An arterial-venous vascular access stenosis detection system based on auscultatory acoustic signals

Abstract

The application discloses an arteriovenous vascular access stenosis detection system based on auscultation acoustic signals and relates to the technical field of vascular access stenosis detection. In the system operation, an auscultation acoustic signal and related parameters are acquired from a patient's body through a cardiac stethoscope, an echocardiogram and a hemodynamic instrument, a data group is acquired, the acquired acoustic signal is preprocessed, features in physiological parameters are extracted, and a stenosis detection index Xzjc is calculated and acquired. The features of the acoustic signal and the physiological parameters are analyzed, the extracted features are used for detecting and positioning the internal information of the artery or vein, the stenosis detection index Xzjc is compared with a preset arteriovenous vascular access width threshold, the clinical evaluation of stenosis is acquired, the detection result and the evaluation report are displayed to the patient and medical staff, the arteriovenous access stenosis detection result is displayed, a report is generated, and the detection process, the evaluation result and the doctor's suggestion are described in detail.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vascular access stenosis detection, in particular to a kind of arteriovenous vascular access stenosis detection system based on auscultation acoustic signal. BACKGROUND

[0002] Auscultation signal is a kind of non-invasive examination method commonly used by doctors in clinical diagnosis, and rich physiological information can be obtained by observing the acoustic signal of the heart and blood vessel area of the patient through a stethoscope. With the continuous progress of medical technology, using auscultation signal to detect arteriovenous vascular access stenosis has become an important clinical demand. The traditional arteriovenous vascular access stenosis detection method has the problems of complicated operation, dependence on doctor's experience and unstable detection results, so a more intelligent and more accurate system is needed to detect and evaluate vascular stenosis.

[0003] In the Chinese invention patent with the application publication number CN110720898A, a kind of arteriovenous vascular access stenosis detection system based on auscultation acoustic signal MUSIC power spectrum feature is disclosed, including acoustic sensor and processor, wherein: acoustic sensor collects the auscultation acoustic signal of arteriovenous vascular access, and transmits the auscultation acoustic signal to processor;After receiving the auscultation acoustic signal, the processor executes the following steps: using MUSIC power spectrum estimation method to process the auscultation acoustic signal, to obtain the MUSIC power spectrum of auscultation acoustic signal;MUSIC power spectrum is equally spaced sampled, and the MUSIC power spectrum feature is obtained;Call the trained classifier to classify the MUSIC power spectrum feature, and output the stenosis degree of arteriovenous vascular access. MUSIC power spectrum feature may be more sensitive to environmental conditions, for example, environmental noise and signal interference may affect the extraction and classification of power spectrum, thereby reducing the stability and reliability of the system.

[0004] In combination with the above application and prior art, the present system uses traditional signal processing method, including filtering, noise reduction and spectrum analysis, to extract key features by analyzing the spectrum, rhythm and intensity of sound signal for arteriovenous vascular access stenosis detection, while the system based on MUSIC power spectrum feature uses MUSIC power spectrum estimation method for high-resolution spectrum detection. The present system integrates multiple medical devices and advanced signal processing technology to realize comprehensive detection and evaluation of patient's vascular stenosis. SUMMARY

[0005] (I) Technical problems solved

[0006] In view of the deficiencies of the prior art, the present application provides an arteriovenous vascular access stenosis detection system based on auscultation acoustic signal, which solves the problems mentioned in the background art.

[0007] (B) Technical solutions

[0008] To achieve the above object, the present application is implemented by the following technical solutions: An arteriovenous vascular access stenosis detection system based on auscultation acoustic signals, comprising a data acquisition module, a signal preprocessing module, a feature extraction module, an arteriovenous access stenosis detection module, a stenosis evaluation module and a result display module;

[0009] The data acquisition module is used to obtain auscultation acoustic signals and related arteriovenous vascular parameters from the patient's body through a cardiac stethoscope, an echocardiogram and a hemodynamic instrument, and to obtain a patient detection data set;

[0010] The signal preprocessing module is used to preprocess the collected patient detection data set, and the preprocessing steps include filtering, noise reduction, amplification and compression processing of the sound signal, removing environmental noise and enhancing the target signal, calibrating and filtering the physiological parameters, and eliminating outliers;

[0011] The feature extraction module is used to extract key features from the preprocessed signal, analyze the frequency spectrum, rhythm and intensity of the sound signal, extract the related information of heartbeat and blood flow in the blood vessel, and extract the features in the physiological parameters, and calculate to obtain: a stenosis detection index Xzjc;

[0012] The arteriovenous access stenosis detection module is used to analyze the features of acoustic signals and physiological parameters, detect and locate the internal information of the artery or vein blood vessel using the extracted features, and combine the patient's clinical data and historical information to make comprehensive judgment and diagnosis;

[0013] The stenosis evaluation module is used to compare the stenosis detection index Xzjc with the preset arteriovenous vascular access width threshold according to the detected stenosis information, position, degree, shape and physiological condition of the patient, to obtain the clinical evaluation of the stenosis, including the characteristics, influence and recommended treatment plan of the stenosis;

[0014] The result display module is used to display the detection results and evaluation report to the patient and medical staff, display the results of arteriovenous access stenosis detection, including the position, degree and recommended processing method of the stenosis, generate a report, and describe the detection process, evaluation results and doctor's recommendations.

[0015] Preferably, the data acquisition module includes a cardiac stethoscope unit, an echocardiogram unit and a hemodynamic instrument unit;

[0016] The cardiac stethoscope unit is used to place the cardiac stethoscope at different positions on the patient's chest to collect acoustic signals of the patient's heart region, and obtain: a heartbeat frequency Xtpl, a heart sound amplitude intensity Xyzf, a heart sound rhythm Xyjl and a frequency spectrum amplitude Ppfd as a first data set;

[0017] The echocardiography unit is used to move the ultrasonic probe on the patient's chest, acquire the ultrasonic images and physiological parameters of the patient's heart and blood vessels using the echocardiography device, record the stenosis site, stenosis degree, stenosis morphology and stenosis type, and acquire the following as the second data set: vessel width Xgkd, stenosis segment diameter Jzzj, stenosis morphology Xzxt and plaque diameter Bkzj.

[0018] The hemodynamic instrument unit is used to monitor the patient's blood flow and related physiological parameters using the hemodynamic instrument, and acquire the following as the third data set by placing the hemodynamic instrument, including an arterial pressure meter and a Doppler ultrasound blood flow meter: maximum blood flow velocity Maxsd, average blood flow velocity Xlsd, pulse wave velocity Mbsd, stenosis before and after blood flow velocity ratio Qhxl and blood flow resistance index Xlzl.

[0019] Preferably, the signal preprocessing module includes a sound signal processing unit and a physiological parameter processing unit.

[0020] The sound signal processing unit is used to preprocess the collected acoustic signals, remove unwanted frequency components in the signals, filter, denoise, amplify and compress the sound signals, remove environmental noise and enhance the target signal.

[0021] The physiological parameter processing unit corrects the physiological parameters according to the calibration curve or actual measurement value of the device, removes high-frequency noise and fluctuations in the physiological parameters, smooths the data curve, and eliminates abnormal values.

[0022] Preferably, the feature extraction module includes a sound signal feature extraction unit and a physiological parameter feature extraction unit.

[0023] The sound signal feature extraction unit is used to extract key features from the preprocessed sound signals, convert the sound signals to the frequency domain through Fourier transform, analyze their spectral features, detect the heartbeat rhythm or other periodic rhythm in the sound signals, and measure the amplitude or energy of the sound signals.

[0024] The physiological parameter feature extraction unit is used to extract key features from the preprocessed physiological parameters, analyze the blood flow velocity curve measured by the echocardiography or hemodynamic instrument, extract the maximum blood flow velocity and average blood flow velocity, extract the heart rate variability feature from the heart rate data to reflect the regulation function of the cardiovascular system, and calculate the following: stenosis detection index Xzjc, sound feature coefficient Sytz, stenosis degree coefficient Xzcd and blood flow velocity coefficient Xlxs.

[0025] The stenosis detection index Xzjc is calculated by the following formula:

[0026] ;

[0027] In the formula, Sytz represents a sound characteristic coefficient, Xzcd represents a stenosis degree coefficient, Xlxs represents a blood flow velocity coefficient, q, w, and e respectively represent proportional coefficients of the sound characteristic coefficient Sytz, the stenosis degree coefficient Xzcd, and the blood flow velocity coefficient Xlxs;

[0028] wherein, , , , and R represents a first correction constant.

[0029] Preferably, the sound characteristic coefficient Sytz is obtained by calculation according to the following formula:

[0030] ;

[0031] In the formula, Xtpl represents a heart beat frequency, Xyzf represents a heart sound amplitude intensity, Xyjl represents a heart sound rhythm, Ppfd represents a spectrum amplitude, t, y, u, and i respectively represent proportional coefficients of the heart beat frequency Xtpl, the heart sound amplitude intensity Xyzf, the heart sound rhythm Xyjl, and the spectrum amplitude Ppfd;

[0032] wherein, , , , , and O represents a second correction constant.

[0033] Preferably, the stenosis degree coefficient Xzcd is obtained by calculation according to the following formula:

[0034] ;

[0035] In the formula, Xgkd represents a blood vessel width, Jzzj represents a stenosis section diameter, Xzxt represents a stenosis shape, Bkzj represents a plaque diameter, a, s, d, and f respectively represent proportional coefficients of the blood vessel width Xgkd, the stenosis section diameter Jzzj, the stenosis shape Xzxt, and the plaque diameter Bkzj;

[0036] wherein, , , , , and G represents a third correction constant.

[0037] Preferably, the blood flow velocity coefficient Xlxs is obtained by calculation according to the following formula:

[0038] ;

[0039] In the formula, Maxsd represents the maximum blood flow velocity, Xlsd represents the average blood flow velocity, Mbsd represents the pulse wave velocity, Qhxl represents the blood flow velocity ratio before and after the stenosis, Xlzl represents the blood flow resistance index, and h, j, k, z, and x represent the proportional coefficients of the maximum blood flow velocity Maxsd, the average blood flow velocity Xlsd, the pulse wave velocity Mbsd, the blood flow velocity ratio before and after the stenosis Qhxl, and the blood flow resistance index Xlzl, respectively.

[0040] wherein, , , , , , and L represents a fourth correction constant.

[0041] Preferably, the arteriovenous access stenosis detection module comprises an acoustic signal analysis unit and a physiological parameter analysis unit.

[0042] The acoustic signal analysis unit is configured to analyze the preprocessed acoustic signal, analyze the spectrum, rhythm, and intensity of the sound signal, identify the related information of the heartbeat and blood flow of the blood vessel, detect and locate the stenosis in the arterial or venous blood vessel by using the acoustic signal characteristics.

[0043] The physiological parameter analysis unit is configured to analyze the preprocessed physiological parameter, analyze the blood flow velocity and heart rate characteristics in the physiological parameter, and assist in detecting and locating the stenosis in the arterial or venous blood vessel.

[0044] Preferably, the stenosis evaluation module comprises a stenosis degree evaluation unit.

[0045] The stenosis degree evaluation unit is configured to analyze the stenosis information detected in the arteriovenous access, including the position, degree, and morphology, compare the stenosis detection index Xzjc with the preset arteriovenous vascular access width threshold M and the preset arteriovenous vascular access width threshold N, and obtain the clinical evaluation of the stenosis.

[0046] When the stenosis detection index Xzjc is less than the preset arteriovenous vascular access width threshold M, it is determined that the stenosis degree is first level, the position, degree, and morphology of the stenosis are confirmed, the stenosis is determined by echocardiography or other imaging examination, the physiological parameters of the patient are monitored, and the patient is suggested to adjust the lifestyle.

[0047] When the preset arteriovenous vascular access width threshold M is less than or equal to the stenosis detection index Xzjc and is less than or equal to the preset arteriovenous vascular access width threshold N, it is determined that the stenosis degree is second level, the position, degree, and morphology of the stenosis are confirmed, drug treatment measures are considered to be taken, and the physiological parameters and symptom changes of the patient are monitored once a week.

[0048] When the stenosis detection index Xzjc is greater than the preset arteriovenous vascular access width threshold N, it is determined that the stenosis degree is level three, the position, degree and morphology of the stenosis are confirmed, the interventional treatment measures are considered, and the arteriovenous vascular conditions of the patient are reviewed three times a week.

[0049] Preferably, the result display module comprises a result display unit and a report generation unit.

[0050] The result display unit is used to display the results of arteriovenous access stenosis detection, including the position, degree and recommended treatment of the stenosis, provide a visual interface, and present the data, echocardiogram and arterial blood flow velocity graph during the detection process.

[0051] The report generation unit is used to automatically generate an evaluation report according to the stenosis degree evaluation result and the physiological condition of the patient, including the characteristics, position and degree of the stenosis, and the treatment suggestions and prognosis information of the doctor, and provide report export and printing functions for the patient and the doctor to refer to and save.

[0052] (Three)beneficial effects

[0053] The present application provides an arteriovenous vascular access stenosis detection system based on auscultation acoustic signals, which has the following beneficial effects:

[0054] (1) When the system is running, the heart stethoscope, echocardiogram and hemodynamic instrument are used to obtain the auscultation acoustic signals and related parameters from the patient, obtain the data set, preprocess the collected acoustic signals, extract the features in the physiological parameters, and calculate to obtain: the stenosis detection index Xzjc, analyze the features of the acoustic signals and physiological parameters, use the extracted features to detect and locate the internal information in the arterial or venous blood vessels, compare the stenosis detection index Xzjc with the preset arteriovenous vascular access width threshold, obtain the clinical evaluation of the stenosis, display the detection results and evaluation report to the patient and medical staff, display the results of arteriovenous access stenosis detection, generate a report, and describe the detection process, evaluation results and doctor's suggestions in detail.

[0055] (2) The present system integrates a multi-source data acquisition unit, including a heart stethoscope, an echocardiogram and a hemodynamic instrument, which realizes comprehensive detection and evaluation of arteriovenous vascular access stenosis from acoustic signals to physiological parameters, and effectively removes noise and outliers to improve the quality and accuracy of the data, which helps to accurately extract key features.

[0056] (3) By comparing the stenosis detection index Xzjc and the preset arteriovenous access width threshold, the system can objectively evaluate the degree of stenosis, reduce the influence of human factors on the results, improve the reliability of the diagnosis, and according to the stenosis degree evaluation result, the system can provide personalized treatment suggestions for different degrees of stenosis, including lifestyle adjustment, drug treatment and interventional treatment, which helps to optimize the treatment plan and improve the treatment effect, and the system provides visual detection results and detailed evaluation reports through the result display module and the report generation unit, so that patients and medical staff can quickly understand the detection results and facilitate subsequent treatment and management. BRIEF DESCRIPTION OF DRAWINGS

[0057] Figure 1 A flowchart of a block diagram of a stenosis detection system for arteriovenous access based on auscultation acoustic signals. DETAILED DESCRIPTION

[0058] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0059] Embodiment 1

[0060] The present application provides a stenosis detection system for arteriovenous access based on auscultation acoustic signals, please refer to Figure 1 , which comprises a data acquisition module, a signal preprocessing module, a feature extraction module, an arteriovenous access stenosis detection module, a stenosis evaluation module and a result display module.

[0061] The data acquisition module is used to obtain auscultation acoustic signals and related arteriovenous vascular parameters from the patient's body through a cardiac stethoscope, an echocardiogram and a hemodynamic instrument, and to obtain a patient detection data set.

[0062] The signal preprocessing module is used to preprocess the collected patient detection data set, and the preprocessing steps include filtering, noise reduction, amplification and compression processing of the sound signal, removing environmental noise and enhancing the target signal, calibrating and filtering the physiological parameters, and eliminating abnormal values.

[0063] The feature extraction module is used to extract key features from the preprocessed signal, analyze the frequency spectrum, rhythm and intensity of the sound signal, extract the related information of heartbeat and blood flow of the blood vessel, and extract the features in the physiological parameters, and calculate to obtain: stenosis detection index Xzjc.

[0064] The arteriovenous access stenosis detection module is used for analyzing the features of the acoustic signals and the physiological parameters, detecting and positioning the internal information of the blood vessels in the arterial or venous blood vessels by using the extracted features, comprehensively judging and diagnosing in combination with the clinical data and historical information of the patient, and obtaining the clinical evaluation of the stenosis.

[0065] The stenosis evaluation module is used for obtaining the clinical evaluation of the stenosis, including the features, influence and recommended treatment scheme of the stenosis, by comparing the detected stenosis information, position, degree, shape and physiological condition of the patient with the preset arteriovenous blood vessel access width threshold value.

[0066] The result display module is used for displaying the detection result and the evaluation report to the patient and medical staff, displaying the result of the arteriovenous access stenosis detection, including the position, degree and recommended processing mode of the stenosis, generating a report, and describing the detection process, evaluation result and doctor's suggestion.

[0067] In this embodiment, the auscultation acoustic signals and related parameters are obtained from the patient by using a cardiac stethoscope, echocardiogram and blood flow dynamics instrument, a data set is obtained, the features in the physiological parameters are extracted by preprocessing the collected acoustic signals, and the following are obtained after calculation: a stenosis detection index Xzjc, the features of the acoustic signals and the physiological parameters are analyzed, the internal information of the blood vessels in the arterial or venous blood vessels is detected and positioned by using the extracted features, the clinical evaluation of the stenosis is obtained by comparing the stenosis detection index Xzjc with the preset arteriovenous blood vessel access width threshold value, the detection result and the evaluation report are displayed to the patient and medical staff, the result of the arteriovenous access stenosis detection is displayed, and a report is generated to describe the detection process, evaluation result and doctor's suggestion in detail.

[0068] Embodiment 2

[0069] This embodiment is an explanation and description in embodiment 1, please refer to Figure 1 , specifically: the data acquisition module includes a cardiac stethoscope unit, an echocardiogram unit and a blood flow dynamics instrument unit;

[0070] The cardiac stethoscope unit is used for placing a cardiac stethoscope at different positions on the chest of the patient to collect the acoustic signals of the heart region of the patient, and obtaining: a heartbeat frequency Xtpl, a heart sound amplitude intensity Xyzf, a heart sound rhythm Xyjl and a frequency spectrum amplitude Ppfd as a first data set;

[0071] The echocardiogram unit is used for moving an ultrasonic probe on the chest of the patient, using an echocardiogram device to obtain the ultrasonic images and physiological parameters of the heart and blood vessels of the patient, recording the stenosis position, stenosis degree, stenosis shape and stenosis type, and obtaining: a blood vessel width Xgkd, a stenosis segment diameter Jzzj, a stenosis shape Xzxt and a plaque diameter Bkzj as a second data set.

[0072] The hemodynamic instrument unit is used for monitoring blood flow and related physiological parameters of a patient using a hemodynamic instrument, and acquiring maximum blood flow velocity Maxsd, average blood flow velocity Xlsd, pulse wave velocity Mbsd, pre- and post-stenosis blood flow velocity ratio Qhxl, and blood flow resistance index Xlzl as a third data set by placing the hemodynamic instrument, including an arterial pressure meter and a Doppler ultrasound blood flow meter.

[0073] The signal preprocessing module includes a sound signal processing unit and a physiological parameter processing unit.

[0074] The sound signal processing unit is used for preprocessing the collected acoustic signals, removing unnecessary frequency components in the signals, filtering, noise reduction, amplification and compression processing of the sound signals, removing environmental noise and enhancing target signals.

[0075] The physiological parameter processing unit corrects the physiological parameters according to the calibration curve or actual measurement value of the device, removes high-frequency noise and fluctuations in the physiological parameters, smooths the data curve, and eliminates abnormal values.

[0076] In this embodiment, through the cardiac stethoscope unit, echocardiogram unit and hemodynamic instrument unit, the system can acquire various data, including acoustic signals, ultrasound images and physiological parameters, improving the richness and comprehensiveness of the data. The first data set includes the acoustic signal features collected by the cardiac stethoscope, the second data set includes the blood vessel related parameters recorded by the echocardiogram, and the third data set includes the blood flow velocity and blood pressure parameters monitored by the hemodynamic instrument. These data reflect the condition of the arteriovenous vascular access from different angles, which is helpful for comprehensive analysis and evaluation. The sound signal processing unit and the physiological parameter processing unit in the signal preprocessing module optimize the data, remove unnecessary frequency components and noise, improve the quality and reliability of the data, and lay a foundation for subsequent feature extraction and analysis. The physiological parameter processing unit corrects the physiological parameters, eliminates high-frequency noise and fluctuations, smooths the data curve, and makes the data more stable and reliable, which helps to accurately reflect the physiological state of the patient. Through diversified data collection and optimized preprocessing, the system can comprehensively evaluate the stenosis of the arteriovenous vascular access, provide objective and comprehensive diagnostic results, and help doctors develop more effective treatment plans.

[0077] Embodiment 3

[0078] This embodiment is an explanation and description in Embodiment 1, please refer to Figure 1 , in particular: the feature extraction module includes a sound signal feature extraction unit and a physiological parameter feature extraction unit.

[0079] The sound signal feature extraction unit is configured to extract key features from the preprocessed sound signal, convert the sound signal to the frequency domain through Fourier transform, analyze the frequency spectrum features, detect the heartbeat rhythm or other periodic rhythm in the sound signal, and measure the amplitude or energy of the sound signal;

[0080] The physiological parameter feature extraction unit is configured to extract key features from the preprocessed physiological parameters, analyze the blood flow velocity curve measured by echocardiography or hemodynamic instruments, extract the maximum blood flow velocity and average blood flow velocity, extract the heart rate variability features from the heart rate data to reflect the regulation function of the cardiovascular system, and calculate the stenosis detection index Xzjc, the sound feature coefficient Sytz, the stenosis degree coefficient Xzcd, and the blood flow velocity coefficient Xlxs.

[0081] The stenosis detection index Xzjc is calculated by the following formula:

[0082] ;

[0083] In the formula, Sytz represents the sound feature coefficient, Xzcd represents the stenosis degree coefficient, Xlxs represents the blood flow velocity coefficient, q, w, and e represent the proportional coefficients of the sound feature coefficient Sytz, the stenosis degree coefficient Xzcd, and the blood flow velocity coefficient Xlxs, respectively.

[0084] wherein, , , , and R represents the first correction constant.

[0085] The sound feature coefficient Sytz is calculated by the following formula:

[0086] ;

[0087] In the formula, Xtpl represents the heartbeat frequency, Xyzf represents the heart sound amplitude intensity, Xyjl represents the heart sound rhythm, Ppfd represents the spectrum amplitude, t, y, u, and i represent the proportional coefficients of the heartbeat frequency Xtpl, the heart sound amplitude intensity Xyzf, the heart sound rhythm Xyjl, and the spectrum amplitude Ppfd, respectively.

[0088] wherein, , , , , and O represents the second correction constant.

[0089] The stenosis degree coefficient Xzcd is calculated by the following formula:

[0090] ;

[0091] wherein Xgkd represents a blood vessel width, Jzzj represents a stenosis section diameter, Xzxt represents a stenosis shape, Bkzj represents a plaque diameter, and a, s, d, and f respectively represent proportional coefficients of the blood vessel width Xgkd, the stenosis section diameter Jzzj, the stenosis shape Xzxt, and the plaque diameter Bkzj;

[0092] wherein, , , , , and G represents a third correction constant.

[0093] The blood flow velocity coefficient Xlxs is calculated by the following equation:

[0094] ;

[0095] wherein Maxsd represents a maximum blood flow velocity, Xlsd represents an average blood flow velocity, Mbsd represents a pulse wave velocity, Qhxl represents a blood flow velocity ratio before and after a stenosis, Xlzl represents a blood flow resistance index, and h, j, k, z, and x respectively represent proportional coefficients of the maximum blood flow velocity Maxsd, the average blood flow velocity Xlsd, the pulse wave velocity Mbsd, the blood flow velocity ratio before and after a stenosis Qhxl, and the blood flow resistance index Xlzl;

[0096] wherein, , , , , , and L represents a fourth correction constant.

[0097] In this embodiment, the sound signal feature extraction unit can convert the sound signal to the frequency domain through Fourier transform, analyze the spectral features, detect the heartbeat rhythm or other periodic rhythm, and measure the amplitude or energy of the sound signal; the physiological parameter feature extraction unit can extract key features from the preprocessed physiological parameters, including maximum blood flow velocity, average blood flow velocity, and heart rate variability, etc., thereby comprehensively reflecting the condition of the arteriovenous vascular access. According to the extracted features, the system can calculate quantitative indexes such as the stenosis detection index Xzjc, the sound feature coefficient Sytz, the stenosis degree coefficient Xzcd, and the blood flow velocity coefficient Xlxs. These indexes can objectively evaluate the stenosis degree and features of the arteriovenous vascular access, providing quantitative diagnostic basis for doctors. The proportional coefficient and the correction constant in the formula can be adjusted according to the actual situation, making the calculation result more accurate and reliable. The introduction of this correction parameter can adapt to the physiological characteristics and data changes of different patients, improving the flexibility and applicability of the system. By comprehensively considering the sound features, physiological parameters, and quantitative indexes, the system can conduct comprehensive analysis and judgment to determine the stenosis degree and type of the arteriovenous vascular access, providing more accurate diagnostic results and treatment suggestions for doctors, which helps to improve the diagnosis and treatment level of diseases.

[0098] Embodiment 4

[0099] This embodiment is an explanation and illustration in Embodiment 1, please refer to Figure 1 , specifically: the arteriovenous access stenosis detection module includes an acoustic signal analysis unit and a physiological parameter analysis unit;

[0100] The acoustic signal analysis unit is used to analyze the preprocessed acoustic signal, analyze the spectrum, rhythm and intensity in the sound signal, identify the related information of heartbeat and blood flow in blood vessels, and detect and locate the stenosis in the arterial or venous blood vessels by using the acoustic signal features;

[0101] The physiological parameter analysis unit is used to analyze the preprocessed physiological parameters, analyze the blood flow velocity and heart rate features in the physiological parameters, and assist in detecting and locating the stenosis in the arterial or venous blood vessels.

[0102] The stenosis evaluation module includes a stenosis degree evaluation unit;

[0103] The stenosis degree evaluation unit is used to analyze the detected stenosis information in the arteriovenous access, including position, degree and morphology, compare the stenosis detection index Xzjc with the preset arteriovenous vascular access width threshold M and the preset arteriovenous vascular access width threshold N, and obtain the clinical evaluation of the stenosis:

[0104] When the stenosis detection index Xzjc is less than the preset arteriovenous access width threshold M, the stenosis degree is determined to be level one, the position, degree and morphology of the stenosis are confirmed, the echocardiogram or other imaging examination is used to determine, the physiological parameters of the patient are monitored, and the patient is suggested to adjust the lifestyle;

[0105] When the preset arteriovenous access width threshold M is less than or equal to the stenosis detection index Xzjc and less than or equal to the preset arteriovenous access width threshold N, the stenosis degree is determined to be level two, the position, degree and morphology of the stenosis are confirmed, the drug treatment measures are considered to be taken, and the physiological parameters and symptom changes of the patient are monitored once a week;

[0106] When the stenosis detection index Xzjc is greater than the preset arteriovenous access width threshold N, the stenosis degree is determined to be level three, the position, degree and morphology of the stenosis are confirmed, the interventional treatment measures are considered to be taken, and the arteriovenous vascular condition of the patient is reviewed three times a week.

[0107] The result display module includes a result display unit and a report generation unit;

[0108] The result display unit is used to display the results of the arteriovenous access stenosis detection, including the position, degree and recommended treatment of the stenosis, provide a visual interface, and present the data, echocardiogram and arterial blood flow velocity graph in the detection process;

[0109] The report generation unit is used to automatically generate an evaluation report according to the stenosis degree evaluation result and the physiological condition of the patient, including the characteristics, position and degree of the stenosis, and the treatment suggestion and prognosis information of the doctor, provide a report export and printing function, and make reference and save for the patient and the doctor.

[0110] In this embodiment, the acoustic signal analysis unit analyzes the pre-processed acoustic signals to identify information related to heartbeats and blood flow in blood vessels, and uses acoustic signal features to detect and locate stenosis in arterial or venous blood vessels. The physiological parameter analysis unit analyzes physiological parameters to assist in detecting and locating stenosis in arterial or venous blood vessels. This comprehensive analysis and localization can provide a comprehensive stenosis detection result. The stenosis evaluation module evaluates and classifies the degree of stenosis based on the detected stenosis information, including location, degree, and morphology, in combination with the stenosis detection index Xzjc and the preset arterial or venous blood vessel passage width threshold. This classification scheme can provide doctors with a clearer judgment of the degree of stenosis in order to take appropriate treatment measures. The results display module can display the results of arterial or venous passage stenosis detection in a visual interface, including the location, degree, and recommended treatment of stenosis, and provide information such as data, echocardiogram, and arterial blood flow velocity graph. The report generation unit automatically generates an evaluation report, including the characteristics, location, and degree of stenosis, as well as the doctor's treatment recommendations and prognosis information. Such functions can help doctors more effectively understand the detection results and provide clear diagnostic reports for patients.

[0111] While embodiments of the present application have been shown and described, it is to be understood that various modifications, substitutions, replacements and variations can be made to these embodiments without departing from the principles and spirit of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A system for detecting arterial-venous vascular access stenosis based on auscultatory acoustic signals, characterized by: The device comprises a data acquisition module, a signal preprocessing module, a feature extraction module, a dynamic and static vein passage stenosis detection module, a stenosis evaluation module and a result display module. The data acquisition module is used to acquire auscultation acoustic signals and related dynamic and static vein vessel parameters from a patient by a heart stethoscope, an echocardiogram and a blood flow dynamics instrument, and to acquire a patient detection data set. The signal preprocessing module is used to preprocess the acquired patient detection data set, and the preprocessing steps include filtering, noise reduction, amplification and compression processing of sound signals, removal of environmental noise and enhancement of target signals, calibration and filtering of physiological parameters, and elimination of abnormal values. The feature extraction module is used to extract key features from the preprocessed signals, analyze the spectrum, rhythm and intensity of sound signals, extract related information of heartbeat and blood flow of vessels, and extract features in physiological parameters, and calculate to acquire a stenosis detection index Xzjc, a sound feature coefficient Sytz, a stenosis degree coefficient Xzcd and a blood flow velocity coefficient Xlxs. In the formula, q, w and e respectively represent proportional coefficients of the sound feature coefficient Sytz, the stenosis degree coefficient Xzcd and the blood flow velocity coefficient Xlxs. Wherein, 0≤q≤1, 0≤w≤1, 0≤e≤1, and q+w+e≤1.0, R represents a first correction constant; Sytz=[(Xtpl*t)+(Xyzf*y)+(Xyjl*u)+(Ppfd*i)]+O; In the formula, Xtpl represents heartbeat frequency, Xyzf represents heart sound amplitude intensity, Xyjl represents heart sound rhythm, Ppfd represents spectrum amplitude, t, y, u and i respectively represent proportional coefficients of the heartbeat frequency Xtpl, the heart sound amplitude intensity Xyzf, the heart sound rhythm Xyjl and the spectrum amplitude Ppfd. Wherein, 0≤t≤1, 0≤y≤1, 0≤u≤1, 0≤i≤1, and t+y+u+i≤1.0, O represents a second correction constant; Xzcd=[(Xgkd*a)+(Jzzj*s)+(Xzxt*d)+(Bkzj*f)]+G; In the formula, Xgkd represents vessel width, Jzzj represents stenosis segment diameter, Xzxt represents stenosis morphology, Bkzj represents plaque diameter, a, s, d and f respectively represent proportional coefficients of the vessel width Xgkd, the stenosis segment diameter Jzzj, the stenosis morphology Xzxt and the plaque diameter Bkzj. Wherein, 0≤a≤1, 0≤s≤1, 0≤d≤1, 0≤f≤1, and a+s+d+f≤1.0, G represents a third correction constant; Xlxs=[(Maxsd*h)+(Xlsd*j)+(Mbsd*k)+(Qhxl*z)+(Xlzl*x)]+L; In the formula, Maxsd represents the maximum blood flow velocity, Xlsd represents the average blood flow velocity, Mbsd represents the pulse wave velocity, Qhxl represents the blood flow velocity ratio before and after the stenosis, Xlzl represents the blood flow resistance index, and h, j, k, z, and x represent the proportional coefficients of the maximum blood flow velocity Maxsd, the average blood flow velocity Xlsd, the pulse wave velocity Mbsd, the blood flow velocity ratio before and after the stenosis Qhxl, and the blood flow resistance index Xlzl, respectively; wherein 0≤h≤1, 0≤j≤1, 0≤k≤1, 0≤z≤1, 0≤x≤1, and h+j+k+z+x≤1.0, and L represents a fourth correction constant; The arteriovenous access stenosis detection module is configured to analyze the characteristics of the acoustic signals and the physiological parameters, detect and locate the internal information of the blood vessels in the arterial or venous vessels using the extracted characteristics, and make comprehensive judgments and diagnoses in combination with the clinical data and historical information of the patient; The stenosis evaluation module is configured to compare the detected stenosis information, position, degree, shape, and physiological condition of the patient with a preset arteriovenous vascular access width threshold through a stenosis detection index Xzjc to obtain a clinical evaluation of the stenosis, including the characteristics, influence, and recommended treatment plan of the stenosis. The result display module is configured to display the detection results and evaluation reports to the patient and medical staff, display the results of the arteriovenous access stenosis detection, including the position, degree, and recommended processing method of the stenosis, generate a report, and describe the detection process, evaluation results, and doctor's recommendations.

2. The auscultatory acoustic signal-based detection system for detecting arterial-venous vascular access stenosis according to claim 1, wherein: The data acquisition module includes a cardiac stethoscope unit, an echocardiogram unit, and a hemodynamic instrument unit; The cardiac stethoscope unit is configured to place a cardiac stethoscope at different positions on the patient's chest to acquire acoustic signals of the patient's heart region, and obtain a heartbeat frequency Xtpl, a heart sound amplitude intensity Xyzf, a heart sound rhythm Xyjl, and a frequency spectrum amplitude Ppfd as a first data set; The echocardiogram unit is configured to move an ultrasonic probe on the patient's chest, use an echocardiogram device to acquire ultrasonic images and physiological parameters of the patient's heart and blood vessels, record the stenosis site, stenosis degree, stenosis shape, and stenosis type, and obtain a blood vessel width Xgkd, a stenosis segment diameter Jzzj, a stenosis shape Xzxt, and a plaque diameter Bkzj as a second data set; The hemodynamic instrument unit is configured to use a hemodynamic instrument to monitor the blood flow and related physiological parameters of the patient, place the hemodynamic instrument including an arterial pressure gauge and a Doppler ultrasound blood flow meter, and obtain a maximum blood flow velocity Maxsd, an average blood flow velocity Xlsd, a pulse wave velocity Mbsd, a blood flow velocity ratio before and after the stenosis Qhxl, and a blood flow resistance index Xlzl as a third data set.

3. The auscultatory acoustic signal-based detection system for detecting arterial-venous vascular access stenosis according to claim 1, wherein: The signal preprocessing module includes a sound signal processing unit and a physiological parameter processing unit; The sound signal processing unit is configured to preprocess the acquired acoustic signals, remove unnecessary frequency components in the signals, filter, denoise, amplify, and compress the sound signals, remove environmental noise, and enhance the target signal. The physiological parameter processing unit corrects the physiological parameters according to the calibration curve or the actual measurement value of the device, removes high-frequency noise and fluctuations in the physiological parameters, smooths the data curve, and eliminates abnormal values.

4. The auscultatory acoustic signal-based detection system for detecting arterial-venous vascular access stenosis according to claim 1, wherein: The feature extraction module includes a sound signal feature extraction unit and a physiological parameter feature extraction unit; The sound signal feature extraction unit is used to extract key features from the preprocessed sound signal, convert the sound signal to the frequency domain through Fourier transform, analyze its spectral features, detect the heartbeat rhythm or other periodic rhythm in the sound signal, and measure the amplitude or energy of the sound signal. The physiological parameter feature extraction unit is used to extract key features from the preprocessed physiological parameters, analyze the blood flow velocity curve measured by echocardiography or hemodynamic instruments, extract the maximum blood flow velocity and average blood flow velocity, extract the heart rate variability features from the heart rate data to reflect the regulation function of the cardiovascular system, and calculate the following: stenosis detection index Xzjc, sound feature coefficient Sytz, stenosis degree coefficient Xzcd, and blood flow velocity coefficient Xlxs.

5. The auscultatory acoustic signal-based detection system for detecting stenosis in an arteriovenous vascular access according to claim 1, wherein: The arteriovenous access stenosis detection module includes an acoustic signal analysis unit and a physiological parameter analysis unit; The acoustic signal analysis unit is used to analyze the preprocessed acoustic signal, analyze the spectrum, rhythm and intensity of the sound signal, identify the related information of heartbeat and blood flow in the blood vessel, and detect and locate the stenosis in the arterial or venous blood vessel using acoustic signal features. The physiological parameter analysis unit is used to analyze the preprocessed physiological parameters, analyze the blood flow velocity and heart rate features in the physiological parameters, and assist in detecting and locating the stenosis in the arterial or venous blood vessel.

6. The auscultatory acoustic signal-based detection system for detecting stenosis in an arteriovenous vascular access according to claim 1, wherein: The stenosis evaluation module includes a stenosis degree evaluation unit. The stenosis degree evaluation unit is used to analyze the stenosis information detected in the arteriovenous access, including location, degree and morphology, and compare the stenosis detection index Xzjc with the preset arteriovenous vascular access width threshold M and the preset arteriovenous vascular access width threshold N to obtain the clinical evaluation of the stenosis: When the stenosis detection index Xzjc is less than the preset arteriovenous vascular access width threshold M, the stenosis degree is determined to be first level, the location, degree and morphology of the stenosis are confirmed, and the stenosis is determined through echocardiography or other imaging examination, the physiological parameters of the patient are monitored, and the patient is suggested to adjust the lifestyle; When the preset arteriovenous vascular access width threshold M is less than or equal to the stenosis detection index Xzjc and is less than or equal to the preset arteriovenous vascular access width threshold N, the stenosis degree is determined to be second level, the location, degree and morphology of the stenosis are confirmed, and drug treatment measures are considered, the physiological parameters and symptom changes of the patient are monitored once a week; When the stenosis detection index Xzjc is greater than the preset arteriovenous vascular access width threshold N, the stenosis degree is determined to be third level, the location, degree and morphology of the stenosis are confirmed, and interventional treatment measures are considered, the arteriovenous vascular condition of the patient is reviewed three times a week.

7. The auscultatory acoustic signal-based detection system for detecting stenosis in an arteriovenous vascular access according to claim 1, wherein: The result display module includes a result display unit and a report generation unit; The result display unit is configured to display the results of the arteriovenous access stenosis detection, including the location, degree and recommended treatment of the stenosis, and provide a visual interface to present the data, echocardiogram and arterial blood flow velocity graph during the detection process; The report generation unit is configured to automatically generate an evaluation report based on the stenosis degree evaluation results and the physiological conditions of the patient, including the characteristics, location and degree of the stenosis, as well as the treatment recommendations and prognosis information of the doctor, and provide report export and printing functions for the patient and the doctor to refer to and save.

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