Urine pH monitoring and collecting device

Abstract

The invention provides a urine pH monitoring and collecting device, and relates to the field of medical instruments. The data acquisition module is used for executing data acquisition through a combined sensor to establish a fusion data set; the microcontroller is used for calling the environment data of the fusion data set, performing pH value data correction of the fusion data set based on the environment data through an environment correction network built in the microcontroller, establishing a first correction result, activating a noise correction network built in the microcontroller, and performing filtering processing on the first correction result based on the noise correction network to obtain a second correction result; establishing a second correction result; and a display module. According to the urine pH monitoring and collecting device, the technical problems that an existing urine pH monitoring and collecting device is low in pH detection accuracy and insufficient in monitoring sensitivity and convenience can be solved, the pH monitoring sensitivity can be improved, the accuracy of a detection result can be ensured, meanwhile, the operation process can be simplified, the user experience can be improved, and the requirement for clinical rapid diagnosis can be effectively met.

Description

Technical Field

[0001] The present application relates to the field of medical devices, and in particular to a urine pH monitoring and collection device. Background Art

[0002] Monitoring urine pH is of great significance in clinical diagnosis and can help doctors determine the health status of patients. Existing urine pH monitoring equipment usually uses the electrode method or the test paper method for measurement. The electrode method requires the use of a special pH meter, which is complicated to operate and has high requirements for the calibration of the equipment; the test paper method is relatively simple, but its sensitivity and accuracy are affected by the quality and operation method of the test paper. Existing test strips usually require manual contact with urine, which may cause cross-contamination, and under different environmental conditions, the reaction time of the test strip and the accuracy of the results will also vary. Therefore, the existing technology still has shortcomings in the sensitivity and convenience of urine pH monitoring.

[0003] At present, there are several major problems with existing urine pH monitoring methods: first, traditional laboratory testing methods are time-consuming and cannot meet the needs of rapid diagnosis; second, the complexity of portable device operation and the requirement for user skills limit its clinical application; finally, the existing test paper method has limitations in sensitivity and accuracy, and is easily affected by the external environment, resulting in unreliable results. Therefore, there is an urgent need for a new type of urine collection device that can improve the sensitivity of pH monitoring, simplify the operation process, and ensure the accuracy of the test results. Summary of the invention

[0004] The purpose of the present application is to provide a urine pH monitoring and collecting device to solve the technical problems of low pH detection accuracy, insufficient monitoring sensitivity and convenience in existing urine pH monitoring and collecting devices.

[0005] In view of the above problems, the present application provides a urine pH monitoring and collection device, including: a segmented sampling module, used to receive a user's input signal, configure an adaptive segmentation strategy based on the input signal, collect the user's urine sample in segments using the adaptive segmentation strategy, and retain the mid-segment sampling result; a data acquisition module, used to import the mid-segment sampling result into a predetermined area, and perform data acquisition through a combined sensor arranged in the predetermined area to establish a fused data set; a microcontroller, used to receive the fused data set, call the environmental data of the fused data set, perform pH value data correction of the fused data set based on the environmental data through an environmental correction network built into the microcontroller, establish a first correction result, activate the noise correction network built into the microcontroller, filter the first correction result based on the noise correction network, and establish a second correction result; a display module, used to receive the second correction result, and perform real-time display of the urine pH value.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0007] By receiving the user's input signal, configuring the adaptive segmentation strategy based on the input signal, collecting the user's urine sample in segments with the adaptive segmentation strategy, and retaining the mid-segment sampling result; then importing the mid-segment sampling result into a predetermined area, and performing data acquisition through a combined sensor set in the predetermined area to establish a fusion data set; then receiving the fusion data set through a microcontroller, calling the environmental data of the fusion data set, and correcting the pH value data of the fusion data set based on the environmental data through the environmental correction network built into the microcontroller, establishing a first correction result, activating the noise correction network built into the microcontroller, filtering the first correction result based on the noise correction network, and establishing a second correction result; finally receiving the second correction result in the display module, and performing real-time display of urine pH value. In other words, by adopting a highly sensitive pH sensor and advanced data processing algorithms, the sensitivity of pH monitoring can be improved, the accuracy of the test results can be ensured, and the operation process can be simplified, and the user experience can be improved, thereby effectively meeting the needs of clinical rapid diagnosis.

[0008] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented according to the contents of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically cited below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0010] Figure 1 This is a schematic diagram of the structure of a urine pH monitoring and collection device for this application;

[0011] Figure 2 This is a schematic diagram of a process for establishing a first calibration result in a urine pH monitoring and collection device according to the present application.

[0012] Description of reference numerals:

[0013] Segmented sampling module 11, data acquisition module 12, microcontroller 13, display module 14. DETAILED DESCRIPTION

[0014] This application provides a urine pH monitoring and collection device to solve the technical problems of low pH detection accuracy, insufficient monitoring sensitivity and convenience in existing urine pH monitoring and collection devices. By adopting a highly sensitive pH sensor and advanced data processing algorithms, the sensitivity of pH monitoring can be improved to ensure the accuracy of the test results. At the same time, the operation process can be simplified and the user experience can be improved, thereby effectively meeting the needs of clinical rapid diagnosis.

[0015] Below, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0016] For examples, please see the attached Figure 1 , the present application provides a urine pH monitoring and collecting device, comprising:

[0017] The segmented sampling module 11 is used to receive an input signal from a user, configure an adaptive segmentation strategy based on the input signal, collect the user's urine sample in segments using the adaptive segmentation strategy, and retain the mid-segment sampling result.

[0018] Specifically, first, the user's input signal is received, and the input signal refers to the urine volume customized by the user. For example, the input signal can be set to three partitions: large, medium and small. The capacity of the large partition is 40 to 60 ml, the capacity of the medium partition is 20 to 40 ml, and the capacity of the small partition is 0 to 20 ml. The user can select the input partition size according to the predicted urine volume. Then, the adaptive segmentation strategy is configured according to the input signal. First, the input signal is parsed, that is, the large, medium, and small signals input by the user are converted into specific capacity information; then, according to the parsed input signal, the preliminary urine collection segmentation rules are set. For example, if the user enters "large", the segmentation strategy may be set to collect more urine each time. If the input is "small", a smaller amount of urine is collected each time. Further call the user's historical database, that is, the database that stores the user's historical urine flow data, analyze the user's historical data, evaluate the user's urine flow pattern, including the size, frequency, time distribution, etc. of the flow, and obtain the user's urine flow evaluation result. Finally, the historical urine flow evaluation results are combined with the previously generated basic segmentation constraints to create a more personalized urine collection strategy, which can automatically adjust the collection parameters according to the user's historical data and current predictions to better meet the user's actual needs.

[0019] According to the adaptive segmentation strategy, the user's urine sample is segmented and collected. First, the flow sensor in the urine collection device is activated to prepare to start monitoring the urine outflow process. Then, the flow sensor is used to monitor the speed and flow of urine outflow in real time, and the flow rate perception results are established, including information such as flow rate changes and flow size. Then, the flow rate perception results are analyzed and compared with the adaptive segmentation strategy established previously, and the segmentation strategy is adjusted according to the flow rate perception results to optimize the segmentation collection process. For example, if the flow rate is fast, the segmentation time interval may need to be shortened; if the flow rate is slow, the segmentation time interval may need to be extended. Finally, the urine sample is collected using the self-optimized segmentation strategy. After the segmentation collection is completed, the urine sample in the middle segment is selected as the retained sample. Usually, the middle segment sample is considered to be the most representative because it avoids interference factors that may exist at the beginning and end, such as initial bubbles or residual liquid at the end.

[0020] The data acquisition module 12 is used to import the mid-segment sampling results into a predetermined area, and perform data acquisition through a combination of sensors arranged in the predetermined area to establish a fused data set.

[0021] Specifically, the retained midstream urine sample is introduced into a pre-set analysis area through a pipeline or a transfer device, and the pre-set area can be a specific container or equipment in the laboratory; then, data of the midstream urine sample is collected by a combination sensor arranged in the pre-set area, wherein the combination sensor includes a pH sensor with high sensitivity and fast response characteristics, and the sensor has a wide measurement range (such as a pH collection range of 0 to 14) and a small error range (such as a collection error range of ±0.01pH); in addition, it also includes a temperature sensor, a humidity sensor and an air pressure sensor for collecting ambient environmental parameters, and a fused data set is obtained according to the data collection results, wherein the fused data set includes urine pH value, ambient temperature, ambient humidity and air pressure.

[0022] The microcontroller 13 is used to receive the fused data set, call the environmental data of the fused data set, perform pH value data correction of the fused data set based on the environmental data through the environmental correction network built in the microcontroller, establish a first correction result, activate the noise correction network built in the microcontroller, filter the first correction result based on the noise correction network, and establish a second correction result.

[0023] Specifically, the microcontroller is the control core, responsible for data collection, processing and transmission. For example, the microcontroller is an ARMCortex-M series. The microcontroller is connected to various sensor interfaces through its I / O port to receive raw data from pH sensors, temperature sensors, humidity sensors and air pressure sensors. The fused data set is received by the microcontroller, and the environmental data of the fused data set is called, wherein the environmental data includes ambient temperature, ambient humidity and air pressure. Then the environmental data is input into the environmental correction network built into the microcontroller, wherein the environmental correction network includes an environmental correction algorithm for adjusting the pH value according to the environmental data to compensate for the influence of environmental factors (temperature, humidity and air pressure) on the measurement results, improve the measurement accuracy, and output the first correction result. Then the noise correction network built into the microcontroller is activated, and the noise correction network includes a noise correction algorithm for processing and reducing random noise or irregular fluctuations in the measurement data to improve the accuracy and reliability of the data. The first correction result is filtered through the noise correction network to obtain the second correction result.

[0024] By constructing an environmental correction network and a noise correction network to perform data correction on urine pH monitoring, the influence of environmental factors and random noise on urine pH measurement can be eliminated or reduced, thereby improving the accuracy and reliability of pH measurement.

[0025] The display module 14 is used to receive the second calibration result and perform real-time display of the urine pH value.

[0026] Specifically, the display module is a key part of the urine pH monitoring and collection device for direct user interaction. It is responsible for displaying the corrected urine pH value to the user in an intuitive manner. The display module includes a liquid crystal display and an LED indicator. The liquid crystal display is used to display the pH value of the urine in real time, and the LED indicator is used to indicate the status (such as normal, abnormal, etc.) so that the user can quickly understand the monitoring results. The second correction result is received through the display module, and the urine pH value is displayed in real time through the liquid crystal display and the LED indicator.

[0027] By providing a urine pH monitoring and collection device, the technical problems of low pH detection accuracy, insufficient monitoring sensitivity and convenience in the existing urine pH monitoring and collection device can be solved. By receiving the user's input signal, configuring an adaptive segmentation strategy based on the input signal, collecting the user's urine sample in segments with the adaptive segmentation strategy, and retaining the mid-segment sampling result; then importing the mid-segment sampling result into a predetermined area, and performing data acquisition through a combined sensor set in the predetermined area to establish a fusion data set; then receiving the fusion data set through a microcontroller, calling the environmental data of the fusion data set, and correcting the pH value data of the fusion data set based on the environmental data through the environmental correction network built in the microcontroller, establishing a first correction result, activating the noise correction network built in the microcontroller, filtering the first correction result based on the noise correction network, and establishing a second correction result; finally receiving the second correction result in the display module, and performing real-time display of urine pH value. In other words, by adopting a highly sensitive pH sensor and an advanced data processing algorithm, the sensitivity of pH monitoring can be improved, the accuracy of the detection results can be ensured, and the operation process can be simplified, and the user experience can be improved, thereby effectively meeting the needs of clinical rapid diagnosis.

[0028] Further, as attached Figure 2 As shown, the pH value data of the fused data set is corrected based on the environmental data through the environmental correction network built into the microcontroller to establish a first correction result, including:

[0029] The environmental data is analyzed to establish calibrated environmental values, wherein the calibrated environmental values ​​include calibrated temperature values, calibrated humidity values, and calibrated air pressure values, and each of the calibrated environmental values ​​carries a fluctuation mark; the temperature compensation layer of the environmental correction network is called to perform pH value data compensation based on the calibrated temperature value, and a temperature compensation result is established; the temperature compensation result is secondary compensated based on a joint compensation network using the calibrated temperature value, calibrated humidity value, calibrated air pressure value, and fluctuation mark, and pH value data correction is completed to establish a first correction result.

[0030] Specifically, the environmental data is analyzed to establish calibrated environmental values. The calibrated environmental values ​​refer to the actual environmental data after analysis, wherein the calibrated environmental values ​​include calibrated temperature values, calibrated humidity values, and calibrated air pressure values, such as the calibrated temperature is 28 degrees Celsius, the calibrated humidity is 45% relative humidity, and the calibrated air pressure is 1013.25 hPa; wherein each calibrated value is accompanied by a fluctuation mark, which usually refers to the fluctuation range of the indicator value, such as the temperature fluctuation mark is ±0.5 degrees Celsius, and the humidity fluctuation mark is ±2% relative humidity.

[0031] Then, the temperature compensation layer of the environmental correction network is called to perform data compensation on the pH value according to the built-in correction algorithm and the calibrated temperature value, that is, the pH value is compensated according to the calibrated temperature value (for example, 28 degrees Celsius). This step is to eliminate the influence of temperature changes on the pH measurement results and obtain a preliminary corrected pH value, that is, the temperature compensation result; further use the joint compensation network, through the built-in joint compensation algorithm, according to the calibrated temperature value, calibrated humidity value, calibrated air pressure value and fluctuation mark, the temperature compensation result is secondary compensated to complete the pH value data correction and obtain the first correction result. This process ensures that the measurement of pH value not only takes into account the influence of temperature, but also comprehensively considers the changes in humidity and air pressure, thereby improving the accuracy and reliability of the measurement.

[0032] Further, the calling of the temperature compensation layer of the environmental correction network to perform pH value data compensation based on the calibrated temperature value and establish a temperature compensation result also includes:

[0033] Call the compensation formula of the temperature compensation layer to compensate the pH value data as follows: Among them, pH(T) represents the temperature compensation result, that is, the pH value after temperature correction, pH measured Characterize the original pH value under the fused data set, T current Characterize the calibration temperature value, T reference Characterizes the reference temperature value, and k is the temperature influence constant.

[0034] Specifically, the temperature compensation formula of the temperature compensation layer is called, wherein in the temperature compensation formula, pH(T) represents the temperature compensation result, that is, the pH value after temperature correction, pH measured Characterize the original pH value under the fused data set, T current Characterize the calibration temperature value, T reference The reference temperature value is represented, and k is the temperature influence constant. Then the calibration temperature value is input into the temperature compensation formula to calculate the temperature compensation result.

[0035] Furthermore, the method of performing secondary compensation on the temperature compensation result based on a joint compensation network by using the calibrated temperature value, the calibrated humidity value, the calibrated air pressure value and the fluctuation mark also includes:

[0036] Call the multidimensional correction function of the joint compensation network to perform quadratic compensation as follows: pH corrected (T) = pH (T) + α (T current -T reference )+βH+γP; where pH corrected (T) represents the first calibration result, T current is the calibration temperature value, T reference It represents the reference temperature value, α is the temperature correction coefficient, which is established based on the temperature corresponding fluctuation mark and historical data, H is the calibrated humidity value, β is the humidity correction coefficient, which is established based on the humidity corresponding fluctuation mark and historical data, P is the calibrated air pressure value, and γ is the air pressure correction coefficient, which is established based on the air pressure corresponding fluctuation mark and historical data.

[0037] Specifically, a multidimensional correction function of a joint compensation network is called, in which pH corrected (T) represents the first calibration result, T current is the calibration temperature value, T reference Characterizes the reference temperature value, α is the temperature correction coefficient, which is established based on the temperature corresponding fluctuation mark and historical data. In the joint compensation network, since temperature compensation has been performed in the first step, the joint compensation network in the second step can weaken the correction weight of the temperature. That is to say, in the multidimensional correction formula, the temperature influence coefficient α should be significantly reduced or only used for fine-tuning to avoid over-compensation. The temperature corresponding fluctuation mark, the historical temperature influence and the temperature correction coefficient are positively correlated, that is, the larger the temperature corresponding fluctuation mark, the greater the historical temperature influence, and the larger the temperature correction coefficient; H is the calibrated humidity value, β is the humidity correction coefficient, which is established based on the humidity corresponding fluctuation mark and historical data. The humidity corresponding fluctuation mark, the historical humidity influence and the humidity correction coefficient are positively correlated, that is, the larger the humidity corresponding fluctuation mark, the greater the historical humidity influence, and the larger the humidity correction coefficient; P is the calibrated air pressure value, γ is the air pressure correction coefficient, which is established based on the air pressure corresponding fluctuation mark and historical data. The air pressure correction coefficient is positively correlated with the air pressure corresponding fluctuation mark and the historical air pressure influence.

[0038] Using a multidimensional correction function, a calibration temperature value, a calibration humidity value, a calibration pressure value, a fluctuation mark and a temperature compensation result are input into the multidimensional correction function to calculate and obtain a first correction result.

[0039] Further, the activating the noise correction network built in the microcontroller, filtering the first correction result based on the noise correction network, and establishing the second correction result also includes:

[0040] The acquisition frequency of the pH sensor in the combined sensor is obtained, and the filter window size is set based on the acquisition frequency; the noise correction network is initialized based on the filter window size, and the filtering process is performed as follows: Among them, pH filtered [n] represents the second correction result, N represents the filter window size, i represents the time step of the filter process backtracking from the current time node n, pH calibrated [ni] represents the first correction result of the ni-th time node, and n is the index of the current time node.

[0041] Specifically, the data acquisition frequency of the pH sensor is read from the combined sensor. The data acquisition frequency is in Hertz (Hz), which indicates the number of data acquisitions per second, for example, 100 samples per second. Then, the size of the filter window is set according to the acquisition frequency of the pH sensor. The filter window size determines the number of data points used in the filtering process, where the window size is proportional to the acquisition frequency to ensure the filtering effect. For example, if the acquisition frequency is 10 Hz, the filter window size is set to 100 data points, that is, each window covers 10 seconds of data. Then, after setting the filter window size, the microcontroller will initialize the noise correction network. The initialization includes setting the parameters of the filtering algorithm, such as the window size, the filter type (such as moving average, low-pass filter, Kalman filter, etc.) and the filter coefficient. After the initialization is completed, the noise correction network is used to perform the filtering process.

[0042] Among them, the filtering function is: Among them, pH filtered [n] represents the second correction result, N represents the filter window size, i represents the time step of the filter process backtracking from the current time node n, pH calibrated [ni] represents the first correction result of the ni-th time node, and n is the index of the current time node. The first correction result is filtered by the filtering function to obtain the second correction result.

[0043] Furthermore, the device also includes:

[0044] The transmission module, after receiving the transmission instruction, establishes a mobile terminal communication connection through a data transmission protocol and sends the urine pH value to the mobile terminal.

[0045] Specifically, after receiving the transmission instruction, the transmission module establishes a communication connection with the mobile terminal through a data transmission protocol, such as using Bluetooth Low Energy (BLE) as the main wireless communication protocol because it is suitable for mobile devices and low-power sensors; then uses the AES (Advanced Encryption Standard) algorithm to encrypt the transmitted urine pH data, and transmits the encrypted data to the mobile terminal to ensure the security of the data during transmission.

[0046] Further, configuring the adaptive segmentation strategy based on the input signal further includes:

[0047] The input signal is analyzed to generate basic segmentation constraints; the user's historical database is called to evaluate the user's urine flow based on the historical database, and an adaptive segmentation strategy is established based on the evaluation results and basic segmentation constraints.

[0048] Specifically, first, the input signal is parsed, that is, the large, medium, small and other signals input by the user are converted into specific capacity information. Then, according to the parsed input signal, the preliminary urine collection segmentation rules are set. For example, if the user input is large, the segmentation strategy may be set to collect more urine each time. If the input is small, a smaller amount of urine is collected each time. The user's historical database is further called, that is, the database that stores the user's historical urine flow data, and the user's historical data is analyzed to evaluate the user's urine flow pattern, including the size, frequency, time distribution, etc. of the flow, to obtain the user's urine flow evaluation results. Finally, the historical urine flow evaluation results are combined with the basic segmentation constraints generated previously to create a more personalized urine collection strategy. This strategy can automatically adjust the collection parameters according to the user's historical data and current predictions to better meet the user's actual needs.

[0049] Furthermore, the method of collecting the urine sample of the user in segments by using an adaptive segmentation strategy and retaining the mid-segment sampling result also includes:

[0050] Activate the flow sensor, perform flow velocity perception for segmented collection of urine samples based on the flow sensor, and establish flow velocity perception results; self-optimize the adaptive segmentation strategy through the flow velocity perception results, use the self-optimization results to complete segmented collection, and retain the mid-segment sampling results.

[0051] Specifically, first, activate the flow sensor in the urine collection device and prepare to start monitoring the urine outflow process. Then, the flow sensor is used to monitor the speed and flow of urine outflow in real time, and establish the flow rate sensing result, including the change of flow rate, the size of flow rate and other information. Then, the flow rate sensing result is analyzed and compared with the adaptive segmentation strategy established previously, and the segmentation strategy is adjusted according to the flow rate sensing result to optimize the segmentation collection process. For example, if the flow rate is fast, the time interval of the segmentation may need to be shortened; if the flow rate is slow, the time interval of the segmentation may need to be extended. Finally, the urine sample is collected using the self-optimized segmentation strategy. After the segmentation collection is completed, the urine sample in the middle segment is selected as the retained sample. Usually, the middle segment sample is considered to be the most representative because it avoids the interference factors that may exist at the beginning and end, such as the initial bubbles or the residual liquid at the end.

[0052] In summary, the urine pH monitoring and collection device provided by the present application has the following technical effects:

[0053] By receiving the user's input signal, configuring the adaptive segmentation strategy based on the input signal, collecting the user's urine sample in segments with the adaptive segmentation strategy, and retaining the mid-segment sampling result; then importing the mid-segment sampling result into a predetermined area, and performing data acquisition through a combined sensor set in the predetermined area to establish a fusion data set; then receiving the fusion data set through a microcontroller, calling the environmental data of the fusion data set, and correcting the pH value data of the fusion data set based on the environmental data through the environmental correction network built into the microcontroller, establishing a first correction result, activating the noise correction network built into the microcontroller, filtering the first correction result based on the noise correction network, and establishing a second correction result; finally receiving the second correction result in the display module, and performing real-time display of urine pH value. In other words, by adopting a highly sensitive pH sensor and advanced data processing algorithms, the sensitivity of pH monitoring can be improved, the accuracy of the test results can be ensured, and the operation process can be simplified, and the user experience can be improved, thereby effectively meeting the needs of clinical rapid diagnosis.

[0054] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0055] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the present application and its equivalent technology, the present application is also intended to include these modifications and variations.

Claims

1. A urine pH monitoring and collection device, characterized in that: The device includes: A segmented sampling module, used to receive an input signal from a user, configure an adaptive segmentation strategy based on the input signal, collect the user's urine sample in segments using the adaptive segmentation strategy, and retain the mid-segment sampling result; A data acquisition module, used for importing the mid-segment sampling results into a predetermined area, and performing data acquisition through a combined sensor arranged in the predetermined area to establish a fused data set; The microcontroller is used to receive the fused data set, call the environmental data of the fused data set, perform pH value data correction of the fused data set based on the environmental data through an environmental correction network built in the microcontroller, establish a first correction result, activate the noise correction network built in the microcontroller, filter the first correction result based on the noise correction network, and establish a second correction result; The display module is used to receive the second calibration result and perform real-time display of the pH value of urine.

2. A urine pH monitoring and collecting device as claimed in claim 1, characterized in that: The step of correcting the pH value data of the fused data set based on the environmental data by using the environmental correction network built into the microcontroller to establish a first correction result also includes: Performing data analysis on the environmental data to establish calibrated environmental values, wherein the calibrated environmental values ​​include calibrated temperature values, calibrated humidity values, and calibrated air pressure values, and each calibrated value in the calibrated environmental values ​​is marked with a fluctuation mark; Call the temperature compensation layer of the environmental correction network to perform pH value data compensation based on the calibrated temperature value and establish a temperature compensation result; The temperature compensation result is subjected to secondary compensation based on a joint compensation network using the calibrated temperature value, the calibrated humidity value, the calibrated air pressure value and the fluctuation mark, the pH value data is corrected, and the first correction result is established.

3. A urine pH monitoring and collecting device as claimed in claim 2, characterized in that: The calling of the temperature compensation layer of the environmental correction network to perform pH value data compensation based on the calibrated temperature value and establish the temperature compensation result also includes: Call the compensation formula of the temperature compensation layer to compensate the pH value data as follows: Among them, pH(T) represents the temperature compensation result, that is, the pH value after temperature correction, pH measured Characterize the original pH value under the fused data set, T current Characterize the calibration temperature value, T reference Characterizes the reference temperature value, and k is the temperature influence constant.

4. A urine pH monitoring and collecting device as claimed in claim 3, characterized in that: The method of performing secondary compensation on the temperature compensation result based on a joint compensation network by using the calibrated temperature value, the calibrated humidity value, the calibrated air pressure value and the fluctuation mark also includes: Call the multidimensional correction function of the joint compensation network to perform quadratic compensation as follows: pH corrected (T)=pH(T)+α(T current -T reference )+βH+γP; Among them, pH corrected (T) represents the first calibration result, T current is the calibration temperature value, T reference It represents the reference temperature value, α is the temperature correction coefficient, which is established based on the temperature corresponding fluctuation mark and historical data, H is the calibrated humidity value, β is the humidity correction coefficient, which is established based on the humidity corresponding fluctuation mark and historical data, P is the calibrated air pressure value, and γ is the air pressure correction coefficient, which is established based on the air pressure corresponding fluctuation mark and historical data.

5. A urine pH monitoring and collecting device as claimed in claim 1, characterized in that: The activating the noise correction network built into the microcontroller, filtering the first correction result based on the noise correction network, and establishing the second correction result also includes: Acquire the acquisition frequency of the pH sensor in the combined sensor, and set the filter window size based on the acquisition frequency; The noise correction network is initialized based on the filter window size and the filtering process is performed as follows: Among them, pH filtered [n] represents the second correction result, N represents the filter window size, i represents the time step of the filter process backtracking from the current time node n, pH calibrated [ni] represents the first correction result of the ni-th time node, and n is the index of the current time node.

6. A urine pH monitoring and collecting device as claimed in claim 1, characterized in that: The device also includes: The transmission module, after receiving the transmission instruction, establishes a mobile terminal communication connection through a data transmission protocol and sends the urine pH value to the mobile terminal.

7. A urine pH monitoring and collecting device as claimed in claim 1, characterized in that: The configuring an adaptive segmentation strategy based on the input signal further includes: Analyze the input signal and generate basic segment constraints; The user's historical database is called, and the user's urine flow rate is evaluated based on the historical database, and an adaptive segmentation strategy is established based on the evaluation results and basic segmentation constraints.

8. A urine pH monitoring and collecting device as claimed in claim 7, characterized in that: The method of collecting the urine sample of the user in segments by using an adaptive segmentation strategy and retaining the mid-segment sampling result also includes: Activate the flow sensor, perform flow velocity sensing for segmented collection of urine samples based on the flow sensor, and establish flow velocity sensing results; The adaptive segmentation strategy is self-optimized through the flow velocity perception results, and the segment collection is completed using the self-optimization results, retaining the mid-segment sampling results.

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