Cardiovascular disease auxiliary diagnosis and treatment scheme recommendation equipment

Abstract

The invention discloses cardiovascular disease auxiliary diagnosis and treatment scheme recommendation equipment which comprises a pulse wave acquisition module, a data preprocessing and feature extraction module, a multi-dimensional index comprehensive analysis module, a diagnosis and treatment scheme recommendation module and a user interaction and data display module. According to the invention, non-invasive early screening of cardiovascular diseases is realized by using pulse wave signals, and the detection cost and risk are reduced; through feature extraction of three dimensions of pulse map disassembly, pulse condition matrix and pulse condition holography, omnibearing assessment of the cardiovascular state is realized. On the basis of multi-dimensional features and an intelligent algorithm, targeted diagnosis and treatment suggestions are provided, and early intervention and disease prevention are facilitated; the equipment supports real-time display, remote transmission and data management, and is convenient for clinical doctors to further analyze and make decisions.

Description

Technical Field

[0001] The present invention relates to the technical field of auxiliary diagnosis and treatment of cardiovascular diseases, and specifically to a device for recommending auxiliary diagnosis and treatment plans for cardiovascular diseases. Background Art

[0002] Cardiovascular diseases (including valvular diseases, coronary heart diseases, heart failure, arrhythmia, abnormal blood pressure, etc.) are one of the main diseases threatening human health. At present, clinical diagnosis mainly relies on traditional means such as imaging examinations, blood tests, electrocardiograms, etc. These methods generally have problems such as invasiveness, long detection cycles, high costs, etc., and are insufficient in sensitivity to early minor lesions. In recent years, as a non-invasive and easily obtainable physiological signal, the information of cardiovascular function contained in the pulse wave has received extensive attention. Research shows that through multi-dimensional analysis of the pulse wave (such as pulse diagram decomposition, pulse matrix construction, extraction of holographic characteristics of the pulse condition, etc.), characteristic parameters related to the cardiovascular health status can be effectively extracted. However, the existing technologies have not formed a standardized pulse wave analysis system, lack a systematic solution for the comprehensive application of multi-dimensional indicators, and it is difficult to meet the clinical needs for early screening and precise diagnosis and treatment of cardiovascular diseases. Therefore, there is an urgent need for a device that can integrate multi-dimensional characteristics of the pulse wave and achieve intelligent diagnosis to improve the diagnosis efficiency and accuracy of cardiovascular diseases. Summary of the Invention

[0003] The purpose of the present invention is to provide a device for recommending auxiliary diagnosis and treatment plans for cardiovascular diseases to solve the problems raised in the above background art.

[0004] To achieve the above purpose, the present invention provides the following technical solution: A device for recommending auxiliary diagnosis and treatment plans for cardiovascular diseases, including a pulse wave acquisition module, a data preprocessing and feature extraction module, a multi-dimensional index comprehensive analysis module, a diagnosis and treatment plan recommendation module, and a user interaction and data display module; the pulse wave acquisition module is signal-connected to the data preprocessing and feature extraction module, the multi-dimensional index comprehensive analysis module, and the diagnosis and treatment plan recommendation module, and the data preprocessing and feature extraction module, the multi-dimensional index comprehensive analysis module, and the diagnosis and treatment plan recommendation module are signal-connected to the user interaction and data display module;

[0005] The pulse wave acquisition module is used to collect the pulse wave signal of the person to be detected in real time;

[0006] The data preprocessing and feature extraction module performs noise filtering, signal smoothing, and normalization processing on the collected pulse wave data; extracts features through pulse diagram decomposition; and constructs a pulse matrix, and obtains holographic information in the pulse wave by using the pulse holographic method to obtain multi-dimensional feature data;

[0007] The multi-dimensional index comprehensive analysis module comprehensively evaluates the risk of cardiovascular diseases based on the obtained multi-dimensional feature data;

[0008] The diagnosis and treatment plan recommendation module gives corresponding diagnosis and treatment suggestions according to the risk assessment results;

[0009] The user interaction and data display module displays the detection results, risk assessment, and recommended plans through a display screen or a mobile terminal.

[0010] Preferably, the pulse wave acquisition module uses a photoplethysmogram detection, pressure, or ultrasonic sensor to collect the pulse wave signal of the detected person in real time.

[0011] Preferably, the features extracted by the pulse graph decomposition include time, pulse amplitude, angle, area, and ratio features;

[0012] The pulse image matrix is used to extract parameters such as pulse length, pulse width, pulse shape, pulse depth, pulse trend, and pulse force;

[0013] The pulse wave holographic information includes sound, ripple, edge, wind, and tide information. Sound is the frequency component, ripple is the periodic fluctuation, edge is the waveform edge feature, wind is the high-frequency noise component, and tide is the low-frequency trend term.

[0014] Preferably, the multi-dimensional index comprehensive analysis module specifically inputs the obtained multi-dimensional feature data into the diagnostic algorithm module. The diagnostic algorithm module can comprehensively evaluate the risk of cardiovascular diseases based on an expert system, a rule engine, or a machine learning model; the analysis results cover the risk levels of various diseases such as valvular heart disease, coronary heart disease, heart failure, arrhythmia, and blood pressure abnormalities.

[0015] Preferably, the diagnosis and treatment plan recommendation module specifically generates personalized diagnosis and treatment suggestions according to the risk assessment results, in combination with past clinical data and an expert knowledge base, including drug treatment, lifestyle adjustment, or further clinical examination suggestions.

[0016] Preferably, the user interaction and data display module supports data storage, remote upload, and interface docking with the hospital information system.

[0017] Compared with the prior art, the beneficial effects of the present invention are:

[0018] (1) Non-invasive and efficient: Using the pulse wave signal to achieve non-invasive early screening of cardiovascular diseases, reducing the detection cost and risk;

[0019] (2) Multi-dimensional comprehensive evaluation: Through the feature extraction of three dimensions of pulse graph decomposition, pulse image matrix, and pulse holography, a comprehensive evaluation of the cardiovascular state is realized;

[0020] (3) Personalized diagnosis and treatment: Based on multi-dimensional features and intelligent algorithms, provide targeted diagnosis and treatment suggestions, which helps with early intervention and disease prevention;

[0021] (4) Convenient data interaction: The device supports real-time display, remote transmission, and data management, facilitating further analysis and decision-making by clinicians. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 is the device module diagram of the present invention;

[0023] Figure 2 is the diagram of pulse pattern decomposition, pulse matrix, and extraction of pulse wave holographic information features of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0024] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0025] Please refer to Figure 1-2 , the present invention provides a device for assisting in the diagnosis of cardiovascular diseases and recommending treatment plans, including a pulse wave acquisition module, a data preprocessing and feature extraction module, a multi-dimensional index comprehensive analysis module, a treatment plan recommendation module, and a user interaction and data display module; the pulse wave acquisition module is signal-connected to the data preprocessing and feature extraction module, the multi-dimensional index comprehensive analysis module, and the treatment plan recommendation module, and the data preprocessing and feature extraction module, the multi-dimensional index comprehensive analysis module, and the treatment plan recommendation module are signal-connected to the user interaction and data display module;

[0026] The pulse wave acquisition module is used to collect the pulse wave signals of the detected person in real time;

[0027] The data preprocessing and feature extraction module performs noise filtering, signal smoothing, and normalization on the collected pulse wave data; extracts features through pulse pattern decomposition; and constructs a pulse matrix, and uses the pulse holographic method to obtain the holographic information in the pulse wave to obtain multi-dimensional feature data;

[0028] The multi-dimensional index comprehensive analysis module comprehensively evaluates the risk of cardiovascular diseases based on the obtained multi-dimensional feature data;

[0029] The treatment plan recommendation module gives corresponding treatment suggestions according to the risk assessment results;

[0030] The user interaction and data display module displays the detection results, risk assessment, and recommended plans through a display screen or a mobile terminal.

[0031] The pulse wave acquisition module uses a photoplethysmogram detection, pressure, or ultrasonic sensor to collect the pulse wave signals of the subject in real time.

[0032] The features extracted by disassembling the pulse diagram include time, pulse amplitude, angle, area, and ratio features;

[0033] The pulse image matrix is used to extract parameters such as pulse length, pulse width, pulse shape, pulse depth, pulse trend, and pulse force;

[0034] The holographic information of the pulse wave includes sound, ripple, edge, wind, and tide information. Sound is the frequency component, ripple is the periodic fluctuation, edge is the waveform edge feature, wind is the high-frequency noise component, and tide is the low-frequency trend term.

[0035] The multi-dimensional index comprehensive analysis module specifically inputs the obtained multi-dimensional feature data into the diagnostic algorithm module. The diagnostic algorithm module can comprehensively evaluate the risk of cardiovascular diseases based on an expert system, a rule engine, or a machine learning model; the analysis results cover the risk levels of various diseases such as valvular heart disease, coronary heart disease, heart failure, arrhythmia, and abnormal blood pressure.

[0036] The diagnosis and treatment plan recommendation module specifically generates personalized diagnosis and treatment suggestions according to the risk assessment results, combined with previous clinical data and the expert knowledge base, including drug treatment, lifestyle adjustment, or suggestions for further clinical examinations.

[0037] The user interaction and data display module supports data storage, remote upload, and interface docking with the hospital information system.

[0038] Example 1:

[0039] Hardware structure and data acquisition:

[0040] The main body of the device is a portable handheld terminal, integrated with a PPG sensor (the transmitter is a green LED, and the receiver is a photodiode) and a pressure sensor, which can simultaneously collect the photoplethysmogram signal and the pressure signal of the radial artery pulse wave. The part where the sensor contacts the skin uses a medical-grade silicone material to ensure the stability of signal coupling. The acquisition circuit includes amplification and filtering modules, which convert the analog signal into a digital signal and then transmit it to the embedded microprocessor for preliminary processing.

[0041] Example 2:

[0042] Data preprocessing and feature extraction:

[0043] Use digital signal processing technology to filter, smooth, and normalize the collected data;

[0044] Disassemble the pulse diagram through a specific algorithm to extract the indicators of time, pulse amplitude, angle, area, and ratio;

[0045] Construct a pulse matrix simultaneously and extract the parameters of pulse length, pulse width, pulse shape, pulse depth, pulse potential, and pulse force;

[0046] Combined with the pulse holographic technology, obtain the holographic features of sound, ripple, edge, wind, and tide in the pulse wave.

[0047] Example 3:

[0048] Multi-dimensional comprehensive analysis and risk assessment:

[0049] Input all the extracted features into the intelligent diagnosis module, which can automatically evaluate the risk of cardiovascular diseases based on a pre-trained model or expert rules;

[0050] The risk assessment results include the risk levels of various cardiovascular diseases (such as valvular heart disease, coronary heart disease, heart failure, arrhythmia, and blood pressure abnormalities).

[0051] Example 4:

[0052] Recommendation of diagnosis and treatment plan and data display:

[0053] According to the risk assessment results, the system matches the corresponding diagnosis and treatment plans from the built-in clinical guidelines and knowledge base;

[0054] The device displays the test results, risk levels, and recommended plans to users and clinicians through a display screen or by connecting to a mobile terminal, and also supports data storage and remote transmission.

[0055] During specific use, the user places the main body of the device, that is, the sensor part of the portable handheld terminal, on the radial artery of the person to be tested and activates the data collection function. The device will automatically collect the pulse wave signals of the person to be tested, including photoplethysmography signals and pressure signals. Subsequently, the data preprocessing and feature extraction module will process the collected data, and through technologies such as filtering, smoothing, and normalization, improve the accuracy and reliability of the data. At the same time, this module will also disassemble the pulse diagram, extract key features such as time, pulse amplitude, angle, area, and ratio, construct a pulse matrix, obtain the parameters of pulse length, pulse width, pulse shape, pulse depth, pulse potential, and pulse force, and extract the holographic features of sound, ripple, edge, wind, and tide using pulse holographic technology, providing comprehensive data support for subsequent comprehensive analysis and risk assessment.

[0056] After completing data preprocessing and feature extraction, the multi-dimensional index comprehensive analysis module will receive these multi-dimensional feature data and input them into a pre-trained intelligent diagnosis model. This model will comprehensively evaluate the risk of cardiovascular diseases based on an expert system, rule engine, or machine learning algorithm and give the risk levels of various cardiovascular diseases.

[0057] Next, based on the risk assessment results and in combination with the built-in clinical guidelines and expert knowledge base, the diagnosis and treatment plan recommendation module will generate personalized diagnosis and treatment suggestions. These suggestions may include drug treatment, lifestyle adjustments, or further clinical examinations, etc., aiming to help the tested individuals effectively prevent or control cardiovascular diseases.

[0058] Finally, the user interaction and data display module will display the test results, risk levels, and recommended plans to the users and clinicians through a display screen or by connecting to a mobile terminal. Users can also choose to store the data or remotely upload it to the hospital information system for further analysis and decision-making by clinicians. During the entire usage process, the high efficiency, accuracy, and convenience of the device will bring great convenience to users and clinicians.

[0059] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. An auxiliary diagnosis and treatment plan recommendation device for cardiovascular diseases, characterized in that: It includes a pulse wave acquisition module, a data preprocessing and feature extraction module, a multi-dimensional index comprehensive analysis module, a diagnosis and treatment plan recommendation module, and a user interaction and data display module; the pulse wave acquisition module is signal-connected to the data preprocessing and feature extraction module, the multi-dimensional index comprehensive analysis module, and the diagnosis and treatment plan recommendation module, and the data preprocessing and feature extraction module, the multi-dimensional index comprehensive analysis module, and the diagnosis and treatment plan recommendation module are signal-connected to the user interaction and data display module; The pulse wave acquisition module is used to collect the pulse wave signal of the detected person in real time; The data preprocessing and feature extraction module performs noise filtering, signal smoothing, and normalization processing on the collected pulse wave data; extracts features through pulse diagram decomposition; And constructs a pulse image matrix, uses the pulse holographic method to obtain the holographic information in the pulse wave, and obtains multi-dimensional feature data; The multi-dimensional index comprehensive analysis module comprehensively evaluates the cardiovascular disease risk based on the obtained multi-dimensional feature data; The diagnosis and treatment plan recommendation module gives corresponding diagnosis and treatment suggestions according to the risk assessment results; The user interaction and data display module displays the detection results, risk assessment, and recommended solutions through a display screen or a mobile terminal.

2. The auxiliary diagnosis and treatment plan recommendation device for cardiovascular diseases according to claim 1, characterized in that: The pulse wave acquisition module uses a photoplethysmogram detection, pressure, or ultrasonic sensor to collect the pulse wave signal of the detected person in real time.

3. The cardiovascular disease assisted diagnosis and treatment plan recommendation device according to claim 1, characterized in that: The feature extraction through pulse diagram decomposition includes time, pulse amplitude, angle, area, and ratio features; The pulse image matrix is used to extract parameters such as pulse length, pulse width, pulse shape, pulse depth, pulse trend, and pulse force; The pulse wave holographic information includes sound, ripple, edge, wind, and tide information. Sound is the frequency component, ripple is the periodic fluctuation, edge is the waveform edge feature, wind is the high-frequency noise component, and tide is the low-frequency trend term.

4. The auxiliary diagnosis and treatment plan recommendation device for cardiovascular diseases according to claim 1, characterized in that: The multi-dimensional index comprehensive analysis module specifically inputs the obtained multi-dimensional feature data into a diagnostic algorithm module. The diagnostic algorithm module can comprehensively evaluate the cardiovascular disease risk based on an expert system, a rule engine, or a machine learning model; the analysis results cover the risk levels of various diseases such as valvular heart disease, coronary heart disease, heart failure, arrhythmia, and abnormal blood pressure.

5. An auxiliary diagnosis and treatment plan recommendation device for cardiovascular diseases according to claim 1, characterized in that: The diagnosis and treatment plan recommendation module specifically generates personalized diagnosis and treatment suggestions according to the risk assessment results, combined with past clinical data and an expert knowledge base, including drug treatment, lifestyle adjustment, or further clinical examination suggestions.

6. An auxiliary diagnosis and treatment plan recommendation device for cardiovascular diseases according to claim 1, characterized in that: The user interaction and data display module supports data storage, remote upload, and interface docking with the hospital information system.

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