Toilet pressure data processing method and system

Abstract

The application discloses a toilet pressure data processing method and system, relates to the technical field of toilet pressure analysis, and comprises the following steps: determining a first contact area according to the distribution of toilet pressure data and contact continuity; selecting high-pressure data points in the toilet pressure data according to a preset high-pressure contact screening strategy, and constructing a toilet ring contour identification curve by using the high-pressure data points; and obtaining actual contact pressure data in the toilet pressure data according to the toilet ring contour identification curve and the first contact area. The application has the beneficial effects that the first contact area and the toilet ring contour identification curve are used to automatically identify the actual contact area and the hollow area in the middle of the toilet ring, the pressure data corresponding to the actual contact area is retained, the pressure data corresponding to the hollow area in the middle of the toilet ring is screened out, the processing of the pressure data matches the data filtering requirements of the toilet, and the processing accuracy and adaptability of the pressure data are improved.

Description

Technical Field

[0001] This application relates to the field of toilet pressure analysis technology, and in particular to a method and system for processing toilet pressure data. Background Technology

[0002] As an ultra-thin surface pressure detection device, the thin-film pressure sensor is used in toilet seats, which are products that come into direct contact with the human body. To optimize the comfort of use, it is necessary to measure the contact area and pressure distribution when the human body comes into contact with the toilet seat. Based on the measurement results, the product structure and shape are iteratively modified to make the product shape conform to ergonomic requirements.

[0003] Related technologies employ a globally unified threshold shielding method for pressure data filtering. This involves setting a single shielding resistance value and uniformly eliminating all detection points with resistance values ​​lower than that value. For example, when the shielding value is 0, even points without actual contact will be counted as contact points; as the shielding value increases, more and more low-resistance points will be shielded.

[0004] This global screening mechanism has a fatal flaw in testing curved products: toilet seats are mostly curved, and when a planar thin-film sensor is placed on a curved surface, it will bend and deform with the surface. This can cause some detection points that are not subjected to real pressure to generate false contact signals due to electrode bending and adhesion. The resistance values ​​of this type of invalid data generated by sensor deformation are in the same range as the low-pressure data of the actual contact edge area of ​​the human body.

[0005] Therefore, the following problems exist in the related technologies for processing toilet pressure data: the globally uniformly set shielding value does not match the actual data filtering requirements, resulting in low accuracy of pressure data processing, and the shielding value needs to be set for different models of toilets, resulting in poor adaptability. Summary of the Invention

[0006] This application addresses the problems of poor accuracy and adaptability in existing toilet pressure data processing technologies by providing a toilet pressure data processing method and system. The method determines a first contact area based on the distribution and contact continuity of the toilet pressure data. High-pressure data points in the toilet pressure data are selected according to a preset high-pressure contact point screening strategy to construct a toilet seat contour recognition curve. The first contact area and the toilet seat contour recognition curve are used together to identify the actual contact area and the hollow area in the middle of the toilet seat. This retains the pressure data corresponding to the actual contact area and filters out the pressure data corresponding to the hollow area in the middle of the toilet seat. This ensures that the pressure data processing matches the data filtering requirements of the toilet, improving the accuracy of the pressure data processing. Furthermore, it eliminates the need for separate manual settings and is adaptable to the pressure data processing of different toilet models.

[0007] To achieve the above technical objectives, this application provides a technical solution: a toilet pressure data processing method, comprising the following steps: determining a first contact area based on the distribution and contact continuity of the toilet pressure data; selecting high-pressure data points from the toilet pressure data according to a preset high-pressure contact point screening strategy, and constructing a toilet seat contour recognition curve using the high-pressure data points; and obtaining actual contact pressure data from the toilet pressure data based on the toilet seat contour recognition curve and the first contact area.

[0008] Furthermore, determining the first contact area based on the distribution of toilet pressure data and contact continuity includes: determining the pressure area based on the physiological characteristics of human sitting and the distribution of toilet pressure data; and taking the area in the pressure area that meets the preset continuous contact point threshold and the preset pressure difference threshold as the first contact area.

[0009] Furthermore, the step of selecting high-pressure data points from the toilet pressure data according to a preset high-pressure contact screening strategy and constructing a toilet seat contour recognition curve using the high-pressure data points includes: screening high-pressure data points from the toilet pressure data according to a first preset pressure difference threshold, and constructing a first contour curve using the high-pressure data points; screening candidate data points from the toilet pressure data according to a second preset pressure difference threshold, using the curvature of the first contour curve as a construction constraint, and constructing a second contour curve according to the candidate data points and the construction constraint; and forming a toilet seat contour recognition curve using the first contour curve and the second contour curve.

[0010] Furthermore, the step of obtaining the actual contact pressure data in the toilet pressure data based on the toilet seat contour recognition curve and the first contact area includes: using the pressure data in the toilet pressure data that is surrounded by the toilet seat contour recognition curve as invalid support data; using the pressure data in the toilet pressure data that is not in the first contact area as abnormal invalid data; filtering out the invalid support data and abnormal invalid data in the toilet pressure data to obtain the actual contact pressure data.

[0011] Furthermore, the process of filtering out invalid support data and abnormal invalid data from the toilet pressure data to obtain actual contact pressure data includes: filtering out invalid support data and abnormal invalid data from the toilet pressure data to obtain a second contact area; identifying abnormal pressure data in the second contact area that meets a preset pressure threshold, and using the area where the abnormal pressure data meets a preset abnormal continuous threshold as the area to be corrected; filtering out pressure data in the area to be corrected that is far from the toilet seat contour recognition curve according to a preset filtering strategy to obtain actual contact pressure data.

[0012] Furthermore, the determination of the pressure area based on the physiological characteristics of human sitting and the distribution of toilet pressure data includes: dividing the toilet seat into different sitting areas according to the contact between the human body and the toilet seat in different sitting postures; obtaining the distribution of toilet pressure data in each sitting area, taking the sitting area with the most pressure data distribution and / or the highest pressure data distribution as the main area, and taking the sitting areas adjacent to the main area as the secondary areas; and forming the pressure area together with the main area and the secondary areas.

[0013] Furthermore, the determination of the pressure zone based on the physiological characteristics of human sitting and the distribution of toilet pressure data includes: Cluster the toilet pressure data to obtain each cluster; select the largest cluster and take the cluster with the greatest similarity to the largest cluster as the cluster to be associated; construct the association path along the toilet pressure data, and construct the pressure area based on the area corresponding to the shortest association path between the largest cluster and the cluster to be associated, the area corresponding to the largest cluster, and the area corresponding to the cluster to be associated.

[0014] Furthermore, the step of filtering candidate data points in the toilet pressure data according to the second preset pressure difference threshold, using the curvature of the first contour curve as a construction constraint, and constructing the second contour curve according to the construction constraint based on the candidate data points includes: calculating the adjacent pressure difference of each toilet pressure data point; when the adjacent pressure difference of the toilet pressure data is greater than or equal to the second preset pressure difference threshold, it is considered to belong to the candidate data point; constructing continuous line segments with the candidate data points; setting a curvature threshold according to the curvature of the first contour curve; and selecting continuous line segments with curvature less than or equal to the curvature threshold as the second contour curve.

[0015] Furthermore, the step of obtaining the actual contact pressure data in the toilet pressure data based on the toilet seat contour recognition curve and the first contact area also includes: taking the area on the left side of the toilet seat contour recognition curve in the first contact area as the first contact area and obtaining the first contact area; taking the area on the right side of the toilet seat contour recognition curve in the first contact area as the second contact area and obtaining the second contact area; calculating the allocation ratio of invalid support data based on the ratio of the first contact area and the second contact area; and superimposing the invalid support data onto the actual contact pressure data of the first contact area and the second contact area according to the allocation ratio of invalid support data to obtain the corrected actual contact pressure data.

[0016] Furthermore, the step of obtaining the actual contact pressure data in the toilet pressure data based on the toilet seat contour recognition curve and the first contact area also includes: correcting the actual contact pressure data according to a preset pressure compensation correlation to obtain the corrected actual contact pressure data.

[0017] Furthermore, the process of constructing the preset pressure compensation correlation includes: acquiring first pressure data from a planar sensor and second pressure data from a shaped sensor under the same sitting posture; wherein, the shaped sensor has a through hole, and the entire edge projection of the through hole is located within the inner edge of the toilet seat; spatially aligning the first pressure data and the second pressure data, calculating the difference between the first pressure data and the second pressure data in the same space, and obtaining a pressure difference distribution matrix; associating the first pressure data with the pressure difference distribution matrix to construct the preset pressure compensation correlation.

[0018] Furthermore, determining the pressure zone based on the physiological characteristics of human sitting and the distribution of toilet pressure data also includes: obtaining the boundary pressure data between the main area and the sub-area, superimposing the boundary pressure data with the pressure data in the sub-area to obtain superimposed pressure data; and replacing the pressure data in the sub-area with the superimposed pressure data.

[0019] Another technical solution provided in this application is a toilet pressure data processing system for implementing the above-mentioned method, comprising: a region determination unit for determining a first contact region based on the distribution and contact continuity of the toilet pressure data; a contour construction unit for selecting high-pressure data points in the toilet pressure data according to a preset high-pressure contact point screening strategy, and constructing a toilet seat contour recognition curve using the high-pressure data points; and a data processing unit for obtaining actual contact pressure data in the toilet pressure data based on the toilet seat contour recognition curve and the first contact region.

[0020] The beneficial effects of this application are as follows: 1. By combining the toilet seat contour recognition curve with the first contact area, the actual contact area between the human body and the toilet seat is determined, and pressure data in false contact areas (such as wrinkled areas, hollow areas in the toilet seat but supported by pressure sensors, etc.) are filtered out, ensuring that the pressure data used in subsequent pressure analysis comes from actual contact, thus improving the accuracy of pressure data processing. Simultaneously, a preset high-pressure contact point screening strategy is used to select high-pressure data points from the toilet pressure data to construct the toilet seat contour recognition curve, eliminating the need for manual input of the toilet seat contour and adapting to different toilet models, thereby improving the adaptability of the pressure data processing solution.

[0021] 2. The pressure area is divided into several unconnected continuous areas based on the continuity between pressure data points. Then, based on the number of pressure data points and the maximum pressure difference within the continuous area, it is determined whether the continuous area belongs to the pressure area caused by actual contact between the human body and the toilet seat, eliminating false situations such as false contact and uniform pressure, and further improving the accuracy of pressure data.

[0022] 3. First, a first contour curve is constructed based on the high-pressure data points. This first contour curve corresponds to the pressure abrupt change boundary where the left and right edges of the urinal make close contact with the buttocks. Therefore, the first contour curve includes two arc-shaped curves, left and right. Then, using the curvature of the first contour curve as a construction constraint, a second contour curve conforming to the curvature of the first contour curve is constructed using candidate data points. This, combined with the first contour curve, forms a complete urinal contour recognition curve. This method ensures the overall accuracy of the urinal contour recognition curve and also identifies data points that conform to the urinal contour even if they are not in a high-pressure area, eliminating the need for manual input of the urinal contour and improving the adaptability of the solution.

[0023] 4. Obtain invalid support data caused by pressure sensor support based on the enclosing range of the toilet seat contour recognition curve. Distribute the invalid support data according to the ratio of the actual contact area on both sides of the toilet seat. Correct the pressure borne by the pressure sensor to both sides of the toilet seat according to the actual sitting posture of the human body, compensate for the pressure deviation caused by the flat sensor support, and improve the accuracy of pressure data processing. Attached Figure Description

[0024] Figure 1 This is a flowchart illustrating a toilet pressure data processing method according to one embodiment of this application.

[0025] Figure 2 This is a schematic diagram illustrating the construction process of the toilet bowl contour recognition curve in one embodiment of this application.

[0026] Figure 3 This is a schematic diagram illustrating the correction process for actual contact pressure data in one embodiment of this application. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description of this application is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely one preferred embodiment of this application and are only used to explain this application. They do not limit the scope of protection of this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0028] like Figure 1 As shown in the first embodiment of this application, the toilet pressure data processing method includes the following steps: The first contact area is determined based on the distribution of toilet pressure data and the continuity of contact. High-pressure data points in the toilet pressure data are selected according to the preset high-pressure contact screening strategy, and toilet seat contour recognition curve is constructed using the high-pressure data points. The actual contact pressure data in the toilet pressure data is obtained based on the toilet seat contour recognition curve and the first contact area.

[0029] In toilet pressure testing or during toilet use, the actual pressure data collected is generated by the contact between the human body and the toilet seat. The actual contact area between the human body and the toilet seat is spatially continuous, without isolated or discrete pressure sampling points. Therefore, by analyzing the pressure data distribution and contact continuity, the true contact area can be determined, filtering out interfering data from other areas. Simultaneously, because the toilet seat has a hollow ring structure, under normal sitting posture, when the thighs or buttocks contact the seat, the middle part lacks rigid support, resulting in higher pressure at the inner edge of the seat compared to other areas. Therefore, a high-pressure contact point screening strategy is used to filter high-pressure data points, constructing a toilet seat contour recognition curve to determine the inner ring contour. Furthermore, based on the toilet seat contour recognition curve and the first contact area, the actual contact area between the human body and the toilet seat is determined, filtering out pressure data from false contact areas (such as wrinkled areas, or the hollow area of ​​the seat supported by the pressure sensor). This ensures that the pressure data used in subsequent pressure analysis originates from actual contact, improving the accuracy of pressure data processing. Meanwhile, by using a preset high-pressure contact screening strategy to select high-pressure data points from the toilet pressure data to construct the toilet seat contour recognition curve, there is no need to manually input the toilet seat contour, which can be adapted to different models of toilets and improve the adaptability of the pressure data processing solution.

[0030] The determination of the first contact area based on the distribution of toilet pressure data and contact continuity includes: The pressure zone is determined based on the physiological characteristics of human sitting and the distribution of toilet pressure data. The area in the pressure zone that meets the preset continuous contact point threshold and the preset differential pressure threshold is designated as the first contact area.

[0031] According to ergonomics, in a normal sitting posture, the buttocks do not contact the entire toilet seat; they typically contact only a portion of it. For example, in a forward-leaning posture, the buttocks contact the front-middle section of the toilet seat, while in a backward-leaning posture, the buttocks contact the middle-rear section. Based on these physiological characteristics of human sitting and the distribution of actual toilet seat pressure data, the pressure area in the current sitting posture can be determined.

[0032] In one embodiment, determining the pressure zone based on the physiological characteristics of human sitting and the distribution of toilet pressure data includes: Based on the contact between the human body and the toilet seat in different sitting postures, the toilet seat is divided into different seating areas. The distribution of toilet pressure data in each seating area is obtained. The seating area with the most or / and the highest pressure data distribution is taken as the main area, and the seating areas adjacent to the main area are taken as the secondary areas. The main area and the sub-area together form the pressure zone.

[0033] Understandably, the division of seating areas can be set by professionals based on their long-term experience with usage, or it can be obtained through data analysis of different people's seating patterns. Since the seating area settings can be configured using any existing data analysis method or expert experience, they will not be elaborated upon here.

[0034] The pressure of the human body in contact with the toilet seat is not uniform throughout. While there may be contact in some areas, the pressure may be weak or insufficient due to the sitting posture, potentially leading to incorrect rejection. Therefore, by identifying the main area based on the distribution of the most pressure data and / or the highest pressure data, and considering the continuous contact between the human body and the toilet seat, the adjacent seating area is designated as a secondary area. Low-pressure contact data within the secondary area is retained, further improving the accuracy of pressure data processing.

[0035] If there are multiple adjacent seating areas in the main area, the sub-area is determined based on the continuity of the pressure data distribution.

[0036] In this embodiment, the toilet seat is divided into a front section, a middle section, and a rear section. When the front section is the main section, the middle section is designated as a secondary section. When the rear section is the main section, the middle section is designated as a secondary section. When the middle section is the main section, if there is a continuous pressure data distribution between the middle and front sections, the front section is designated as the secondary section; conversely, if there is a continuous pressure data distribution between the middle and rear sections, the rear section is designated as the secondary section.

[0037] Understandably, when pressure sensors are installed on toilet seats, the relative positions of the pressure data points collected by the pressure sensors with the seating area on the toilet seat are used to determine which seating area they belong to.

[0038] At this point, determining the pressure zone based on the physiological characteristics of human sitting and the distribution of toilet pressure data also includes: Obtain the boundary pressure data between the main region and the sub-region, and overlay the boundary pressure data with the pressure data in each sub-region to obtain the overlaid pressure data; Replace the individual pressure data in the sub-region with the superimposed pressure data.

[0039] Since most of the pressure data in the sub-region is low-pressure data, it is highly likely that it will be filtered out in the subsequent pressure data screening because it is below the threshold. Therefore, the pressure data in the sub-region is superimposed and calculated using the boundary pressure data between the main region and the sub-region to avoid subsequent erroneous screening.

[0040] It is understandable that the superimposed pressure data is only used to avoid the erroneous screening of pressure data in the subsequent sub-regions. The initial pressure data in the sub-regions is still retained. After the pressure data processing is completed, the superimposed pressure data is replaced with the initial pressure data to avoid anomalies in the subsequent pressure analysis.

[0041] In practical applications, the boundary pressure data can also be superimposed with pressure data that is lower than the preset screening pressure threshold. The preset screening pressure threshold can be set based on expert experience.

[0042] In another embodiment, determining the pressure zone based on the physiological characteristics of human sitting and the distribution of toilet pressure data includes: Cluster the toilet pressure data to obtain the various clusters; Select the largest cluster and choose the cluster with the greatest similarity to the largest cluster as the cluster to be associated. Construct a correlation path along the toilet pressure data, and construct the pressure region based on the region corresponding to the shortest correlation path between the largest cluster and the cluster to be correlated, the region corresponding to the largest cluster, and the region corresponding to the cluster to be correlated.

[0043] In this case, instead of pre-dividing the region, the distribution of pressure data is used to determine the current seating situation of the human body, and then clusters are associated to obtain the pressure area corresponding to the seating situation of the human body.

[0044] Clustering of toilet pressure data can be performed using any existing clustering method, such as a connected component labeling algorithm based on spatial adjacency or a density-based spatial clustering algorithm with noise.

[0045] The toilet pressure data is divided into different clusters by clustering, and then the similarity between different clusters is calculated. Since the human buttocks are usually symmetrical, the distribution of pressure data will also be approximately symmetrical. The current human sitting position is determined by the cluster with the highest similarity to the largest cluster. For example, when the human is sitting in a forward-leaning posture, the shortest association path between the cluster to be associated and the largest cluster is the front part of the toilet seat. When the human is sitting in a backward-leaning posture, the shortest association path between the cluster to be associated and the largest cluster is the back part of the toilet seat.

[0046] In this case, no additional regional division is required, thus retaining low-pressure but effective pressure data and avoiding the erroneous screening of pressure data.

[0047] Similarly, in this case, the minimum boundary pressure data of the largest cluster and the cluster to be associated is superimposed with the pressure data in the region corresponding to the shortest association path to obtain superimposed pressure data. At the same time, the pressure data in the region corresponding to the shortest association path is retained. The superimposed pressure data is only used to avoid the pressure data in the region corresponding to the shortest association path being mistakenly filtered out.

[0048] Understandably, any existing similarity algorithm can be used to calculate the similarity. In practical applications, considering the possibility of excessive forward-leaning posture, a similarity threshold can be set. If the similarity between any cluster and the largest cluster is less than the similarity threshold, it is considered to be in an excessive forward-leaning posture. In this case, only the area corresponding to the largest cluster is taken as the pressure area.

[0049] In one embodiment, the region in the pressure-bearing area that satisfies both a preset continuous contact point threshold and a preset differential pressure threshold is defined as the first contact region, including: Continuity analysis is performed on the pressure data of each pressure region to obtain the continuous region; Calculate the pressure difference between the maximum and minimum pressure data in a continuous region, count the number of pressure data in the continuous region, and when the pressure difference in the continuous region is greater than a preset pressure difference threshold and the number of pressure data in the continuous region is greater than a preset continuous contact point threshold, the continuous region is designated as the first contact region.

[0050] In this situation, analyzing the continuity of pressure data points within the pressure zone can be achieved using connectivity analysis algorithms such as the neighborhood connectivity algorithm. This divides all pressure data points within the pressure zone into several unconnected continuous regions. Then, based on the number of pressure data points within each continuous region and the maximum pressure difference, it can be determined whether the continuous region is a pressure zone caused by human contact with the toilet seat, eliminating false cases of indirect contact or uniform pressure, thus further improving the accuracy of the pressure data.

[0051] In this embodiment, the preset threshold for continuous contact points is 100, and the preset pressure difference threshold is 30 kPa. When a human body comes into contact with the toilet seat, the pressure difference between different parts is large. Therefore, there must be a large pressure difference in the actual contact area. The preset pressure difference threshold can filter out false situations of uniform pressure.

[0052] In another embodiment, the region in the pressure-bearing area that satisfies both a preset continuous contact point threshold and a preset differential pressure threshold is defined as the first contact region, including: Continuity analysis is performed on the pressure data of each pressure region to obtain the continuous region; High-voltage data points are extracted from the pressure-bearing area according to the preset high-voltage contact screening strategy, and continuous areas without high-voltage data points are screened out. Calculate the pressure difference between the maximum and minimum pressure data in the retained continuous area, count the number of pressure data in the retained continuous area, and when the pressure difference in the retained continuous area is greater than a preset pressure difference threshold and the number of pressure data in the retained continuous area is greater than a preset continuous contact point threshold, the retained continuous area is regarded as the first contact area.

[0053] In this scenario, high-pressure data points in the pressure zone are first screened according to a preset high-pressure contact screening strategy, retaining continuous areas with high-pressure data points. Then, the pressure difference and pressure data quantity are calculated for the retained continuous areas to determine the first contact area. Since the actual contact area when a person sits down inevitably includes the part with the highest pressure value, preliminary screening of continuous areas is performed based on high-pressure data points to eliminate all false signals that do not include the core load-bearing parts, thereby improving the accuracy of pressure data processing.

[0054] Understandably, high-voltage data points are also selected during the construction of the toilet bowl contour recognition curve. Since the order in which the first contact area and the toilet bowl contour recognition curve are constructed can be set as needed, the high-voltage data point selection step can be set in the earlier construction step, and the already selected high-voltage data points can be directly retrieved in the later construction step. If the first contact area and the toilet bowl contour recognition curve are constructed simultaneously, the high-voltage data point selection step can also be set before the step of constructing both simultaneously.

[0055] The preset high-voltage contact screening strategy includes: Calculate the adjacent pressure difference of each toilet pressure data point. When the adjacent pressure difference of the toilet pressure data point is greater than or equal to the first preset pressure difference threshold, it is considered to belong to the high pressure data point.

[0056] The pressure sensor is an array of M rows × N columns of tiny detection units. Each detection unit outputs a corresponding pressure data. In an 8-neighborhood, each detection unit has four sets of adjacent detection units: vertically adjacent detection units, horizontally adjacent detection units, and two sets of diagonally adjacent detection units. The absolute value of the pressure difference between each set of adjacent detection units is then calculated, which is the adjacent pressure difference. When the adjacent pressure difference is greater than or equal to a first preset pressure difference threshold, a high-pressure boundary point is considered to exist between these two detection units.

[0057] It is understandable that during the first contact area identification process, the calculation is based on the adjacent pressure difference corresponding to the detection unit located within the pressure area.

[0058] like Figure 2 As shown, high-pressure data points are selected from the toilet pressure data according to a preset high-pressure contact screening strategy, and a toilet seat contour recognition curve is constructed using the high-pressure data points, including: Based on the first preset differential pressure threshold, high-pressure data points in the toilet pressure data are filtered, and a first contour curve is constructed using the high-pressure data points. Candidate data points in the toilet pressure data are selected according to the second preset differential pressure threshold. The curvature of the first contour curve is used as the construction constraint. The second contour curve is constructed according to the construction constraint based on the candidate data points. The first contour curve and the second contour curve are used to form the outline recognition curve of the toilet.

[0059] If the high-voltage data points have already been extracted in the previous steps, they can be retrieved directly from the previous steps.

[0060] First, a first contour curve is constructed based on high-pressure data points. This first contour curve corresponds to the pressure abrupt change boundary where the edges of the urinal and the buttocks make close contact. Therefore, the first contour curve comprises two arc-shaped curves, left and right. Then, using the curvature of the first contour curve as a construction constraint, a second contour curve conforming to the curvature of the first contour curve is constructed using candidate data points. These two curves are then combined to form a complete urinal contour recognition curve. This method ensures the overall accuracy of the urinal contour recognition curve and also identifies data points that conform to the urinal contour even if they are not in a high-pressure area. It eliminates the need for manual input of the urinal contour, improving the adaptability of the solution.

[0061] In this embodiment, the first preset differential pressure threshold is 20 kPa, and the second preset differential pressure threshold is 3 kPa.

[0062] In other cases, the pre-defined high-voltage contact screening strategy includes: Obtain historical toilet pressure data, select several candidate pressure data from the historical toilet pressure data according to the preset high pressure ratio, and use the smallest candidate pressure data as the preset high pressure threshold. The pressure data points that are greater than or equal to the preset high pressure threshold in the currently acquired toilet pressure data are taken as high pressure data points.

[0063] By using a preset high pressure ratio, several candidate pressure data points are selected from historical data, ensuring that the preset high pressure threshold is in a high range. The minimum value among the candidate pressure data is then selected as the preset high pressure threshold, so that the corresponding high pressure data point can be identified regardless of the body type of person sitting down.

[0064] The preset high-pressure ratio is 10%. Based on this preset high-pressure ratio, several candidate pressure data points are selected from historical toilet pressure data, including: Candidate pressure data are extracted from each group of historical toilet pressure data according to a preset high-pressure ratio; or... Candidate pressure data are extracted from all historical toilet pressure data according to the preset high pressure ratio.

[0065] In the first method, when candidate pressure data is extracted from each set of historical toilet pressure data according to a preset high-pressure ratio, each set of historical toilet pressure data corresponds to a set of candidate pressure data. The minimum value of each set of candidate pressure data is used as the preset high-pressure threshold corresponding to the highest value of the historical toilet pressure data. At this time, the preset high-pressure threshold is retrieved according to the highest value pressure data in the currently acquired toilet pressure data to adapt to the sitting situation of people of different body types.

[0066] In the second approach, when candidate pressure data is extracted from all historical toilet pressure data according to a preset high-pressure ratio, all historical toilet pressure data correspond to a set of candidate pressure data. The minimum value of this set of candidate pressure data is the preset high-pressure threshold. This globally unified processing reflects the overall distribution pattern and simplifies the algorithm.

[0067] In other embodiments, the process of filtering candidate data points from the toilet pressure data based on a second preset differential pressure threshold, using the curvature of the first contour curve as a construction constraint, and constructing the second contour curve based on the candidate data points and the construction constraint includes: Calculate the adjacent pressure difference of each toilet pressure data point. When the adjacent pressure difference of the toilet pressure data point is greater than or equal to the second preset pressure difference threshold, it is considered to belong to the candidate data point. Continuous line segments are constructed using candidate data points. A curvature threshold is set based on the curvature of the first contour curve. Continuous line segments with curvature less than or equal to the curvature threshold are selected as the second contour curve.

[0068] In this embodiment, the curvature threshold is 30% of the curvature of the first contour curve.

[0069] The actual contact pressure data obtained from the toilet seat pressure data based on the toilet seat contour recognition curve and the first contact area includes: The pressure data enclosed by the toilet seat contour recognition curve in the toilet pressure data is considered invalid support data; Pressure data that is not located in the first contact area in the toilet pressure data is considered abnormal and invalid. The toilet pressure data is filtered out for invalid support data and abnormal invalid data to obtain the actual contact pressure data.

[0070] Among them, invalid support data can be screened out after the toilet bowl contour recognition curve is constructed, and abnormal invalid data can also be screened out after the first contact area is constructed. Alternatively, invalid support data and abnormal invalid data can be screened out simultaneously after the toilet bowl contour recognition curve is constructed and the first contact area is constructed.

[0071] In this embodiment, pressure data points that are not in actual contact areas are screened out through the first contact area, and pressure data points with no support in the middle of the toilet seat are screened out through the toilet seat contour recognition curve, thereby pre-screening invalid pressure data points and improving the accuracy of subsequent pressure analysis.

[0072] It is understood that the pressure sensor can be a planar sensor or a sensor with a hollow center; regardless of the type of sensor, the pressure data processing scheme in this embodiment is applicable. In the application of a planar sensor, because the hollow part of the toilet seat contains a planar sensor, pressure is generated at the position corresponding to the hollow part of the toilet seat when a person sits down. In this case, the toilet seat contour recognition curve can filter out this portion of invalid support data. In the application of a sensor with a hollow center, the sensor may not perfectly conform to the toilet seat. In this case, the toilet seat contour recognition curve can also filter out invalid support data where the center does not conform to the toilet seat contour.

[0073] In other embodiments, filtering out invalid support data and abnormal invalid data from the toilet pressure data to obtain actual contact pressure data includes: Screen out invalid support data and abnormal invalid data in the toilet pressure data to obtain the second contact area; Identify abnormal pressure data in the second contact area that meet a preset pressure threshold, and use the area where the abnormal pressure data meets a preset abnormal continuous threshold as the area to be corrected. Based on the preset screening strategy, pressure data that is far from the toilet bowl outline recognition curve in the area to be corrected is screened out to obtain actual contact pressure data.

[0074] After filtering out invalid and abnormally invalid data, abnormal pressure data identification continues in the second contact area. By analyzing the continuity of abnormal pressure data, it is determined whether there may be invalid pressure data under the influence of wrinkles in the current area, thereby filtering out these false signals and further improving the accuracy of pressure data processing.

[0075] In this embodiment, the preset pressure threshold is 0.5 kPa, and the preset abnormal consecutive threshold is 5. Pressure data less than 0.5 kPa in the second contact area is considered abnormal pressure data. If there are 5 consecutive abnormal pressure data, the area is considered as the area to be corrected. Since the human buttock is a continuous and complete physiological structure, if a continuous low pressure point appears in a region, it is very likely that it is a local false break caused by sensor wrinkles or a false hole caused by the separation of the sensor from the toilet seat. At this time, filtering out the pressure data in the area to be corrected that is far from the toilet seat contour recognition curve can improve the accuracy of the actual contact pressure data.

[0076] The preset screening strategy includes: setting a screening quantity based on a preset continuous anomaly threshold, and screening out pressure data in the area to be corrected that are far from the toilet seat contour recognition curve. The screening quantity can be obtained by subtracting one from the preset continuous anomaly threshold. For example, in this embodiment, the preset continuous anomaly threshold is 5, so the screening quantity is 4, screening out the 4 pressure data points furthest from the toilet seat contour recognition curve in the area to be corrected. Even if the pressure data point closest to the toilet seat contour recognition curve is low pressure, it is highly likely to be a genuine edge depression. Screening it out would cause the contact contour to shrink excessively inward, resulting in a smaller-than-expected contact area. Since the human body is a continuous physiological structure, there will not be an isolated, non-contact cavity with a depth exceeding one pressure data point within the contact area. Therefore, the four pressure data points furthest from the toilet seat contour recognition curve are highly likely to be pressure data caused by non-human contact.

[0077] In other embodiments, the rear section of the toilet seat is identified, and areas in the rear section of the toilet seat with pressure data greater than 10 kPa are identified as areas to be processed. Shape feature analysis is performed on the areas to be processed. If the area to be processed is a long vertical strip, it is identified as a wrinkled false signal area. If the area to be processed includes fewer than nine detection units and presents a scattered block or irregular shape, it is identified as a wrinkled false signal area, and the pressure data in the wrinkled false signal area is screened out.

[0078] The rear section of the toilet seat corresponds to the contact area between the buttocks and tailbone. When a person is in a leaning-back sitting position, the pressure sensor in this area is stretched longitudinally, producing long, narrow, scattered, or irregularly shaped folds. By analyzing the shape characteristics of the area to be processed, these spurious folds can be filtered out, improving the accuracy of pressure data processing.

[0079] As a second embodiment of this application, the difference from the first embodiment is that, in obtaining the actual contact pressure data in the toilet pressure data based on the toilet seat contour recognition curve and the first contact area, the method further includes: The area located to the left of the toilet bowl outline recognition curve in the first contact area is taken as the first contact area, and the first contact area is obtained. The area located to the right of the toilet bowl outline recognition curve in the first contact area is taken as the second contact area, and the second contact area is obtained. The allocation ratio of invalid support data is calculated based on the ratio of the first contact area to the second contact area. The invalid support data is superimposed onto the actual contact pressure data of the first contact area and the second contact area according to the allocation ratio of the invalid support data, so as to obtain the corrected actual contact pressure data.

[0080] Since human body weight is fixed, the total pressure exerted on the toilet seat is also fixed. This is because the spurious pressure in the central support area generated by the planar sensor is essentially the sum of the less pressure actually borne by the two edges. By distributing the pressure according to the proportion of the actual contact area on both sides, the pressure data on both sides is corrected, compensating for the pressure deviation caused by the planar sensor support, and improving the accuracy of the pressure data.

[0081] Furthermore, since the contact area on both sides changes dynamically when the human body is in different sitting postures such as leaning to the side, leaning forward, or leaning backward, the compensation result is more adapted to the actual sitting posture by dynamically adjusting the ratio of the first contact area and the second contact area. In the pressure analysis of toilet seat design scenarios, the corrected actual contact pressure data is more consistent with the actual sitting posture, thus improving the accuracy of toilet seat pressure analysis under different sitting postures.

[0082] The calculation of the allocation ratio of invalid support data based on the ratio of the first contact area to the second contact area includes: Calculate the sum of the areas of the first contact area and the second contact area, and use the ratio of the first contact area to the sum of the areas as the allocation ratio of the first contact area, and use the ratio of the second contact area to the sum of the areas as the allocation ratio of the second contact area.

[0083] In this embodiment, the sum of invalid data is first allocated to the first contact area and the second contact area according to the allocation ratio, and then evenly distributed within each contact area to preserve the relative shape of the original pressure distribution, only increasing the overall pressure value and ensuring the accuracy of subsequent pressure analysis.

[0084] It is understood that this embodiment is applied to the correction of pressure data from a planar sensor.

[0085] like Figure 3 As shown, in Embodiment 3 of this application, the difference from Embodiment 1 is that obtaining the actual contact pressure data in the toilet seat pressure data based on the toilet seat contour recognition curve and the first contact area further includes: The actual contact pressure data is corrected according to the preset pressure compensation correlation to obtain the corrected actual contact pressure data.

[0086] The process of constructing the preset pressure compensation correlation includes: Under the same sitting posture, first pressure data from a planar sensor and second pressure data from a shaped sensor are acquired; wherein, the shaped sensor has a through hole, and the entire edge projection of the through hole is located within the inner edge of the toilet seat. The first pressure data and the second pressure data are spatially aligned, and the difference between the first pressure data and the second pressure data in the same space is calculated to obtain the pressure difference distribution matrix. The first pressure data is correlated with the pressure difference distribution matrix to construct a preset pressure compensation correlation.

[0087] In this scenario, by analyzing the pressure data differences between a planar sensor and a hollowed-out, irregularly shaped sensor under the same sitting posture, the pressure deviation distribution caused by the planar sensor's central support is calculated. Furthermore, the constructed preset pressure compensation correlation can be stored and reused. Moreover, different toilet models also exhibit differences in pressure distribution. By analyzing the correlation between the initial pressure data and the pressure difference distribution matrix, the characteristics of the pressure difference under different pressure distributions are extracted. Thus, by calibrating the pressure difference under different sitting postures for a single toilet model, support correction for all toilet models under the pressure collected by the planar sensor can be achieved.

[0088] In this embodiment, the distribution characteristics of the first pressure data and the distribution characteristics of the pressure difference are obtained, and the two distribution characteristics are correlated. Then, after the planar sensor collects pressure data and calculates the actual contact pressure data, it can be directly matched with the distribution characteristics of the first pressure data to extract the distribution characteristics of the pressure difference. These pressure difference distribution characteristics are then used to correct the actual contact pressure data, further improving the accuracy of the pressure data from the planar sensor.

[0089] It is understandable that when the first pressure data and pressure difference distribution matrix under different sitting postures are obtained, a preset pressure compensation correlation relationship can be constructed using correlation analysis methods such as interpolation or regression models.

[0090] In other cases, the preset pressure compensation correlation can also be set based on expert experience. That is, the compensation value is set according to the actual contact pressure data of different degrees, and the compensation value is calculated by superimposing the high and low pressure levels of the actual contact pressure data.

[0091] As a third embodiment of this application, a toilet pressure data processing system, connected to a pressure sensor, includes: The area determination unit is used to determine the first contact area based on the distribution of toilet pressure data and contact continuity. The contour building unit is used to select high-pressure data points from the toilet pressure data according to a preset high-pressure contact screening strategy, and to construct a toilet seat contour recognition curve using the high-pressure data points. The data processing unit is used to obtain the actual contact pressure data in the toilet pressure data based on the toilet seat contour recognition curve and the first contact area.

[0092] In this embodiment, the pressure sensor can be either a planar sensor or an irregularly shaped sensor. The region determination unit and the contour determination unit can both be connected to the pressure sensor, synchronously acquiring pressure data and respectively performing the first contact area determination and the construction of the concave contour recognition curve. Alternatively, the region determination unit and the contour determination unit can be connected sequentially, with the front unit connected to the pressure sensor and the rear unit receiving the pressure data processed by the front unit for secondary processing.

[0093] The data processing unit can be connected after the region determination unit and the contour determination unit. At this time, invalid data in the toilet pressure data is filtered out based on the first contact area output by the region determination unit and the contour determination unit and the toilet seat contour recognition curve.

[0094] The data processing unit can also be associated with the region determination unit and the contour determination unit respectively. When the region determination unit outputs the first contact area, it immediately filters out invalid data in the toilet pressure data based on the first contact area; when the contour determination unit outputs the toilet seat contour recognition curve, it immediately filters out invalid data in the toilet pressure data based on the toilet seat contour recognition curve. At this time, when the region determination unit is a front unit, the contour determination unit receives the pressure data filtered out based on the first contact area from the data processing unit and performs toilet seat contour recognition curve construction; when the contour determination unit is a front unit, the region determination unit receives the pressure data filtered out based on the toilet seat contour recognition curve from the data processing unit and performs first contact area determination.

[0095] The specific embodiments described above are preferred embodiments of the toilet pressure data processing method and system of this application, and are not intended to limit the specific scope of this application. The scope of this application includes but is not limited to the specific embodiments described above. All equivalent changes made in accordance with the shape and structure of this application are within the protection scope of this application.

Claims

1. A method for processing toilet pressure data, characterized in that: Includes the following steps: The first contact area is determined based on the distribution of toilet pressure data and the continuity of contact. High-pressure data points in the toilet pressure data are selected according to the preset high-pressure contact screening strategy, and toilet seat contour recognition curve is constructed using the high-pressure data points. The actual contact pressure data in the toilet pressure data is obtained based on the toilet seat contour recognition curve and the first contact area. The step of obtaining the actual contact pressure data in the toilet pressure data based on the toilet seat contour recognition curve and the first contact area includes: The pressure data enclosed by the toilet seat contour recognition curve in the toilet pressure data is considered invalid support data; Pressure data that is not located in the first contact area in the toilet pressure data is considered abnormal and invalid. Filter out invalid support data and abnormal invalid data in the toilet pressure data to obtain the actual contact pressure data; Determining the first contact area based on the distribution of toilet pressure data and contact continuity includes: The pressure zone is determined based on the physiological characteristics of human sitting and the distribution of toilet pressure data. The area in the pressure zone that meets the preset continuous contact point threshold and the preset differential pressure threshold is designated as the first contact area.

2. The toilet pressure data processing method as described in claim 1, characterized in that: The step of selecting high-pressure data points from the toilet pressure data according to a preset high-pressure contact screening strategy, and constructing a toilet seat contour recognition curve using the high-pressure data points, includes: Based on the first preset differential pressure threshold, high-pressure data points in the toilet pressure data are filtered, and a first contour curve is constructed using the high-pressure data points. Candidate data points in the toilet pressure data are selected according to the second preset differential pressure threshold. The curvature of the first contour curve is used as the construction constraint. The second contour curve is constructed according to the construction constraint based on the candidate data points. The first contour curve and the second contour curve are used to form the outline recognition curve of the toilet ring.

3. The toilet pressure data processing method as described in claim 1, characterized in that: The process of filtering out invalid support data and abnormal invalid data from the toilet pressure data to obtain actual contact pressure data includes: Screen out invalid support data and abnormal invalid data in the toilet pressure data to obtain the second contact area; Identify abnormal pressure data in the second contact area that meet a preset pressure threshold, and use the area where the abnormal pressure data meets a preset abnormal continuous threshold as the area to be corrected. Based on the preset screening strategy, pressure data that is far from the toilet bowl outline recognition curve in the area to be corrected is screened out to obtain actual contact pressure data.

4. The toilet pressure data processing method as described in claim 1, characterized in that: The determination of the pressure zone based on the physiological characteristics of human sitting and the distribution of toilet pressure data includes: Based on the contact between the human body and the toilet seat in different sitting postures, the toilet seat is divided into different seating areas. The distribution of toilet pressure data in each seating area is obtained. The seating area with the most or / and the highest pressure data distribution is taken as the main area, and the seating areas adjacent to the main area are taken as the secondary areas. The main area and the sub-area together form the pressure zone.

5. The toilet pressure data processing method as described in claim 1, characterized in that: The determination of the pressure zone based on the physiological characteristics of human sitting and the distribution of toilet pressure data includes: Cluster the toilet pressure data to obtain the various clusters; Select the largest cluster and choose the cluster with the greatest similarity to the largest cluster as the cluster to be associated. Construct a correlation path along the toilet pressure data, and construct the pressure region based on the region corresponding to the shortest correlation path between the largest cluster and the cluster to be correlated, the region corresponding to the largest cluster, and the region corresponding to the cluster to be correlated.

6. The toilet pressure data processing method as described in claim 2, characterized in that: The step of filtering candidate data points from the toilet pressure data according to the second preset pressure difference threshold, using the curvature of the first contour curve as a construction constraint, and constructing the second contour curve according to the candidate data points and the construction constraint includes: Calculate the adjacent pressure difference of each toilet pressure data point. When the adjacent pressure difference of the toilet pressure data point is greater than or equal to the second preset pressure difference threshold, it is considered to belong to the candidate data point. Continuous line segments are constructed using candidate data points. A curvature threshold is set based on the curvature of the first contour curve. Continuous line segments with curvature less than or equal to the curvature threshold are selected as the second contour curve.

7. The toilet pressure data processing method as described in claim 1, characterized in that: The step of obtaining the actual contact pressure data in the toilet pressure data based on the toilet seat contour recognition curve and the first contact area also includes: The area located to the left of the toilet bowl outline recognition curve in the first contact area is taken as the first contact area, and the first contact area is obtained. The area located to the right of the toilet bowl outline recognition curve in the first contact area is taken as the second contact area, and the second contact area is obtained. The allocation ratio of invalid support data is calculated based on the ratio of the first contact area to the second contact area. The invalid support data is superimposed onto the actual contact pressure data of the first contact area and the second contact area according to the allocation ratio of the invalid support data, so as to obtain the corrected actual contact pressure data.

8. The toilet pressure data processing method as described in claim 1, characterized in that: The step of obtaining the actual contact pressure data in the toilet pressure data based on the toilet seat contour recognition curve and the first contact area also includes: The actual contact pressure data is corrected according to the preset pressure compensation correlation to obtain the corrected actual contact pressure data.

9. The toilet pressure data processing method as described in claim 8, characterized in that: The process of constructing the preset pressure compensation correlation includes: Under the same sitting posture, first pressure data from a planar sensor and second pressure data from a shaped sensor are acquired; wherein, the shaped sensor has a through hole, and the entire edge projection of the through hole is located within the inner edge of the toilet seat. The first pressure data and the second pressure data are spatially aligned, and the difference between the first pressure data and the second pressure data in the same space is calculated to obtain the pressure difference distribution matrix. The first pressure data is correlated with the pressure difference distribution matrix to construct a preset pressure compensation correlation.

10. The toilet pressure data processing method as described in claim 1, 4, or 5, characterized in that: Determining pressure zones based on human physiological characteristics when sitting and the distribution of toilet pressure data also includes: Obtain the boundary pressure data between the main region and the sub-region, and overlay the boundary pressure data with the pressure data in each sub-region to obtain the overlaid pressure data; Replace the individual pressure data in the sub-region with the superimposed pressure data.

11. A toilet pressure data processing system, used to implement the method as described in any one of claims 1 to 10, characterized in that: include: The area determination unit is used to determine the first contact area based on the distribution of toilet pressure data and contact continuity. The contour building unit is used to select high-pressure data points from the toilet pressure data according to a preset high-pressure contact screening strategy, and to construct a toilet seat contour recognition curve using the high-pressure data points. The data processing unit is used to obtain the actual contact pressure data in the toilet pressure data based on the toilet seat contour recognition curve and the first contact area.

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