Arteriovenous vascular access stenosis detection system based on auscultation acoustic signal

Abstract

The invention discloses an arteriovenous vascular access stenosis detection system based on auscultation acoustic signals, and relates to the technical field of vascular access stenosis detection.During operation of the system, the auscultation acoustic signals and related parameters are obtained from a patient through a heart stethoscope, an echocardiogram and a hemodynamic instrument, and a data set is obtained; the method comprises the following steps: preprocessing collected acoustic signals, extracting features in physiological parameters, calculating to obtain a stenosis detection index Xzjc, analyzing the features of the acoustic signals and the physiological parameters, and detecting and positioning blood vessel internal information in arteries or veins by using the extracted features. Comparing the stenosis detection index Xzjc with a preset arteriovenous vascular access width threshold value to obtain clinical evaluation of stenosis, displaying a detection result and an evaluation report to a patient and medical personnel, displaying an arteriovenous access stenosis detection result, generating a report, and detailedly describing a detection process, the evaluation result and suggestions of a doctor.

Description

Technical Field

[0001] The present invention relates to the technical field of vascular access stenosis detection, and specifically to a arteriovenous vascular access stenosis detection system based on auscultatory acoustic signals. Background Art

[0002] Auscultatory signals are a non-invasive examination method commonly used by doctors in clinical diagnosis. By observing the acoustic signals in the cardiac and vascular regions of patients with a stethoscope, rich physiological information can be obtained. With the continuous progress of medical technology, using auscultatory signals for arteriovenous vascular access stenosis detection has become an important clinical need. Traditional arteriovenous vascular access stenosis detection methods have problems such as cumbersome operations, reliance on doctor experience, and unstable detection results. Therefore, a more intelligent and accurate system is needed to detect and evaluate vascular stenosis.

[0003] In a Chinese invention patent with the application publication number CN110720898A, a arteriovenous vascular access stenosis detection system based on the MUSIC power spectrum characteristics of auscultatory acoustic signals is disclosed, including an acoustic sensor and a processor, where: the acoustic sensor collects the auscultatory acoustic signals of the arteriovenous vascular access and transmits the auscultatory acoustic signals to the processor; after receiving the auscultatory acoustic signals, the processor performs the following steps: processing the auscultatory acoustic signals using the MUSIC power spectrum estimation method to obtain the MUSIC power spectrum of the auscultatory acoustic signals; performing equally spaced sampling on the MUSIC power spectrum to obtain MUSIC power spectrum characteristics; calling a trained classifier to classify the MUSIC power spectrum characteristics and output the stenosis degree of the arteriovenous vascular access. The MUSIC power spectrum characteristics may be more sensitive to environmental conditions. For example, environmental noise and signal interference may affect the extraction and classification of the power spectrum, thereby reducing the stability and reliability of the system.

[0004] Combined with the above application and the prior art, the system adopted in the present invention uses traditional signal processing methods, including filtering, noise reduction, and spectrum analysis, to extract key features by analyzing the spectrum, rhythm, and intensity of sound signals for arteriovenous vascular access stenosis detection, while the system based on MUSIC power spectrum characteristics uses the MUSIC power spectrum estimation method for high-resolution spectrum detection. The present system realizes the comprehensive detection and evaluation of the vascular stenosis condition of patients by integrating a variety of medical devices and advanced signal processing technologies. Summary of the Invention

[0005] (I) Technical Problems to be Solved

[0006] Aiming at the deficiencies of the prior art, the present invention provides a arteriovenous vascular access stenosis detection system based on auscultatory acoustic signals, which solves the problems mentioned in the background art.

[0007] (2) Technical solution

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions: A detection system for arteriovenous access stenosis based on auscultatory acoustic signals, comprising a data acquisition module, a signal preprocessing module, a feature extraction module, an arteriovenous access stenosis detection module, a stenosis assessment module, and a result display module;

[0009] The data acquisition module is used to obtain auscultatory acoustic signals and relevant arteriovenous vascular parameters from the patient through a cardiac stethoscope, echocardiogram, and hemodynamic instrument, and obtain a patient detection data set;

[0010] The signal preprocessing module is used to preprocess the collected patient detection data set. The preprocessing steps include filtering, noise reduction, amplification, and compression of the sound signal to remove environmental noise and enhance the target signal, and calibration and filtering of physiological parameters to eliminate outliers;

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

[0012] The arteriovenous access stenosis detection module is used to analyze the characteristics of acoustic signals and physiological parameters, use the extracted features to detect and locate the internal information of blood vessels in arteries or veins, and combine the patient's clinical data and historical information for comprehensive judgment and diagnosis;

[0013] The stenosis assessment module is used to compare the detected stenosis information, location, degree, morphology, and the patient's physiological condition with a preset arteriovenous vascular access width threshold through the stenosis detection index Xzjc to obtain a clinical assessment of the stenosis, including the characteristics, impacts, and recommended treatment plans of the stenosis;

[0014] The result display module is used to display the detection results and evaluation reports to the patient and medical staff, display the results of arteriovenous access stenosis detection, including the location, degree, and recommended treatment methods of the stenosis, generate a report, and describe the detection process, evaluation results, and doctor's suggestions.

[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 collect acoustic signals in the patient's heart area by placing a cardiac stethoscope at different positions on the patient's chest, and obtain: heart rate Xtpl, heart sound amplitude intensity Xyzf, heart sound rhythm Xyjl, and spectral amplitude Ppfd, as the first data set;

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

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

[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 signal, remove unnecessary frequency components in the signal, perform filtering, noise reduction, amplification, and compression processing on the sound signal, remove environmental noise, and enhance the target signal;

[0021] The physiological parameter processing unit corrects the collected 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 outliers.

[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 signal, convert the sound signal to the frequency domain through Fourier transform, analyze its spectral features, detect the heartbeat rhythm or other periodic rhythms in the sound signal, and measure the amplitude or energy of the sound signal;

[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 echocardiogram or hemodynamic instrument, extract the maximum blood flow velocity and the average blood flow velocity, extract the heart rate variability feature from the heart rate data to reflect the regulatory function of the cardiovascular system, and calculate to obtain: the stenosis detection index Xzjc, the sound feature coefficient Sytz, the stenosis degree coefficient Xzcd, and the blood flow velocity coefficient Xlxs;

[0025] The stenosis detection index Xzjc is calculated and obtained through the following formula:

[0026] ;

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

[0028] Among them, , , , and , R represents the first correction constant.

[0029] Preferably, the sound feature coefficient Sytz is obtained by calculating through the following formula:

[0030] ;

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

[0032] Among them, , , , , and , O represents the second correction constant.

[0033] Preferably, the stenosis degree coefficient Xzcd is obtained by calculating through the following formula:

[0034] ;

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

[0036] Among them, , , , , and , G represents the third correction constant.

[0037] Preferably, the blood flow velocity coefficient Xlxs is obtained by calculating through 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 stenosis, Xlzl represents the blood flow resistance index, and h, j, k, z, and x respectively represent the proportionality coefficients of the maximum blood flow velocity Maxsd, the average blood flow velocity Xlsd, the pulse wave velocity Mbsd, the blood flow velocity ratio Qhxl before and after stenosis, and the blood flow resistance index Xlzl;

[0040] Among them, , , , , , and , where L represents the fourth correction constant.

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

[0042] 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 relevant information of the heartbeat and blood vessel blood flow, and use the acoustic signal characteristics to detect and locate the stenosis in the artery or vein;

[0043] The physiological parameter analysis unit is used to analyze the preprocessed physiological parameters, analyze the blood flow velocity and heart rate characteristics in the physiological parameters, and assist in detecting and locating the stenosis in the artery or vein.

[0044] Preferably, the stenosis assessment module includes a stenosis degree assessment unit;

[0045] The stenosis degree assessment unit is used to analyze the stenosis information detected in the arteriovenous access, including the location, degree, and morphology, and compare the stenosis detection index Xzjc with the preset arteriovenous blood vessel access width threshold M and the preset arteriovenous blood vessel access width threshold N to obtain the clinical assessment of the stenosis:

[0046] When the stenosis detection index Xzjc < the preset arteriovenous blood vessel access width threshold M, it is determined that the stenosis degree is grade one, the location, degree, and morphology of the stenosis are confirmed, and it is determined by echocardiogram or other imaging examinations, the physiological parameters of the patient are monitored, and the patient is advised to adjust the lifestyle;

[0047] When the preset arteriovenous blood vessel access width threshold M ≤ the stenosis detection index Xzjc ≤ the preset arteriovenous blood vessel access width threshold N, it is determined that the stenosis degree is grade two, the location, degree, and morphology of the stenosis are confirmed, drug treatment measures are considered, and the physiological parameters and symptom changes of the patient are monitored once a week;

[0048] When the stenosis detection index Xzjc > the preset arteriovenous vascular access width threshold N, the stenosis degree is determined to be grade three, the location, degree, and morphology of the stenosis are confirmed, interventional treatment measures are considered, and the arteriovenous vascular condition of the patient is rechecked three times a week.

[0049] Preferably, the result display module includes 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 location, degree, and recommended treatment methods of the stenosis, provide a visual interface, and present the data, echocardiogram, and arterial blood flow velocity diagram during the detection process;

[0051] The report generation unit is used to automatically generate an evaluation report based on the stenosis degree evaluation result and the patient's physiological condition, including the characteristics, location, and degree of the stenosis, as well as the doctor's treatment recommendations and prognosis information, and provide report export and printing functions for patients and doctors to refer to and save.

[0052] (III) Beneficial effects

[0053] The present invention provides a stenosis detection system for arteriovenous vascular access based on auscultatory acoustic signals, having the following beneficial effects:

[0054] (1) When the system runs, auscultatory acoustic signals and related parameters are obtained from the patient through a cardiac stethoscope, echocardiogram, and hemodynamic instrument to obtain a data set. By preprocessing the collected acoustic signals, the characteristics in the physiological parameters are extracted, and after calculation, the stenosis detection index Xzjc is obtained. The characteristics of the acoustic signals and physiological parameters are analyzed, and the internal information of the blood vessels in the artery or vein is detected and located using the extracted characteristics. By comparing the stenosis detection index Xzjc with the preset arteriovenous vascular access width threshold, a clinical evaluation of the stenosis is obtained, and the detection results and evaluation report are shown to the patient and medical staff, displaying the results of arteriovenous access stenosis detection, generating a report, and detailing the detection process, evaluation results, and doctor's suggestions.

[0055] (2) This system integrates multi-source data acquisition units, including a cardiac stethoscope, echocardiogram, and hemodynamic instrument, and comprehensively detects and evaluates the stenosis of arteriovenous vascular access from multiple aspects of information from acoustic signals to physiological parameters. The system uses a sound signal processing unit and a physiological parameter processing unit to preprocess the data, effectively removing noise and outliers, improving the quality and accuracy of the data, and helping to accurately extract key features.

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

[0057] Figure 1 It is a schematic block diagram flow chart of a stenosis detection system for arteriovenous vascular access based on auscultatory acoustic signals of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0058] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with 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 the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0059] Embodiment 1

[0060] The present invention provides a stenosis detection system for arteriovenous vascular access based on auscultatory acoustic signals. Please refer to Figure 1 , which includes a data acquisition module, a signal preprocessing module, a feature extraction module, a stenosis detection module for arteriovenous access, a stenosis evaluation module, and a result display module;

[0061] The data acquisition module is used to obtain auscultatory acoustic signals and related arteriovenous vascular parameters from the patient through a cardiac stethoscope, echocardiogram, and hemodynamic instrument, and obtain a patient detection data set;

[0062] The signal preprocessing module is used to preprocess the acquired patient detection data set. The preprocessing steps include filtering, noise reduction, amplification, and compression processing of the sound signal to remove environmental noise and enhance the target signal, and calibrating and filtering the physiological parameters to eliminate outliers;

[0063] The feature extraction module is used to extract key features from the preprocessed signal, analyze the spectrum, rhythm, and intensity of the sound signal, extract relevant information on heartbeats and vascular blood flow, extract features in the physiological parameters, and calculate to obtain: the stenosis detection index Xzjc;

[0064] The arteriovenous access stenosis detection module is used to analyze the characteristics of acoustic signals and physiological parameters, detect and locate the internal vascular information in arteries or veins using the extracted characteristics, and make a comprehensive judgment and diagnosis in combination with the patient's clinical data and historical information;

[0065] The stenosis assessment module is used to compare the detected stenosis information, location, degree, morphology, and the patient's physiological condition with the preset arteriovenous vascular access width threshold through the stenosis detection index Xzjc to obtain a clinical assessment of the stenosis, including the characteristics, impacts, and recommended treatment plans of the stenosis;

[0066] The result display module is used to display the detection results and evaluation reports to patients and medical staff, show the results of arteriovenous access stenosis detection, including the location, degree, and recommended treatment methods of the stenosis, generate a report, and describe the detection process, evaluation results, and doctor's suggestions.

[0067] In this embodiment, through a stethoscope, echocardiogram, and hemodynamic instrument, auscultatory acoustic signals and related parameters are obtained from the patient to obtain a data set. By preprocessing the collected acoustic signals, the characteristics in the physiological parameters are extracted, and after calculation, the stenosis detection index Xzjc is obtained. Analyze the characteristics of acoustic signals and physiological parameters, use the extracted characteristics to detect and locate the internal vascular information in arteries or veins, compare the stenosis detection index Xzjc with the preset arteriovenous vascular access width threshold to obtain a clinical assessment of the stenosis, and display the detection results and evaluation reports to patients and medical staff, show the results of arteriovenous access stenosis detection, generate a report, and describe in detail the detection process, evaluation results, and doctor's suggestions.

[0068] Embodiment 2

[0069] This embodiment is an explanatory description based on Embodiment 1. Please refer to Figure 1 , specifically: The data acquisition module includes a stethoscope unit, an echocardiogram unit, and a hemodynamic instrument unit;

[0070] The stethoscope unit is used to collect the acoustic signals in the patient's heart area by placing a stethoscope at different positions on the patient's chest, and obtain: heart rate Xtpl, heart sound amplitude intensity Xyzf, heart sound rhythm Xyjl, and spectral amplitude Ppfd as the first data set;

[0071] The echocardiogram unit is used to move an ultrasound probe on the patient's chest, use an echocardiogram device to obtain ultrasound images and physiological parameters of the patient's heart and blood vessels, record the stenosis site, stenosis degree, stenosis morphology, and stenosis type, and obtain: blood vessel width Xgkd, stenosis segment diameter Jzzj, stenosis morphology Xzxt, and plaque diameter Bkzj as the second data set;

[0072] The hemodynamic instrument unit is used to monitor the blood flow and related physiological parameters of a patient using hemodynamic instruments. By placing hemodynamic instruments, including an arterial pressure gauge and a Doppler ultrasound blood flow meter, the following are obtained: maximum blood flow velocity Maxsd, average blood flow velocity Xlsd, pulse wave velocity Mbsd, blood flow velocity ratio Qhxl before and after stenosis, and blood flow resistance index Xlzl, as the third data set.

[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 to preprocess the collected acoustic signals, remove unwanted frequency components in the signals, and perform filtering, noise reduction, amplification, and compression processing on the sound signals to remove environmental noise and enhance the target signals;

[0075] The physiological parameter processing unit corrects the collected 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 outliers.

[0076] In this embodiment, through the stethoscope unit, echocardiogram unit, and hemodynamic instrument unit, the system can obtain a variety of 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 characteristics collected by the 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 status of the arteriovenous vascular access from different angles and are 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 unwanted 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, and smooths the data curve, making the data more stable and reliable, and helping 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 formulate more effective treatment plans.

[0077] Embodiment 3

[0078] This embodiment is an explanatory description based on Embodiment 1. Please refer to Figure 1 , specifically: 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 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 rhythms in the sound signal, and measure the amplitude or energy of the sound signal;

[0080] 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 echocardiogram 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 regulatory function of the cardiovascular system, and calculate to obtain: stenosis detection index Xzjc, sound feature coefficient Sytz, stenosis degree coefficient Xzcd, and blood flow velocity coefficient Xlxs;

[0081] The stenosis detection index Xzjc is calculated and obtained through 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, and q, w, and e respectively represent the proportionality coefficients of the sound feature coefficient Sytz, stenosis degree coefficient Xzcd, and blood flow velocity coefficient Xlxs;

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

[0085] The sound feature coefficient Sytz is calculated and obtained through the following formula:

[0086] ;

[0087] In the formula, Xtpl represents the heart rate, Xyzf represents the heart sound amplitude intensity, Xyjl represents the heart sound rhythm, Ppfd represents the spectral amplitude, and t, y, u, and i respectively represent the proportionality coefficients of the heart rate Xtpl, heart sound amplitude intensity Xyzf, heart sound rhythm Xyjl, and spectral amplitude Ppfd;

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

[0089] The stenosis degree coefficient Xzcd is calculated and obtained through the following formula:

[0090] ;

[0091] In the formula, Xgkd represents the blood vessel width, Jzzj represents the diameter of the stenosis segment, Xzxt represents the stenosis morphology, Bkzj represents the plaque diameter, and a, s, d, and f respectively represent the proportionality coefficients of the blood vessel width Xgkd, the diameter of the stenosis segment Jzzj, the stenosis morphology Xzxt, and the plaque diameter Bkzj;

[0092] Among them, , , , , and , G represents the third correction constant.

[0093] The blood flow velocity coefficient Xlxs is obtained by calculating through the following formula:

[0094] ;

[0095] 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 stenosis, Xlzl represents the blood flow resistance index, and h, j, k, z, and x respectively represent the proportionality 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 stenosis Qhxl, and the blood flow resistance index Xlzl;

[0096] Among them, , , , , , and , L represents the fourth correction constant.

[0097] In this embodiment, the voice signal feature extraction unit can convert the voice signal into the frequency domain through Fourier transform, analyze the spectral features, detect the heartbeat rhythm or other periodic rhythms, and measure the amplitude or energy of the voice signal; the physiological parameter feature extraction unit can extract key features from the preprocessed physiological parameters, including the maximum blood flow velocity, average blood flow velocity, and heart rate variability, etc., so as to comprehensively reflect 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, voice feature coefficient Sytz, stenosis degree coefficient Xzcd, and blood flow velocity coefficient Xlxs. These indexes can objectively evaluate the stenosis degree and features of the arteriovenous vascular access, providing a quantitative diagnostic basis for doctors. The proportional coefficient and correction constant in the formula can be adjusted according to the actual situation to make the calculation results 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 voice features, physiological parameters, and quantitative indexes, the system can conduct a 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 explanatory description based on 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 voice signal, identify the relevant information of the heartbeat and vascular blood flow, and use the acoustic signal features to detect and locate the stenosis in the artery or vein;

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

[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 the 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:

[0104] When the stenosis detection index Xzjc < the preset arteriovenous access width threshold M, the stenosis degree is determined to be grade one. Confirm the location, degree and morphology of the stenosis, which is determined by echocardiogram or other imaging examinations. Monitor the patient's physiological parameters and recommend that the patient adjust their lifestyle;

[0105] When the preset arteriovenous access width threshold M ≤ stenosis detection index Xzjc ≤ preset arteriovenous access width threshold N, the stenosis degree is determined to be grade two. Confirm the location, degree and morphology of the stenosis, consider taking drug treatment measures, and monitor the patient's physiological parameters and symptom changes once a week;

[0106] When the stenosis detection index Xzjc > the preset arteriovenous access width threshold N, the stenosis degree is determined to be grade three. Confirm the location, degree and morphology of the stenosis, consider interventional treatment measures, and review the arteriovenous vascular conditions of the patient 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 arteriovenous access stenosis detection, including the location, degree and recommended treatment methods of the stenosis, provide a visual interface, and present the data, echocardiogram and arterial blood flow velocity map during the detection process;

[0109] The report generation unit is used to automatically generate an evaluation report based on the stenosis degree evaluation result and the patient's physiological condition, including the characteristics, location and degree of the stenosis, as well as the doctor's treatment recommendations and prognosis information, and provide report export and printing functions for the patient and doctor to refer to and save.

[0110] In this embodiment, the acoustic signal analysis unit analyzes the preprocessed acoustic signal, identifies the relevant information of the heartbeat and blood vessel blood flow, and uses the acoustic signal characteristics to detect and locate the stenosis in the arterial or venous blood vessels. The physiological parameter analysis unit analyzes the physiological parameters to assist in detecting and locating the stenosis in the arterial or venous blood vessels. This comprehensive analysis and location can provide comprehensive stenosis detection results. The stenosis evaluation module compares the detected stenosis information, including the location, degree, and morphology, with the preset arteriovenous access width threshold in combination with the stenosis detection index Xzjc to evaluate and classify the stenosis degree. This classification scheme can provide doctors with a clearer judgment of the stenosis degree so as to take corresponding treatment measures. The result display module can display the results of arteriovenous access stenosis detection in a visual interface, including the location, degree, and recommended treatment methods of the stenosis, and provide information such as data, echocardiogram, and arterial blood flow velocity map. The report generation unit automatically generates an evaluation report, including the characteristics, location, and degree of the stenosis, as well as the doctor's treatment suggestions and prognosis information. Such a function can help doctors understand the detection results more effectively and provide clear diagnostic reports for patients.

[0111] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A system for detecting arteriovenous vascular stenosis based on auscultatory acoustic signals, characterized in that: It includes a data acquisition module, a signal preprocessing module, a feature extraction module, an arteriovenous access stenosis detection module, a stenosis assessment module and a result display module; The data acquisition module is used to obtain auscultation acoustic signals and related arteriovenous blood vessel parameters from the patient through a cardiac stethoscope, an echocardiogram and a hemodynamic instrument to obtain a patient detection data group; The signal preprocessing module is used to preprocess the collected patient test data group, and the preprocessing steps include filtering, denoising, amplifying and compressing the sound signal, removing environmental noise and enhancing the target signal, calibrating and filtering the physiological parameters, and eliminating abnormal values; The feature extraction module is used to extract key features from the preprocessed signal, analyze the spectrum, rhythm and intensity of the sound signal, extract relevant information of heartbeat and blood flow in blood vessels, extract features in physiological parameters, and obtain after calculation: stenosis detection index Xzjc; The arteriovenous access stenosis detection module is used to analyze the characteristics of acoustic signals and physiological parameters, use the extracted characteristics to detect and locate the internal information of blood vessels in arteries or veins, and make a comprehensive judgment and diagnosis in combination with the patient's clinical data and historical information; The stenosis assessment module is used to obtain a clinical assessment of the stenosis, including the characteristics, impact and recommended treatment plan of the stenosis, by comparing the stenosis detection index Xzjc with a preset arteriovenous vascular access width threshold according to the detected stenosis information, location, degree, morphology and the patient's physiological condition; The result display module is used to display the test results and evaluation reports to patients and medical staff, display the results of arteriovenous access stenosis detection, including the location, degree and recommended treatment of the stenosis, and generate a report describing the test process, evaluation results and doctor's recommendations.

2. The arteriovenous vascular access stenosis detection system based on auscultatory acoustic signals according to claim 1, characterized in that: The data acquisition module includes a cardiac stethoscope unit, an echocardiogram unit and a hemodynamic instrument unit; The cardiac stethoscope unit is used to collect acoustic signals of the patient's heart area by placing the cardiac stethoscope at different positions on the patient's chest, and obtain: heartbeat frequency Xtpl, heart sound amplitude intensity Xyzf, heart sound rhythm Xyjl and spectrum amplitude Ppfd as the first data group; The ultrasound cardiography unit is used to move the ultrasound probe on the patient's chest, use the ultrasound cardiography device to obtain ultrasound images and physiological parameters of the patient's heart and blood vessels, record the stenosis site, stenosis degree, stenosis morphology and stenosis type, and obtain: blood vessel width Xgkd, stenosis segment diameter Jzzj, stenosis morphology Xzxt and plaque diameter Bkzj as the second data group; The hemodynamic instrument unit is used to monitor the patient's blood flow and related physiological parameters using hemodynamic instruments. By placing hemodynamic instruments, including an arterial pressure meter and a Doppler ultrasonic blood flow meter, the following data sets are obtained: maximum blood flow velocity Maxsd, average blood flow velocity Xlsd, pulse wave velocity Mbsd, ratio of blood flow velocity before and after stenosis Qhxl, and blood flow resistance index Xlzl, as the third data group.

3. The arteriovenous vascular access stenosis detection system based on auscultatory acoustic signals according to claim 1, characterized in that: The signal preprocessing module includes a sound signal processing unit and a physiological parameter processing unit; The sound signal processing unit is used to pre-process the collected acoustic signal, remove unnecessary frequency components in the signal, filter, reduce noise, amplify and compress the sound signal, remove environmental noise and enhance the target signal; The physiological parameter processing unit corrects the collected physiological parameters according to the calibration curve of the device or the actual measured value, removes high-frequency noise and fluctuations in the physiological parameters, smoothes the data curve, and eliminates abnormal values.

4. The arteriovenous vascular access stenosis detection system based on auscultatory acoustic signals according to claim 1, characterized in that: 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 into the frequency domain through Fourier transform, analyze its spectrum 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 the echocardiogram or hemodynamic instrument, extract the maximum blood flow velocity and the average blood flow velocity, extract the heart rate variability characteristics from the heart rate data to reflect the regulatory function of the cardiovascular system, and obtain after calculation: stenosis detection index Xzjc, sound characteristic coefficient Sytz, stenosis degree coefficient Xzcd and blood flow velocity coefficient Xlxs; The stenosis detection index Xzjc is calculated by the following formula: ； Wherein, Sytz represents the sound characteristic 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 characteristic coefficient Sytz, the stenosis degree coefficient Xzcd and the blood flow velocity coefficient Xlxs respectively; in, , , ,and , R represents the first correction constant.

5. The arteriovenous vascular access stenosis detection system based on auscultatory acoustic signals according to claim 4, characterized in that: The sound characteristic coefficient Sytz is calculated by the following formula: ； Wherein, Xtpl represents the heart rate, Xyzf represents the amplitude intensity of heart sound, Xyjl represents the rhythm of heart sound, Ppfd represents the spectrum amplitude, t, y, u and i represent the proportional coefficients of heart rate Xtpl, heart sound amplitude intensity Xyzf, heart sound rhythm Xyjl and spectrum amplitude Ppfd respectively; in, , , , ,and , O represents the second correction constant.

6. The arteriovenous vascular access stenosis detection system based on auscultatory acoustic signals according to claim 4, characterized in that: The stenosis degree coefficient Xzcd is calculated by the following formula: ； Where, Xgkd represents the vessel width, Jzzj represents the stenosis segment diameter, Xzxt represents the stenosis morphology, Bkzj represents the plaque diameter, a, s, d and f represent the proportional coefficients of the vessel width Xgkd, the stenosis segment diameter Jzzj, the stenosis morphology Xzxt and the plaque diameter Bkzj, respectively; in, , , , ,and , G represents the third correction constant.

7. The arteriovenous vascular access stenosis detection system based on auscultatory acoustic signals according to claim 4, characterized in that: The blood flow velocity coefficient Xlxs is calculated by the following formula: ； Wherein, Maxsd represents the maximum blood flow velocity, Xlsd represents the average blood flow velocity, Mbsd represents the pulse wave velocity, Qhxl represents the ratio of blood flow velocity before and after stenosis, Xlzl represents the blood flow resistance index, 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 ratio of blood flow velocity before and after stenosis Qhxl and the blood flow resistance index Xlzl respectively; in, , , , , ,and , L represents the fourth correction constant.

8. The arteriovenous vascular access stenosis detection system based on auscultatory acoustic signals according to claim 1, characterized in that: 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 in the sound signal, identify the relevant information of the heartbeat and blood flow in the blood vessels, and use the acoustic signal characteristics to detect and locate the stenosis in the artery or vein; The physiological parameter analysis unit is used to analyze the pre-processed physiological parameters, analyze the blood flow velocity and heart rate characteristics in the physiological parameters, and assist in detecting and locating the stenosis in the artery or vein.

9. The arteriovenous vascular access stenosis detection system based on auscultatory acoustic signals according to claim 1, characterized in that: The stenosis assessment module includes a stenosis degree assessment unit; The stenosis degree evaluation unit is used to analyze the stenosis information detected in the arteriovenous access, including the position, degree and morphology, and compare the stenosis detection index Xzjc with the preset arteriovenous access width threshold M and the preset arteriovenous access width threshold N to obtain a clinical evaluation of the stenosis: When the stenosis detection index Xzjc is less than the preset arteriovenous vascular access width threshold M, the stenosis is determined to be level one, and the location, degree and morphology of the stenosis are confirmed by echocardiography or other imaging examinations, the patient's physiological parameters are monitored, and the patient is advised to adjust his or her lifestyle; When the preset arteriovenous access width threshold M≤stenosis detection index Xzjc≤preset arteriovenous access width threshold N, the stenosis degree is determined to be level 2, the location, degree and morphology of the stenosis are confirmed, drug treatment measures are considered, and the patient's physiological parameters and symptom changes are monitored once a week; When the stenosis detection index Xzjc is greater than the preset arteriovenous vascular access width threshold N, the degree of stenosis is determined to be level three. The location, degree and morphology of the stenosis are confirmed, interventional treatment measures are considered, and the patient's arteriovenous condition is reviewed three times a week.

10. The arteriovenous vascular access stenosis detection system based on auscultatory acoustic signals according to claim 1, characterized in that: The result display module includes a result display unit and a report generation unit; The result display unit is used to display the results of the arteriovenous access stenosis detection, including the location, degree and recommended treatment of the stenosis, and to provide a visual interface to present the data during the detection process, the echocardiogram and the arterial blood flow velocity diagram; The report generating unit is used to automatically generate an assessment report based on the stenosis degree assessment result and the patient's physiological condition, including the characteristics, location and degree of stenosis, as well as the doctor's treatment recommendations and prognosis information, and provides report export and printing functions for patients and doctors to refer to and save.

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