A method and system for monitoring the intra-abdominal pressure of a newborn

Abstract

An embodiment of the present invention provides a method and system for monitoring neonatal intra-abdominal pressure, belonging to the field of medical electronics technology. The method is implemented based on a wrinkled microcrack flexible sensor, and the method includes: obtaining a collection signal based on the wrinkled microcrack flexible sensor attached to the abdominal cavity, and preprocessing the collection signal; performing data analysis based on the preprocessed collection signal to obtain the corresponding abdominal wall tension; calling a corresponding intra-abdominal pressure mapping model based on the abdominal wall tension, and outputting the corresponding intra-abdominal pressure based on the intra-abdominal pressure mapping model; pushing the intra-abdominal pressure to the user end. The method of the present invention provides a sustainable and continuous monitoring solution for intra-abdominal pressure monitoring, greatly improving the safety, convenience and accuracy of intra-abdominal pressure monitoring.

Description

Technical Field

[0001] The present invention relates to the field of medical electronics, and particularly to a method for monitoring neonatal intra-abdominal pressure and a neonatal intra-abdominal pressure monitoring system. Background Art

[0002] With the progress of medical technology, the monitoring of intra-abdominal pressure (IAP) has become increasingly important in clinical practice, especially during the treatment of neonates and critically ill patients. Intra-abdominal hypertension (IAH) has been recognized as being associated with multiple severe complications, including intestinal necrosis, organ failure, etc. Traditional intra-abdominal pressure measurement methods are mainly divided into invasive and non-invasive categories. Existing invasive methods, such as abdominal puncture or bladder pressure measurement, although capable of providing relatively accurate pressure data, due to their invasive nature, may pose risks such as infection and injury. Especially in high-risk groups such as neonates, the use of such methods is extremely inconvenient and dangerous. On the other hand, non-invasive methods, such as indirectly inferring intra-abdominal pressure by measuring abdominal circumference, gastric pressure, or using airbags, although able to reduce patient discomfort and risks, these methods have low precision, cannot provide real-time and continuous pressure change data, and there are still certain limitations in their application to neonates.

[0003] With the development of flexible sensor technology, intra-abdominal pressure monitoring devices based on flexible strain sensors have gradually attracted attention. Flexible sensors have high sensitivity, good flexibility, and the ability for continuous monitoring, and can non-invasively and real-time monitor intra-abdominal pressure without disturbing the normal physiological activities of patients. However, currently, the application of most flexible sensors still faces some challenges in the signal acquisition and analysis process, especially in precisely establishing a stable and accurate mapping relationship between the signals measured by the sensor and the actual intra-abdominal pressure.

[0004] Existing technologies usually rely on traditional resistance change signals to infer strain values and pressures. However, due to uneven contact between the sensor and the abdominal wall, elastic differences in the abdominal wall, as well as the influence of sensor sensitivity and environmental factors, the accuracy of these methods is limited. In addition, the signal preprocessing process in existing technologies is mostly simple filtering and amplification, lacking an accurate model to associate the complex relationship between abdominal wall tension and intra-abdominal pressure, and unable to achieve high-precision and personalized pressure monitoring.

[0005] Therefore, there is an urgent need in the existing technology for a non-invasive, real-time, and high-precision intra-abdominal pressure monitoring solution that can improve the measurement accuracy while ensuring safety, and accurately map the strain signal to the intra-abdominal pressure by establishing a scientific model to meet the clinical demand for continuous and real-time pressure monitoring. Summary of the Invention

[0006] The objective of the embodiments of the present invention is to provide a method for monitoring neonatal intra-abdominal pressure, so as to at least solve the problem that the existing solutions cannot ensure accurate monitoring of intra-abdominal pressure without creating wounds.

[0007] To achieve the above objective, the first aspect of the present invention provides a method for monitoring neonatal intra-abdominal pressure. The method is implemented based on a wrinkled microcrack flexible sensor, and the method includes: obtaining a collected signal based on the wrinkled microcrack flexible sensor attached to the abdominal cavity, and preprocessing the collected signal; performing data analysis based on the preprocessed collected signal to obtain the corresponding abdominal wall tension; invoking the corresponding intra-abdominal pressure mapping model based on the abdominal wall tension, and outputting the corresponding intra-abdominal pressure based on the intra-abdominal pressure mapping model; pushing the intra-abdominal pressure to the user terminal.

[0008] Optionally, the collected signal is a resistance change signal; the preprocessing of the collected signal includes: converting the resistance change signal into a corresponding voltage signal; sequentially performing filtering processing, amplification processing, and digitization processing on the voltage information to obtain the corresponding preprocessed collected signal.

[0009] Optionally, the performing data analysis based on the preprocessed collected signal to obtain the corresponding abdominal wall tension includes: determining the abdominal varicose parameters based on the preprocessed collected signal; determining the corresponding abdominal wall tension based on the abdominal varicose parameters and the corresponding abdominal wall tension calculation model; where the abdominal wall tension calculation model is:

[0010]

[0011] where is the abdominal wall tension; is the elastic modulus of the preset abdominal tissue; is the abdominal varicose parameter; is the abdominal tissue thickness.

[0012] Optionally, the determination rule for determining the abdominal varicose parameters based on the preprocessed collected signal is:

[0013]

[0014] where is the strain sensitivity factor of the pre-calibrated sensor; is the relative resistance change of the preprocessed collected signal; is the initial resistance of the wrinkled microcrack flexible sensor in the non-deformed state.

[0015] Optionally, the method further includes: constructing a corresponding intra-abdominal pressure mapping model, and the construction rule is: based on Laplace's law and tissue mechanics principles, constructing the functional relationship between abdominal wall tension and intra-abdominal pressure as the initial intra-abdominal pressure mapping model; collecting historical test data, and performing corresponding intra-abdominal pressure calibration on the abdominal wall tension in the historical test data to obtain training samples; performing fitting training on the initial intra-abdominal pressure mapping model based on the training samples to obtain a training model with a convergence result meeting the expectation as the intra-abdominal pressure mapping model.

[0016] Optionally, the pushing the intra-abdominal pressure to the user terminal includes: determining a corresponding data visualization scheme based on the magnitude relationship between the intra-abdominal pressure and each preset intra-abdominal pressure standard value; performing visualization of the intra-abdominal pressure based on the determined data visualization scheme, and pushing the visualization result to the user terminal.

[0017] A second aspect of the present invention provides a neonatal intra-abdominal pressure monitoring system, which is implemented based on a wrinkled microcrack flexible sensor. The system includes: an acquisition unit for obtaining an acquisition signal based on the wrinkled microcrack flexible sensor attached to the abdominal cavity and preprocessing the acquisition signal; an analysis unit for performing data analysis on the preprocessed acquisition signal to obtain the corresponding abdominal wall tension; a mapping unit for calling a corresponding intra-abdominal pressure mapping model based on the abdominal wall tension and outputting the corresponding intra-abdominal pressure based on the intra-abdominal pressure mapping model; a pushing unit for pushing the intra-abdominal pressure to the user terminal.

[0018] Optionally, the acquisition unit includes: a sensor module including a wrinkled microcrack flexible sensor and an attachment layer for attaching to the abdominal cavity; a signal processing module for performing preprocessing of the acquisition signal of the sensor module.

[0019] Optionally, the signal processing module includes, connected in sequence: a sensing interface for receiving the acquisition signal; a conversion circuit module for converting the resistance signal of the sensor into a voltage signal; a filtering circuit module for removing noise and interference in the signal; an ADC conversion module for converting the analog voltage signal into a digital signal; a control unit for converting the digital signal into a signal to be transmitted; a Bluetooth module for wirelessly transmitting the signal to be transmitted to an upper computer.

[0020] On the other hand, the present invention provides a computer-readable storage medium, which stores instructions thereon, and when running on a computer, enables the computer to execute the above-mentioned neonatal intra-abdominal pressure monitoring method.

[0021] Through the above technical solution, the solution of the present invention can accurately collect the changes in abdominal wall tension by closely attaching the flexible sensor to the abdominal cavity, and effectively filter out noise through the preprocessing technology to ensure the stability and accuracy of the collected signal. Then, based on the preprocessed signal data, the abdominal wall tension is analyzed, and the tension value is converted into the corresponding abdominal cavity pressure through the abdominal cavity pressure mapping model, so as to provide an accurate estimation of the abdominal cavity pressure. The key advantage of this solution is that it adopts a personalized abdominal cavity pressure mapping model, which makes up for the deficiency in accuracy in the prior art, making the monitoring of abdominal cavity pressure more accurate and reliable, especially suitable for high-risk groups such as newborns. Finally, by pushing the monitoring results to the user terminal in real time, a sustainable and continuous monitoring solution is provided, greatly improving the safety, convenience and accuracy of abdominal cavity pressure monitoring.

[0022] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent specific embodiments section. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The drawings are used to provide a further understanding of the embodiments of the present invention, and constitute a part of the specification. They are used together with the following specific embodiments to explain the embodiments of the present invention, but do not constitute a limitation to the embodiments of the present invention. In the drawings:

[0024] Figure 1 is a flowchart of the steps of a method for monitoring neonatal abdominal cavity pressure provided by an embodiment of the present invention;

[0025] Figure 2 is a system structure diagram of a neonatal abdominal cavity pressure monitoring system provided by an embodiment of the present invention;

[0026] Figure 3 is a schematic structural diagram of a signal processing module provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] The following will describe in detail the specific embodiments of the present invention with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0028] Figure 1 is a method flowchart of a method for monitoring neonatal abdominal cavity pressure provided by an embodiment of the present invention. As Figure 1 shown, an embodiment of the present invention provides a method for monitoring neonatal abdominal cavity pressure. The method is implemented based on a wrinkled microcrack flexible sensor, and the method includes:

[0029] Step S10: Obtain a collected signal based on a wrinkled microcrack flexible sensor attached to the abdominal cavity, and preprocess the collected signal.

[0030] Specifically, the acquired signal is a resistance change signal; the preprocessing of the acquired signal includes: converting the resistance change signal into a corresponding voltage signal; performing filtering, amplification, and digitization processing on the voltage information in sequence to obtain a corresponding preprocessed acquired signal.

[0031] In the embodiment of the present invention, based on the technical solution of the pleated microcrack flexible sensor attached to the abdominal cavity, an innovative signal acquisition and processing method is adopted. By accurately acquiring the strain signal caused by abdominal varices, a non-invasive, real-time, and high-precision abdominal cavity pressure monitoring means is provided. The core of this method is to obtain the resistance change signal of the abdominal wall through the pleated microcrack flexible sensor and perform a series of preprocessing on these signals to ensure the accuracy and stability of the data.

[0032] The sensor is attached to the surface of the abdominal cavity to sense the change of abdominal cavity pressure. This sensor has high sensitivity and good flexibility and can sense the subtle deformation of the abdominal skin without interfering with normal physiological activities. When the abdominal cavity pressure changes, the microcrack structure of the sensor will deform with the pressure change, resulting in a change in resistance. These resistance change signals are the original signals collected, which reflect the strain situation of the abdominal wall. In this way, the sensor can accurately reflect the influence of abdominal cavity pressure on the abdominal wall and provide a basis for the real-time monitoring of abdominal cavity pressure.

[0033] However, the resistance change signal itself is relatively weak and vulnerable to noise interference. Therefore, the collected signal must be preprocessed. The preprocessing process includes several key steps such as signal conversion, filtering, amplification, and digitization, aiming to improve the signal-to-noise ratio of the signal and ensure the accuracy of subsequent data analysis. Specifically, it includes:

[0034] 1) Signal conversion: Convert the collected resistance change signal into a voltage signal. By using a resistance voltage division circuit, the change in resistance value will be directly converted into a voltage change, which makes the signal easier to process and amplify. Since the resistance change signal itself is weak and affected by various environmental factors (such as temperature fluctuations, sensor stability), directly analyzing the resistance signal may lead to errors. Therefore, the first step to ensure signal accuracy is to convert the resistance change signal into a voltage signal.

[0035] 2) Filtering processing: After the voltage signal is converted, it is still affected by electromagnetic interference, external noise, etc. Therefore, the signal must be filtered. By removing high-frequency noise and irrelevant signals, the real effective signal is extracted. The filtering process usually uses a low-pass filter, which can remove noise signals outside the frequency range and retain useful low-frequency change information to ensure the stability and accuracy of the signal.

[0036] 3) Amplification processing: The amplitude of the voltage signal is usually small and cannot be directly used for subsequent digitization and analysis. To improve the usability and sensitivity of the signal, the voltage signal needs to be amplified by an operational amplifier. The operational amplifier can amplify the signal to an appropriate voltage range for subsequent digital conversion.

[0037] In another possible implementation, since the amplifier will not only amplify the useful signal but also amplify the noise. To effectively improve the signal quality, noise suppression techniques must be combined. Specific methods include: using a low-noise amplifier (LNA) in the analog front-end design, optimizing the circuit layout to reduce electromagnetic interference, and using power filtering and shielding measures to reduce external interference. In addition, band-pass or low-pass filters can be added to the signal path to filter out invalid noise outside the frequency band. In the digital signal processing stage, algorithms such as average filtering, Kalman filtering, and wavelet transform can also be used to further reduce noise. Through the collaborative design of "amplification + noise filtering", the signal-to-noise ratio of the signal can be significantly improved, thus ensuring the stability of the data and the accuracy of the analysis results.

[0038] 4) Digitization processing: The amplified voltage signal is digitized by an analog-to-digital converter (ADC) to convert the analog voltage signal into a digital signal. The digital signal is convenient for the microprocessor to perform further data analysis and calculation, ensuring that there is no information loss or accuracy degradation during the signal processing and transmission process. The high-precision conversion of the ADC can accurately convert the signal into digital data, providing accurate input for the subsequent pressure calculation model.

[0039] Based on the solution of the present invention, the resistance change signal is converted into a voltage signal, which is convenient for processing and amplification; then through filtering and amplification processing, the noise is further removed and the signal strength is enhanced; finally, through digital conversion, the accuracy and stability of the signal during processing and transmission are ensured. Such a signal preprocessing method provides a reliable basis for subsequent data analysis, ensuring that the real-time monitoring results of intra-abdominal pressure are more accurate and reliable. In addition, through this preprocessing process, it is possible to monitor the intra-abdominal pressure in real time and continuously under non-invasive conditions, avoiding the risks and inconveniences brought by traditional invasive measurement methods. This makes the technical solution have broad prospects in the application of newborns, elderly patients and other high-risk groups, being able to reduce medical risks and improve the comfort of patients.

[0040] Step S20: Perform data analysis based on the preprocessed acquisition signal to obtain the corresponding abdominal wall tension.

[0041] Specifically, determine the abdominal varicose parameters based on the preprocessed acquisition signal; determine the corresponding abdominal wall tension based on the abdominal varicose parameters and the corresponding abdominal wall tension calculation model; wherein, the abdominal wall tension calculation model is:

[0042]

[0043] Among them, is the abdominal wall tension; is the elastic modulus of the preset abdominal tissue; is the abdominal varicose parameter; is the abdominal tissue thickness.

[0044] In the embodiments of the present invention, based on the preprocessed acquired signals, first, the abdominal varicose parameter is obtained through analysis, and this parameter reflects the degree of abdominal wall deformation caused by the abdominal cavity pressure. Specifically, the acquired signals (such as resistance change signals) are preprocessed, converted into voltage signals, and further processed through filtering, amplification, and digitization to obtain strain data regarding the abdominal wall deformation. These data are used to calculate the abdominal varicose parameter. The relationship between the abdominal wall tension T, the abdominal varicose parameter ε, the tissue elastic modulus E, and the abdominal tissue thickness h indicates that the abdominal wall tension not only depends on the deformation (i.e., strain) caused by the abdominal cavity pressure but is also affected by the mechanical properties of the abdominal tissue itself (such as elastic modulus and thickness). The elastic modulus E and the abdominal varicose parameter ε jointly determine the deformation response of the abdominal wall. A higher elastic modulus and a larger varicose parameter mean that the abdominal wall is more difficult to deform, thus generating a greater abdominal wall tension. The abdominal tissue thickness h is directly proportional to the abdominal wall tension. The greater the thickness, the greater the tension, reflecting the influence of the abdominal wall thickness on the force distribution and tension generation.

[0045] Preferably, due to the individual differences in the elastic modulus of the abdominal tissue and the abdominal tissue thickness, in abdominal cavity pressure monitoring, traditional methods use unified parameters for calculation, which may lead to measurement errors, especially in neonates, the elderly, or other special populations. To improve the accuracy and personalization of the monitoring results, this solution proposes a method for dynamically estimating the elastic modulus and thickness of the abdominal tissue based on imaging technology combined with sensor data, thereby solving the problems caused by individual differences in these parameters.

[0046] Specifically, ultrasonic imaging technology or CT / MRI imaging data can be combined to obtain the accurate thickness of the abdomen. By performing imaging analysis on the patient's abdomen, using image processing technology to extract the thickness data of the abdominal wall, and combining the tissue types (such as skin, muscle, fat, etc.) of different parts of the abdomen, the average thickness value of the local abdominal wall is obtained. These data can be updated in real time, avoiding the use of fixed average thickness values in traditional methods.

[0047] For the elastic modulus, the hardness of abdominal tissues is measured in real time through dynamic ultrasound elastography techniques (such as ultrasound elastography or acoustic wave propagation velocity testing). This technique detects the degree of deformation of abdominal tissues under the action of external forces and calculates the elastic modulus of the abdominal wall tissues. Combining the real-time data of the sensor, through a regression model or machine learning algorithm, the elastic modulus of the patient can be dynamically estimated based on the current abdominal wall strain and tissue type of the patient. This method can automatically update the elastic modulus value during each measurement to improve the accuracy of monitoring.

[0048] Specifically, the determination rule for determining the abdominal varicose parameters based on the preprocessed acquisition signal is as follows:

[0049]

[0050] Wherein, is the strain sensitivity factor of the pre-calibrated sensor; is the relative resistance change of the preprocessed acquisition signal; is the initial resistance of the wrinkled microcrack flexible sensor in the undeformed state.

[0051] In the embodiment of the present invention, the process of determining the abdominal varicose parameters based on the preprocessed acquisition signal first involves measuring the resistance change of the abdominal wall caused by the change in abdominal cavity pressure through the sensor. Since the resistance value of the sensor changes with the deformation of the abdominal wall caused by the abdominal cavity pressure, this change can be used to calculate the degree of deformation of the abdominal wall, that is, the abdominal varicose parameters. To ensure the accuracy of the measurement, it is first necessary to understand the strain sensitivity factor of the sensor, which is obtained through a pre-calibration process and reflects the response ability of the sensor to abdominal varicose changes.

[0052] Specifically, the calculation of the abdominal varicose parameters depends on the ratio between the acquired resistance change data and the initial resistance, combined with the strain sensitivity factor of the sensor. The initial resistance value is the reference resistance of the sensor when the abdominal cavity pressure has not changed and is used to compare the current resistance change. This process ensures that the resistance change can be accurately converted into a deformation amount and can effectively reflect the actual strain of the abdominal wall. In this way, the degree of abdominal varicose can be calculated, that is, the physical deformation of the abdomen caused by the change in internal pressure.

[0053] This strain measurement method based on the resistance change signal enables non-invasive and real-time monitoring of the deformation of the abdominal wall, providing reliable data support for the calculation and evaluation of the abdominal cavity pressure. The implementation of this technology greatly improves the accuracy of the measurement and has high sensitivity, and can adapt to the individual differences of different patients, providing a more accurate pressure monitoring scheme for clinical practice.

[0054] Step S30: Based on the abdominal wall tension, call the corresponding intra-abdominal pressure mapping model, and output the corresponding intra-abdominal pressure based on the intra-abdominal pressure mapping model.

[0055] Specifically, the method further includes: constructing a corresponding intra-abdominal pressure mapping model, and the construction rule is: based on Laplace's law and tissue mechanics principles, construct the functional relationship between abdominal wall tension and intra-abdominal pressure as the initial intra-abdominal pressure mapping model; collect historical test data, and perform corresponding intra-abdominal pressure calibration on the abdominal wall tension in the historical test data to obtain training samples; perform fitting training on the initial intra-abdominal pressure mapping model based on the training samples to obtain a training model with a convergence result meeting the expectations, as the intra-abdominal pressure mapping model.

[0056] In the embodiment of the present invention, in this intra-abdominal pressure monitoring solution, based on the measured abdominal wall tension, accurate estimation of intra-abdominal pressure (IAP) is achieved by calling the intra-abdominal pressure mapping model. Specifically, constructing a scientific and accurate intra-abdominal pressure mapping model is the key, and this model can convert abdominal wall tension into the corresponding intra-abdominal pressure. To ensure the efficiency and reliability of the model, this solution proposes a model construction process, which is trained and optimized through various means, and finally forms a mapping model that meets clinical requirements.

[0057] Specifically, the construction of this model first needs to establish the functional relationship between abdominal wall tension and intra-abdominal pressure based on Laplace's law and tissue mechanics principles. According to Laplace's law, there is a certain proportional relationship between abdominal wall tension and IAP, especially in a closed spherical or cylindrical cavity. The actual abdominal wall structure and abdominal cavity shape are much more complex than the simple structures described in Laplace's law. Therefore, in addition to the basic Laplace's law, tissue mechanics principles need to be combined to further correct the model. Tissue mechanics principles consider factors such as the elastic properties of the abdominal wall and the non-linear response of tissues, which are crucial for accurately estimating intra-abdominal pressure.

[0058] Furthermore, to make the model have practical application value, it must be trained with actual clinical data. First, through the collection of historical test data, the abdominal wall tension data of patients under different intra-abdominal pressure conditions are obtained. These test data use the intra-abdominal pressure obtained by a known standard method (bladder pressure measurement method) as the calibration value, and the corresponding abdominal wall tension is measured by a flexible sensor. Each set of data includes a known intra-abdominal pressure value and the corresponding abdominal wall tension value. After collecting these historical test data, next, perform intra-abdominal pressure calibration on the abdominal wall tension in the historical test data. Through this step, a calibration pressure value corresponding to the standard intra-abdominal pressure method (bladder pressure method) is provided for each set of data. These calibration values will be used as training samples for subsequent model training.

[0059] Furthermore, using these training samples, the initially established intra-abdominal pressure mapping model can be fitted and trained. The purpose of the fitting training is to compare the calibrated historical data with the output of the initial mapping model and continuously adjust the model parameters to reduce the prediction error. During the fitting process, common regression analysis methods such as the least squares method are used to optimize the model to better adapt to the actual data. In addition, machine learning methods such as support vector machines (SVM) or neural networks can also be used to further improve the non-linear fitting ability of the model. These optimization methods enable the model to accurately predict the abdominal pressure under different clinical data and patient conditions. After multiple trainings and optimizations, a training model that meets the expectations is finally obtained. The output of this model is very close to the actual abdominal pressure measurement value and has strong adaptability and accuracy.

[0060] Based on the solution of the present invention, by combining Laplace's law and tissue mechanics principles, a more practical mapping model of abdominal wall tension and intra-abdominal pressure is established. This model takes into account the elasticity, thickness, and tissue characteristics of the abdominal wall and can provide more accurate prediction of intra-abdominal pressure. Through the collection and calibration of historical test data, the model can be adjusted according to the individual differences of different patients, making the monitoring of intra-abdominal pressure for each patient more personalized. By dynamically adjusting the model parameters, it can adapt to different intra-abdominal pressure change situations. The model can predict the intra-abdominal pressure in real time based on the real-time obtained abdominal wall tension signal, making non-invasive and accurate monitoring possible and avoiding the risks brought by traditional invasive methods. Through the training samples and the optimization process, the prediction results of the model have a high consistency compared with traditional measurement methods (such as the bladder pressure method), greatly improving the reliability and accuracy of intra-abdominal pressure monitoring.

[0061] Step S40: Push the intra-abdominal pressure to the user terminal.

[0062] Specifically, determine the corresponding data visualization scheme based on the magnitude relationship between the intra-abdominal pressure and each preset intra-abdominal pressure standard value; perform the visualization of the intra-abdominal pressure based on the determined data visualization scheme and push the visualization result to the user terminal.

[0063] In the embodiment of the present invention, the monitoring of intra-abdominal pressure not only provides a numerical result, but also includes presenting the result to doctors or medical staff in a suitable manner to facilitate their quick and accurate clinical decisions. For this purpose, after obtaining the intra-abdominal pressure data, through the design of the visualization scheme according to the actual situation, the pressure value can be presented to the user in an intuitive and easy-to-understand way. This process includes the measurement of the intra-abdominal pressure value, comparison with the preset standard value, selection of a suitable display method, and finally pushing it to the user terminal.

[0064] Furthermore, during the entire monitoring process, the intra-abdominal pressure data obtained does not exist in isolation but needs to be compared with preset standard values. These standard values usually come from medical literature, clinical experience, or historical data and can be used to define the normal range and the danger range, as well as the different clinical significances at different pressure values. Refer to the IAP grading (2013 Pediatric ACS standard), 1 mmHg = 1.33 cmH2O. For example:

[0065] 1) Normal: 4 - 10 mmHg (5.3 - 13.3 cmH2O)

[0066] 2) Grade I increased intra-abdominal pressure: 10 - 15 mmHg (13.3 - 20 cmH2O)

[0067] 3) Grade II: 16 - 20 mmHg (21 - 26.6 cmH2O), closely follow up the changes in the condition.

[0068] 4) Grade III: 21 - 25 mmHg (28 - 33.3 cmH2O), surgical intervention is required.

[0069] 5) Grade IV: >25 mmHg (>33.3 cmH2O), immediate surgical intervention is required.

[0070] By comparing the intra-abdominal pressure value obtained from real-time monitoring with these standard values, it is possible to determine which stage the current intra-abdominal pressure is in, which provides a basis for subsequent visual presentation and decision-making.

[0071] Furthermore, according to the comparison result between the intra-abdominal pressure and the preset standard value, an appropriate data visualization scheme is automatically selected. Different intra-abdominal pressure levels correspond to different display methods to ensure that users can intuitively identify the pressure changes and clinical urgency. Common visualization schemes include:

[0072] 1) Color coding: Represent different pressure values through color changes. For example, pressures within the normal range may be displayed in green, mildly high pressures in yellow, and severely high pressures in red.

[0073] 2) Chart display: For example, use real-time line charts, bar charts, or pie charts to show the changing trend of intra-abdominal pressure over time. In this way, doctors can intuitively see the fluctuations in intra-abdominal pressure, helping them understand the patient's condition.

[0074] 3) Numerical display: Display the specific intra-abdominal pressure value next to or above the chart and mark it in combination with the standard range. This enables doctors to quickly see the specific value and its clinical significance.

[0075] 4) Warning prompt: When the abdominal cavity pressure reaches or exceeds a certain critical value, the doctor is reminded to intervene by means of an alarm or highlighting.

[0076] Furthermore, after the visualization scheme is determined, the data will be transmitted to the user side through a wireless communication module (such as Bluetooth, Wi-Fi or mobile network). The user side is usually the doctor's workstation, mobile device or hospital monitoring. The specific operation process is as follows:

[0077] 1) Real-time data acquisition: The sensor collects and processes the abdominal cavity pressure data in real time through connection with the control unit.

[0078] 2) Data transmission: After signal processing and analysis, the data is converted into a visualized format and transmitted to the user side wirelessly. During the data transmission process, the integrity and security of the data are ensured to prevent data loss or leakage.

[0079] 3) User-side display: The doctor or medical staff receives the abdominal cavity pressure data through devices such as workstations, smartphones, and tablets, and presents it in a predetermined visualization scheme. These devices can update the display results in real time, allowing the doctor to react based on the latest data.

[0080] Based on the solution of the present invention, through wireless transmission, the abdominal cavity pressure data can be pushed to the user side in real time, enabling the doctor to obtain the change situation of the abdominal cavity pressure in the shortest time, achieving quick response and timely intervention. Especially when the abdominal cavity pressure enters the dangerous range, the doctor can take measures immediately. By comparing with the standard value in real time, it can effectively avoid the doctor's misunderstanding or neglect of the pressure value, reduce the error of traditional manual monitoring, and improve the reliability of the data. Through methods such as color coding, chart display, and numerical annotation, complex pressure data is converted into information that is easy for doctors to understand, helping doctors make decisions faster. Especially in emergency situations, it can quickly judge whether intervention measures need to be taken. Automatic monitoring and data visualization enable doctors to focus more on other aspects of the patient, reduce the cumbersome manual recording and analysis work, and improve medical efficiency. By continuously updating and adjusting the visualization scheme, personalized display modes can be provided according to the specific situation of the patient (such as medical history, body type, age, etc.), further improving the accuracy and practicality of abdominal cavity pressure monitoring.

[0081] Figure 2 It is the system structure diagram of the neonatal abdominal cavity pressure monitoring system provided by an embodiment of the present invention. As Figure 2As shown, an embodiment of the present invention provides a neonatal intra-abdominal pressure monitoring system, which includes: an acquisition unit for obtaining an acquisition signal based on a wrinkled microcrack flexible sensor attached to the abdominal cavity and preprocessing the acquisition signal; an analysis unit for performing data analysis on the preprocessed acquisition signal to obtain the corresponding abdominal wall tension; a mapping unit for calling a corresponding intra-abdominal pressure mapping model based on the abdominal wall tension and outputting the corresponding intra-abdominal pressure based on the intra-abdominal pressure mapping model; and a pushing unit for pushing the intra-abdominal pressure to the user terminal.

[0082] Preferably, the acquisition unit includes: a sensor module including a wrinkled microcrack flexible sensor and an attachment layer for attaching to the abdominal cavity; and a signal processing module for performing preprocessing of the acquisition signal of the sensor module.

[0083] Preferably, as Figure 3 , the signal processing module includes, connected in sequence: a sensing interface for receiving the acquisition signal; a conversion circuit module for converting the resistance signal of the sensor into a voltage signal; a filtering circuit module for removing noise and interference in the signal; an ADC conversion module for converting the analog voltage signal into a digital signal; a control unit for converting the digital signal into a signal to be transmitted; and a Bluetooth module for wirelessly transmitting the signal to be transmitted to the host computer.

[0084] An embodiment of the present invention also provides a computer-readable storage medium, on which instructions are stored, and when running on a computer, the computer is made to execute the above-mentioned neonatal intra-abdominal pressure monitoring method.

[0085] Those skilled in the art can understand that all or part of the steps in the method for implementing the above embodiments can be completed by instructing relevant hardware through a program. The program is stored in a storage medium, including several instructions for making a single-chip microcomputer, a chip or a processor execute all or part of the steps of the method according to various embodiments of the present invention. The aforementioned storage medium includes: various media such as a USB flash drive, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disc that can store program codes.

[0086] The optional embodiments of the present invention have been described in detail above in conjunction with the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details in the above embodiments. Within the scope of the technical concept of the embodiments of the present invention, various simple modifications can be made to the technical solutions of the embodiments of the present invention, and these simple modifications all fall within the protection scope of the embodiments of the present invention. In addition, it should be noted that in the above specific embodiments, the various specific technical features described can be combined in any suitable manner without conflict. To avoid unnecessary repetition, the embodiments of the present invention will not separately describe various possible combination methods.

[0087] In addition, any combination can be made between various different embodiments of the present invention, as long as it does not violate the idea of the embodiments of the present invention, and it should also be regarded as the content disclosed by the embodiments of the present invention.

Claims

1. A method for monitoring the intra-abdominal pressure of a neonate, characterized in that, The method is implemented based on a wrinkled microcrack flexible sensor, and the method includes: Obtaining an acquisition signal based on a wrinkled microcrack flexible sensor attached to the abdominal cavity, and preprocessing the acquisition signal; wherein, The acquisition signal is a resistance change signal; the preprocessing of the acquisition signal includes: Converting the resistance change signal into a corresponding voltage signal; sequentially performing filtering processing, amplification processing, and digitization processing on the voltage signal to obtain a corresponding preprocessed acquisition signal; Determining abdominal varicose parameters based on the preprocessed acquisition signal; Determining the corresponding abdominal wall tension based on the abdominal varicose parameters and the corresponding abdominal wall tension calculation model; wherein, The abdominal wall tension calculation model is: Among them, is the abdominal wall tension; is the elastic modulus of the preset abdominal tissue; is the abdominal varicose parameter; is the abdominal tissue thickness; The determination rule for determining abdominal varicose parameters based on the preprocessed acquisition signal is: Among them, is the strain sensitivity factor of the pre-calibrated sensor; is the relative resistance change of the pre-processed acquired signal; is the initial resistance of the wrinkled microcrack flexible sensor in the non-deformed state; Invoking a corresponding intra-abdominal pressure mapping model based on the abdominal wall tension, and outputting a corresponding abdominal cavity pressure based on the intra-abdominal pressure mapping model; Pushing the abdominal cavity pressure to the user side.

2. The method according to claim 1, wherein The method further includes: Constructing a corresponding intra-abdominal pressure mapping model, and the construction rule is: Constructing a functional relationship between the abdominal wall tension and the abdominal cavity pressure based on Laplace's law and tissue mechanics principles as the initial intra-abdominal pressure mapping model; Collecting historical test data, and performing corresponding abdominal cavity pressure calibration on the abdominal wall tension in the historical test data to obtain training samples; Performing fitting training on the initial intra-abdominal pressure mapping model based on the training samples to obtain a training model with a convergence result meeting expectations as the intra-abdominal pressure mapping model.

3. The method according to claim 1, wherein The pushing the abdominal cavity pressure to the user side includes: Determining a corresponding data visualization scheme based on the magnitude relationship between the abdominal cavity pressure and each preset abdominal cavity pressure standard value; Performing visualization of the abdominal cavity pressure based on the determined data visualization scheme, and pushing the visualization result to the user side.

4. A neonatal intra-abdominal pressure monitoring system, characterized in that, The system is applied to the neonatal abdominal cavity pressure monitoring method described in any one of claims 1-3. The system is implemented based on a wrinkled microcrack flexible sensor, and the system includes: An acquisition unit, configured to obtain an acquisition signal based on a wrinkled microcrack flexible sensor attached to the abdominal cavity, and preprocess the acquisition signal; An analysis unit, configured to perform data analysis based on the preprocessed acquisition signal to obtain a corresponding abdominal wall tension; A mapping unit, configured to invoke a corresponding intra-abdominal pressure mapping model based on the abdominal wall tension, and output a corresponding abdominal cavity pressure based on the intra-abdominal pressure mapping model; A pushing unit, configured to push the abdominal cavity pressure to the user side.

5. The system according to claim 4, wherein The acquisition unit includes: A sensor module, including a wrinkled microcrack flexible sensor and an attachment layer, and the attachment layer is used to attach to the abdominal cavity; A signal processing module, configured to perform preprocessing of the acquisition signal obtained by the sensor module.

6. The system according to claim 4, wherein The signal processing module includes components connected in sequence: A sensing interface, configured to receive the acquisition signal; A conversion circuit module, configured to convert the resistance signal of the sensor into a voltage signal; A filtering circuit module, configured to remove noise and interference in the signal; An ADC conversion module, configured to convert the analog voltage signal into a digital signal; A control unit, configured to convert the digital signal into a signal to be transmitted; A Bluetooth module for wirelessly transmitting a signal to be transmitted to a host computer.

7. A computer-readable storage medium, characterized in that, Instructions are stored on the computer-readable storage medium, and when running on a computer, cause the computer to execute the neonatal intra-abdominal pressure monitoring method according to any one of claims 1-3.

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