Intravesical Urine Volume Measurement System Based on Flexible Ultrasound Patch

Abstract

The present invention discloses a bladder urine volume measurement system based on a flexible ultrasonic patch, belonging to the field of flexible electronic sensing technology, including: a data acquisition module for real-time monitoring and acquisition of the urine volume in the patient's bladder based on the flexible ultrasonic patch to obtain an image of the urine volume in the patient's bladder based on the flexible ultrasonic patch; a data transmission module for transmitting the image of the urine volume in the patient's bladder based on the flexible ultrasonic patch to a urine volume measurement platform; and a urine volume measurement platform for performing pattern recognition and measurement of the urine volume in the patient's bladder according to the image of the urine volume in the patient's bladder based on the flexible ultrasonic patch to determine the measurement result of the urine volume in the bladder based on the flexible ultrasonic patch. The present invention solves the problem that the existing method cannot effectively and accurately measure the urine volume in the patient's bladder based on the flexible ultrasonic patch, resulting in poor measurement effect of the urine volume in the patient's bladder. The present invention can effectively and accurately measure the urine volume in the patient's bladder based on the flexible ultrasonic patch, and can improve the measurement effect of the urine volume in the patient's bladder.

Description

Technical Field

[0001] The present invention relates to the field of flexible electronic sensing technology, and specifically to a bladder urine volume measurement system based on a flexible ultrasonic patch. Background Art

[0002] With the aging of the population and the improvement of the quality of life, the incidence of diseases such as Alzheimer's disease and brain injury is increasing; among these diseases, urinary problems are a common problem faced by many patients, and accurate urine volume monitoring is crucial for the treatment and rehabilitation of patients; doctors usually use invasive methods such as urinary catheters or cystography to detect the urine volume in the patient's bladder. However, these methods may cause discomfort and risks to the patient, such as infection, bleeding, etc.

[0003] Chinese Patent No. CN117379055A discloses a wearable flexible magnetic field sensing probe for monitoring bladder urine volume, including a flexible encapsulation layer and a magnetic field sensing array located within the flexible encapsulation layer; wherein, the magnetic field sensing array is an array formed by arranging multiple magnetoresistive chips, and the pins of the magnetoresistive chips are led out of the flexible encapsulation layer through wires; by improving the component structure of the wearable flexible magnetic field sensing probe and their setting methods, arranging and encapsulating the magnetic field sensing array in the flexible encapsulation layer, and cooperating with the implantable magnetic composite mesh already developed in the prior art, it is possible to monitor the real-time morphology of the implantable magnetic composite mesh in the body through magnetic field sensing, thereby realizing the real-time monitoring of the bladder urine volume; however, this patent has the following defects:

[0004] The existing technology cannot effectively and accurately measure the urine volume in the patient's bladder based on a flexible ultrasonic patch, resulting in poor measurement effect of the urine volume in the patient's bladder. Summary of the Invention

[0005] The purpose of the present invention is to provide a bladder urine volume measurement system based on a flexible ultrasonic patch, which can effectively and accurately measure the urine volume in the patient's bladder based on the flexible ultrasonic patch, improve the measurement effect of the urine volume in the patient's bladder, and solve the problems raised in the above background art.

[0006] To achieve the above purpose, the present invention provides the following technical solutions:

[0007] A bladder urine volume measurement system based on a flexible ultrasonic patch, comprising:

[0008] A data acquisition module, used to monitor and collect the urine volume situation in the patient's bladder in real time based on the flexible ultrasonic patch, and obtain an image of the urine volume in the patient's bladder based on the flexible ultrasonic patch;

[0009] A data transmission module, used to transmit the image of the urine volume in the patient's bladder based on the flexible ultrasonic patch to the urine volume measurement platform;

[0010] A urine volume measurement platform for performing pattern recognition and measurement on the urine volume in a patient's bladder based on an image of the urine volume in the patient's bladder obtained by a flexible ultrasonic patch, and determining a measurement result of the urine volume in the bladder based on the flexible ultrasonic patch.

[0011] Preferably, the data acquisition module includes:

[0012] A flexible ultrasonic patch for obtaining an image of the urine volume in the patient's bladder;

[0013] Among them, the flexible ultrasonic patch is composed of two ultra-thin wafers and a high-frequency ultrasonic transducer. When the flexible ultrasonic patch is attached to the surface of the patient's bladder, the ultrasonic transducer emits ultrasonic waves. After being reflected by the bladder wall, the ultrasonic waves are received by the ultrasonic transducer and converted into electrical signals for output. Through the flexible piezoelectric ultrasonic probe of the flexible ultrasonic patch, an image of the urine volume in the patient's bladder based on the flexible ultrasonic patch is obtained.

[0014] Preferably, the data transmission module includes:

[0015] A data transmitting unit for transmitting an image of the urine volume in the patient's bladder based on the flexible ultrasonic patch;

[0016] A data receiving unit for receiving an image of the urine volume in the patient's bladder based on the flexible ultrasonic patch;

[0017] According to the measurement requirements of the urine volume in the bladder based on the flexible ultrasonic patch, a data transmission link is established between the data transmitting unit and the data receiving unit;

[0018] Among them, the data transmitting unit receives an image of the urine volume in the patient's bladder based on the flexible ultrasonic patch transmitted from the data acquisition module, and the data transmitting unit transmits the received image of the urine volume in the patient's bladder based on the flexible ultrasonic patch to the data receiving unit;

[0019] Among them, the data receiving unit receives an image of the urine volume in the patient's bladder based on the flexible ultrasonic patch transmitted from the data transmitting unit, and the data receiving unit transmits the received image of the urine volume in the patient's bladder based on the flexible ultrasonic patch to the urine volume measurement platform.

[0020] Preferably, to establish a data transmission link between the data transmitting unit and the data receiving unit, the following operations are performed:

[0021] The data transmitting unit transmits an instruction to request the establishment of a data transmission link to the data receiving unit;

[0022] The data receiving unit receives the instruction transmitted by the data transmitting unit to request the establishment of a data transmission link. The data receiving unit retrieves its own data transmission channels and checks whether there are any idle data transmission channels in the data receiving unit;

[0023] When there is an idle data transmission channel in the data receiving unit, the data receiving unit transmits an instruction to the data transmitting unit to agree to establish a data transmission link.

[0024] The data transmitting unit receives the instruction transmitted by the data receiving unit to agree to establish a data transmission link, and the data transmitting unit establishes a data transmission link with the data receiving unit according to the instruction transmitted by the data receiving unit to transmit the urine volume image in the patient's bladder based on the flexible ultrasonic patch.

[0025] Preferably, the urine volume measurement platform includes:

[0026] An image processing module for processing the urine volume image in the patient's bladder based on the flexible ultrasonic patch to determine the urine volume feature image in the patient's bladder based on the flexible ultrasonic patch.

[0027] A urine volume measurement module for measuring the urine volume in the patient's bladder to determine the measurement result of the urine volume in the bladder based on the flexible ultrasonic patch.

[0028] Preferably, the image processing module includes:

[0029] An image denoising unit for performing denoising processing on the urine volume image in the patient's bladder;

[0030] Obtain the urine volume image in the patient's bladder based on the flexible ultrasonic patch;

[0031] Based on the median filter, perform denoising processing on the urine volume image in the patient's bladder based on the flexible ultrasonic patch. Among them, replace the value of a point in the urine volume image in the patient's bladder based on the flexible ultrasonic patch with the median value of the values of each point in a neighborhood of this point, and let the pixels with relatively large differences in the gray values of the surrounding pixels take values closer to the values of the surrounding pixels, thereby eliminating isolated noise points, removing the noise of the urine volume image in the patient's bladder based on the flexible ultrasonic patch, and protecting the edge of the urine volume image in the patient's bladder based on the flexible ultrasonic patch.

[0032] An image enhancement unit for performing enhancement processing on the urine volume image in the patient's bladder;

[0033] Obtain the denoised urine volume image in the patient's bladder;

[0034] Based on the image enhancement technology, perform enhancement processing on the denoised urine volume image in the patient's bladder;

[0035] Perform contrast enhancement and sharpening processing on the denoised urine volume image in the patient's bladder to highlight the detailed features in the denoised urine volume image in the patient's bladder and make the urine volume area in the bladder more obvious.

[0036] An image segmentation unit for segmenting the urine volume image in the patient's bladder;

[0037] Obtain the enhanced urine volume image in the patient's bladder;

[0038] Based on image cropping and magnification techniques, extract the region of interest (ROI) from the enhanced urine volume image in the patient's bladder. Among them, extract the meaningful feature parts in the enhanced urine volume image in the patient's bladder, remove the irrelevant background in the enhanced urine volume image in the patient's bladder, focus the analysis on the key parts of the enhanced urine volume image in the patient's bladder, and determine the urine volume feature image of the patient's bladder based on the flexible ultrasonic patch.

[0039] Preferably, the urine volume measurement module includes:

[0040] A model construction unit for constructing a bladder urine volume measurement model based on a flexible ultrasonic patch;

[0041] According to the bladder urine volume measurement requirements based on the flexible ultrasonic patch, collect the historical urine volume images in the patient's bladder based on the flexible ultrasonic patch;

[0042] Divide the historical urine volume images in the patient's bladder based on the flexible ultrasonic patch to determine the bladder urine volume measurement training set and the bladder urine volume measurement test set;

[0043] Select a convolutional neural network model framework suitable for bladder urine volume measurement based on the flexible ultrasonic patch, and train the selected convolutional neural network model framework suitable for bladder urine volume measurement based on the flexible ultrasonic patch using the bladder urine volume measurement training set;

[0044] Determine the bladder urine volume measurement model based on the flexible ultrasonic patch;

[0045] A model optimization unit for optimizing the bladder urine volume measurement model based on the flexible ultrasonic patch to determine the optimal bladder urine volume measurement model based on the flexible ultrasonic patch.

[0046] Preferably, the urine volume measurement module further includes:

[0047] A urine volume measurement unit for measuring the urine volume in the patient's bladder;

[0048] Obtain the urine volume feature image of the patient's bladder based on the flexible ultrasonic patch;

[0049] Input the urine volume feature image of the patient's bladder based on the flexible ultrasonic patch into the optimal bladder urine volume measurement model based on the flexible ultrasonic patch;

[0050] Perform pattern recognition and classification on the characteristic images of the urine volume in the patient's bladder based on the flexible ultrasonic patch, according to the characteristics of the characteristic images of the urine volume in the patient's bladder based on the flexible ultrasonic patch, divide the characteristic images of the urine volume in the patient's bladder based on the flexible ultrasonic patch into certain categories, and then measure the urine volume in the patient's bladder;

[0051] Determine the measurement result of the urine volume in the bladder based on the flexible ultrasonic patch.

[0052] Preferably, the data acquisition module includes:

[0053] A reflected signal analysis unit, which is used to analyze the signal intensity and clarity of the received ultrasonic feedback signal that is reflected back based on a set signal feedback loop, and obtain the signal intensity and clarity of the real-time feedback signal;

[0054] A feedback signal quality optimization curve construction unit, which is used to optimize and predict the signal intensity and clarity of the ultrasonic feedback signal under different urine volumes in the bladder through a reflection signal optimization model based on a BP neural network, and draw the optimal signal intensity curve and the optimal clarity curve of the urine volume feedback optimized signal according to the prediction results;

[0055] A real-time signal quality judgment unit, which is used to obtain the optimal signal intensity and the optimal clarity corresponding to the real-time urine volume in the bladder through the optimal signal intensity curve and the optimal clarity curve respectively according to the real-time measurement result of the urine volume in the bladder, and calculate the signal quality evaluation index by using the following formula:

[0056] Wherein, is the signal quality evaluation index, is the signal intensity of the real-time feedback signal, is the optimal signal intensity corresponding to the real-time urine volume in the bladder, is the clarity of the real-time feedback signal, is the optimal clarity corresponding to the real-time urine volume in the bladder;

[0057] A transmission frequency adjustment unit, which is used to calculate the intensity difference between the signal intensity of the real-time feedback signal and the corresponding optimal signal intensity, and the clarity difference between the clarity of the real-time feedback signal and the corresponding optimal clarity when the signal quality evaluation index is greater than a preset threshold, and adjust the transmission frequency of the ultrasonic transducer.

[0058] Preferably, the feedback signal quality optimization curve construction unit includes:

[0059] A dataset construction subunit, which is used to obtain the stored ultrasonic emission information, ultrasonic feedback signals, and their corresponding signal intensity and clarity data, perform data cleaning to eliminate abnormal data, and group the cleaned stored data to form a training set, a validation set, and a test set;

[0060] A model construction subunit, which is used to construct a BP neural network model, and adaptively train, tune parameters, and test the model using the training set, validation set, and test set respectively to obtain a reflection signal optimization model;

[0061] The loss function for training the BP neural network model is as follows: Among them, is the th predicted signal intensity or predicted clarity, is the total number of signal intensities or the total number of clarities in the training set, is the th signal intensity or clarity in the training set.

[0062] Compared with the prior art, the beneficial effects of the present invention are:

[0063] The present invention performs real-time monitoring and acquisition of the urine volume in the patient's bladder through a flexible ultrasonic patch, obtains an image of the urine volume in the patient's bladder based on the flexible ultrasonic patch, processes the image of the urine volume in the patient's bladder based on the flexible ultrasonic patch to determine a characteristic image of the urine volume in the patient's bladder based on the flexible ultrasonic patch, performs pattern recognition and classification on the characteristic image of the urine volume in the patient's bladder based on the flexible ultrasonic patch using the optimal measurement model of the urine volume in the bladder based on the flexible ultrasonic patch, divides the characteristic image of the urine volume in the patient's bladder based on the flexible ultrasonic patch into certain categories according to the characteristics of the characteristic image of the urine volume in the patient's bladder based on the flexible ultrasonic patch, and then measures the urine volume in the patient's bladder to determine the measurement result of the urine volume in the bladder based on the flexible ultrasonic patch, which can effectively and accurately measure the urine volume in the patient's bladder based on the flexible ultrasonic patch and improve the measurement effect of the urine volume in the patient's bladder. Description of the Drawings

[0064] Figure 1 is the module schematic diagram of the urine volume measurement system in the bladder based on the flexible ultrasonic patch of the present invention;

[0065] Figure 2 is the structural block diagram of the urine volume measurement system in the bladder based on the flexible ultrasonic patch of the present invention. Detailed Embodiments

[0066] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0067] In order to solve the problem that the existing technology cannot effectively and accurately measure the urine volume in the patient's bladder based on a flexible ultrasonic patch, resulting in poor measurement effect of the urine volume in the patient's bladder, please refer to Figure 1 - Figure 2 , the following technical solutions are provided in this embodiment:

[0068] A urine volume measurement system in the bladder based on a flexible ultrasonic patch, comprising:

[0069] A data acquisition module, configured to monitor and acquire the urine volume situation in the patient's bladder in real time based on the flexible ultrasonic patch, and obtain an image of the urine volume in the patient's bladder based on the flexible ultrasonic patch;

[0070] In this embodiment, the data acquisition module includes:

[0071] A flexible ultrasonic patch, configured to obtain an image of the urine volume in the patient's bladder;

[0072] Among them, the flexible ultrasonic patch is composed of two ultra-thin wafers and a high-frequency ultrasonic transducer. When the flexible ultrasonic patch is attached to the surface of the patient's bladder, the ultrasonic transducer emits ultrasonic waves. After being reflected by the bladder wall, the ultrasonic waves are received by the ultrasonic transducer and converted into electrical signals for output. Through the flexible piezoelectric ultrasonic probe of the flexible ultrasonic patch, an image of the urine volume in the patient's bladder based on the flexible ultrasonic patch is obtained.

[0073] It should be noted that the flexible ultrasonic patch is a key component of the urine volume measurement system in the bladder. It is made of materials with excellent flexibility and biocompatibility and can be easily attached to the skin surface.

[0074] A data transmission module, configured to transmit the image of the urine volume in the patient's bladder based on the flexible ultrasonic patch to the urine volume measurement platform;

[0075] In this embodiment, the data transmission module includes:

[0076] A data transmitting unit, configured to transmit the image of the urine volume in the patient's bladder based on the flexible ultrasonic patch;

[0077] A data receiving unit, configured to receive the image of the urine volume in the patient's bladder based on the flexible ultrasonic patch;

[0078] According to the urine volume measurement requirements in the bladder based on the flexible ultrasonic patch, a data transmission link is established between the data transmitting unit and the data receiving unit;

[0079] Specifically, the data transmission unit transmits an instruction requesting to establish a data transmission link to the data reception unit;

[0080] The data reception unit receives the instruction transmitted by the data transmission unit requesting to establish a data transmission link, and the data reception unit retrieves its own data transmission channels to check whether there are any idle data transmission channels in the data reception unit;

[0081] When there are idle data transmission channels in the data reception unit, the data reception unit transmits an instruction agreeing to establish a data transmission link to the data transmission unit;

[0082] The data transmission unit receives the instruction transmitted by the data reception unit agreeing to establish a data transmission link, and the data transmission unit establishes a data transmission link with the data reception unit according to the instruction transmitted by the data reception unit agreeing to establish a data transmission link, for transmitting the urine volume image in the patient's bladder based on the flexible ultrasonic patch;

[0083] Among them, the data transmission unit receives the urine volume image in the patient's bladder based on the flexible ultrasonic patch transmitted by the data acquisition module, and the data transmission unit transmits the received urine volume image in the patient's bladder based on the flexible ultrasonic patch to the data reception unit;

[0084] Among them, the data reception unit receives the urine volume image in the patient's bladder based on the flexible ultrasonic patch transmitted by the data transmission unit, and the data reception unit transmits the received urine volume image in the patient's bladder based on the flexible ultrasonic patch to the urine volume measurement platform.

[0085] It should be noted that the transmission of the urine volume image in the patient's bladder based on the flexible ultrasonic patch can be achieved through wireless communication technologies such as Bluetooth and Wi-Fi.

[0086] The urine volume measurement platform is used to perform pattern recognition and measurement on the urine volume in the patient's bladder according to the urine volume image in the patient's bladder based on the flexible ultrasonic patch, and determine the measurement result of the urine volume in the bladder based on the flexible ultrasonic patch.

[0087] In this embodiment, the urine volume measurement platform includes:

[0088] The image processing module is used to process the urine volume image in the patient's bladder based on the flexible ultrasonic patch to determine the urine volume feature image in the patient's bladder based on the flexible ultrasonic patch;

[0089] In this embodiment, the image processing module includes:

[0090] The image denoising unit is used to perform denoising processing on the urine volume image in the patient's bladder;

[0091] Obtain an image of the urine volume in a patient's bladder based on a flexible ultrasonic patch;

[0092] Based on a median filter, denoise the image of the urine volume in a patient's bladder based on a flexible ultrasonic patch. Among them, replace the value of a point in the image of the urine volume in a patient's bladder based on a flexible ultrasonic patch with the median value of the values of each point in a neighborhood of this point, and make the pixels with relatively large differences in the gray values of the surrounding pixels take values close to the values of the surrounding pixels, so as to eliminate isolated noise points, remove the noise of the image of the urine volume in a patient's bladder based on a flexible ultrasonic patch, and protect the edge of the image of the urine volume in a patient's bladder based on a flexible ultrasonic patch;

[0093] An image enhancement unit for enhancing the image of the urine volume in a patient's bladder;

[0094] Obtain the denoised image of the urine volume in a patient's bladder;

[0095] Based on image enhancement technology, enhance the denoised image of the urine volume in a patient's bladder;

[0096] Perform contrast enhancement and sharpening processing on the denoised image of the urine volume in a patient's bladder, highlight the detailed features in the denoised image of the urine volume in a patient's bladder, and make the urine volume area in the bladder more obvious;

[0097] An image segmentation unit for segmenting the image of the urine volume in a patient's bladder;

[0098] Obtain the enhanced image of the urine volume in a patient's bladder;

[0099] Based on image cropping and magnification techniques, extract the region of interest (ROI) from the enhanced image of the urine volume in a patient's bladder. Among them, extract the meaningful feature parts in the enhanced image of the urine volume in a patient's bladder, remove the irrelevant background in the enhanced image of the urine volume in a patient's bladder, make the focus of analysis concentrate on the key parts of the enhanced image of the urine volume in a patient's bladder, and determine the image of the urine volume characteristics in a patient's bladder based on a flexible ultrasonic patch.

[0100] A urine volume measurement module for measuring the urine volume in a patient's bladder and determining the measurement result of the urine volume in the bladder based on a flexible ultrasonic patch.

[0101] In this embodiment, the urine volume measurement module includes:

[0102] A model construction unit for constructing a measurement model of the urine volume in a bladder based on a flexible ultrasonic patch;

[0103] According to the measurement requirements of the urine volume in a bladder based on a flexible ultrasonic patch, collect historical images of the urine volume in a patient's bladder based on a flexible ultrasonic patch;

[0104] Divide the historical images of the urine volume in the patient's bladder based on the flexible ultrasonic patch to determine the training set and the test set for measuring the urine volume in the bladder.

[0105] Select a convolutional neural network model framework suitable for measuring the urine volume in the bladder based on the flexible ultrasonic patch, and train the selected convolutional neural network model framework suitable for measuring the urine volume in the bladder based on the training set for measuring the urine volume in the bladder.

[0106] Determine the model for measuring the urine volume in the bladder based on the flexible ultrasonic patch.

[0107] The model optimization unit is used to optimize the model for measuring the urine volume in the bladder based on the flexible ultrasonic patch to determine the optimal model for measuring the urine volume in the bladder based on the flexible ultrasonic patch.

[0108] Among them, based on the test set for measuring the urine volume in the bladder, perform performance testing on the model for measuring the urine volume in the bladder based on the flexible ultrasonic patch, judge whether the performance of the model for measuring the urine volume in the bladder based on the flexible ultrasonic patch meets the standard requirements, and determine the test results of the model for measuring the urine volume in the bladder.

[0109] According to the test results of the model for measuring the urine volume in the bladder, conduct mining analysis on the model for measuring the urine volume in the bladder based on the flexible ultrasonic patch, adjust the parameters and optimize the structure settings, iterate the model for measuring the urine volume in the bladder based on the flexible ultrasonic patch repeatedly, and determine the optimal model for measuring the urine volume in the bladder based on the flexible ultrasonic patch, and the performance of its optimal model for measuring the urine volume in the bladder based on the flexible ultrasonic patch can meet the standard requirements of the model for measuring the urine volume in the bladder.

[0110] The urine volume measurement unit is used to measure the urine volume in the patient's bladder.

[0111] Obtain the characteristic image of the urine volume in the patient's bladder based on the flexible ultrasonic patch.

[0112] Input the characteristic image of the urine volume in the patient's bladder based on the flexible ultrasonic patch into the optimal model for measuring the urine volume in the bladder based on the flexible ultrasonic patch.

[0113] Based on the optimal model for measuring the urine volume in the bladder based on the flexible ultrasonic patch, perform pattern recognition and classification on the characteristic image of the urine volume in the patient's bladder based on the flexible ultrasonic patch, divide the characteristic image of the urine volume in the patient's bladder based on the flexible ultrasonic patch into a certain category according to the characteristics of the characteristic image of the urine volume in the patient's bladder based on the flexible ultrasonic patch, and then measure the urine volume in the patient's bladder.

[0114] Determine the measurement result of the urine volume in the bladder based on the flexible ultrasonic patch.

[0115] Based on the foregoing embodiments, the data acquisition module includes:

[0116] A reflected signal analysis unit, configured to analyze the signal intensity and clarity of the received ultrasonic feedback signal reflected back based on a set signal feedback loop, and obtain the signal intensity and clarity of the real-time feedback signal;

[0117] A feedback signal quality optimization curve construction unit, configured to optimize and predict the signal intensity and clarity of the ultrasonic feedback signal under different urine volumes in the bladder through a reflection signal optimization model based on a BP neural network, and draw an optimal signal intensity curve and an optimal clarity curve of the urine volume feedback optimization signal according to the prediction results;

[0118] A real-time signal quality judgment unit, configured to obtain the optimal signal intensity and optimal clarity corresponding to the real-time urine volume in the bladder through the optimal signal intensity curve and the optimal clarity curve respectively according to the real-time urine volume measurement result in the bladder, and calculate a signal quality evaluation index using the following formula:

[0119] where, is the signal quality evaluation index, is the signal intensity of the real-time feedback signal, is the optimal signal intensity corresponding to the real-time urine volume in the bladder, is the clarity of the real-time feedback signal, is the optimal clarity corresponding to the real-time urine volume in the bladder;

[0120] A transmission frequency adjustment unit, configured to calculate the intensity difference between the signal intensity of the real-time feedback signal and the corresponding optimal signal intensity, and the clarity difference between the clarity of the real-time feedback signal and the corresponding optimal clarity when the signal quality evaluation index is greater than a preset threshold, and adjust the transmission frequency of the ultrasonic transducer.

[0121] Specifically, based on historical data, the quality of the ultrasonic feedback signal is optimized using the reflection signal optimization model to obtain the optimal signal intensity and optimal clarity of the ultrasonic feedback signal corresponding to different urine volumes, and a reference curve is constructed therefrom; the signal intensity and clarity of the real-time feedback signal are respectively compared with the optimal signal intensity and optimal clarity queried on the reference curve for the corresponding urine volume, and the above algorithm is used to evaluate the signal quality. If the signal quality deviates too far from the optimum, the ultrasonic signal transmission frequency is adjusted according to the difference in signal quality parameters, combined with the mutual relationship between ultrasonic signal transmission and human reflection, so as to make the quality of the reflected signal received during the measurement process the best or close to the best as much as possible. Through this technical means, the reliability of the measurement result can be prevented from being affected by signal quality problems, and the credibility of the measurement result can be guaranteed. By introducing the signal quality evaluation index using the above algorithm, the quantification of quality evaluation is realized, the influence of human subjective factors is avoided, and the objectivity and reliability of the evaluation are improved.

[0122] Based on the foregoing embodiments, the feedback signal quality optimization curve construction unit includes:

[0123] A data set construction subunit, configured to obtain stored ultrasonic emission information, ultrasonic feedback signals, and their corresponding signal intensity and clarity data, perform data cleaning to remove abnormal data, and group the cleaned stored data correspondingly to form a training set, a validation set, and a test set;

[0124] A model construction subunit, configured to construct a BP neural network model, and perform adaptive training, parameter tuning, and testing on the model using the training set, the validation set, and the test set respectively to obtain a reflection signal optimization model;

[0125] The loss function for training the BP neural network model is as follows:

[0126] where is the th predicted signal intensity or predicted clarity, is the total number of signal intensities or the total number of clarities in the training set, is the th signal intensity or clarity in the training set.

[0127] Specifically, a corresponding model is constructed using a BP neural network. Through learning and adaptive training, a reflection signal optimization model for optimizing the prediction of signal strength and clarity is obtained. To make this model applicable to the urine volume measurement scenario of the present invention, the stored historical data is processed and respectively composed into data sets for the reflection signal optimization model to learn and adaptively train. The loss function of the training is set to accelerate the training process as much as possible. Through parameter tuning and testing, the reflection signal optimization model meets the target accuracy requirements, so that in subsequent use, the accuracy and reliability of the optimal signal quality reference curve obtained from its data processing results are guaranteed to ensure accurate urine volume measurement results under different physiological conditions.

[0128] It should be noted that pattern recognition is to classify samples into certain categories according to the characteristics of the samples by computational methods. Pattern recognition is to study the automatic processing and interpretation of patterns by computer using mathematical techniques, and the environment and objects are collectively referred to as "patterns". With the development of computer technology, it is possible for humans to study complex information processing processes. An important form of this process is the recognition of the environment and objects by living organisms. Pattern recognition mainly focuses on image processing and computer vision, speech and language information processing, brain network groups, brain-like intelligence, etc., and studies the mechanism of human pattern recognition and effective computational methods. Among them, in medical diagnosis, pattern recognition has achieved results in cancer cell detection, X-ray photo analysis, blood test, chromosome analysis, electrocardiogram diagnosis, and electroencephalogram diagnosis.

[0129] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device.

[0130] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A bladder urine volume measurement system based on a flexible ultrasonic patch, characterized in that: include: A data acquisition module is used to monitor and collect the urine volume in the patient's bladder in real time based on the flexible ultrasonic patch, and obtain an image of the urine volume in the patient's bladder based on the flexible ultrasonic patch; A data transmission module, used for transmitting the urine volume image in the patient's bladder based on the flexible ultrasound patch to the urine volume measurement platform; A urine volume measurement platform, which is used to perform pattern recognition and measurement of the urine volume in the patient's bladder based on the urine volume image in the patient's bladder based on the flexible ultrasonic patch, and determine the measurement result of the urine volume in the bladder based on the flexible ultrasonic patch; The data acquisition module comprises: A reflection signal analysis unit is used to analyze the signal strength and clarity of the ultrasonic feedback signal received and reflected based on a set signal feedback loop, so as to obtain the signal strength and clarity of the real-time feedback signal; A feedback signal quality optimization curve construction unit is used to optimize the signal strength and clarity of the ultrasonic feedback signal under different urine volumes in the bladder through a reflection signal optimization model based on a BP neural network, and to draw an optimal signal strength curve and an optimal clarity curve of the urine volume feedback optimization signal according to the prediction results; The real-time signal quality judgment unit is used to obtain the optimal signal strength and optimal clarity corresponding to the real-time bladder urine volume through the optimal signal strength curve and the optimal clarity curve according to the real-time bladder urine volume measurement result, and calculate the signal quality evaluation index using the following formula: in, is the signal quality evaluation index, To provide real-time feedback on the signal strength of the signal, The optimal signal strength corresponding to the real-time urine volume in the bladder, To provide real-time feedback on the clarity of the signal, The best clarity for real-time urine volume in the bladder; The transmitting frequency adjustment unit is used to calculate the strength difference between the signal strength of the real-time feedback signal and the corresponding optimal signal strength, as well as the clarity difference between the clarity of the real-time feedback signal and the corresponding optimal clarity when the signal quality evaluation index is greater than a preset threshold, and adjust the transmitting frequency of the ultrasonic transducer.

2. The bladder urine volume measurement system based on a flexible ultrasonic patch according to claim 1, characterized in that: The data acquisition module comprises: A flexible ultrasound patch to obtain images of urine volume in a patient’s bladder; Among them, the flexible ultrasonic patch consists of two ultra-thin chips and a high-frequency ultrasonic transducer. When the flexible ultrasonic patch is attached to the surface of the patient's bladder, the ultrasonic transducer emits ultrasonic waves, which are reflected by the bladder wall and received by the ultrasonic transducer and converted into electrical signal output. Through the flexible piezoelectric ultrasonic probe of the flexible ultrasonic patch, an image of the urine volume in the patient's bladder based on the flexible ultrasonic patch is obtained.

3. The bladder urine volume measurement system based on a flexible ultrasonic patch according to claim 2, characterized in that: The data transmission module comprises: A data transmitting unit, used for transmitting an image of the urine volume in the patient's bladder based on the flexible ultrasound patch; A data receiving unit, used for receiving an image of urine volume in a patient's bladder based on a flexible ultrasonic patch; According to the demand for measuring urine volume in the bladder based on the flexible ultrasonic patch, a data transmission link is established between the data transmitting unit and the data receiving unit; The data transmitting unit receives the urine volume image of the patient's bladder based on the flexible ultrasonic patch transmitted from the data acquisition module, and the data transmitting unit transmits the received urine volume image of the patient's bladder based on the flexible ultrasonic patch to the data receiving unit; The data receiving unit receives the patient's bladder urine volume image based on the flexible ultrasonic patch transmitted from the data transmitting unit, and the data receiving unit transmits the received patient's bladder urine volume image based on the flexible ultrasonic patch to the urine volume measurement platform.

4. The bladder urine volume measurement system based on a flexible ultrasonic patch according to claim 3, characterized in that: To establish a data transmission link between the data transmitting unit and the data receiving unit, perform the following operations: The data transmitting unit transmits an instruction requesting to establish a data transmission link to the data receiving unit; The data receiving unit receives the instruction transmitted by the data transmitting unit requesting to establish a data transmission link, and the data receiving unit searches its own data transmission channel to check whether the data receiving unit has an idle data transmission channel; When there is an idle data transmission channel in the data receiving unit, the data receiving unit transmits an instruction to the data transmitting unit to agree to establish a data transmission link; The data transmitting unit receives an instruction from the data receiving unit agreeing to establish a data transmission link, and the data transmitting unit establishes a data transmission link with the data receiving unit according to the instruction from the data receiving unit agreeing to establish a data transmission link, so as to transmit an image of the urine volume in the patient's bladder based on the flexible ultrasonic patch.

5. The system for measuring urine volume in the bladder based on a flexible ultrasonic patch according to claim 4, characterized in that: The urine volume measurement platform comprises: An image processing module, used for processing the image of the urine volume in the patient's bladder based on the flexible ultrasonic patch, and determining a characteristic image of the urine volume in the patient's bladder based on the flexible ultrasonic patch; The urine volume measurement module is used to measure the urine volume in the patient's bladder and determine the urine volume measurement result in the bladder based on the flexible ultrasonic patch.

6. The system for measuring urine volume in the bladder based on a flexible ultrasonic patch according to claim 5, characterized in that: The image processing module comprises: An image denoising unit, used for denoising an image of urine volume in a patient's bladder; Acquire images of urine volume in a patient's bladder using a flexible ultrasound patch; Based on the median filter, the patient's bladder urine volume image based on the flexible ultrasonic patch is subjected to denoising processing, wherein the value of a point in the patient's bladder urine volume image based on the flexible ultrasonic patch is replaced by the median value of each point in a field of the point, so that pixels with a relatively large difference in grayscale values ​​of surrounding pixels are replaced with values ​​close to the surrounding pixel values, thereby eliminating isolated noise points, removing noise from the patient's bladder urine volume image based on the flexible ultrasonic patch, and protecting the edge of the patient's bladder urine volume image based on the flexible ultrasonic patch; An image enhancement unit, used for enhancing the image of urine volume in the patient's bladder; Obtain a denoised image of the urine volume in the patient's bladder; Based on image enhancement technology, the denoised image of the patient's bladder urine volume is enhanced; The denoised image of the urine volume in the patient's bladder is subjected to contrast enhancement and sharpening processing to highlight the detailed features in the denoised image of the urine volume in the patient's bladder and make the urine volume area in the bladder more obvious; An image segmentation unit, used for segmenting the image of urine volume in the patient's bladder; Obtain enhanced images of the urine volume in the patient's bladder; Based on image cropping and magnification technology, the region of interest ROI is extracted from the enhanced patient bladder urine volume image, wherein the meaningful feature parts in the enhanced patient bladder urine volume image are extracted, and the irrelevant background in the enhanced patient bladder urine volume image is removed, so that the focus of analysis is concentrated on the key parts of the enhanced patient bladder urine volume image, and the characteristic image of the patient bladder urine volume based on the flexible ultrasonic patch is determined.

7. The system for measuring urine volume in the bladder based on a flexible ultrasonic patch according to claim 6, characterized in that: The urine volume measurement module comprises: A model building unit, used for building a bladder urine volume measurement model based on a flexible ultrasonic patch; According to the demand for measuring urine volume in the bladder based on the flexible ultrasound patch, historical images of urine volume in the bladder of patients based on the flexible ultrasound patch are collected; The patient's bladder urine volume historical images based on the flexible ultrasound patch are divided to determine the bladder urine volume measurement training set and the bladder urine volume measurement test set; Selecting a convolutional neural network model framework suitable for measuring urine volume in the bladder based on a flexible ultrasonic patch, and training the selected convolutional neural network model framework suitable for measuring urine volume in the bladder based on a flexible ultrasonic patch based on a training set of urine volume in the bladder; A model for measuring urine volume in the bladder based on a flexible ultrasound patch was determined; The model optimization unit is used to optimize the intra-bladder urine volume measurement model based on the flexible ultrasonic patch, and determine the optimal intra-bladder urine volume measurement model based on the flexible ultrasonic patch.

8. The system for measuring urine volume in the bladder based on a flexible ultrasonic patch according to claim 7, characterized in that: The urine volume measurement module further includes: A urine volume measuring unit, used for measuring the urine volume in the patient's bladder; Acquire characteristic images of urine volume in the patient's bladder based on a flexible ultrasound patch; Inputting the characteristic image of the urine volume in the patient's bladder based on the flexible ultrasound patch into the optimal bladder urine volume measurement model based on the flexible ultrasound patch; Based on the optimal bladder urine volume measurement model based on the flexible ultrasonic patch, the patient's bladder urine volume characteristic image based on the flexible ultrasonic patch is pattern recognized and classified, and the patient's bladder urine volume characteristic image based on the flexible ultrasonic patch is divided into certain categories according to the characteristics of the patient's bladder urine volume characteristic image based on the flexible ultrasonic patch, so as to measure the patient's bladder urine volume; The results of intravesical urine volume measurement based on a flexible ultrasound patch were determined.

9. The system for measuring urine volume in the bladder based on a flexible ultrasonic patch according to claim 8, characterized in that: The feedback signal quality optimization curve construction unit includes: The data set construction subunit is used to obtain the stored ultrasonic emission information, ultrasonic feedback signal and its corresponding signal strength and clarity data, perform data cleaning to remove abnormal data, and group the cleaned stored data into corresponding groups to form training sets, verification sets and test sets; The model building subunit is used to build a BP neural network model, and use the training set, validation set and test set to perform adaptive training, parameter adjustment and testing on the model to obtain a reflection signal optimization model; The loss function of BP neural network model training is as follows: in, For the A predicted signal strength or a predicted clarity, is the total number of signal strengths or clarity in the training set, In the training set signal strength or clarity.

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