Prone position surgery facial pressure adjustment method and system based on pressure sensing

Abstract

The present invention relates to the technical field of pressure control, specifically a face pressure adjustment method and system for prone surgery based on pressure sensing, including the following steps: Based on an embedded micro pressure sensor, detect the pressure values of key facial regions, analyze the pressure distribution, and analyze the concentrated stress state of each facial region through the change trend of the pressure values to obtain the pressure distribution trend data of the facial regions. In the present invention, through pressure sensing technology and a dynamic adjustment mechanism, it is possible to effectively identify and alleviate the problem of uneven pressure on the face during prone surgery, monitor and analyze the pressure distribution in real time, accurately adjust the pressure in highly sensitive regions to transfer to low-sensitive regions to achieve uniform distribution, reduce tissue damage caused by long-term local compression, balance the support forces of each pressure point, optimize face pressure adjustment, and improve distribution stability through pressure fluctuation monitoring and correction to avoid uneven phenomena caused by fluctuations, thereby enhancing the comfort and safety of the surgery.

Description

Technical Field

[0001] The present invention relates to the technical field of pressure control, and particularly to a prone position surgical facial pressure adjustment method and system based on pressure sensing. Background Art

[0002] The technical field of pressure control includes technical means for ensuring that the pressure of a controlled object remains stable or meets specific requirements under specific conditions through the detection, adjustment, and feedback control of pressure. The core content of this technical field is to detect pressure changes through a pressure sensing device, adjust pressure parameters using an adjustment device, and combine a feedback control mechanism to achieve dynamic balance or distribution optimization of pressure. Pressure control technology has a wide range of applications in fields such as medical equipment, industrial manufacturing, and aerospace, 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 prone position surgical facial pressure adjustment method refers to a method of detecting the pressure distribution on a patient's face through a pressure sensing device and combining a dynamic adjustment device to adjust the pressure on the facial support area in real time. For example, the method disclosed in the Chinese patent with publication number CN 119033562 A and title "A Special Prone Position Headrest and Its Use and Adjustment Method" addresses the problems of uneven pressure and excessive local pressure at the contact area between the face and the body position pad during prone position surgery. It uses a pressure sensor to collect pressure data from different areas of the face, analyzes the data through a control module, and adjusts the support structure to redistribute the facial pressure, avoiding long-term pressure on local areas. The specific technical means include: several support pads are arranged on a seat frame adapted to the shape of the human face in a liftable manner, and several support pads are arranged independently at intervals. The uppermost part of the support pad contacts the human face through a soft pillow, and the lower part of the soft pillow is arranged on a lifting mechanism through a connecting member. A pressure sensor is arranged corresponding to each support pad position, and the pressure of the facial support area is adjusted using a lifting mechanism such as an adjustable support airbag or deformable material to ensure dynamic uniform distribution of the support force.

[0004] Although the prior art realizes the detection and feedback adjustment of facial pressure through a pressure sensing device, in the actual operation process, the adjustment of the facial pressure distribution still faces certain limitations. Due to the imprecise arrangement of the pressure sensor array and the design of the adjustment mechanism, it is easy to cause excessive pressure in some highly sensitive areas or uneven local pressure distribution. Especially under the support of the complex facial structure, it is difficult to avoid excessive compression in some areas. In the actual application of the existing dynamic adjustment device, it cannot effectively adapt to the differences in the pressure requirements of different facial areas, resulting in the failure of the support adjustment in some areas to respond to the pressure change in a timely manner, and it cannot effectively relieve the discomfort or the risk of tissue damage caused by long-term compression. The change of pressure fluctuation cannot be fully controlled and corrected, which makes it difficult to maintain a stable state of facial pressure during the operation, resulting in frequent fluctuations in the pressure distribution during the operation and affecting the patient's comfort. The prior art 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 a long operation. Summary of the Invention

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

[0006] To achieve the above object, the present invention adopts the following technical solutions: A method for adjusting facial pressure during prone surgery based on pressure sensing, comprising the following steps:

[0007] S1: Based on an embedded micro pressure sensor, detect the pressure values of key facial areas, including the forehead, eyebrow arch, cheekbone and mandibular areas, collect and analyze the pressure conditions, identify the concentrated force state in combination with the pressure change trend, extract the pressure fluctuation range, summarize the regional pressure characteristics, estimate the trend to analyze the regional pressure difference and the pressure concentration point, and obtain the facial regional pressure distribution trend data;

[0008] S2: Based on the facial regional pressure distribution trend data, extract the pressure values of the highly sensitive areas and the load-bearing capacity of the low-sensitive areas, analyze the pressure deviation between the two areas, calculate the transfer feasibility, optimize the pressure transfer process, match the pressure dispersion amount with the load-bearing capacity, redistribute the pressure in the sensitive areas, obtain the regional force state after dispersion, update the regional pressure characteristics, and optimize the adjustment amount of the stressed area to obtain an optimized force adjustment data set;

[0009] S3: Based on the optimized force adjustment dataset, combined with the elastic parameters of the flexible support material, extract the key force points in the region, identify the buffer requirements in the high-pressure region, optimize the high-pressure buffer adjustment, disperse the pressure at the pressure concentration point, superimpose the buffer adjustment amount and the optimized force distribution value, adjust the balance of the force point distribution, combine with the adjusted force characteristics, generate the pressure distribution value after flexible adjustment, and optimize the balanced distribution of the support points to obtain the support balanced state data;

[0010] S4: Based on the support balanced state data, combined with the pressure fluctuation amplitude, extract the support balanced state, analyze the influence of the fluctuation change on the flexible pressure distribution, identify the pressure deviation value, optimize the distribution state, combined with the pressure fluctuation correction amplitude, adjust the distribution deviation of the time period, extract the overall pressure balanced state, optimize the dynamic characteristics of the pressure distribution, and obtain the adjustment result of the facial pressure state in the prone position.

[0011] As a further solution of the present invention, the specific steps for obtaining the facial area pressure distribution trend data are as follows:

[0012] S111: Based on the embedded micro pressure sensor, record the pressure values of the forehead, eyebrow arch, cheekbone and mandible regions in real time, identify the pressure values of the sensing points in each region, use the pressure value of each point as the input variable, and calculate the average pressure value of the region to obtain the average pressure data of the key facial regions;

[0013] S112: Based on the average pressure data of the key facial regions, for the fluctuation range and change trend of the regional pressure values, normalize the absolute deviation and square difference of the sensing point pressure values, and use the formula:

[0014] ;

[0015] Obtain the pressure fluctuation data of the facial area;

[0016] Among them, represents the pressure fluctuation value of the region ; represents the pressure value of the th sensing point in the region ; represents the average pressure value of the region ; represents the total number of sensing points in the region, is the adjustment coefficient;

[0017] S113: According to the pressure fluctuation data of the facial area, judge whether the pressure fluctuation value of each region exceeds the determination threshold of concentrated force, calibrate the concentrated force state by setting the threshold, and mark the region with a fluctuation value greater than the threshold as the concentrated force region to obtain the facial area pressure distribution trend data.

[0018] As a further solution of the present invention, the steps for obtaining the stress state of the dispersed area are specifically as follows:

[0019] S211: Based on the facial area pressure distribution trend data, analyze the pressure dispersion amount of the highly sensitive area, analyze the deviation between the pressure value of the highly sensitive area and the standard threshold, adjust the pressure of the highly sensitive area using a weighting coefficient, and generate the pressure dispersion amount of the highly sensitive area and the dispersion capacity of the low sensitive area;

[0020] S212: Invoke the pressure dispersion amount of the highly sensitive area and the dispersion capacity of the low sensitive area, analyze the transfer amount of the pressure from the highly sensitive area to the low sensitive area, identify the acceptable transfer amount according to the upper limit of the dispersion capacity of the low sensitive area, and use the formula:

[0021] ;

[0022] Calculate the pressure transfer amount;

[0023] Wherein, represents the pressure transfer amount, is the sensitivity adjustment coefficient, represents the pressure value of the highly sensitive area, is the dispersion capacity of the low sensitive area;

[0024] S213: Invoke the pressure transfer amount to re - distribute the pressure of the highly sensitive area, update the pressure state of each facial area according to the distribution after pressure transfer, perform balance adjustment of facial pressure, and obtain the stress state of the dispersed area.

[0025] As a further solution of the present invention, the steps for obtaining the optimized stress adjustment data set are specifically as follows:

[0026] S221: Based on the stress state of the dispersed area, extract the average value and fluctuation value of the stress direction and magnitude of the boundary points, determine the correction value through 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;

[0027] S222: Based on the regional boundary stress adjustment state table, analyze the distribution characteristics of the internal stress points, identify the stress change trend and the stress difference between adjacent points, divide the stress distribution range inside the area, update the stress parameters and record the changes, and obtain the internal distribution change table of the stress area;

[0028] S223: Based on the internal distribution change table of the stress area, extract the stress adjustment values of the internal points and boundary points of the area, normalize the stress data of the whole area, re - optimize the area adjustment amount according to the global stress balance parameter, and update the stress data to obtain the optimized stress adjustment data set.

[0029] As a further solution of the present invention, the steps for obtaining the pressure distribution value after flexible adjustment are specifically as follows:

[0030] S311: Based on the optimized force-adjusted data set, analyze the buffer adjustment amount of the high-pressure area according to the regional force state and the deformation ability of the flexible support material, calculate the elastic deformation value of the support material, and generate the buffer adjustment amount of the high-pressure area in combination with the distribution of key stress points in the area;

[0031] S312: Based on the buffer adjustment amount of the high-pressure area, analyze the pressure distribution of each key stress point, superimpose the buffer adjustment amount on the dispersed regional force state, and use the formula:

[0032] ;

[0033] Calculate and generate the total pressure value of the key stress points;

[0034] Wherein, represents the total pressure value of the key stress points, 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;

[0035] S313: According to the total pressure value of the key stress points, identify the total support pressure of each area of the face, perform regional statistics on the flexible adjustment pressure values of the key stress points, and optimize the pressure fluctuation within the area through smoothing processing to obtain the pressure distribution value after flexible adjustment.

[0036] As a further solution of the present invention, the steps for obtaining the support balance state data are specifically as follows:

[0037] S321: Based on the pressure distribution value after flexible adjustment, extract the pressure magnitude and corresponding spatial position of each point in the pressure distribution, analyze the pressure change gradient between adjacent points and compare the gradient values, screen the high and low gradient areas, adjust the flexible weight of the pressure points, and generate a flexible pressure distribution adjustment table;

[0038] 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 distance between the support points, the pressure center, and the pressure contribution value, reallocate the support point range, adjust the support point spacing, and correct the position parameters to generate an optimized distribution table of the support points;

[0039] S323: Based on the optimized distribution table of the support points, summarize the optimized position parameters of the support points, combine the pressure distribution data, analyze the global pressure distribution ratio of each support point, adjust the spatial position of the support points, optimize the distribution balance, verify the balanced state, update the pressure distribution and support point position data, and obtain the support balance state data.

[0040] As a further solution of the present invention, the steps for obtaining the adjustment result of the prone position facial pressure state are specifically as follows:

[0041] S411: Based on the support balance state data, extract the pressure fluctuation amplitude and the flexible pressure distribution value, analyze the change amplitude of the pressure value, screen the key threshold range according to the fluctuation amplitude, and generate a pressure fluctuation and flexible distribution change rate matrix;

[0042] S412: Perform cross-correction on the pressure fluctuation and flexible distribution change rate matrix. By analyzing the influence of the fluctuation amplitude on the flexible pressure distribution value, use the formula:

[0043] ;

[0044] Calculate and generate the corrected pressure fluctuation amplitude;

[0045] Wherein, 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 coefficient, represents the flexible distribution correction coefficient;

[0046] S413: Combine the corrected pressure fluctuation amplitude, analyze 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, optimize the distribution deviation in each time period, and obtain the adjustment result of the prone position facial pressure state.

[0047] The prone position surgical facial pressure adjustment system based on pressure sensing, which is used to execute the above-mentioned prone position surgical facial pressure adjustment method based on pressure sensing. The system includes:

[0048] The pressure detection module, based on an embedded micro pressure sensor, detects the pressure values on the forehead, eyebrow arch, cheekbone and mandible of the face, extracts the pressure change trend in each area, analyzes the pressure amplitude difference in each time period, extracts the pressure concentration distribution area, analyzes the total pressure and pressure ratio in the area, and obtains the facial pressure distribution characteristic data;

[0049] The pressure dispersion module matches the pressure values in the highly sensitive areas with the pressure-bearing capacities in the low-sensitive areas based on the facial pressure distribution characteristic data, extracts the parts where the pressure values in the highly sensitive areas exceed the range, analyzes the pressure transfer amount in the highly sensitive areas and the remaining capacity in the low-sensitive areas, analyzes the pressure state after the transfer, optimizes the pressure distribution in the highly sensitive areas, and obtains the pressure dispersion adjustment state data;

[0050] The flexible adjustment module calls the elastic parameters of the flexible support material based on the pressure dispersion adjustment state data, extracts the corresponding buffer adjustment values for the high-pressure areas, superimposes the adjustment values in the high-pressure areas with the dispersion state, analyzes the pressure differences between the high-pressure areas and the low-pressure areas after the superposition, extracts the flexible support point distribution parameters, and obtains the support balance state data;

[0051] The fluctuation correction module extracts the time-period fluctuation amplitude of the pressure values based on the support balance state data, cross-compares the fluctuation amplitude with the regional pressure balance value, extracts the influence amount of the pressure fluctuation on the dynamic distribution value within the region, and conducts a cumulative analysis of the fluctuation amplitude and the flexible support point adjustment value to obtain the adjustment result of the facial pressure state in the prone position.

[0052] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0053] In the present invention, through the pressure sensing technology and the dynamic adjustment mechanism, it is possible to more effectively identify and address the problem of uneven pressure on the face during prone position surgery. Based on the real-time monitoring and analysis of the pressure distribution, it is possible to accurately identify the pressure concentration in the highly sensitive areas and targetedly transfer the pressure from these areas to the low-sensitive areas. This not only ensures that the pressure on different areas of the face is evenly distributed during the surgery but also significantly reduces tissue damage caused by long-term local pressure. Combining with the buffering ability of the flexible support material, precise buffer adjustment is carried out on the local high-pressure areas, making the support force at each pressure point more balanced, thereby achieving more delicate and optimized facial pressure adjustment. By monitoring and correcting the pressure fluctuations, the stability of the pressure distribution is further enhanced, avoiding uneven pressure caused by excessive fluctuation amplitude. This not only effectively improves the risk of local high pressure on the face in traditional methods but also achieves a more balanced and stable facial support through more refined dynamic adjustment, effectively ensuring facial comfort and safety during the surgery. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 is a schematic diagram of the working process of the present invention;

[0055] Figure 2 is a flowchart of the pressure distribution trend data of the facial area in the present invention;

[0056] Figure 3 is a flowchart of the force state of the dispersed area in the present invention;

[0057] Figure 4 It is the flowchart of the optimized force adjustment data set in the present invention;

[0058] Figure 5 It is the flowchart of the pressure distribution value after flexible adjustment in the present invention;

[0059] Figure 6 It is the flowchart of the support balance state data in the present invention;

[0060] Figure 7 It is the flowchart of the adjustment result of the facial pressure state in the prone position in the present invention. Specific embodiments

[0061] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to 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 used to limit the present invention.

[0062] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the accompanying drawings, and is 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 should not be construed as a limitation of the present invention. In addition, in the description of the present invention, "a plurality of" means two or more unless otherwise specifically defined. Embodiment 1

[0063] Please refer to Figure 1 , the present invention provides a technical solution: a method for adjusting the facial pressure in a prone position surgery based on pressure sensing, including the following steps:

[0064] S1: Based on an embedded micro pressure sensor, detect the pressure values of key facial areas, including the forehead, eyebrow arch, cheekbone and mandibular areas, collect and analyze the pressure conditions, identify the concentrated force state in combination with the pressure change trend, extract the pressure fluctuation range, summarize the regional pressure characteristics, estimate the trend to analyze the regional pressure difference and the pressure concentration point, and obtain the facial area pressure distribution trend data;

[0065] S2: Based on the facial area pressure distribution trend data, extract the pressure values of highly sensitive areas and the load-bearing capacities of low-sensitive areas, analyze the pressure deviation between the two areas, calculate the transfer feasibility, optimize the pressure transfer process, match the pressure dispersion amount with the load-bearing capacity, redistribute the pressure in the sensitive areas, obtain the force state of the area after dispersion, update the area pressure characteristics, and optimize the adjustment amount of the stressed area to obtain the optimized force adjustment data set;

[0066] S3: Based on the optimized force adjustment data set, combined with the elastic parameters of the flexible support material, extract the key force points of the area, identify the buffer requirements of the high-pressure area, optimize the high-pressure buffer adjustment, disperse the pressure at the pressure concentration point, superimpose the buffer adjustment amount and the optimized force distribution value, adjust the balance of the force point distribution, combine with the adjusted force characteristics, generate the pressure distribution value after flexible adjustment, and optimize the balanced distribution of the support points to obtain the support balance state data;

[0067] S4: Based on the support balance state data, combined with the pressure fluctuation amplitude, extract the support balance state, analyze the influence of the fluctuation change on the flexible pressure distribution, identify the pressure deviation value, optimize the distribution state, combined with the pressure fluctuation correction amplitude, adjust the distribution deviation of the time period, extract the overall pressure balance state, optimize the dynamic characteristics of the pressure distribution, and obtain the adjustment result of the prone position facial pressure state.

[0068] The face pressure adjustment method for prone position surgery based on pressure sensing in the present invention is proposed based on the face pressure adjustment structure in the prior art. The face pressure adjustment structure includes several cushions that are liftably arranged on a seat frame adapted to the shape of the human face. Among them, several cushions are arranged independently at intervals. The uppermost part of the cushion contacts the human face through a soft pillow made of flexible support material. The lower part of the soft pillow is arranged on the lifting mechanism through a connecting member. The entire operation process starts from pressure detection. Through an embedded micro pressure sensor, the embedded micro pressure sensor is arranged at each cushion position to monitor the pressure exerted by the face on the cushion. The cushion is mainly used to support the patient's face to ensure that when the patient is in the prone position, the key areas of the face (such as the forehead, eyebrow arch, cheekbone, and mandible) are evenly supported to avoid local overpressure. The lifting mechanism is used to adjust the pressure distribution in these areas. Cooperating with the soft pillow made of flexible support material, through the high elastic characteristics of the flexible support material, it can adaptively deform according to the pressure requirements of different parts of the face, thereby effectively reducing the pressure on sensitive areas. The embedded micro pressure sensor is accurately arranged in the key areas corresponding to face support. Through these sensors, the system can real-time monitor and collect the pressure values of various parts of the face, providing data support for subsequent pressure evaluation and adjustment. Since the human face bones are uneven, during the support process with conventional soft support pads, different areas of the face will inevitably bear different pressures. For example, areas where the face bones are more prominent, such as the forehead, eyebrow arch, cheekbone, and mandible, will bear greater pressure, which is extremely likely to cause blood circulation obstruction in the skin of this area and result in pressure injuries. Each sensing point in each area of the present invention can sense subtle pressure changes. The data is recorded and analyzed. First, the pressure distribution situation is evaluated, and then the concentrated stress state of each area of the face is analyzed through the change trend to generate pressure distribution trend data. For the concentrated stress area, by further calculating the pressure dispersion amount in the highly sensitive area and the load-bearing capacity in the low sensitive area, the possibility and amount of pressure transfer from the highly sensitive area to the low sensitive area are analyzed to complete the preliminary pressure redistribution. Then, combined with the characteristics of the flexible support material (such as high elastic material), the pressure distribution in the high-pressure area is buffered and adjusted and optimized through the lifting mechanism. The lifting mechanism is automatically controlled by the system. The embedded pressure sensor real-time collects the pressure data of different areas of the patient's face. The system algorithm analyzes the pressure concentration situation in the highly sensitive area and the load-bearing capacity in the low sensitive area based on these data, calculates the pressure transfer amount from the highly sensitive area to the low sensitive area through the pressure dispersion formula, and at the same time combines the elastic modulus and deformation ability of the flexible support material 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, realizing the gradual redistribution of pressure, and at the same time ensuring that the load-bearing capacity of the low sensitive area is not exceeded. The pressure transfer process is dynamically controlled by the algorithm, real-time monitoring the pressure state of each area, and combining with the dynamic adjustment ability of the flexible cushion to finely optimize the pressure distribution.The entire system realizes the dynamic balance of pressure distribution by collecting data through sensors, analyzing and optimizing algorithms, and adjusting with flexible pads, avoiding tissue damage caused by local high pressure on the face, and ensuring the safety and comfort of prone position surgery. The adjusted pressure after dispersion is superimposed with 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 also detects the support balance state in real time, corrects the pressure fluctuation amplitude, optimizes the pressure distribution state in each time period, and finally realizes the balance and stable support of the facial pressure in prone position surgery.

[0069] In the implementation process, the actual needs of the prone position surgery environment are fully considered. Embedded micro pressure sensors are arranged in the key areas where the patient contacts the surgical support surface to ensure accurate perception of the real-time changes in pressure in each area, and at the same time avoid tissue ischemia or damage caused by 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. The flexible support material can generate corresponding elastic deformation according to the force condition in the high-pressure area, thereby reducing the local pressure peak. The system can effectively identify the sensitivity differences in different facial areas by dynamically analyzing the force state of each area, and gradually disperse the load in the high-pressure area to the low-sensitivity area to ensure that no excessive pressure accumulation will occur in the low-sensitivity area during the pressure transfer process. The design of the entire process is based on the actual needs of the surgical environment and human anatomical characteristics, so as to achieve uniform pressure distribution and improve the comfort and surgical safety of patients.

[0070] Specific methods for adjusting and dispersing pressure. Pressure adjustment is first based on the real-time data obtained by the pressure sensor to judge the pressure concentration state in the high-sensitivity area. By analyzing the fluctuation range and concentrated force characteristics of the pressure value, the system matches the pressure dispersion amount in the high-sensitivity area and the bearing capacity in the low-sensitivity area, and gradually transfers the pressure exceeding the range in the high-sensitivity area to the low-sensitivity area. The transfer and dispersion of pressure are mainly carried out in the following ways: Use the pressure sensor to obtain the pressure data in the high-sensitivity area in real time, judge the pressure concentration state, and combine the fluctuation range and force characteristics to analyze the pressure dispersion demand in the high-sensitivity area and the bearing capacity in the low-sensitivity area, and gradually transfer the pressure exceeding the threshold in the high-sensitivity area to the low-sensitivity area. It will first identify the maximum bearing pressure upper limit in the low-sensitivity area to ensure that the transferred pressure will not have a negative impact on this area. After the pressure transfer is completed, the system uses the elastic characteristics of the flexible support material to buffer and adjust the high-pressure area, combines the material deformation amount with the pressure value, further refines the pressure distribution optimization, monitors the pressure fluctuation in the entire adjustment process, corrects abnormal values, smooths the pressure distribution, and ensures dynamic stability. By optimizing the support state of key stress points, the pressure is homogenized and the stability of long-term support is realized.

[0071] Through the monitoring of embedded sensors and the dynamic adjustment response of the lifting mechanism combined with flexible support materials, and the optimization of pressure distribution based on data analysis, the present invention can not only effectively relieve the problem of excessive force on the high-pressure areas of the face, but also ensure the dynamic balance of pressure distribution. It has high operability and practicability in actual surgical scenarios, provides a more comfortable surgical support experience for patients, and reduces surgical risks at the same time.

[0072] The facial area pressure distribution trend data includes facial pressure distribution information, the force-bearing state of key areas, and pressure concentration data of each area. The force-bearing state of the dispersed areas includes the pressure transfer results of highly sensitive areas, the load-bearing state 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 highly sensitive areas, and the load-bearing adjustment value of low-sensitive areas. The pressure distribution value after flexible adjustment includes the buffer parameters of high-pressure areas, the distribution state of flexible support points, and the data of uniform regional force-bearing. The support balance state data includes the balanced distribution results of support points, the optimized distribution value of support force, and the overall pressure balance parameters. The adjustment results of the prone position facial pressure state include the optimized pressure distribution state, the corrected data of the fluctuation range, and the overall facial pressure balance index.

[0073] Please refer to Figure 2 , and the specific steps for obtaining the facial area pressure distribution trend data are as follows:

[0074] S111: Based on the embedded micro pressure sensors, the pressure values of the forehead, eyebrow arch, cheekbone, and mandible regions are recorded in real time, the pressure values of the sensing points in each region are identified, the pressure value of each point is used as an input variable, and the average pressure value of the region is calculated to obtain the average pressure data of the key facial regions;

[0075] Data collection is carried out by region. Each sensing point records the continuously sampled pressure signal as pressure time series data. Preliminary processing is performed on the time series data of each region. By calculating the average pressure value of each sensing point, the abnormal points and noise in the sampling signal are removed. The removal of abnormal points is completed by setting upper and lower threshold values. The range of the threshold values is set according to the sensor calibration data and the reasonable interval of physiological pressure. The missing data is filled by linear interpolation method for the data after removing abnormal points. After filling, the pressure mean value of each region is calculated, and finally the average pressure data of the key facial regions is generated.

[0076] S112: Based on the average pressure data of the key facial regions, for the fluctuation range and change trend of the regional pressure values, the absolute deviation and squared difference of the sensing point pressure values are normalized, and the formula is used:

[0077] ;

[0078] To obtain the pressure fluctuation data of the facial area;

[0079] Among them, represents the pressure fluctuation value of area ; represents the pressure value of the th sensing point in area ; represents the average pressure value of area ; represents the total number of sensing points in the area;

[0080] The advantage of the formula is that by combining the absolute deviation and the squared difference of the area pressure fluctuation and introducing the adjustment coefficient the recognition ability of the area with large pressure fluctuation is improved, and higher calculation accuracy is achieved;

[0081] In the formula represents the pressure fluctuation value of area ; represents the pressure value of the th sensing point in area ; represents the average pressure value of area ; is the adjustment coefficient, which is used to increase the influence of the squared difference and is obtained by monitoring the pressure data sampling frequency and the coverage range of the sensing points , the pressure value of the sensing point is directly collected by the sensor, and the area average pressure value is calculated through ; the adjustment coefficient

[0082] Assume that the number of sensing points in a certain area is , and the collected pressure values are ;

[0083] According to the formula, the area average pressure value is calculated as: ;

[0084] Then, according to the formula, the absolute deviation part of the area pressure fluctuation value is calculated:

[0085] ;

[0086] Calculate the squared difference part and introduce the adjustment coefficient :

[0087] ;

[0088] Finally, the regional pressure fluctuation value is obtained: ;

[0089] This result indicates that the regional pressure fluctuation value of 1.34 reflects a relatively large change in the regional pressure, which can be used for the determination of the subsequent concentrated force-bearing area.

[0090] S113: According to the pressure fluctuation data of the facial area, determine whether the pressure fluctuation value of each area exceeds the determination threshold of the concentrated force. Calibrate the concentrated force state by setting the threshold, mark the area with a fluctuation value greater than the threshold as the concentrated force-bearing area, and obtain the pressure distribution trend data of the facial area;

[0091] Compare the pressure fluctuation value with the set concentrated force threshold. The concentrated force threshold is set as the upper quantile by analyzing the distribution of the pressure fluctuation values in multiple experimental data. Mark the area where the pressure fluctuation value is greater than as the concentrated force-bearing area. First, analyze the change trend of the pressure fluctuation through the time series curve of the fluctuation value, calculate the range of the fluctuation values of each area, and perform local smoothing on the fluctuation value curve. The smoothing method is completed by the five-point moving average method. Finally, compare the smoothed fluctuation value with the set threshold point by point to obtain the concentrated force-bearing area, and finally obtain the pressure distribution trend data of the facial area.

[0092] Please refer to Figure 3 , and the specific steps for obtaining the force-bearing state of the dispersed area are as follows:

[0093] S211: Based on the pressure distribution trend data of the facial area, analyze the pressure dispersion amount of the highly sensitive area, analyze the deviation between the pressure value of the highly sensitive area and the standard threshold, and adjust the pressure of the highly sensitive area by using the weighting coefficient to generate the pressure dispersion amount of the highly sensitive area and the dispersion capacity of the low sensitive area;

[0094] Call the pressure distribution trend data of the facial area, analyze the pressure dispersion amount in the highly sensitive area and the dispersion capacity in the low sensitive area, classify and calculate through the pressure values in the highly sensitive area and the low sensitive area. The pressure value in the highly sensitive area needs to be statistically processed based on the pressure time series data collected multiple times. After removing outliers and noise, calculate the mean value, and further extract the maximum value, minimum value, and fluctuation range of the pressure value. Determine whether the pressure in the highly sensitive area exceeds the threshold, and divide the highly sensitive area based on this. The selection of the threshold is based on the upper limit of the high-pressure range of historical data. The dispersion capacity of the low sensitive area is calculated by multiplying the bearing area of a single area by the material stress intensity. The bearing area is comprehensively determined by the distribution quantity of pressure sensors in this area and the sensing range of a single sensor. The stress intensity is provided by material experiment data. After completing the above area division, call the pressure distribution trend data for area matching, further calculate the pressure distribution correlation degree between the highly sensitive area and the low sensitive area, and obtain the matching data of the pressure dispersion amount in the highly sensitive area and the dispersion capacity in the low sensitive area, which is used for the calculation and optimization of the subsequent pressure transfer amount.

[0095] S212: Call the pressure dispersion amount in the highly sensitive area and the dispersion capacity in the low sensitive area, analyze the transfer amount of pressure from the highly sensitive area to the low sensitive area, identify the acceptable transfer amount according to the upper limit of the dispersion capacity of the low sensitive area, and use the formula:

[0096] ;

[0097] Calculate the pressure transfer amount;

[0098] Among them, represents the pressure transfer amount, is the adjustment sensitivity coefficient, represents the pressure value in the highly sensitive area, is the dispersion capacity of the low sensitive area;

[0099] The benefit of the formula is that by correlating the pressure value in the highly sensitive area with the dispersion capacity in the low sensitive area, and introducing the non-linear adjustment coefficient , it effectively balances the pressure transfer rate in the highly sensitive area and the dispersion acceptance ability in the low sensitive area in the pressure transfer calculation, thereby improving the accuracy and stability of pressure distribution;

[0100] is the adjustment sensitivity coefficient, used to adjust the influence degree of the pressure transfer in the highly sensitive area on the dispersion capacity, represents the th pressure value in the highly sensitive area, which is obtained by calculating the mean value after removing outliers through collecting the time series data of pressure sensors multiple times. The dispersion capacity Calculated by multiplying the bearing area of this region by the material's bearing limit, is a non-linear adjustment term. By controlling the transfer rate, it reduces the impact on the dispersion capacity of the low-sensitivity region when the pressure value in the high-sensitivity region is too high, and finally obtains the pressure transfer amount ;

[0101] Set the pressure value in the high-sensitivity region to 10, 12, 15, and the dispersion capacity of the low-sensitivity region to 20, 25, 30. The adjustment coefficient . The pressure sensing value is measured by a sensor. The capacity of the low-sensitivity region is based on the region area of 100, 125, 150 square units, and the material bearing limit is set to 2 units of pressure. Through region pressure value acquisition and capacity calculation;

[0102] Substitute into the formula: ;

[0103] First term calculation: ;

[0104] Second term calculation: ;

[0105] Third term calculation: ;

[0106] Total pressure transfer amount: ;

[0107] This result shows that the total transferred pressure amount is 349.05, indicating that the pressure in the high-sensitivity region can be balanced and dispersed to the low-sensitivity region after calculation, ensuring that the pressure distribution is within a reasonable range and providing support for the subsequent dispersion state.

[0108] S213: Call the pressure transfer amount to reallocate the pressure in the high-sensitivity region. According to the distribution after pressure transfer, update the pressure state of each facial region and perform a balance adjustment of the facial pressure to obtain the force state of the dispersed region;

[0109] By combining the initial pressure distribution in the highly sensitive areas and further redistributing the pressure, the dispersion capacity of the low-sensitive areas and the pressure release criteria of the high-sensitive areas need to be considered during the distribution process. Call the pressure distribution trend data and the pressure transfer amount to perform pressure distribution for each area. By setting the upper and lower limits of the pressure bearing capacity of the area, use the pressure transfer iteration method to complete the redistribution. First, set the maximum pressure release ratio for each high-sensitive area, calculate the remaining pressure value after each release according to the transfer amount, and update the bearing state of the low-sensitive areas. Complete the real-time distribution of pressure through the pressure release formula, gradually transfer the remaining pressure in the high-sensitive areas to the low-sensitive areas, and update the pressure state of each area at the same time. For the pressure in the high-sensitive areas that has not been fully transferred, adjust the remaining pressure transfer amount again until the pressure in all areas tends to balance. Evaluate the stress state of the dispersed areas through the regional pressure distribution map, and determine whether the preset balance state is reached after dispersion. Finally, generate the stress state of the dispersed areas.

[0110] Please refer to Figure 4 , and the specific steps for obtaining the optimized stress adjustment data set are as follows:

[0111] S221: Based on the stress state of the dispersed areas, extract the average and fluctuation values of the stress direction and magnitude of the boundary points. Determine the correction value through differential calculation, adjust the stress state of each boundary point, record the correction value and the stress parameters, and obtain the regional boundary stress adjustment status table;

[0112] Through the point-by-point analysis of the boundary point data, obtain the specific stress information of each boundary point in the three-dimensional space. Decompose the stress value of each boundary point into components along different directions, and calculate the average value and standard deviation of the component data of all boundary points as the basic statistical characteristics of the overall boundary stress. Compare the stress differences between adjacent points through differential calculation, identify the points with abnormal changes and calculate the correction value of the points. The correction value is iteratively adjusted by setting the stress balance condition. The initial correction value can be initialized according to the set threshold ratio and updated in subsequent iterations. Apply the correction value to the components of the stress direction according to the ratio and adjust the stress state of each boundary point in real time until the overall fluctuation value is less than the preset stable value. Finally, record the correction value of each boundary point and the adjusted stress parameters, and output the regional boundary stress adjustment status table.

[0113] S222: Based on the regional boundary stress adjustment status table, analyze the distribution characteristics of the internal stress points, identify the stress change trend and the stress difference between adjacent points, divide the stress distribution range inside the area, update the stress parameters and record the changes, and obtain the internal distribution change table of the stressed area;

[0114] For the force application points inside the region, calculate the total force values at each point in different directions, and conduct statistical analysis of the overall trend in combination with the adjustment values of the boundary points. Divide the region into several sub-regions, and by analyzing the force distribution characteristics inside each sub-region point by point, identify the range of regions where the force difference between adjacent points is relatively large. Use the associated force model between the boundary points and the internal points to infer the central point of concentrated force in the sub-region, and classify it according to its influence weight on the overall region. Adjust the force parameters within each sub-region, and perform multiple iterative corrections on the parameter values in combination with the force change trend until the fluctuation value inside the sub-region meets the set conditions. Finally, obtain the internal force distribution range and change record of each region, and generate an internal distribution change table of the force application region.

[0115] S223: Based on the internal distribution change table of the force application region, extract the force adjustment values of the internal points and boundary points in the region, normalize the force data of the overall region, re-optimize the region adjustment amount according to the global force balance parameter, update the force data, and obtain the optimized force adjustment data set;

[0116] First, make the force values of all region points dimensionless to remove the influence of the force magnitude unit, making the force data between different regions comparable. According to the force adjustment value and the global force balance parameter, determine the final adjustment amount for each point. The calculation of the adjustment amount combines the force balance condition of the overall region, and weight is assigned to the historical force state of each point during the adjustment process to ensure the continuity and optimization effect of the data. Through the gradual iterative optimization of the full-region data, finally, on the basis of meeting the global balance condition, update the force data of all points and generate the optimized force adjustment data set to complete the overall optimization of the facial pressure adjustment in the pressure-induced prone position surgery.

[0117] Please refer to Figure 5 , and the specific steps for obtaining the pressure distribution value after flexible adjustment are as follows:

[0118] S311: Based on the optimized force adjustment data set, analyze the buffer adjustment amount of the high-pressure region according to the force state of the region and the deformation ability of the flexible support material, calculate the elastic deformation value of the support material, and generate the buffer adjustment amount of the high-pressure region in combination with the distribution of the key force application points in the region.

[0119] By analyzing the stress state of the optimized area and the deformation ability of the flexible support material, calculate the buffer adjustment amount for the high-pressure area. Extract the key stress points from the optimized stress adjustment dataset according to the pressure value of each high-pressure area. Combine the elastic modulus, support area, and deformation amount of the support material, and define the buffer capacity of the support material as the deformation when the material is compressed multiplied by the effective support area. According to the area attribution and pressure concentration degree of each stress point, judge the stress points in the area where the pressure value exceeds or approaches the elastic critical value, calculate the pressure release amount caused by its deformation, and further combine the mechanical parameters of the support material and the stress point distribution in the area to disperse the buffer effect of the support material to each stress point, and finally generate the buffer adjustment amount for the high-pressure area to provide support for subsequent pressure superposition calculation.

[0120] S312: Based on the buffer adjustment amount of the high-pressure area, analyze the pressure distribution of each key stress point, and superimpose the buffer adjustment amount on the dispersed area stress state, using the formula:

[0121] ;

[0122] Calculate the total pressure value of the key stress points;

[0123] Among them, represents the total pressure value of the key stress points, is the adjustment coefficient of the flexible material, 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;

[0124] The benefit of the formula is that by combining the elastic modulus of the support material, the support area and the deformation amount to optimize the basic pressure value of the dispersed area, and at the same time introduce the non-linear adjustment coefficient

[0125] effectively enhances the flexibility and accuracy of the calculation, so that the deformation adjustment effect of the flexible support material can reflect the dynamic adjustment ability under different pressure distributions; The adjustment coefficient of the flexible material is used to describe the dynamic adjustment ability of the flexible material under different basic pressure values This value is obtained by fitting the experimental data of the flexible material, is the basic pressure value after dispersion, extracted from the optimized area stress adjustment dataset, is the elastic modulus of the support material, directly obtained through laboratory mechanical tests, is the effective stress-bearing area of the support material, calculated from the geometric distribution of the support points and the material contact area. is the deformation amount, calculated based on the relationship between the elastic modulus of the material and the pressure, and finally is the total pressure value at the key stress points;

[0126] Let the foundation pressure value in the dispersed area be 12, the elastic modulus of the flexible material be 50, the support area be 2, the deformation amount be 0.1, and the adjustment coefficient is determined to be 0.05 according to experimental fitting;

[0127] Substitute into the formula: ;

[0128] Calculate the buffer adjustment term: ;

[0129] Calculate the total pressure value: ;

[0130] The result shows that the total pressure value at the key stress points is 18.25, indicating that the flexible support material has a significant effect on optimizing the dispersed pressure. After calculating the pressure values of all key stress points through this formula, the flexible adjusted pressure values of each stress point can be obtained, providing an accurate pressure optimization basis for further generating the flexible adjusted pressure distribution values.

[0131] S313: According to the total pressure value of the key stress points, identify the total support pressure of each area of the face, perform regional statistics on the flexible adjusted pressure values of the key stress points, optimize the pressure fluctuations within the area through smoothing processing, and obtain the flexible adjusted pressure distribution value;

[0132] By statistically analyzing and distributing the pressure points region by region, calculate the total support pressure value of the facial area, assign the adjusted pressure values of all key stress points to their corresponding facial areas, extract the regional coordinates of each key stress point, and integrate the regional pressure according to the distribution of the stress points. The weighted sum of the pressure values of each area is used to obtain the regional total pressure value. For areas with large fluctuations in pressure values, further smooth the pressure distribution through the moving average method, and use the five-point moving average method to locally adjust the pressure values within the area to avoid pressure deviations caused by abnormal pressure values at individual stress points. After adjusting the regional pressure values to be stable, combined with the total amount and distribution range of the regional pressure, further verify the final distribution state through the regional distribution map, and finally generate the flexible adjusted pressure distribution value, providing complete optimized pressure distribution data for further improving the facial support state.

[0133] Please refer toFigure 6 , the specific steps for obtaining the supporting equilibrium state data are:

[0134] 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;

[0135] 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.

[0136] 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;

[0137] 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.

[0138] S323: Based on the optimized distribution table of support points, summarize the optimized position parameters of support points, combine the pressure distribution data, analyze the global pressure distribution ratio of each support point, control the operation of the lifting mechanism, drive the support points to move by the lifting mechanism, adjust the spatial positions of the support points, optimize the distribution balance, verify the balance state, update the pressure distribution and support point position data, and obtain the support balance state data;

[0139] Calculate the ratio value of each support point in the global pressure distribution, further optimize the spatial positions of the support points. Through the statistical analysis of the global pressure distribution ratio of support points, determine the distribution range of support points with too high or too low pressure, make necessary spatial position adjustments to the support points, control the operation of the lifting mechanism, drive the support points to move by the lifting mechanism. The adjustment principle is to enhance the support effect in the area with excessive pressure and reduce the support redundancy in the area with too little pressure at the same time. The optimization of the distribution balance is achieved through the point-by-point inspection of the pressure around each support point. Continue to adjust the positions of the support points in the area that has not reached the balance state, and verify whether the pressure balance state of the entire area meets the design requirements. Update the optimized positions of each support point and the flexible pressure distribution data to form the final balanced optimization result of the pressure distribution and support point positions, output the support balance state data, and provide support for the precise adjustment of the facial pressure distribution during prone surgery.

[0140] Please refer to Figure 7 , and the steps to obtain the adjustment result of the prone facial pressure state are specifically as follows:

[0141] S411: Based on the support balance state data, extract the pressure fluctuation amplitude and the flexible pressure distribution value, analyze the change amplitude of the pressure value, screen the key threshold range according to the fluctuation amplitude, and generate a pressure fluctuation and flexible distribution change rate matrix;

[0142] First, split the pressure fluctuation amplitude within each time period. By calculating the pressure difference value between the pressure value at each time point and the adjacent time point, obtain the fluctuation amplitude data sequence of each time period, extract the change situation of the flexible pressure distribution value within the corresponding time period, calculate the ratio of the flexible pressure distribution value to the reference pressure as the flexible pressure deviation factor. Subsequently, screen the fluctuation amplitude data and the flexible pressure deviation factor of all time periods, eliminate the data of time periods with small fluctuation amplitudes or insignificant differences between the deviation factors and the reference values, and generate a pressure fluctuation and flexible distribution change rate matrix.

[0143] S412: Perform cross-correction on the pressure fluctuation and flexible distribution change rate matrix. By analyzing the influence of the fluctuation amplitude on the flexible pressure distribution value, use the formula:

[0144] ;

[0145] Calculate and generate the corrected pressure fluctuation amplitude;

[0146] Among them, 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 coefficient, represents the flexible distribution correction coefficient;

[0147] The advantage of the formula is that it corrects the balance of the influence of flexible pressure on fluctuations through the product relationship between the flexible pressure distribution value and the pressure fluctuation amplitude, and at the same time introduces the weight parameter of the pressure reference value to optimize the correction efficiency of the fluctuation range;

[0148] First, obtain the data sequence of the fluctuation amplitude parameter By analyzing the time series pressure values and calculating the fluctuation range within each time period (for example, the difference between the maximum pressure value and the minimum pressure value within 1 second is used as the fluctuation amplitude), the specific value of is obtained, and the flexible pressure distribution value is obtained through the pressure sensor data. The flexible pressure value distribution in each time period is compared with the reference pressure value , and the reference pressure value is obtained from the mean value of the historical data. At the same time, the weight parameters and are calculated through the correlation between the flexible pressure and the change of the reference pressure, and finally substituted into the formula for calculation;

[0149] Set: , , , , ;

[0150] Substitute into the formula for calculation: ;

[0151] The result shows that the corrected pressure fluctuation amplitude is 5.97. This value represents the correction value of the pressure fluctuation to the flexible pressure distribution and can be used as the fluctuation correction input item in subsequent calculations to optimize the adjustment coefficient.

[0152] S413: Combine the corrected pressure fluctuation amplitude, analyze 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, optimize the distribution deviation in each time period, and obtain the adjustment result of the prone face pressure state;

[0153] First, analyze the deviation of the corrected pressure fluctuation amplitude from the difference with the reference pressure. For the corrected pressure fluctuation amplitude data series, obtain the deviation range of the pressure distribution by calculating the standard deviation between the pressure distribution in each time period and the reference value. At the same time, optimize the pressure distribution deviation value in each time period, and use the corrected fluctuation amplitude as a weight parameter to perform weighted processing on 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, and finally, smooth optimization is performed on the flexible pressure distribution state in each time period to generate the adjustment result of the prone position facial pressure state.

[0154] The prone position surgical facial pressure adjustment system based on pressure sensing is used to execute the above-mentioned prone position surgical facial pressure adjustment method based on pressure sensing. The system includes:

[0155] The pressure detection module, based on an embedded micro pressure sensor, detects the pressure values on the forehead, eyebrow arch, cheekbone, and mandible of the face, extracts the pressure change trend in each area, analyzes the pressure amplitude difference in each time period, extracts the pressure concentration distribution area, analyzes the total pressure and pressure ratio in the area, and obtains the facial pressure distribution characteristic data;

[0156] The pressure dispersion module, based on the facial pressure distribution characteristic data, matches the pressure value in the highly sensitive area with the bearing capacity in the low sensitive area, extracts the part of the pressure value in the highly sensitive area that exceeds the range, analyzes the pressure transfer amount in the highly sensitive area and the remaining capacity in the low sensitive area, analyzes the pressure state after transfer, optimizes the pressure distribution in the highly sensitive area, and obtains the pressure dispersion adjustment state data; obtains the adjustment parameters of each lifting mechanism according to the pressure dispersion adjustment state data, and respectively controls the work of multiple lifting mechanisms according to the adjustment parameters. The multiple lifting mechanisms drive the respective support points to move, thereby dispersing the pressure value. The flexible adjustment module, based on the pressure dispersion adjustment state data, calls the elastic parameters of the flexible support material, extracts the corresponding buffer adjustment value in the high-pressure area, superimposes the adjustment value in the high-pressure area and the dispersion state, analyzes the pressure difference between the high-pressure area and the low-pressure area after superposition, extracts the flexible support point distribution parameters, and obtains the support balance state data; respectively controls the work of multiple lifting mechanisms, and the multiple lifting mechanisms drive the respective support points to move. Since the adjustment position distances of each lifting mechanism are not necessarily the same, flexible adjustment is formed in the overall adjustment area.

[0157] The fluctuation correction module, based on the support balance state data, extracts the time period fluctuation amplitude of the pressure value, cross-compares the fluctuation amplitude with the regional pressure balance value, extracts the influence amount of the pressure fluctuation on the dynamic value of the distribution within the area, and performs cumulative analysis on the fluctuation amplitude and the flexible support point adjustment value to obtain the adjustment result of the prone position facial pressure state.

[0158] The above are only the preferred embodiments of the present invention, and do not limit the present invention in other forms. Any person skilled in the art may use the technical content disclosed above to make changes or modifications into equivalent embodiments with equivalent changes and apply them to other fields. However, as long as it does not depart from the technical solution content of the present invention, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention still fall 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. 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: judging whether the pressure fluctuation value of each area exceeds a threshold for determining concentrated force according to the pressure fluctuation data of the facial area, calibrating the concentrated force state by setting a threshold, marking the area with a fluctuation value greater than the threshold as a concentrated force area, and obtaining 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; 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 force-bearing point, the total support pressure of each area of ​​the face is identified, the flexible adjustment pressure value of the key force-bearing 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; 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 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.

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 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.

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 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.

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 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.

6. 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 5, 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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