein, the physiological characteristic data includes body surface topology data, image scan data, and individual characteristic indicators; The user's skeletal model is reconstructed based on the image scan data; Based on the body surface topology data and the skeletal model, biomechanical simulation analysis is performed, and corrections are made in conjunction with the individual characteristic indicators to obtain the initial posture of the head frame and the positioning pad in the positioning management device.

[0062] In some embodiments of this application, the step of performing biomechanical simulation analysis based on the body surface topology data and the skeletal model, and then correcting it using the individual characteristic indicators to obtain the initial posture of the head frame and the positioning pad in the positioning management device, specifically includes: Biomechanical simulation analysis is performed based on the body surface topology data and the skeletal model. During the simulation, a multi-level finite element model is constructed based on the skeletal model, and the constraints of the multi-level finite element model are determined by combining the body surface topology data and the skeletal model. The initial support parameters of the body position management device are obtained through simulation analysis. Based on the individual characteristic indicators, the initial support parameters are corrected to obtain the initial posture of the head frame and the positioning pad in the positioning management device.

[0063] This application first collects pressure sensing data from a position management device based on a pressure sensor array, then determines the component to be adjusted based on the pressure sensing data, and subsequently determines the adjustment action of the component. Compared to existing pressure sensing pads that can only provide a thermal map of the pressure area and cannot provide precise data, still requiring adjustment based on experience, this application determines the component to be adjusted and then the adjustment action based on pressure sensing data. This allows for data quantification, and the accuracy of determining the component to be adjusted and its adjustment action can be improved based on the quantified precise data, thereby improving the accuracy of prone surgical position management. Furthermore, based on the initial posture of the component to be adjusted and its adjustment action, the posture is adjusted. Compared to existing manual position management using position pads, which cannot be pre-set and requires multiple manual adjustments during surgery, this application uses modeling and simulation based on the user's physiological characteristic data to pre-set the initial posture of the component to be adjusted. This allows for pre-setting an initial posture that matches the user's physiological characteristics before surgery, ensuring user comfort while reducing or even avoiding intraoperative position adjustments, thereby improving the efficiency of prone surgical position management.

[0064] It should be understood that the system provided in this application corresponds to the aforementioned method. The body position adjustment system for prone surgery provided in this application can realize the body position adjustment method for prone surgery provided in any of the embodiments of this application.

[0065] Adaptively, embodiments of this application also provide a computer device and a computer-readable storage medium.

[0066] The computer device includes: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor; The processor executes the computer program to implement a body position adjustment method for prone surgery according to this application.

[0067] The computer-readable storage medium stores multiple instructions, which are adapted for loading by a processor to execute a body position adjustment method for prone surgery according to this application.

[0068] The above description represents some embodiments of this application, providing a further detailed explanation of the purpose, technical solution, and beneficial effects of this application. It should be understood that the above-described embodiments of this application should not be construed as limiting this application. In particular, any changes, modifications, equivalent substitutions, and variations made by those skilled in the art within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for adjusting body position during prone surgery, characterized in that, The method is applied to a posture management device, the posture management device including a headrest and a posture pad; the method includes: Pressure sensor data of the body positioning management device is collected based on a pressure sensor array; wherein the pressure sensor array is respectively installed at preset locations on the head frame and the body positioning pad; Based on the pressure sensing data, the component to be adjusted in the body position management device is determined, and based on the analysis of the pressure sensing data, the adjustment action of the component to be adjusted is determined. Based on the initial posture of the component to be adjusted, the posture of the component to be adjusted is adjusted according to the adjustment action of the component to be adjusted, so that the user can complete the posture adjustment according to the guidance of the posture management device; wherein, the initial posture is obtained by modeling and simulation analysis based on the user's physiological characteristic data.

2. The method for adjusting body position during prone surgery according to claim 1, characterized in that, The pressure sensing data includes first pressure sensing data of the headrest and second pressure sensing data of the positioning pad; determining the adjustable component of the positioning management device based on the pressure sensing data specifically includes: Regional pressure analysis was performed on the first pressure sensing data and the second pressure sensing data respectively to obtain the first pressure region distribution and the second pressure region distribution. Based on a preset pressure threshold, a first region and a second region are obtained from the first pressure region distribution and the second pressure region distribution, respectively; wherein, the first region is the region in the first pressure region distribution where the pressure value is greater than the preset pressure threshold; and the second region is the region in the second pressure region distribution where the pressure value is greater than the preset pressure threshold. Shape analysis is performed on the first region and the second region respectively to identify the shape distribution of the first region and the second region, and the adjustment component of the body position management device is determined based on the shape distribution of the first region and the second region.

3. The method for adjusting body position during prone surgery according to claim 2, characterized in that, The step of determining the adjustable component of the body position management device based on the shape distribution of the first region and the second region specifically includes: If the shape of the first region is a strip-shaped distribution, then the head frame is used as the component to be adjusted; If the shape of the second region is elliptical, then the positioning pad is used as the component to be adjusted.

4. The method for adjusting body position during prone surgery according to claim 3, characterized in that, The step of determining the adjustment action of the component to be adjusted based on the analysis of the pressure sensing data specifically includes: If the component to be adjusted is the head frame, then the rotation angle of the head frame is calculated and determined based on the average pressure difference and average pressure change rate obtained by analyzing the pressure sensing data, and the adjustment action of the head frame is determined based on the rotation angle of the head frame. If the component to be adjusted is the positioning pad, then the pressure adjustment amount of the positioning pad is calculated and determined based on the pressure area obtained by analyzing the pressure sensing data, and the adjustment action of the positioning pad is determined based on the pressure adjustment amount of the positioning pad.

5. The method for adjusting body position during prone surgery according to claim 1, characterized in that, The initial posture is obtained based on modeling and simulation analysis of the user's physiological characteristic data, specifically including: Acquire the user's physiological characteristic data; wherein, the physiological characteristic data includes body surface topology data, image scan data, and individual characteristic indicators; The user's skeletal model is reconstructed based on the image scan data; Based on the body surface topology data and the skeletal model, biomechanical simulation analysis is performed, and corrections are made in conjunction with the individual characteristic indicators to obtain the initial posture of the head frame and the positioning pad in the positioning management device.

6. The method for adjusting body position during prone surgery according to claim 5, characterized in that, The step of performing biomechanical simulation analysis based on the body surface topology data and the skeletal model, and making corrections based on the individual characteristic indicators, to obtain the initial posture of the head frame and positioning pad in the positioning management device, specifically includes: Biomechanical simulation analysis is performed based on the body surface topology data and the skeletal model. During the simulation, a multi-level finite element model is constructed based on the skeletal model, and the constraints of the multi-level finite element model are determined by combining the body surface topology data and the skeletal model. The initial support parameters of the body position management device are obtained through simulation analysis. Based on the individual characteristic indicators, the initial support parameters are corrected to obtain the initial posture of the head frame and the positioning pad in the positioning management device.

7. A method for adjusting body position during prone surgery according to any one of claims 1 to 6, characterized in that, Also includes: Collect postoperative complication data from the user; Based on a machine learning model, the postoperative complication data, pressure sensing data, adjustment actions of the adjustable component, and initial posture are correlated and analyzed. Based on the correlation analysis results, the initial posture of the adjustable component is optimized.

8. A body position adjustment system for prone surgery, characterized in that, The system is applied to a body positioning management device, which includes a head frame and a positioning pad; the system includes a pressure data acquisition module, a component motion determination module, and a component posture adjustment module. The pressure data acquisition module is used to acquire pressure sensing data of the body position management device based on the pressure sensor array; wherein the pressure sensor array is respectively installed at preset positions on the head frame and the body position pad; The component action determination module is used to determine the component to be adjusted in the body position management device based on the pressure sensing data, and to determine the adjustment action of the component to be adjusted based on the analysis of the pressure sensing data. The component posture adjustment module is used to adjust the posture of the component to be adjusted based on its initial posture and the adjustment action of the component, so that the user can complete the posture adjustment according to the guidance of the posture management device; wherein, the initial posture is obtained by modeling and simulation analysis based on the user's physiological characteristic data.

9. A computer device, characterized in that, include: processor; Memory; A computer program stored in the memory and configured to be executed by the processor; When the processor executes the computer program, it implements a body position adjustment method for prone surgery as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a plurality of instructions adapted for loading by a processor to execute a position adjustment method for prone surgery as described in any one of claims 1 to 7.

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