Prone position operation face pressure adjusting method and system based on pressure induction

Abstract

The invention relates to the technical field of pressure control, in particular to a prone position surgery face pressure adjusting method and system based on pressure induction, and the method comprises the following steps: based on an embedded miniature pressure sensor, detecting the pressure value of a face key area, analyzing the pressure distribution condition, and calculating the face pressure value; the concentrated stress state of each area of the face is analyzed through the pressure value change trend, and face area pressure distribution trend data are obtained. In the invention, through a pressure sensing technology and a dynamic adjustment mechanism, the problem of uneven pressure of the face in a prone position operation can be effectively identified and relieved, pressure distribution can be monitored and analyzed in real time, the pressure of a high-sensitivity area is accurately adjusted to be transferred to a low-sensitivity area, uniform distribution is realized, tissue damage caused by local long-term compression is reduced, and the operation safety is improved. The support force of each pressed point is balanced, the face pressure adjustment is optimized, the distribution stability is improved through pressure fluctuation monitoring and correction, the non-uniform phenomenon caused by fluctuation is avoided, and the surgical comfort and safety are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of pressure control, and in particular to a method and system for adjusting facial pressure during prone position surgery based on pressure sensing. Background Art

[0002] The field of pressure control technology includes technical means to ensure that the pressure of the controlled object remains stable or meets specific requirements under specific conditions through pressure detection, regulation and feedback control. The core content of this technical field is to detect pressure changes through pressure sensing devices, adjust pressure parameters using regulating devices, and combine feedback control mechanisms to achieve dynamic balance or distribution optimization of pressure. Pressure control technology is widely used in medical equipment, industrial manufacturing, aerospace and other fields, especially in scenarios that require high-precision and high-stability pressure management, such as pressure distribution adjustment in surgical support and liquid fluid pressure control.

[0003] Among them, the facial pressure adjustment method for prone surgery refers to a method of detecting the pressure distribution of the patient's face through a pressure sensing device, and combining a dynamic adjustment device to adjust the pressure of the facial support area in real time, such as the method disclosed in the Chinese patent with publication number CN 119033562 A and the name of a prone position special head frame and its use adjustment method. This method aims at the problems of uneven pressure and excessive local pressure at the contact part between the patient's face and the position pad during prone surgery. The pressure sensor is used to collect pressure data of different areas of the face, and the control module is used to analyze the data, and the support structure is adjusted to achieve redistribution of facial pressure to avoid long-term pressure on local areas. The specific technical means include: a plurality of support pads are arranged on a seat frame adapted to the shape of the human face in a liftable manner, wherein the plurality of support pads are independently arranged at intervals, the uppermost part of the support pad is in contact with the human face through a soft pillow, and the lower part of the soft pillow is arranged on a lifting mechanism through a connector, and a pressure sensor is arranged at each support pad position. The lifting mechanism is used to adjust the pressure of the facial support area, such as adjusting the support airbag or deformable material, to ensure dynamic and uniform distribution of the support force.

[0004] Although the existing technology realizes the detection and feedback adjustment of facial pressure through pressure sensing devices, in actual operation, the pressure distribution adjustment of the face still faces certain limitations. Since the layout of the pressure sensor array and the design of the adjustment mechanism are not precise enough, it is easy to cause excessive pressure or uneven local pressure distribution in some highly sensitive areas. Especially under the support of the complex structure of the face, it is difficult to avoid excessive compression of some areas. In actual applications, the existing dynamic adjustment device cannot effectively adapt to the differences in pressure requirements of different areas of the face, resulting in the support adjustment of some areas failing to respond to pressure changes in time, and unable to effectively alleviate the discomfort or tissue damage risks caused by long-term pressure. The changes in pressure fluctuations cannot be fully controlled and corrected, which makes it difficult to maintain a stable state of facial pressure during surgery, resulting in frequent fluctuations in pressure distribution during surgery, which affects the patient's comfort. The existing technology is still insufficient in fine adjustment and pressure fluctuation control, and cannot effectively ensure the continuous stable support and comfortable experience of the face during long-term surgery. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a method and system for adjusting facial pressure during prone surgery based on pressure sensing.

[0006] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: a method for adjusting facial pressure during prone surgery based on pressure sensing, comprising the following steps: S1: Based on embedded micro pressure sensors, the pressure values ​​of key facial areas, including the forehead, brow arch, cheekbones and mandibular area, are detected. The pressure conditions are collected and analyzed. The concentrated stress state is identified based on the pressure change trend. The pressure fluctuation range is extracted. The regional pressure characteristics are summarized. The trend analysis of regional pressure differences and pressure concentration points is estimated to obtain the pressure distribution trend data of the facial area. S2: Based on the pressure distribution trend data of the facial area, extract the pressure value of the high-sensitive area and the carrying capacity of the low-sensitive area, analyze the pressure deviation of the two areas, calculate the transfer feasibility, optimize the pressure transfer process, match the pressure dispersion and carrying capacity, redistribute the pressure of the sensitive area, obtain the regional force state after dispersion, update the regional pressure characteristics, and optimize the adjustment amount of the force area to obtain the optimized force adjustment data set; S3: Based on the optimized force adjustment data set, combined with the elastic parameters of the flexible support material, extract the key force points in the region, identify the buffering requirements of the high-pressure area, optimize the high-pressure buffering adjustment, disperse the pressure of the pressure concentration point, superimpose the buffering adjustment amount and the optimized force distribution value, adjust the distribution balance of the force points, combine the adjusted force characteristics, generate the pressure distribution value after flexibility adjustment, and optimize the balanced distribution of the support points to obtain the support equilibrium state data; S4: Based on the support equilibrium state data, the support equilibrium state is extracted in combination with the pressure fluctuation amplitude, the influence of the fluctuation change on the flexible pressure distribution is analyzed, the pressure deviation value is identified, and the distribution state is optimized. In combination with the pressure fluctuation correction amplitude, the time period distribution deviation is adjusted, the overall pressure equilibrium state is extracted, the dynamic characteristics of the pressure distribution are optimized, and the prone facial pressure state adjustment result is obtained.

[0007] As a further solution of the present invention, the steps for acquiring the facial area pressure distribution trend data are specifically as follows: S111: Based on the embedded micro pressure sensor, the pressure values ​​of the forehead, brow arch, cheekbone and mandibular area are recorded in real time, the pressure value of the sensing point in each area is identified, the pressure value of each point is used as the input variable, and the average pressure value of the area is calculated to obtain the average pressure data of the key facial areas; S112: Based on the average pressure data of the key facial areas, the absolute deviation and square difference of the pressure values ​​of the sensing points are normalized according to the fluctuation range and change trend of the regional pressure values, using the formula: ; Obtain pressure fluctuation data of the facial area; in, Representative area The pressure fluctuation value, Representative area Middle The pressure value of each sensing point, Representative area The average pressure value, Represents the total number of sensor points in the area, is the adjustment factor; S113: Based on the pressure fluctuation data of the facial area, determine whether the pressure fluctuation value of each area exceeds the judgment threshold of concentrated force, calibrate the concentrated force state by setting the threshold, mark the area with a fluctuation value greater than the threshold as a concentrated force area, and obtain the pressure distribution trend data of the facial area.

[0008] As a further solution of the present invention, the step of obtaining the stress state of the dispersed region is specifically as follows: S211: Based on the facial area pressure distribution trend data, analyzing the pressure dispersion of the high-sensitive area, analyzing the deviation between the pressure value of the high-sensitive area and the standard threshold, adjusting the pressure of the high-sensitive area by using a weighting coefficient, and generating the pressure dispersion of the high-sensitive area and the dispersion capacity of the low-sensitive area; S212: calling the pressure dispersion amount of the high-sensitivity area and the dispersion capacity of the low-sensitivity area, analyzing the transfer amount of the pressure from the high-sensitivity area to the low-sensitivity area, and identifying the acceptable transfer amount according to the dispersion capacity upper limit of the low-sensitivity area, using the formula: ; The pressure transfer amount is calculated; in, Indicates the amount of pressure transfer, To adjust the sensitivity coefficient, Represents the pressure value of the highly sensitive area, Dispersed capacity for low-sensitivity areas; S213: The pressure transfer amount is called to redistribute the pressure of the highly sensitive area, and the pressure state of each facial area is updated according to the distribution of the pressure after the pressure transfer, and the facial pressure is balanced and adjusted to obtain the regional force state after the dispersion.

[0009] As a further solution of the present invention, the step of obtaining the optimized force adjustment data set is specifically: S221: Based on the dispersed regional stress state, extract the stress direction, average value and fluctuation value of the boundary points, determine the correction value by differential calculation, adjust the stress state of each boundary point, record the correction value and stress parameters, and obtain the regional boundary stress adjustment state table; S222: Based on the region boundary force adjustment state table, analyze the distribution characteristics of the internal force points, identify the force change trend and the force difference of adjacent points, divide the force distribution range inside the region, update the force parameters and record the changes, and obtain the internal distribution change table of the force region; S223: Based on the internal distribution change table of the force area, the force adjustment values ​​of the internal points and boundary points of the area are extracted, the force data of the entire area are normalized, the area adjustment amount is re-optimized according to the global force balance parameters, the force data is updated, and the optimized force adjustment data set is obtained.

[0010] As a further solution of the present invention, the step of obtaining the pressure distribution value after the flexibility adjustment is specifically as follows: S311: Based on the optimized force adjustment data set, according to the regional force state and the deformation capacity of the flexible support material, the buffer adjustment amount of the high-pressure area is analyzed, the elastic deformation value of the support material is calculated, and the buffer adjustment amount of the high-pressure area is generated in combination with the distribution of key force points in the area; S312: Based on the buffer adjustment amount of the high-pressure area, analyze the pressure distribution of each key stress point, add the buffer adjustment amount to the stress state of the dispersed area, and use the formula: ; Calculate and generate the total pressure value of key stress points; in, Indicates the total pressure value of the key stress point, is the flexible material adjustment coefficient, is the basic pressure value of the dispersed area, is the elastic modulus of the flexible support material, is the material support area, is the elastic deformation value of the support material; S313: According to the total pressure value of the key stress point, the total support pressure of each facial area is identified, the flexible adjustment pressure value of the key stress point is statistically analyzed in the region, and the pressure fluctuation in the region is optimized by smoothing to obtain the pressure distribution value after flexible adjustment.

[0011] As a further solution of the present invention, the step of acquiring the supporting equilibrium state data is specifically as follows: S321: based on the pressure distribution value after the flexibility adjustment, extract the pressure magnitude and corresponding spatial position of each point in the pressure distribution, analyze the pressure change gradient of adjacent points and compare the gradient values, select high and low gradient areas, adjust the flexibility weight of the pressure point, and generate a flexible pressure distribution adjustment table; S322: Based on the flexible pressure distribution adjustment table, extract the adjusted regional pressure distribution data and the support point positions, determine the pressure balance center, identify the support point, the distance between the pressure center and the pressure contribution value, reallocate the support point range, adjust the support point spacing, correct the position parameters, and generate a support point optimization distribution table; S323: Based on the support point optimization distribution table, summarize the support point optimization position parameters, combine with the pressure distribution data, analyze the global pressure distribution ratio of each support point, adjust the spatial position of the support point, optimize the distribution balance, verify the equilibrium state, update the pressure distribution and support point position data, and obtain the support equilibrium state data.

[0012] As a further solution of the present invention, the step of obtaining the result of the prone facial pressure state adjustment is specifically: S411: extracting the pressure fluctuation amplitude and the flexible pressure distribution value based on the support equilibrium state data, analyzing the pressure value change amplitude, screening the key threshold range according to the fluctuation amplitude, and generating a pressure fluctuation and flexible distribution change rate matrix; S412: Cross-correct the pressure fluctuation and flexibility distribution change rate matrix, and analyze the influence of the fluctuation amplitude on the flexible pressure distribution value, using the formula: ; Calculate and generate the corrected pressure fluctuation amplitude; in, Represents the corrected pressure fluctuation amplitude, Represents the pressure fluctuation amplitude, represents the flexible pressure distribution value, Represents the pressure reference value, represents the fluctuation correction factor, represents the flexibility distribution correction coefficient; S413: In combination with the corrected pressure fluctuation amplitude, according to the difference between the pressure reference value of each time period and the current pressure distribution, the deviation of the time period pressure distribution is analyzed, the distribution deviation of each time period is optimized, and the prone facial pressure state adjustment result is obtained.

[0013] A facial pressure adjustment system for prone position surgery based on pressure sensing, the facial pressure adjustment system for prone position surgery based on pressure sensing is used to perform the facial pressure adjustment method for prone position surgery based on pressure sensing, the system comprising: The pressure detection module is based on embedded micro pressure sensors to detect the pressure values ​​of the forehead, brow arch, cheekbone and mandible, extract the pressure change trend of each area, analyze the pressure amplitude difference in each time period, extract the pressure concentrated distribution area, analyze the total regional pressure and pressure proportion, and obtain facial pressure distribution feature data; The pressure dispersion module matches the pressure value of the high-sensitive area with the pressure bearing capacity of the low-sensitive area based on the facial pressure distribution feature data, extracts the part of the pressure value of the high-sensitive area that exceeds the range, analyzes the pressure transfer amount of the high-sensitive area and the remaining capacity of the low-sensitive area, analyzes the pressure state after the transfer, optimizes the pressure distribution of the high-sensitive area, and obtains the pressure dispersion adjustment state data; The flexible adjustment module calls the elastic parameters of the flexible support material based on the pressure dispersion adjustment state data, extracts the buffer adjustment value corresponding to the high-pressure area, superimposes the adjustment value of the high-pressure area with the dispersion state, analyzes the pressure difference between the high-pressure area and the low-pressure area after superposition, extracts the distribution parameters of the flexible support points, and obtains the support equilibrium state data; The fluctuation correction module extracts the time period fluctuation amplitude of the pressure value based on the support equilibrium state data, cross-compares the fluctuation amplitude with the regional pressure equilibrium value, extracts the influence of the pressure fluctuation on the dynamic value distributed in the region, and cumulatively analyzes the fluctuation amplitude and the flexible support point adjustment value to obtain the prone facial pressure state adjustment result.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, through pressure sensing technology and dynamic adjustment mechanism, it is possible to more effectively identify and deal with the problem of uneven pressure on the face during prone position surgery. Based on real-time monitoring and analysis of pressure distribution, it is possible to accurately identify the pressure concentration in high-sensitive areas and transfer pressure from areas to low-sensitive areas in a targeted manner. This not only ensures that the pressure in different areas of the face is evenly distributed during surgery, but also significantly reduces tissue damage caused by long-term local pressure. Combined with the buffering capacity of flexible support materials, precise buffering adjustments are made to local high-pressure areas, so that the supporting force of each pressure point is more balanced, thereby achieving more detailed and optimized facial pressure regulation. By monitoring and correcting pressure fluctuations, the stability of pressure distribution is further improved, and uneven pressure caused by excessive fluctuations is avoided. This not only effectively improves the risk of local high pressure on the face in traditional methods, but also achieves more balanced and stable facial support through more sophisticated dynamic adjustments, effectively ensuring facial comfort and safety during surgery. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic diagram of the workflow of the present invention; Figure 2 It is a flow chart of the pressure distribution trend data of the facial area in the present invention; Figure 3 It is a flow chart of the stress state of the dispersed region in the present invention; Figure 4 It is a flow chart of the optimized force adjustment data set in the present invention; Figure 5 It is a flow chart of the pressure distribution value after flexibility adjustment in the present invention; Figure 6 A flow chart of supporting equilibrium state data in the present invention; Figure 7 The figure is a flow chart of the adjustment result of the facial pressure state in the prone position in the present invention. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0017] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined. Example 1

[0018] See also Figure 1 The present invention provides a technical solution: a method for adjusting facial pressure during prone surgery based on pressure sensing, comprising the following steps: S1: Based on embedded micro pressure sensors, the pressure values ​​of key facial areas, including the forehead, brow arch, cheekbones and mandibular area, are detected. The pressure conditions are collected and analyzed. The concentrated stress state is identified based on the pressure change trend. The pressure fluctuation range is extracted. The regional pressure characteristics are summarized. The trend analysis of regional pressure differences and pressure concentration points is estimated to obtain the pressure distribution trend data of the facial area. S2: Based on the pressure distribution trend data of the facial area, the pressure value of the high-sensitive area and the carrying capacity of the low-sensitive area are extracted, the pressure deviation between the two areas is analyzed, the transfer feasibility is calculated, the pressure transfer process is optimized, the pressure dispersion amount and the carrying capacity are matched, the pressure of the sensitive area is redistributed, the regional force state after dispersion is obtained, the regional pressure characteristics are updated, and the adjustment amount of the force area is optimized to obtain the optimized force adjustment data set; S3: Based on the optimized force adjustment data set, combined with the elastic parameters of the flexible support material, extract the key force points in the region, identify the buffering requirements of the high-pressure area, optimize the high-pressure buffer adjustment, disperse the pressure of the pressure concentration point, superimpose the buffer adjustment amount and the optimized force distribution value, adjust the distribution balance of the force points, combine the adjusted force characteristics, generate the pressure distribution value after flexibility adjustment, and optimize the balanced distribution of the support points to obtain the support equilibrium state data; S4: Based on the support equilibrium state data, the support equilibrium state is extracted in combination with the pressure fluctuation amplitude, the influence of fluctuation changes on the flexible pressure distribution is analyzed, the pressure deviation value is identified, and the distribution state is optimized. In combination with the pressure fluctuation correction amplitude, the time period distribution deviation is adjusted, the overall pressure equilibrium state is extracted, the dynamic characteristics of the pressure distribution are optimized, and the pressure state adjustment result of the prone face is obtained.

[0019] The method for adjusting facial pressure in prone surgery based on pressure sensing of the present invention is proposed based on the facial pressure adjustment structure in the prior art, which includes a plurality of support pads that can be lifted and lowered on a frame that is adapted to the shape of the human face, wherein the plurality of support pads are independently arranged at intervals, the top of the support pads are in contact with the human face through a soft pillow made of a flexible support material, and the bottom of the soft pillow is arranged on a lifting mechanism through a connector, and the entire operation process starts with pressure detection, through an embedded micro pressure sensor, the embedded micro pressure sensor is arranged at each support pad position, and is used to monitor the pressure given to the support pad by the face, and the support pad is mainly used to support the patient's face, ensuring that when the patient is in a prone position, the key areas of the face (such as the forehead, brow arch, cheekbone and mandible) are evenly supported to avoid local excessive pressure. The lifting mechanism is used to adjust the pressure distribution of these areas, and cooperates with the soft pillow made of a flexible support material, and through the high elasticity of the flexible support material, it can be adaptively deformed according to the pressure requirements of different parts of the face, thereby effectively reducing the pressure on sensitive areas. Embedded micro pressure sensors are precisely set in the key areas of the corresponding facial support. Through these sensors, the system can monitor and collect the pressure values ​​of various parts of the face in real time, providing data support for subsequent pressure assessment and adjustment. Due to the unevenness of the human facial bones, the use of conventional soft support pads will inevitably cause different areas of the face to bear different pressures. For example, the forehead, brow arch, cheekbone and mandible, where the facial bones are more prominent, will bear greater pressure, which can easily cause blood circulation in the skin of this area to be blocked and produce pressure damage. The sensing points in each area of ​​the present invention can sense subtle pressure changes, and the data is recorded and analyzed. First, the pressure distribution is evaluated, and then the concentrated force state of each area of ​​the face is analyzed through the change trend to generate pressure distribution trend data. For the concentrated force area, by further calculating the pressure dispersion of the high-sensitive area and the bearing capacity of the low-sensitive area, the possibility and amount of pressure transfer from the high-sensitive area to the low-sensitive area are analyzed to complete the preliminary pressure redistribution. Combined with the characteristics of flexible support materials (such as high-elastic materials), the pressure distribution of the high-pressure area is optimized through the buffer adjustment of the lifting mechanism, and the lifting mechanism is automatically controlled by the system. The embedded pressure sensor collects pressure data from different areas of the patient's face in real time. Based on this data, the system algorithm analyzes the pressure concentration in the highly sensitive area and the carrying capacity of the low-sensitive area. The pressure transfer amount from the high-sensitive area to the low-sensitive area is calculated through the pressure dispersion formula. At the same time, the elastic modulus and deformation capacity of the flexible support material are combined to dynamically optimize the pressure distribution in the high-pressure area. When the pressure in the highly sensitive area is too high, the lifting mechanism combines with the flexible support material to buffer and disperse the pressure to the low-pressure area through deformation, thereby achieving a gradual redistribution of pressure and ensuring that the carrying capacity of the low-sensitive area is not exceeded. The pressure transfer process is dynamically controlled by the algorithm, which monitors the pressure state of each area in real time and finely optimizes the pressure distribution in combination with the dynamic adjustment capability of the flexible support pad.The entire system achieves dynamic balance of pressure distribution through sensor data collection, algorithm analysis and optimization, and flexible pad adjustment, avoiding tissue damage caused by local high pressure on the face and ensuring the safety and comfort of prone surgery. The dispersed pressure is superimposed on the adjustment amount of the flexible support material to optimize the support state of each key stress point, and finally generate the pressure distribution value after flexible adjustment. To ensure the dynamic balance of the entire pressure adjustment process, the system will also perform real-time detection of the support balance state, correct the pressure fluctuation amplitude, optimize the pressure distribution state in each time period, and finally achieve balanced and stable support of facial pressure during prone surgery.

[0020] During the implementation process, the actual needs of the prone surgical environment were fully considered. Embedded micro pressure sensors were arranged in the key areas where the patient contacts the surgical support surface to ensure that the real-time changes in pressure in each area can be accurately sensed, while preventing patients from suffering from tissue ischemia or damage due to excessive local pressure during long-term surgery. The lifting mechanism combined with the application of flexible support materials improves the adaptability of pressure distribution adjustment. Flexible support materials can produce corresponding elastic deformation according to the stress conditions in the high-pressure area, thereby reducing the local pressure peak. The system can effectively identify the sensitivity differences of different facial areas by dynamically analyzing the stress state of each area, and gradually disperse the load of the high-pressure area to the low-sensitivity area, ensuring that the pressure transfer process will not cause excessive pressure accumulation in the low-sensitivity area. The design of the entire process is based on the actual needs of the surgical environment and the anatomical characteristics of the human body, so as to achieve uniform pressure distribution and improve patient comfort and surgical safety.

[0021] The specific method of adjusting and dispersing pressure is as follows: the pressure adjustment is first based on the real-time data obtained by the pressure sensor to determine the pressure concentration state of the high-sensitive area. By analyzing the fluctuation range of the pressure value and the concentrated force characteristics, the system matches the pressure dispersion amount of the high-sensitive area with the bearing capacity of the low-sensitive area, and gradually transfers the pressure that exceeds the range of the high-sensitive area to the low-sensitive area. The transfer and dispersion of pressure are mainly carried out in the following ways: using the pressure sensor to obtain the pressure data of the high-sensitive area in real time, determine the pressure concentration state, and combine the fluctuation range and force characteristics to analyze the pressure dispersion requirements of the high-sensitive area and the bearing capacity of the low-sensitive area, and gradually transfer the pressure that exceeds the threshold in the high-sensitive area to the low-sensitive area. The maximum bearing pressure upper limit of the low-sensitive area will be identified first to ensure that the transferred pressure will not have a negative impact on the area. After completing the pressure transfer, the system uses the elastic properties of the flexible support material to buffer and adjust the high-pressure area, combines the material deformation with the pressure value, further refines the pressure distribution optimization, monitors the pressure fluctuation of the entire adjustment process, corrects the abnormal value, smoothes the pressure distribution, and ensures dynamic stability. By optimizing the support state of the key force points, pressure uniformity and long-term support stability are achieved.

[0022] The present invention uses embedded sensor monitoring and a lifting mechanism combined with the dynamic adjustment response of flexible support materials, and optimizes pressure distribution based on data analysis. It can not only effectively alleviate the problem of excessive force in high-pressure areas of the face, but also ensure the dynamic balance of pressure distribution. It is highly operational and practical in actual surgical scenarios, providing patients with a more comfortable surgical support experience while reducing surgical risks.

[0023] The facial area pressure distribution trend data includes facial pressure distribution information, stress status of key areas, and pressure concentration data of each area. The regional stress status after dispersion includes the pressure transfer results of high-sensitive areas, the load-bearing status of low-sensitive areas, and the pressure dispersion balance results. The optimized force adjustment data set includes the optimized regional pressure dispersion value, the pressure reduction value of high-sensitive areas, and the load-bearing adjustment value of low-sensitive areas. The pressure distribution value after flexible adjustment includes the buffer parameter of high-pressure area, the distribution status of flexible support points, and the regional force uniformization data. The support balance status data includes the support point balance distribution results, the support force optimization distribution value, and the overall pressure balance parameters. The prone facial pressure status adjustment results include the optimized pressure distribution status, the fluctuation amplitude correction data, and the overall facial pressure balance index.

[0024] See also Figure 2 ,The steps for obtaining the facial area pressure distribution trend data are as follows: S111: Based on the embedded micro pressure sensor, the pressure values ​​of the forehead, brow arch, cheekbone and mandibular area are recorded in real time, the pressure value of the sensing point in each area is identified, the pressure value of each point is used as the input variable, and the average pressure value of the area is calculated to obtain the average pressure data of the key facial areas; Data collection is performed through partitioning. Each sensing point records the continuously sampled pressure signal as pressure time series data. The time series data of each area is preliminarily processed. The average pressure value of each sensing point is calculated to remove outliers and noise in the sampling signal. The removal of outliers is completed by setting upper and lower thresholds. The range of the threshold is set according to the sensor calibration data and the reasonable physiological range of pressure. The missing data is supplemented by the linear interpolation method after the outliers are removed. After the supplement, the pressure mean of each area is calculated to finally generate the average pressure data of the key areas of the face.

[0025] S112: Based on the average pressure data of the key areas of the face, the absolute deviation and square difference of the pressure values ​​of the sensing points are normalized according to the fluctuation range and change trend of the regional pressure values, using the formula: ; Obtain pressure fluctuation data of the facial area; in, Representative area The pressure fluctuation value, Representative area Middle The pressure value of each sensing point, Representative area The average pressure value, Represents the total number of sensor points in the area, is the adjustment factor; The formula is useful because it combines the absolute deviation and squared difference of regional pressure fluctuations and introduces an adjustment factor Improved the ability to identify areas with large pressure fluctuations, achieving higher calculation accuracy; in the formula Representative area The pressure fluctuation value, Representative area Middle The pressure value of each sensing point, Representative area The average pressure value, Represents the total number of sensor points in the area, To adjust the coefficient, used to increase the influence of the square error, the pressure data sampling frequency and the coverage of the sensing points are monitored to obtain , pressure value at the sensing point The average pressure value of the area is directly collected by the sensor pass The adjustment factor is calculated Corrected settings based on historical data; Assume that the number of sensor points in a certain area is The collected pressure value is ; The regional average pressure is calculated according to the formula: ; Then calculate the absolute deviation of the regional pressure fluctuation value according to the formula: ; Calculate the square difference and introduce the adjustment factor : ; Finally, the regional pressure fluctuation value is obtained: ; The result shows that the regional pressure fluctuation value of 1.34 reflects that the pressure change in this area is relatively large, which can be used to determine the subsequent concentrated stress area.

[0026] S113: judging whether the pressure fluctuation value of each area exceeds the judgment threshold of concentrated force according to the pressure fluctuation data of the facial area, calibrating the concentrated force state by setting the threshold, marking the area with a fluctuation value greater than the threshold as the concentrated force area, and obtaining the pressure distribution trend data of the facial area; The pressure fluctuation value is compared with the set concentrated force threshold. The concentrated force threshold is set as the upper quantile by analyzing the distribution of pressure fluctuation values ​​in multiple experimental data. The area is marked as the concentrated force area. First, the changing trend of pressure fluctuation is analyzed by the fluctuation value time series curve, the range of fluctuation value in each area is calculated, and the fluctuation value curve is locally smoothed by the five-point sliding mean method. Finally, the smoothed fluctuation value is compared with the set threshold point by point to obtain the concentrated force area, and finally the pressure distribution trend data of the facial area is obtained.

[0027] See also Figure 3 , the specific steps for obtaining the regional stress state after dispersion are as follows: S211: Based on the facial area pressure distribution trend data, analyzing the pressure dispersion of the high-sensitive area, analyzing the deviation between the pressure value of the high-sensitive area and the standard threshold, using a weighted coefficient to adjust the pressure of the high-sensitive area, and generating the pressure dispersion of the high-sensitive area and the dispersion capacity of the low-sensitive area; The pressure distribution trend data of the facial area is called to analyze the pressure dispersion of the high-sensitive area and the dispersion capacity of the low-sensitive area. The pressure values ​​of the high-sensitive area and the low-sensitive area are classified and calculated. The pressure value of the high-sensitive area needs to be statistically processed according to the pressure time series data collected multiple times. The mean is calculated after removing the abnormal points and noise, and the maximum, minimum and fluctuation range of the pressure value are further extracted to determine whether the pressure in the high-sensitive area exceeds the threshold, and the high-sensitive area is divided accordingly. The threshold is selected based on the upper limit of the high-pressure interval of the historical data. The dispersion capacity of the low-sensitive area is calculated by the product of the pressure-bearing area of ​​its single area and the material stress intensity. The pressure-bearing area is comprehensively determined by the number of pressure sensors distributed in the area and the sensing range of a single sensor. The stress intensity is provided by the material experimental data. After completing the above-mentioned area division, the pressure distribution trend data is called for area matching, and the pressure distribution correlation between the high-sensitive area and the low-sensitive area is further calculated to obtain the matching data of the pressure dispersion of the high-sensitive area and the dispersion capacity of the low-sensitive area for the subsequent calculation and optimization of the pressure transfer amount.

[0028] S212: Call the pressure dispersion amount of the high-sensitivity area and the dispersion capacity of the low-sensitivity area, analyze the transfer amount of the pressure from the high-sensitivity area to the low-sensitivity area, and identify the acceptable transfer amount according to the upper limit of the dispersion capacity of the low-sensitivity area, using the formula: ; The pressure transfer amount is calculated; in, Indicates the amount of pressure transfer, To adjust the sensitivity coefficient, Represents the pressure value of the highly sensitive area, Dispersed capacity for low-sensitivity areas; The formula is useful in that by using the pressure value of the high-sensitivity area Distribute capacity with less sensitive areas Association, and introduce nonlinear adjustment coefficient , in the pressure transfer calculation, the pressure transfer rate of the highly sensitive area and the dispersion acceptance capacity of the low-sensitive area are effectively balanced, thereby improving the accuracy and stability of the pressure distribution; To adjust the sensitivity coefficient, it is used to adjust the impact of pressure transfer in highly sensitive areas on the dispersion capacity. Indicates The pressure value of the high-sensitivity area is obtained by collecting the time series data of the pressure sensor multiple times, removing the outliers and calculating the average value, and the dispersion capacity of the low-sensitivity area is obtained. It is calculated by multiplying the pressure-bearing area of ​​the region by the material bearing limit. It is a nonlinear adjustment item. By controlling the transfer rate, the influence of the high pressure value in the high-sensitive area on the dispersion capacity of the low-sensitive area is reduced, and finally the pressure transfer amount is obtained. ; Set the pressure value of the highly sensitive area 10, 12, 15, dispersed capacity in low-sensitivity areas The adjustment coefficient is 20, 25, 30. ,The pressure sensing value is measured by the sensor, and the capacity of the low-sensitivity area is 100, 125, and 150 square units according to the area, and the material bearing limit is set to 2 units of pressure, through the regional pressure value collection and capacity calculation; Substituting into the formula: ; First calculation: ; Second calculation: ; The third calculation: ; Total pressure transfer: ; The result shows that the total transferred pressure is 349.05, indicating that the pressure in the high-sensitivity area can be balanced and dispersed to the low-sensitivity area after calculation, ensuring that the pressure distribution is within a reasonable range and providing support for the subsequent dispersion state.

[0029] S213: calling the pressure transfer amount to redistribute the pressure of the highly sensitive area, updating the pressure state of each facial area according to the distribution of the pressure transfer, adjusting the balance of the facial pressure, and obtaining the regional force state after the dispersion; By combining the initial pressure distribution of the highly sensitive area, the pressure is further redistributed. The dispersion capacity of the low-sensitive area and the pressure release standard of the high-sensitive area need to be considered in the distribution process. The pressure distribution trend data and the pressure transfer amount are called to perform pressure distribution in each area. The upper and lower limits of the pressure bearing capacity of the area are set, and the redistribution is completed by using the pressure transfer iteration method. First, the maximum pressure release ratio of each highly sensitive area is set, and the residual pressure value after each release is calculated according to the transfer amount, and the bearing state of the low-sensitive area is updated. The real-time distribution of pressure is completed through the pressure release formula, and the residual pressure of the high-sensitive area is gradually transferred to the low-sensitive area. At the same time, the pressure state of each area is updated. For the pressure of the high-sensitive area that has not been completely transferred, the residual pressure transfer amount is adjusted again until the pressure of all areas tends to be balanced. The stress state of the dispersed area is evaluated through the regional pressure distribution diagram to determine whether the preset equilibrium state is reached after dispersion, and finally the regional stress state after dispersion is generated.

[0030] See also Figure 4 , the steps for obtaining the optimized force adjustment data set are as follows: S221: based on the dispersed regional stress state, extract the stress direction, average value and fluctuation value of the boundary points, determine the correction value by differential calculation, adjust the stress state of each boundary point, record the correction value and stress parameters, and obtain the regional boundary stress adjustment state table; By analyzing the boundary point data point by point, the specific force information of each boundary point in three-dimensional space is obtained, the force value of each boundary point is decomposed into components along different directions, and the average value and standard deviation of the component data of all boundary points are calculated as the basic statistical characteristics of the overall force of the boundary. The force difference between adjacent points is compared through differential calculation, the points with abnormal changes are identified and the correction value of the point is calculated. The correction value is iteratively adjusted by setting the force balance condition. The initial correction value can be initialized according to the set threshold ratio and updated in subsequent iterations. The application of the correction value is proportionally distributed to the components in the force direction, and the force state of each boundary point is adjusted in real time until the overall fluctuation value is less than the preset stable value. Finally, the correction value and the adjusted force parameters of each boundary point are recorded, and the regional boundary force adjustment state table is output.

[0031] S222: Based on the regional boundary force adjustment state table, analyze the distribution characteristics of the internal force points, identify the force change trend and the force difference of adjacent points, divide the force distribution range inside the region, update the force parameters and record the changes, and obtain the internal distribution change table of the force region; For the stress points inside the area, the total stress value of each point in different directions is calculated, and the overall trend is statistically analyzed in combination with the adjustment value of the boundary point. The area is divided into several sub-areas, and the stress distribution characteristics inside each sub-area are analyzed point by point to identify the area range with a large difference in stress between adjacent points. The associated stress model between the boundary points and the internal points is used to infer the concentrated stress center point of the sub-area, and the sub-area is classified according to its influence weight on the overall area. The stress parameters in each sub-area are adjusted, and the parameter values ​​are iteratively corrected multiple times in combination with the stress change trend until the fluctuation value inside the sub-area meets the set conditions. Finally, the internal force distribution range and change record of each area are obtained, and a distribution change table of the stress area is generated.

[0032] S223: based on the internal distribution change table of the force area, extract the force adjustment values ​​of the internal points and boundary points of the area, normalize the force data of the entire area, re-optimize the area adjustment amount according to the global force balance parameter, update the force data, and obtain the optimized force adjustment data set; First, the force values ​​of all regional points are dimensionless to remove the influence of the force size unit, so that the force data between different regions are comparable. The final adjustment amount of each point is determined according to the force adjustment value and the global force balance parameter. The adjustment amount is calculated in combination with the force balance condition of the entire region, and the historical force state of each point is weighted during the adjustment process to ensure data continuity and optimization effect. Through the gradual iterative optimization of the data of the entire region, the force data of all points are finally updated on the basis of satisfying the global balance condition, and the optimized force adjustment data set is generated to complete the overall optimization of facial pressure adjustment in pressure-sensing prone surgery.

[0033] See also Figure 5 , the specific steps for obtaining the pressure distribution value after flexibility adjustment are: S311: Based on the optimized force adjustment data set, according to the regional force state and the deformation capacity of the flexible support material, the buffer adjustment amount of the high-pressure area is analyzed, the elastic deformation value of the support material is calculated, and the buffer adjustment amount of the high-pressure area is generated in combination with the distribution of key force points in the area; By analyzing the optimized regional stress state and the deformation capacity of the flexible support material, the buffering adjustment amount of the high-pressure area is calculated, and the key stress points are extracted from the optimized stress adjustment data set according to the pressure value of each high-pressure area. Combined with the elastic modulus, support area and deformation of the support material, the buffering capacity of the support material is defined as the deformation of the material under pressure multiplied by the effective support area. According to the regional affiliation and pressure concentration of each stress point, the stress points in the region whose pressure values ​​exceed or approach the elastic critical value are judged, and the pressure release caused by their deformation is calculated. Further combined with the mechanical parameters of the support material and the distribution of stress points in the region, the buffering effect of the support material is dispersed to each stress point, and finally the buffering adjustment amount of the high-pressure area is generated to provide support for subsequent pressure superposition calculations.

[0034] S312: Based on the buffer adjustment amount in the high-pressure area, analyze the pressure distribution of each key stress point, and superimpose the buffer adjustment amount on the stress state of the dispersed area, using the formula: ; Calculate and generate the total pressure value of key stress points; in, Indicates the total pressure value of the key stress point, is the flexible material adjustment coefficient, is the basic pressure value of the dispersed area, is the elastic modulus of the flexible support material, is the material support area, is the elastic deformation value of the support material; The formula is useful in that by incorporating the elastic modulus of the support material , support area and shape The buffer capacity of the dispersed area has a basic pressure value. Optimize and introduce nonlinear adjustment coefficient , which effectively enhances the flexibility and accuracy of the calculation, so that the deformation regulation of the flexible support material can reflect the dynamic adjustment ability under different pressure distributions; It is the adjustment coefficient of the flexible material, which is used to describe the flexible material under different basic pressure values. The dynamic adjustment capability under the condition of the flexible material is obtained by fitting the experimental data of the flexible material. is the dispersed basic pressure value, extracted from the optimized regional force adjustment data set. The elastic modulus of the supporting material is obtained directly through laboratory mechanical testing. is the effective force-bearing area of ​​the support material, which is calculated by the geometric distribution of the support points and the material contact area. is the deformation variable, which is calculated based on the relationship between the elastic modulus and pressure of the material, and finally obtained It is the total pressure value of the key stress point; Assume the base pressure value of the dispersed area =12, elastic modulus of flexible material is 50, the support area is 2, shape variable is 0.1, adjustment coefficient It was determined to be 0.05 based on experimental fitting; Substituting into the formula: ; Calculate the buffer adjustment: ; Calculate the total pressure value: ; The results show that the total pressure value of the key stress points is 18.25, indicating that the flexible support material has a significant optimization effect on the dispersed pressure. After calculating the pressure values ​​of all key stress points using this formula, the flexible adjusted pressure value of each stress point can be obtained, providing an accurate pressure optimization basis for further generating the flexible adjusted pressure distribution value.

[0035] S313: According to the total pressure value of the key stress point, the total support pressure of each area of ​​the face is identified, the flexible adjustment pressure value of the key stress point is statistically analyzed in the area, and the pressure fluctuation in the area is optimized by smoothing to obtain the pressure distribution value after the flexibility adjustment; By conducting statistics and distribution analysis on pressure points area by area, the total support pressure value of the facial area is calculated, the adjusted pressure values ​​of all key stress points are attributed to their corresponding facial areas, the regional coordinates of each key stress point are extracted, and the regional pressure is integrated according to the distribution of the stress points. The pressure value of each area is weighted summed to obtain the total regional pressure value. For areas with large pressure value fluctuations, the pressure distribution is further smoothed by the sliding average method, and the five-point moving average method is used to locally adjust the pressure value in the area to avoid pressure deviation caused by abnormal pressure values ​​of individual stress points. After the regional pressure value is adjusted to a stable state, combined with the total amount and distribution range of the regional pressure, the final distribution state is further verified through the regional distribution map, and finally the flexibly adjusted pressure distribution value is generated to provide complete optimized pressure distribution data for further improving the facial support state.

[0036] See also Figure 6 , the specific steps for obtaining the supporting equilibrium state data are: S321: based on the pressure distribution value after flexibility adjustment, extract the pressure magnitude and corresponding spatial position of each point in the pressure distribution, analyze the pressure change gradient of adjacent points and compare the gradient values, select high and low gradient areas, adjust the flexibility weight of the pressure point, and generate a flexible pressure distribution adjustment table; The specific position coordinates of each pressure value in three-dimensional space are recorded point by point, and the pressure gradient between each point is calculated. The pressure gradient change value of adjacent points is obtained by differential calculation, and the gradient values ​​are compared to screen out high-gradient and low-gradient areas. The core point with the most drastic pressure change in the high-gradient area is determined by calculating the cumulative gradient value of each point. The low-gradient area is screened by the mean and fluctuation range of the pressure value to determine the stable distribution point, and the flexibility weight of each area is adjusted. The weight adjustment is based on the spatial position of the point and the surrounding gradient value. A lower flexibility weight is assigned to the high-gradient area to reduce the pressure difference, and a higher flexibility weight is assigned to the low-gradient area to enhance the support capacity. The adjusted flexibility weight value of each point is recorded, and combined with the pressure distribution gradient characteristics, a flexible pressure distribution adjustment table is generated to provide basic data for subsequent support optimization.

[0037] S322: Based on the flexible pressure distribution adjustment table, extract the adjusted regional pressure distribution data and the support point positions, determine the pressure balance center, identify the support point, the distance between the pressure center and the pressure contribution value, reallocate the support point range, adjust the support point spacing, correct the position parameters, and generate the support point optimization distribution table; The contribution of each support point to the pressure is calculated, and the balance center of the regional pressure is determined. The determination of the pressure balance center is based on the weighted average of the pressure value of each point and its spatial position. By traversing the pressure data around the support point, the distance value between the support point and the pressure balance center is identified, and the optimized distribution of the support points in the region is calculated in combination with the actual pressure contribution value of each support point. The distribution range of the support points is re-divided. According to the relationship between the pressure contribution value and the distance from the balance center, the support points are appropriately moved closer to the pressure concentration area to reduce the pressure center offset, and the spacing between the support points is adjusted. The spacing correction is based on the flexibility weight. The spacing between support points in the low gradient area is appropriately increased, and the spacing between support points in the high gradient area is reduced to ensure a more uniform distribution of the support points. Finally, the specific position parameters of the support points are corrected, and an optimized distribution table of support points is generated.

[0038] S323: Based on the support point optimization distribution table, the support point optimization position parameters are summarized, and combined with the pressure distribution data, the global pressure distribution ratio of each support point is analyzed, the lifting mechanism is controlled to work, the lifting mechanism drives the support point to move, the spatial position of the support point is adjusted, the distribution balance is optimized, the equilibrium state is verified, the pressure distribution and the support point position data are updated, and the support equilibrium state data is obtained; Calculate the proportion of each support point in the global pressure distribution, further optimize the spatial position of the support point, determine the distribution range of too high or too low pressure points through statistical analysis of the global support point pressure distribution ratio, make necessary spatial position adjustments to the support points, control the operation of the lifting mechanism, and drive the support points to move. The principle of adjustment is to enhance the support effect in areas with excessive pressure, while reducing support redundancy in areas with too little pressure. The balance of optimized distribution is achieved by checking the pressure around each support point point by point. Continue to adjust the support point position for areas that have not reached a balanced state, and verify whether the pressure balance state of the entire area meets the design requirements. Update the optimized position and flexible pressure distribution data of each support point to form the final balanced optimization result of pressure distribution and support point position, output support balance state data, and provide support for precise adjustment of facial pressure distribution in prone surgery.

[0039] See also Figure 7 , the specific steps for obtaining the results of the prone facial pressure state adjustment are: S411: based on the support equilibrium state data, extract the pressure fluctuation amplitude and the flexible pressure distribution value, analyze the pressure value change amplitude, screen the key threshold range according to the fluctuation amplitude, and generate the pressure fluctuation and flexible distribution change rate matrix; Firstly, the pressure fluctuation amplitude in each time period is split, and the fluctuation amplitude data sequence of each time period is obtained by calculating the pressure value at each time point and the pressure difference value at the adjacent time points. The change of the flexible pressure distribution value in the corresponding time period is extracted, and the ratio between the flexible pressure distribution value and the baseline pressure is calculated as the flexible pressure deviation factor. Then, the fluctuation amplitude data and the flexible pressure deviation factor of all time periods are screened, and the time period data with small fluctuation amplitude or insignificant difference between the deviation factor and the baseline value are eliminated to generate the pressure fluctuation and flexibility distribution change rate matrix.

[0040] S412: Cross-correct the pressure fluctuation and flexibility distribution change rate matrix, and analyze the influence of the fluctuation amplitude on the flexible pressure distribution value, using the formula: ; Calculate and generate the corrected pressure fluctuation amplitude; in, Represents the corrected pressure fluctuation amplitude, Represents the pressure fluctuation amplitude, represents the flexible pressure distribution value, Represents the pressure reference value, represents the fluctuation correction factor, represents the flexibility distribution correction coefficient; The benefit of the formula is that the balance of the influence of the flexible pressure on the fluctuation is corrected by the product relationship between the flexible pressure distribution value and the pressure fluctuation amplitude, and the weight parameter of the pressure reference value is introduced to optimize the correction efficiency of the fluctuation range. First, get the fluctuation range parameters By analyzing the pressure values ​​in the time series and calculating the fluctuation range in each time period (for example, the difference between the maximum and minimum pressure values ​​within 1 second is taken as the fluctuation range), we can get The specific value of the flexible pressure distribution value The flexible pressure value distribution of each time period is compared with the reference pressure value through the pressure sensor data acquisition. For comparison, the baseline pressure value Obtained from the mean of historical data, and the weight parameter and It is calculated through the correlation between the flexible pressure and the reference pressure change, and finally substituted into the formula for calculation; set up: , , , , ; Enter the formula to calculate: ; The result shows that the corrected pressure fluctuation amplitude is 5.97, which represents the correction value of pressure fluctuation to the flexible pressure distribution and can be used as a fluctuation correction input item in subsequent calculations to optimize the adjustment coefficient.

[0041] S413: combining the corrected pressure fluctuation amplitude, analyzing the deviation of the pressure distribution in each time period according to the difference between the pressure reference value and the current pressure distribution in each time period, optimizing the distribution deviation in each time period, and obtaining the result of the facial pressure state adjustment in the prone position; Firstly, the deviation between the corrected pressure fluctuation amplitude and the baseline pressure difference is analyzed. For the corrected pressure fluctuation amplitude data sequence, the deviation range of the pressure distribution is obtained by calculating the standard deviation between the pressure distribution and the baseline value in each time period. At the same time, the pressure distribution deviation value in each time period is optimized. The corrected fluctuation amplitude is used as the weight parameter to weight the distribution deviation value to further calculate the adjustment coefficient of the distribution deviation value. The adjustment coefficient is normalized according to the change rate of the distribution deviation value. Finally, the flexible pressure distribution state of each time period is smoothly optimized to generate the pressure state adjustment result of the prone face.

[0042] The facial pressure adjustment system for prone position surgery based on pressure sensing is used to perform the facial pressure adjustment method for prone position surgery based on pressure sensing, and the system comprises: The pressure detection module is based on embedded micro pressure sensors to detect the pressure values ​​of the forehead, brow arch, cheekbone and mandible, extract the pressure change trend of each area, analyze the pressure amplitude difference in each time period, extract the pressure concentrated distribution area, analyze the total regional pressure and pressure proportion, and obtain facial pressure distribution feature data; Based on the facial pressure distribution feature data, the pressure dispersion module matches the pressure value of the high-sensitive area with the pressure bearing capacity of the low-sensitive area, extracts the part of the pressure value of the high-sensitive area that exceeds the range, analyzes the pressure transfer amount of the high-sensitive area and the remaining capacity of the low-sensitive area, analyzes the pressure state after the transfer, optimizes the pressure distribution of the high-sensitive area, and obtains the pressure dispersion adjustment state data; according to the pressure dispersion adjustment state data, the adjustment parameters of each lifting mechanism are obtained, and the multiple lifting mechanisms are controlled to work according to the adjustment parameters. The multiple lifting mechanisms drive each support point to move, thereby dispersing the pressure value. Based on the pressure dispersion adjustment state data, the flexible adjustment module calls the elastic parameters of the flexible support material, extracts the buffer adjustment value corresponding to the high-pressure area, superimposes the high-pressure area adjustment value with the dispersion state, analyzes the pressure difference between the high-pressure area and the low-pressure area after superposition, extracts the distribution parameters of the flexible support points, and obtains the support equilibrium state data; the multiple lifting mechanisms are controlled to work respectively, and the multiple lifting mechanisms drive each support point to move respectively. Since the adjustment position distance of each lifting mechanism is not certain, flexible adjustment is formed in the overall adjustment area.

[0043] The fluctuation correction module extracts the fluctuation amplitude of the pressure value over a certain period of time based on the support equilibrium state data, cross-compares the fluctuation amplitude with the regional pressure equilibrium value, extracts the influence of the pressure fluctuation on the dynamic value of the distribution within the region, and cumulatively analyzes the fluctuation amplitude and the adjustment value of the flexible support point to obtain the adjustment result of the facial pressure state in the prone position.

[0044] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A method for adjusting facial pressure during prone surgery based on pressure sensing, characterized in that: The following steps are involved: S1: Based on embedded micro pressure sensors, the pressure values ​​of key facial areas, including the forehead, brow arch, cheekbones and mandibular area, are detected. The pressure conditions are collected and analyzed. The concentrated stress state is identified based on the pressure change trend. The pressure fluctuation range is extracted. The regional pressure characteristics are summarized. The trend analysis of regional pressure differences and pressure concentration points is estimated to obtain the pressure distribution trend data of the facial area. S2: Based on the pressure distribution trend data of the facial area, extract the pressure value of the high-sensitive area and the carrying capacity of the low-sensitive area, analyze the pressure deviation of the two areas, calculate the transfer feasibility, optimize the pressure transfer process, match the pressure dispersion and carrying capacity, redistribute the pressure of the sensitive area, obtain the regional force state after dispersion, update the regional pressure characteristics, and optimize the adjustment amount of the force area to obtain the optimized force adjustment data set; S3: Based on the optimized force adjustment data set, combined with the elastic parameters of the flexible support material, extract the key force points in the region, identify the buffering requirements of the high-pressure area, optimize the high-pressure buffering adjustment, disperse the pressure of the pressure concentration point, superimpose the buffering adjustment amount and the optimized force distribution value, adjust the distribution balance of the force points, combine the adjusted force characteristics, generate the pressure distribution value after flexibility adjustment, and optimize the balanced distribution of the support points to obtain the support equilibrium state data; S4: Based on the support equilibrium state data, the support equilibrium state is extracted in combination with the pressure fluctuation amplitude, the influence of the fluctuation change on the flexible pressure distribution is analyzed, the pressure deviation value is identified, and the distribution state is optimized. In combination with the pressure fluctuation correction amplitude, the time period distribution deviation is adjusted, the overall pressure equilibrium state is extracted, the dynamic characteristics of the pressure distribution are optimized, and the prone facial pressure state adjustment result is obtained.

2. The method for adjusting facial pressure in prone position surgery based on pressure sensing according to claim 1, characterized in that: The steps for acquiring the facial area pressure distribution trend data are specifically as follows: S111: Based on the embedded micro pressure sensor, the pressure values ​​of the forehead, brow arch, cheekbone and mandibular area are recorded in real time, the pressure value of the sensing point in each area is identified, the pressure value of each point is used as the input variable, and the average pressure value of the area is calculated to obtain the average pressure data of the key facial areas; S112: Based on the average pressure data of the key facial areas, the absolute deviation and square difference of the pressure values ​​of the sensing points are normalized according to the fluctuation range and change trend of the regional pressure values, using the formula: ； Obtain pressure fluctuation data of the facial area; in, Representative area The pressure fluctuation value, Representative area Middle The pressure value of each sensing point, Representative area The average pressure value, represents the total number of sensing points in the area, and w is the adjustment coefficient; S113: Based on the pressure fluctuation data of the facial area, determine whether the pressure fluctuation value of each area exceeds the judgment threshold of concentrated force, calibrate the concentrated force state by setting the threshold, mark the area with a fluctuation value greater than the threshold as a concentrated force area, and obtain the pressure distribution trend data of the facial area.

3. The method for adjusting facial pressure in prone position surgery based on pressure sensing according to claim 2, characterized in that: The steps for obtaining the regional stress state after the dispersion are specifically as follows: S211: Based on the facial area pressure distribution trend data, analyzing the pressure dispersion of the high-sensitive area, analyzing the deviation between the pressure value of the high-sensitive area and the standard threshold, adjusting the pressure of the high-sensitive area by using a weighting coefficient, and generating the pressure dispersion of the high-sensitive area and the dispersion capacity of the low-sensitive area; S212: calling the pressure dispersion amount of the high-sensitivity area and the dispersion capacity of the low-sensitivity area, analyzing the transfer amount of the pressure from the high-sensitivity area to the low-sensitivity area, and identifying the acceptable transfer amount according to the dispersion capacity upper limit of the low-sensitivity area, using the formula: ； The pressure transfer amount is calculated; in, Indicates the amount of pressure transfer, To adjust the sensitivity coefficient, Represents the pressure value of the highly sensitive area, Dispersed capacity for low-sensitivity areas; S213: The pressure transfer amount is called to redistribute the pressure of the highly sensitive area, and the pressure state of each facial area is updated according to the distribution of the pressure after the pressure transfer, and the facial pressure is balanced and adjusted to obtain the regional force state after the dispersion.

4. The method for adjusting facial pressure in prone position surgery based on pressure sensing according to claim 3, characterized in that: The steps for obtaining the optimized force adjustment data set are specifically as follows: S221: Based on the dispersed regional stress state, extract the stress direction, average value and fluctuation value of the boundary points, determine the correction value by differential calculation, adjust the stress state of each boundary point, record the correction value and stress parameters, and obtain the regional boundary stress adjustment state table; S222: Based on the region boundary force adjustment state table, analyze the distribution characteristics of the internal force points, identify the force change trend and the force difference of adjacent points, divide the force distribution range inside the region, update the force parameters and record the changes, and obtain the internal distribution change table of the force region; S223: Based on the internal distribution change table of the force area, the force adjustment values ​​of the internal points and boundary points of the area are extracted, the force data of the entire area are normalized, the area adjustment amount is re-optimized according to the global force balance parameters, the force data is updated, and the optimized force adjustment data set is obtained.

5. The method for adjusting facial pressure in prone position surgery based on pressure sensing according to claim 4, characterized in that: The steps for obtaining the pressure distribution value after the flexibility adjustment are specifically as follows: S311: Based on the optimized force adjustment data set, according to the regional force state and the deformation capacity of the flexible support material, the buffer adjustment amount of the high-pressure area is analyzed, the elastic deformation value of the support material is calculated, and the buffer adjustment amount of the high-pressure area is generated in combination with the distribution of key force points in the area; S312: Based on the buffer adjustment amount of the high-pressure area, analyze the pressure distribution of each key stress point, add the buffer adjustment amount to the stress state of the dispersed area, and use the formula: ； Calculate and generate the total pressure value of key stress points; in, Indicates the total pressure value of the key stress point, is the flexible material adjustment coefficient, is the basic pressure value of the dispersed area, is the elastic modulus of the flexible support material, is the material support area, is the elastic deformation value of the support material; S313: According to the total pressure value of the key stress point, the total support pressure of each facial area is identified, the flexible adjustment pressure value of the key stress point is statistically analyzed in the region, and the pressure fluctuation in the region is optimized by smoothing to obtain the pressure distribution value after flexible adjustment.

6. The method for adjusting facial pressure in prone position surgery based on pressure sensing according to claim 5, characterized in that: The steps for obtaining the supporting equilibrium state data are specifically as follows: S321: based on the pressure distribution value after the flexibility adjustment, extract the pressure magnitude and corresponding spatial position of each point in the pressure distribution, analyze the pressure change gradient of adjacent points and compare the gradient values, select high and low gradient areas, adjust the flexibility weight of the pressure point, and generate a flexible pressure distribution adjustment table; S322: Based on the flexible pressure distribution adjustment table, extract the adjusted regional pressure distribution data and the support point positions, determine the pressure balance center, identify the support point, the distance between the pressure center and the pressure contribution value, reallocate the support point range, adjust the support point spacing, correct the position parameters, and generate a support point optimization distribution table; S323: Based on the support point optimization distribution table, summarize the support point optimization position parameters, combine with the pressure distribution data, analyze the global pressure distribution ratio of each support point, adjust the spatial position of the support point, optimize the distribution balance, verify the equilibrium state, update the pressure distribution and support point position data, and obtain the support equilibrium state data.

7. The method for adjusting facial pressure in prone position surgery based on pressure sensing according to claim 6, characterized in that: The steps for obtaining the result of the prone facial pressure state adjustment are specifically as follows: S411: extracting the pressure fluctuation amplitude and the flexible pressure distribution value based on the support equilibrium state data, analyzing the pressure value change amplitude, screening the key threshold range according to the fluctuation amplitude, and generating a pressure fluctuation and flexible distribution change rate matrix; S412: Cross-correct the pressure fluctuation and flexibility distribution change rate matrix, and analyze the influence of the fluctuation amplitude on the flexible pressure distribution value, using the formula: ； Calculate and generate the corrected pressure fluctuation amplitude; in, Represents the corrected pressure fluctuation amplitude, Represents the pressure fluctuation amplitude, represents the flexible pressure distribution value, Represents the pressure reference value, represents the fluctuation correction factor, represents the flexibility distribution correction coefficient; S413: In combination with the corrected pressure fluctuation amplitude, according to the difference between the pressure reference value of each time period and the current pressure distribution, the deviation of the time period pressure distribution is analyzed, the distribution deviation of each time period is optimized, and the prone facial pressure state adjustment result is obtained.

8. A facial pressure adjustment system for prone position surgery based on pressure sensing, characterized in that: According to the method for adjusting facial pressure in prone position surgery based on pressure sensing according to any one of claims 1 to 7, the system comprises: The pressure detection module is based on embedded micro pressure sensors to detect the pressure values ​​of the forehead, brow arch, cheekbone and mandible, extract the pressure change trend of each area, analyze the pressure amplitude difference in each time period, extract the pressure concentrated distribution area, analyze the total regional pressure and pressure proportion, and obtain facial pressure distribution feature data; The pressure dispersion module matches the pressure value of the high-sensitive area with the pressure bearing capacity of the low-sensitive area based on the facial pressure distribution feature data, extracts the part of the pressure value of the high-sensitive area that exceeds the range, analyzes the pressure transfer amount of the high-sensitive area and the remaining capacity of the low-sensitive area, analyzes the pressure state after the transfer, optimizes the pressure distribution of the high-sensitive area, and obtains the pressure dispersion adjustment state data; The flexible adjustment module calls the elastic parameters of the flexible support material based on the pressure dispersion adjustment state data, extracts the buffer adjustment value corresponding to the high-pressure area, superimposes the adjustment value of the high-pressure area with the dispersion state, analyzes the pressure difference between the high-pressure area and the low-pressure area after superposition, extracts the distribution parameters of the flexible support points, and obtains the support equilibrium state data; The fluctuation correction module extracts the time period fluctuation amplitude of the pressure value based on the support equilibrium state data, cross-compares the fluctuation amplitude with the regional pressure equilibrium value, extracts the influence of the pressure fluctuation on the dynamic value distributed in the region, and cumulatively analyzes the fluctuation amplitude and the flexible support point adjustment value to obtain the prone facial pressure state adjustment result.

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