A device platform for simulating human skin sweating

Abstract

The invention discloses a human skin sweating simulation equipment platform, which relates to the technical field of skin sweating simulation, and solves the problem that the humidity data of the external environment and the corresponding temperature data need to be considered, the calculation amount is large, and the corresponding sweating simulation efficiency is affected. The invention analyzes the change of temperature and sweating rate under different humidity value states to analyze whether there are line segments with the same trend between the humidity values, so as to determine the sweating parameters with the same trend, and determines the control process by analyzing whether S belongs to the humidity interval. When S belongs to the humidity interval, only one set of change curves needs to be determined, and the determination rate is faster and the operating loss is lower. When S does not belong to the humidity interval, several change curves need to be determined, and the determination rate is slow and the operating loss is high. Therefore, in order to determine the supply and demand pressure more quickly, it is preferentially analyzed whether the S value meets the corresponding analysis requirements to ensure the rapid determination of the parameters.

Description

Technical Field

[0001] This invention relates to the field of skin sweating simulation technology, specifically to a device platform for simulating human skin sweating. Background Art

[0002] Simulating human skin sweating requires considering multiple factors, including temperature, humidity, blood flow, and nervous system control; here are some possible methods:

[0003] Use thermistors or temperature sensors to measure ambient temperature and skin surface temperature, and calculate the probability of sweating based on this data;

[0004] A humidity sensor is used to monitor the humidity level of the surrounding environment and adjust the amount of sweating according to changes in humidity.

[0005] This promotes sweating by increasing blood flow to the skin's surface, mimicking blood circulation. This can be achieved using a microprocessor-controlled water pump or fan.

[0006] Artificial neural networks are used to simulate the human nervous system's control over sweating. This method requires a large amount of data and computational resources, but it can provide more accurate results.

[0007] Application CN116893625A discloses an adaptive feedback simulation device and method for active sweating of the human body in low-pressure environments. It comprises a segmental human body model shell, a temperature acquisition device, a temperature control device, an adaptive feedback prediction module for temperature and sweating rate, and a sweating control device. The adaptive feedback prediction module for temperature and sweating rate has been modified for low-pressure environments. The prediction module exchanges data in real time with the temperature acquisition device, temperature control device, and sweating control device to achieve accurate simulation of the skin temperature and sweating rate of the segmental human body model shell under low-pressure conditions. The features and beneficial effects of this invention are: it simulates the changes in sweat secretion rate caused by the regulation of sweat gland activity by the human nervous system under low-pressure conditions through active sweating; it can simulate the local skin temperature field of the human body's thermoregulation system under an adaptive feedback mechanism in low-pressure environments, with temperature distribution and sweating rate closer to the real physiological state. It can be applied to ergonomic research of protective clothing for human bodies in low-pressure environments such as aviation and high-altitude areas.

[0008] When simulating human skin, the computational workload is large because it is necessary to consider the humidity and temperature data of the external environment, which will affect the efficiency of the sweating simulation. Since the sweating simulation is a real-time process, the specific simulation data may be biased, thus affecting the sweating effect of human skin. Summary of the Invention

[0009] To address the shortcomings of existing technologies, this invention provides a device platform for simulating human skin sweating, which solves the problem that the large amount of computation required to consider external environmental humidity and corresponding temperature data affects the efficiency of sweating simulation.

[0010] To achieve the above objectives, the present invention provides the following technical solution: a device platform simulating human skin sweating, comprising:

[0011] The data acquisition terminal obtains standard human body data on temperature and sweating rate from different humidity levels in the cloud data.

[0012] The data processing unit processes standard human body data on temperature and sweating rate across different humidity levels to determine the trend of sweating rate changes. Based on the numerical changes in this trend, related humidity data exhibiting the same trend are categorized into the same humidity range, and the processed data is transferred to the same trend parameter storage unit. Specifically:

[0013] Based on different humidity data, a sweating rate change curve is generated according to the sweating rate corresponding to the change in the corresponding temperature value.

[0014] From the sweating rate change curve, the changing trends of different trend segments are identified sequentially. Each different trend segment exhibits a different trend, determined by the coordinates of the two points preceding and following it. A linear equation is then established, and a value K is selected from this equation. This K value is used to define the changing trend K of the corresponding trend segment, and the changing trends of different trend segments are thus labeled as Kt. i , where i represents different trend segments;

[0015] Those belonging to the same trend K i The trend segments are labeled as similar intervals, and the corresponding temperature parameters are determined. Based on the maximum and minimum values ​​of the temperature parameters, the trend K is determined. i The corresponding temperature range;

[0016] Confirm the existence of a trend K from different humidity data. i For the same trend line segment, determine whether the temperature ranges corresponding to such trend line segments intersect. If they do, mark the intersecting segments as the same type of value. From several sets of humidity data with the same type of value, confirm the same humidity range and transfer the same humidity range and other related data to the same trend parameter storage terminal for storage. If there is no intersection, no marking is performed.

[0017] The numerical monitoring terminal monitors the external humidity and temperature of this sweating equipment platform and transmits the real-time monitoring data to the control center.

[0018] The control center, based on the acquired external ambient temperature and humidity, determines the corresponding sweating rate from the same trend parameter storage terminal. Subsequently, based on this sweating rate, it controls the supply and demand pressure of the equipment platform to induce sweating, including:

[0019] The acquired ambient humidity is denoted as S, and the ambient temperature is denoted as W.

[0020] First, determine whether S belongs to the humidity range. If it does, determine the temperature range within this humidity range. The temperature range is the temperature value of the endpoint determined by the intersection segment. Directly determine its sweating rate and label it as CH. Use a preset conversion factor to determine the supply and demand pressure of its water source and perform real-time control.

[0021] If S does not belong to the humidity range, then determine the sweating rate change curve corresponding to S, and determine the sweating rate corresponding to W in real time from this change curve. Then, use the preset conversion factor to determine the water supply and demand pressure and perform real-time control.

[0022] The analysis center performs surface analysis on the monitored real-time video to determine whether the sweating of the sweating platform meets the standards. Based on the specific analysis, it identifies and displays any abnormal areas on the sweating surface, including:

[0023] Based on the sweating rate determined by the control center, the total sweating value ZZ within a certain period T is determined, where T is a preset value and the total sweating value is the sum of sweating parameters over several unit times.

[0024] Based on the monitored real-time video, the total amount of sweating on the sweating surface is determined and denoted as ZS. The surface of the sweating surface is equipped with a miniature sensor to monitor the sweating parameters per unit time of the corresponding sweating opening.

[0025] If ZZ-ZS≥Y1, then the sweating surface is marked as abnormal; otherwise, no marking is performed. Y1 is a preset value.

[0026] Based on the abnormal sweating of the sweating surface, the micro-images of each different sweating point at different unit times were identified, and the initial and final micro-images of the corresponding unit time were recorded:

[0027] The edge contours of the confirmed initial micro-image and the final micro-image are used to determine the area difference between the initial micro-image and the final micro-image, which is Mc = M2 - M1, where M1 is the area parameter of the initial micro-image and M2 is the area parameter of the final micro-image. The area difference Mc is determined based on the area parameters of the two.

[0028] The mean value Mc of the area difference of different sweat outlets at different unit times was calculated to determine MJ. t , where t represents different sweat outlets;

[0029] Several groups of MJ t Perform linear clustering, randomly select a set of circle centers, and then cluster them according to their corresponding MJ values. t The radius parameter is used to determine the corresponding circle. Based on the different outward-spreading circles, the area difference between adjacent circles is determined. If the area difference is ≥ Y2, where Y2 is a preset value, then the circle outside this area difference is marked as an abnormal circle, and its corresponding sweating opening is marked as an abnormal area. If the area difference is < Y2, then no marking is performed.

[0030] Preferably, it also includes a display unit to display the marked abnormal areas.

[0031] This invention provides a device platform that simulates human skin sweating. Compared with existing technologies, it has the following advantages:

[0032] This invention analyzes the changes in temperature and sweating rate under different humidity levels to determine if there are similar trending segments between humidity values ​​and locks in the corresponding temperature range to identify sweating parameters with the same trend. By analyzing whether S belongs to the humidity range, the control process is determined. When S belongs to the humidity range, only one set of change curves needs to be determined, which is faster and has lower operating losses. When S does not belong to the humidity range, several change curves need to be determined, which is slower and has higher operating losses. Therefore, in order to determine the supply and demand pressure more quickly, the analysis of whether the S value meets the corresponding analysis requirements is prioritized to ensure the rapid determination of parameters.

[0033] Subsequently, the video of the sweating process of the equipment platform is monitored. Based on the specific monitoring video, the sweating parameters generated by each different sweat outlet are determined. When the generated sweating parameters deviate during the clustering process, the corresponding abnormal sweat outlet is identified through linear clustering and marked as abnormal. This allows for timely handling, determination of the sweating effect of the sweating surface, timely maintenance, and timely processing to ensure the simulation effect of the simulation platform. Attached Figure Description

[0034] Figure 1 This is a schematic diagram of the principle framework of the present invention;

[0035] Figure 2 This is a schematic diagram of the simulation device of the present invention. Detailed Implementation

[0036] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0037] Example 1

[0038] Please see Figure 1 This application provides a device platform for simulating human skin sweating, including a data acquisition terminal, a data processing terminal, a common-parameter storage terminal, a numerical monitoring terminal, a control center, a video monitoring terminal, an analysis center, and a display unit;

[0039] The data acquisition end obtains standard human body data on temperature and sweating rate from different humidity data in the cloud, and transmits the obtained standard human body data to the data processing end. The obtained data is stored in the cloud in advance and determined by the operator in advance based on simulation experience and simulation data.

[0040] The data processing unit processes standard human body data on temperature and sweating rate from different humidity levels to determine the trend of sweating rate changes. Based on the numerical changes in the trend, related humidity data with the same trend are labeled into the same humidity range, and the processed data is transmitted to the same trend parameter storage unit. The specific method of data processing is as follows:

[0041] Based on different humidity data, a sweating rate change curve is generated according to the sweating rate corresponding to the change in the corresponding temperature value.

[0042] From the sweating rate change curve, the changing trends of different trend segments are identified sequentially. Each different trend segment exhibits a different trend, determined by the coordinates of the two points preceding and following it. A linear equation is then established, and a value K is selected from this equation. This K value is used to define the changing trend K of the corresponding trend segment, and the changing trends of different trend segments are thus labeled as Kt. i Where i represents different trend segments, for example, the resulting linear equation is Y = Kx + b, where the K value inside the equation is the trend value of the corresponding trend segment;

[0043] Those belonging to the same trend K i The trend segments are labeled as similar intervals, and the corresponding temperature parameters are determined. Based on the maximum and minimum values ​​of the temperature parameters, the trend K is determined. i The corresponding temperature range;

[0044] Confirm the existence of a trend K from different humidity data.i The same trend line segments are used to determine whether the temperature ranges corresponding to these trend line segments intersect. If they do, the intersecting segments are marked as the same type of value. If they do not, they are not marked. From several sets of humidity data with the same type of value, the same humidity range is identified and the same humidity range and other related data are transferred to the same trend parameter storage terminal.

[0045] Example: To facilitate subsequent numerical parameter control, humidity data is determined from different sweating data.

[0046] If there are three sets of humidity parameters S1, S2, and S3, and the internal temperature parameters of these three sets of humidity parameters will produce different sweating rates, then when the temperature parameter changes, different sweating rates will be produced, resulting in different sweating rate trends. If S1 and S2 have the same sweating rate within a certain temperature change range, then the temperature range corresponding to this type of temperature change is [S1, S2]. Storing this type of data will facilitate subsequent numerical control.

[0047] Among them, the numerical monitoring end monitors the external humidity and external temperature of this sweating equipment platform and transmits the real-time monitoring data to the control center. The specific data are monitored by corresponding sensors, including humidity sensors and temperature sensors. The humidity sensor monitors the ambient humidity, and the temperature sensor monitors the ambient temperature.

[0048] The control center, based on the acquired external ambient temperature and humidity, determines the corresponding sweating rate from the same trend parameter storage terminal. Subsequently, it controls the supply and demand pressure of the equipment platform based on this sweating rate to ensure that the sweating platform can sweat normally. The specific control methods include:

[0049] The acquired ambient humidity is denoted as S, and the ambient temperature is denoted as W.

[0050] First, determine whether S belongs to the humidity range. If it does, determine the temperature range within this humidity range. The temperature range is determined by the endpoint temperature value determined by the intersection segment. Directly determine its sweating rate and label it as CH. Use a preset conversion factor to determine the water supply and demand pressure and perform real-time control.

[0051] If S does not belong to the humidity range, then determine the sweating rate change curve corresponding to S, and determine the sweating rate corresponding to W in real time from this change curve. Then, use the preset conversion factor to determine the water supply and demand pressure and perform real-time control.

[0052] Specifically, the reason for confirming whether S belongs to the humidity range is to minimize the operating losses of the system and reduce the computing power. When S belongs to the corresponding humidity range, there is no need to change the supply and demand pressure too much. When the temperature changes, the original preset parameters can be changed. When S does not belong to the corresponding humidity range, the supply and demand pressure will change significantly. This change process requires confirming the change curve corresponding to each different humidity value, and then determining the corresponding sweating parameters to determine the supply and demand pressure.

[0053] When S falls within the humidity range, only one set of variation curves needs to be determined, which is faster and has lower operating losses. When S does not fall within the humidity range, several variation curves need to be determined, which is slower and has higher operating losses. Therefore, in order to determine the supply and demand pressure more quickly, we should prioritize analyzing whether the S value meets the corresponding analysis requirements to ensure the rapid determination of parameters.

[0054] Example 2

[0055] Among them, the video monitoring terminal monitors the sweating surface of the sweating platform and transmits the real-time video to the analysis center. Specifically, the sweating surface of the sweating platform is equipped with several sweat outlets, and its sweating surface is composed of a heat source layer, a sweat source layer and an epidermal layer, etc., and each sweat outlet is permeated with corresponding sweat droplets to simulate human sweating.

[0056] The analysis center performs surface analysis on the monitored real-time video to determine whether the sweating of the sweating platform meets the standards. Based on the specific analysis, it identifies and displays any abnormal areas on the sweating surface. The specific methods of analysis include:

[0057] Based on the sweating rate determined by the control center, the total sweating value ZZ within a certain period T is determined, where T is a preset value and its specific value is determined by the operator based on experience. The total sweating value is the sum of sweating parameters over several unit times.

[0058] Based on the monitored real-time video, the total amount of sweating on the sweating surface is determined and denoted as ZS. The surface of the sweating surface is equipped with a miniature sensor to monitor the sweating parameters per unit time of the corresponding sweating opening.

[0059] If ZZ-ZS≥Y1, then the sweating surface is marked as abnormal; otherwise, no marking is performed. Y1 is a preset value, and its specific value is determined by the operator based on experience.

[0060] Based on the abnormal sweating of the sweating surface, the micro-images of each different sweating point at different unit times were identified, and the initial and final micro-images of the corresponding unit time were recorded:

[0061] The edge contours of the confirmed initial micro-image and the final micro-image are used to determine the area difference between the initial micro-image and the final micro-image, which is Mc = M2 - M1, where M1 is the area parameter of the initial micro-image and M2 is the area parameter of the final micro-image. The area difference Mc is determined based on the area parameters of the two.

[0062] The mean value Mc of the area difference of different sweat outlets at different unit times was calculated to determine MJ. t , where t represents different sweat outlets;

[0063] Several groups of MJ t Perform linear clustering, randomly select a set of circle centers, and then cluster them according to their corresponding MJ values. t As a radius parameter, the corresponding circle is determined. Based on the different outward circles, the area difference between adjacent circles is determined. If the area difference is ≥ Y2, where Y2 is a preset value and its specific value is determined by the operator based on experience, then the circle outside this area difference is marked as an abnormal circle, and its corresponding sweating opening is marked as an abnormal area. Otherwise, no marking is made.

[0064] For example, when a corresponding abnormality occurs at an abnormal point, the sweating rate will slow down, which will affect the overall sweating effect and cause errors in the simulation process. By using linear clustering, the corresponding abnormal sweating points can be identified and marked for timely processing to determine the sweating effect of the sweating surface.

[0065] The display unit shows the marked abnormal areas, allowing operators to intervene and address these abnormal areas promptly, ensuring the proper handling of sweating.

[0066] Example 3

[0067] It also includes a simulated human skin sweating device associated with this equipment platform, combined with Figure 2The device mainly comprises 1 water injection channel, 2 water outlet array channels (D = 0.3 mm), 3 porous human skin-like structure (AVG = ~100 μm), 4 tension rod, 5 water storage chamber, 6 water outlet, and 7 tension sensor and display device. The device is divided into two parts: a simulated human sweating platform and fabric adhesion testing accessories. The operating mechanism is as follows: Simulated sweat is injected into the water storage chamber (5) at a certain injection rate through an external injection pump in the water injection channel (1), while the water outlet (6) is closed. Once the water storage chamber (5) is full, the simulated sweat will evenly seep out from the water outlet array channels (2) and wet the porous human skin-like structure (3). Continued injection of simulated human sweat, when the injected water pressure exceeds a critical pressure, will cause the simulated sweat to seep out from the porous human skin-like structure (3), ultimately achieving the effect of simulating human sweating.

[0068] Example 4

[0069] In its specific implementation, this embodiment includes all the implementation processes of the above three sets of embodiments.

[0070] Some of the data in the above formulas are numerical calculations with dimensions removed, and the contents not described in detail in this specification are all prior art known to those skilled in the art.

[0071] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A device platform for simulating human skin sweating, characterized in that: include: The data collection end obtains standard human body data of temperature and sweating rate in different humidity data from the cloud data; The data processing end processes the standard human body data of temperature and sweating rate in different humidity data to determine the changing trend of sweating rate. Based on the numerical change of the changing trend, the related humidity data with the same trend are calibrated into the same humidity interval, and the processed data is transmitted to the storage end with the same trend parameter. The specific method is as follows: Based on different humidity data, a sweat rate change curve is generated according to the sweat rate corresponding to the corresponding temperature value change; From the sweat rate change curve, the change trends of different trend segments are confirmed in turn, where the change trends of each different trend segment are different. The change trend is the coordinates of the two points before and after the corresponding trend segment. The linear equation is determined, and then the K value is selected from the linear equation. This K value is calibrated as the change trend K of the corresponding trend segment, and the change trends of different trend segments are calibrated as K i , where i represents different trend line segments; will belong to the same change trend K i The trend line segment is marked as a similar interval, and the corresponding temperature parameter is determined. Based on the maximum and minimum values ​​of the temperature parameter, the change trend K is determined. i The corresponding temperature range; From different humidity data, confirm whether there is a trend of change K i The same trend line segment is determined, and whether the temperature intervals corresponding to such trend line segments are crossed. If so, the crossed segments are marked as the same type of values. From several groups of humidity data with the same type of values, the same humidity interval is confirmed, and the same humidity interval and other related data are transmitted to the same trend parameter storage end for storage; The numerical monitoring terminal monitors the external environmental humidity and external environmental temperature of the sweating device platform, and transmits the specific values ​​monitored in real time to the control center; The control center determines the corresponding sweating rate from the same trend parameter storage terminal based on the acquired external environment temperature and external environment humidity, and then controls the supply and demand pressure of the device platform based on the sweating rate to make the sweating platform sweat, including: The acquired external environment humidity is calibrated as S, and the external environment temperature is calibrated as W; It is preferred to determine whether S belongs to the humidity interval. If so, the temperature interval within the humidity interval is determined. The temperature interval is the endpoint temperature value determined by the cross section, and the sweating rate is directly determined and calibrated as CH. The preset conversion factor is used to determine the supply and demand pressure of the water source and perform real-time control. If S does not belong to the humidity range, the sweat rate change curve corresponding to S is determined, and the sweat rate corresponding to W is determined from the change curve in real time, and then the preset conversion factor is used to determine the supply and demand pressure of the water source and perform real-time control; The analysis center determines whether the sweating condition of the sweating platform meets the standard by performing surface analysis on the monitored real-time video, and based on the specific analysis, determines whether there are abnormal areas on the sweating surface of the sweating platform, and locks such abnormal areas and displays them; including: Based on the sweating rate determined by the control center, a total sweating value ZZ determined within a certain period T is determined, wherein T is a preset value, and the total sweating value is the sum of sweating parameters of a certain number of unit times; Based on the monitored real-time video, the total number of sweating on the sweating surface is determined, and the determined total number of sweating is calibrated as ZS, wherein a micro sensor is provided on the surface of the sweating surface to monitor the sweating parameters per unit time of the corresponding sweating opening; If ZZ-ZS≥Y1, the sweating surface is calibrated as abnormal sweating, otherwise, no calibration is performed, where Y1 is the preset value; Based on the abnormal sweating of the sweating surface, the micro-images of each different sweating outlet at different unit times are confirmed, and the initial micro-image and the terminal micro-image of the corresponding unit time are recorded: Confirm the edge profiles of the initial microimage and the terminal microimage, and determine the area difference Mc between the initial microimage and the terminal microimage based on the edge profiles, wherein M1 is the area parameter of the initial microimage, and M2 is the area parameter of the terminal microimage. The area difference Mc is determined based on the area parameters of the two; The area difference Mc of different sweat outlets in different unit time is averaged to determine MJ t , where t represents different sweating outlets; Several groups of MJ t Perform linear clustering, randomly select a set of circle centers, and use the corresponding MJ t As the radius parameter, the corresponding circle is determined, and the area difference between adjacent circles is determined based on the different scattered circles. If the area difference is ≥ Y2, where Y2 is a preset value, the circle outside the area difference is calibrated as an abnormal circle, and the corresponding sweat outlet is calibrated as an abnormal area.

2. The device platform for simulating human skin sweating according to claim 1, characterized in that: If there is no intersection between the temperature intervals corresponding to the trend line segments, no calibration is performed.

3. The device platform for simulating human skin sweating according to claim 1, characterized in that: When the area difference is less than Y2, no marking is performed.

4. The device platform for simulating human skin sweating according to claim 1, characterized in that: It also includes a display unit for displaying the marked abnormal area.

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