Clinical intelligent monitoring exercise system suitable for cardiovascular medicine department

Abstract

The invention discloses a clinical intelligent monitoring exercise system suitable for the cardiovascular medicine department, and the system comprises an intelligent fitness module which is provided with a plurality of sensors and is used for collecting the physiological signal and motion state information of a user in real time; the edge calculation unit is responsible for preliminarily processing sensor data; the cloud analysis platform is used for deeply analyzing the uploaded data by using a machine learning model; the mobile application program is used for displaying personal health reports, exercise suggestions and progress tracking; and the medical expert system is integrated on the cloud platform, contains abundant medical knowledge bases and diagnosis rules, and assists doctors in making professional judgments. The invention provides a set of complete intelligent monitoring exercise system, which not only overcomes the defects in the prior art, but also creates a brand new cardiovascular medicine clinical management mode, and has important social significance and wide application prospects.

Description

Technical Field

[0001] The present invention relates to the technical field of health monitoring, and in particular to an intelligent monitoring and training system suitable for clinical cardiovascular medicine. Background Art

[0002] Cardiovascular disease is one of the leading causes of death and disability worldwide, seriously affecting patients' quality of life and life expectancy. In clinical practice of cardiovascular medicine, proper physical exercise plays a vital role in improving heart function, controlling disease progression, and promoting recovery. However, traditional exercise guidance methods often lack personalization and real-time monitoring, and cannot meet the high requirements of modern medicine for accuracy and safety.

[0003] Although the fitness equipment and wearable devices currently on the market can provide basic physiological parameter monitoring, such as heart rate, blood oxygen saturation, etc., most of them are not specially designed for cardiovascular diseases and cannot fully consider the special needs of patients. These devices can usually only record data and give simple feedback, and it is difficult to dynamically adjust the intensity and frequency of exercise according to individual differences, which may lead to insufficient or excessive exercise, increase the burden on the heart, and even cause the risk of acute cardiovascular events.

[0004] Existing systems generally lack effective communication mechanisms with doctors, and patients often do not receive timely guidance and support from professional doctors when receiving exercise advice. At the same time, due to the lack of advanced data analysis capabilities and prediction models, existing technologies are difficult to achieve a comprehensive assessment of the user's health status and early warning of potential risks, limiting their application value in cardiovascular disease management. Summary of the invention

[0005] 1. Technical Problems Solved

[0006] The technical problems to be solved by the present invention are the various problems mentioned in the above background technology, and an intelligent monitoring and training system suitable for clinical cardiovascular medicine is provided.

[0007] 2. Technical Solution

[0008] In order to solve the above technical problems, the technical solution provided by the present invention is: an intelligent monitoring and training system suitable for clinical cardiovascular medicine, comprising:

[0009] The smart fitness module is equipped with multiple sensors to collect the user's physiological signals and exercise status information in real time;

[0010] an edge computing unit, connected to the smart fitness device, responsible for preliminary processing of sensor data, extracting feature values, and executing an immediate response strategy in an emergency;

[0011] The cloud-based analysis platform, which is connected to the edge computing unit via the Internet, uses machine learning models to conduct in-depth analysis of the uploaded data, assess the user's cardiovascular health, predict potential risks, and develop a personalized exercise plan;

[0012] The mobile application, as the user interface, displays personal health reports, exercise suggestions and progress tracking; it also supports video calling function, which facilitates remote guidance and consultation from doctors;

[0013] The medical expert system, integrated on the cloud platform, contains a rich medical knowledge base and diagnostic rules to assist doctors in making professional judgments and can automatically adjust exercise plans to suit rehabilitation needs at different stages.

[0014] As an improvement, the sensors equipped in the smart fitness module specifically include an electrocardiogram sensor, a blood pressure monitor, an accelerometer and a gyroscope, which are used to comprehensively monitor changes in the user's physiological parameters during exercise.

[0015] As an improvement, the edge computing unit also has an anomaly detection function. When it monitors that the user's physiological indicators exceed the preset safety range, it can immediately take protective measures, such as stopping the operation of the exercise equipment or issuing an alarm.

[0016] As an improvement, the cloud analysis platform adopts advanced machine learning algorithms, including deep neural network DNN and convolutional neural network CNN, to perform pattern recognition and trend prediction on the collected data, thereby providing users with more accurate health management services.

[0017] As an improvement, the mobile application has a personalized setting option that allows users to set goals according to their own circumstances, adjust reminder frequency, and select the type of exercise they are interested in.

[0018] As an improvement, the medical expert system is built based on the principles of evidence-based medicine and can continuously update and improve its internal knowledge base and decision-making logic according to the latest clinical guidelines and research results.

[0019] As an improvement, it also includes a data security module to ensure that all transmitted and stored data is encrypted, complies with relevant laws and regulations, and protects the security of patients' personal information.

[0020] 3. Beneficial Effects

[0021] The advantages of the present invention compared with the prior art are:

[0022] 1. The intelligent monitoring and exercise system of the present invention can monitor the cardiovascular health status of the user in real time, ensuring that any abnormal situation during the exercise process can be quickly detected and corresponding measures can be taken, greatly improving safety. For example, when the heart rate or blood pressure is monitored to be out of the safe range, the edge computing unit can immediately stop the operation of the exercise equipment or issue an alarm to prevent possible cardiovascular events. Through the advanced machine learning algorithm cloud analysis platform, the user's physiological data can be deeply analyzed, not only to assess the current health status, but also to predict potential risks, and provide each user with an accurate personalized exercise plan. This data-driven decision support helps optimize the rehabilitation process and improve the treatment effect.

[0023] 2. The mobile application of the intelligent monitoring and exercise system of the present invention provides an intuitive and easy-to-use interface, allowing users to flexibly set exercise goals, reminder frequency and exercise types according to their needs, enhancing the user experience. At the same time, the video call function allows doctors to remotely guide patients and answer questions in a timely manner, strengthening the communication and trust between doctors and patients. The medical expert system is built based on the latest evidence-based medicine principles, combined with a rich medical knowledge base and diagnostic rules, to assist doctors in making more accurate professional judgments, and can dynamically adjust exercise plans to meet the rehabilitation needs of different stages. This not only improves the quality of medical services, but also promotes academic research and technological progress. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 This is a structural diagram of an intelligent monitoring and training system suitable for clinical cardiovascular medicine of the present invention. DETAILED DESCRIPTION

[0025] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only 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 ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0026] Embodiment 1

[0027] like Figure 1 As shown, an intelligent monitoring and training system suitable for clinical use in cardiovascular medicine comprises:

[0028] The smart fitness module is equipped with multiple sensors to collect the user's physiological signals and exercise status information in real time;

[0029] an edge computing unit, connected to the smart fitness device, responsible for preliminary processing of sensor data, extracting feature values, and executing an immediate response strategy in an emergency;

[0030] The cloud-based analysis platform, which is connected to the edge computing unit via the Internet, uses machine learning models to conduct in-depth analysis of the uploaded data, assess the user's cardiovascular health, predict potential risks, and develop a personalized exercise plan;

[0031] The mobile application, as the user interface, displays personal health reports, exercise suggestions and progress tracking; it also supports video calling function, which facilitates remote guidance and consultation from doctors;

[0032] The medical expert system, integrated on the cloud platform, contains a rich medical knowledge base and diagnostic rules to assist doctors in making professional judgments and can automatically adjust exercise plans to suit rehabilitation needs at different stages.

[0033] The sensors equipped in the smart fitness module specifically include electrocardiogram sensors, blood pressure monitors, accelerometers and gyroscopes, which are used to comprehensively monitor changes in the user's physiological parameters during exercise. The edge computing unit also has an abnormality detection function. When it is monitored that the user's physiological indicators exceed the preset safety range, protective measures can be taken immediately, such as stopping the operation of the exercise equipment or issuing an alarm.

[0034] The cloud analysis platform uses advanced machine learning algorithms, including deep neural networks (DNN) and convolutional neural networks (CNN), to perform pattern recognition and trend prediction on the collected data, thereby providing users with more accurate health management services. The mobile application has personalized setting options that allow users to set goals, adjust reminder frequency, and select the type of exercise they are interested in based on their own circumstances.

[0035] The medical expert system is built based on the principles of evidence-based medicine. It can continuously update and improve its internal knowledge base and decision-making logic according to the latest clinical guidelines and research results. It also includes a data security module to ensure that all transmitted and stored data are encrypted, comply with relevant laws and regulations, and protect the personal information security of patients.

[0036] Working principle of the present invention:

[0037] 1. Smart fitness module

[0038] The smart fitness module is one of the core components of this system. It is equipped with a variety of high-precision sensors, including but not limited to electrocardiogram (ECG) sensors, blood pressure monitors, accelerometers and gyroscopes. These sensors can collect the user's physiological signals (such as heart rate, heart rhythm, blood pressure, etc.) and exercise status information (such as exercise intensity, posture changes, etc.) in real time. For example, the ECG sensor can continuously record the heart's electrical signals to detect arrhythmias; the blood pressure monitor can regularly measure blood pressure values ​​to ensure that exercise is performed within a safe range. Accelerometers and gyroscopes are used to monitor the user's exercise posture and activity level to help evaluate the effect of exercise and prevent injuries caused by improper posture.

[0039] 2. Edge computing unit

[0040] The edge computing unit is closely connected to the smart fitness module and is responsible for the preliminary processing of sensor data. It can not only extract key feature values, such as average heart rate, maximum heart rate, exercise duration, etc., but also implement immediate response strategies in emergency situations. For example, when the user's heart rate or blood pressure is monitored to exceed the preset safety range, the edge computing unit will immediately trigger an alarm and take protective measures according to the preset rules, such as stopping the operation of the exercise equipment or issuing a voice prompt to remind the user to rest or seek help. In addition, the edge computing unit also has a local storage function, which can save important data in the case of unstable network and upload it to the cloud after the network is restored.

[0041] 3. Cloud-based analysis platform

[0042] The cloud analysis platform is connected to the edge computing unit via the Internet, and uses advanced machine learning algorithms (such as deep neural network DNN and convolutional neural network CNN) to conduct in-depth analysis of the uploaded data. These algorithms can identify complex patterns and trends, assess users' cardiovascular health, predict potential risks, and develop personalized exercise plans. For example, based on historical data and current physiological indicators, the cloud analysis platform can generate daily / weekly exercise recommendations with clear goals, maximum allowed heart rate range, and other considerations. In addition, the platform will continuously update model parameters to adapt to the needs and changes of different users.

[0043] 4. Mobile App

[0044] As the user interface, the mobile application provides an intuitive and easy-to-use operation experience. Users can view personal health reports, exercise suggestions and progress tracking through the application to understand their physical condition and exercise results. The application also has personalized setting options, allowing users to set goals according to their own situation, adjust the reminder frequency, and choose the type of exercise they are interested in. For example, users can choose different aerobic exercises or strength training programs and arrange exercise plans according to their own time and energy. In addition, the application supports video call function, which is convenient for doctors to provide remote guidance and consultation, and enhances communication and interaction between doctors and patients.

[0045] 5. Medical Expert System

[0046] The medical expert system is integrated on the cloud platform and contains a rich medical knowledge base and diagnostic rules to assist doctors in making professional judgments. The system is built on the principles of evidence-based medicine and can continuously update and improve its internal knowledge base and decision-making logic based on the latest clinical guidelines and research results. For example, when a user has abnormal physiological indicators, the medical expert system can automatically adjust the exercise plan based on the built-in diagnostic rules and recommend appropriate drug treatment or lifestyle improvement suggestions. In addition, doctors can view the latest progress of each patient through a dedicated management system and initiate video conferences when necessary to provide face-to-face professional guidance.

[0047] 6.Data security module

[0048] In order to protect the security of users' personal information, the system also includes a dedicated data security module. All transmitted and stored data is encrypted to ensure that it is not stolen or tampered with during network transmission. The system strictly abides by relevant laws and regulations, such as the Cybersecurity Law of the People's Republic of China and the General Data Protection Regulation (GDPR), to protect patients' privacy and personal information security. For example, users can choose which data can be shared with doctors and which data is for personal use only, which increases the transparency of the system and user trust.

[0049] Implementation Example

[0050] Suppose a patient with coronary heart disease is using this system for rehabilitation exercises. First, the patient needs to complete a comprehensive physical examination and establish a personal health profile, including past medical history, current medication, physical measurement results, etc. Based on this information, the system will generate an initial exercise prescription, clearly defining daily / weekly goals, maximum allowed heart rate range, and other precautions.

[0051] Before using smart fitness equipment each time, patients need to wear the corresponding sensor device and start the activity according to the instructions. During this period, the device will continuously collect various physiological indicators and synchronize them to the edge computing unit via Bluetooth or other wireless communication methods. If any abnormal changes are detected (such as too fast heart rate, difficulty breathing, etc.), the edge computing unit will immediately take measures, such as sounding an alarm, prompting a rest, or directly cutting off the power supply to prevent accidents.

[0052] At the same time, the pre-processed data will be sent to the cloud analysis platform, where it will be further analyzed by professional AI algorithms, updating the user's health status assessment and optimizing subsequent exercise arrangements accordingly. Doctors can view the latest progress of each patient by logging into a dedicated management system and initiate video conferences when necessary to provide face-to-face professional guidance.

[0053] Throughout the entire process, every link in the system strictly follows data security standards to ensure that all operations are legal and compliant. Through this closed-loop health management process, patients can not only exercise effectively in a safe environment, but also get support and advice from professional doctors at any time, thereby improving rehabilitation effects and quality of life.

[0054] In summary, the present invention provides a complete intelligent monitoring and exercise system, which not only solves the deficiencies in the prior art, but also creates a new clinical management model for cardiovascular medicine, which has important social significance and broad application prospects.

[0055] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0056] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

[0057] The present invention and its embodiments are described above, and such description is not restrictive. The drawings show only one embodiment of the present invention, and the actual structure is not limited thereto. In short, if ordinary technicians in the field are inspired by it, without departing from the purpose of the invention, they can design a structure and embodiment similar to the technical solution without creativity, which should belong to the protection scope of the present invention.

Claims

1. An intelligent monitoring and training system suitable for clinical cardiovascular medicine, characterized in that: include: The smart fitness module is equipped with multiple sensors to collect the user's physiological signals and exercise status information in real time; an edge computing unit, connected to the smart fitness device, responsible for preliminary processing of sensor data, extracting feature values, and executing an immediate response strategy in an emergency; The cloud-based analysis platform, which is connected to the edge computing unit via the Internet, uses machine learning models to conduct in-depth analysis of the uploaded data, assess the user's cardiovascular health, predict potential risks, and develop a personalized exercise plan; The mobile application, as the user interface, displays personal health reports, exercise suggestions and progress tracking; it also supports video calling function, which facilitates remote guidance and consultation from doctors; The medical expert system, integrated on the cloud platform, contains a rich medical knowledge base and diagnostic rules to assist doctors in making professional judgments and can automatically adjust exercise plans to suit rehabilitation needs at different stages.

2. The intelligent monitoring and training system suitable for clinical cardiovascular medicine according to claim 1, characterized in that: The sensors equipped in the smart fitness module specifically include an electrocardiogram sensor, a blood pressure monitor, an accelerometer and a gyroscope, which are used to comprehensively monitor changes in the user's physiological parameters during exercise.

3. The intelligent monitoring and training system suitable for clinical cardiovascular medicine according to claim 1, characterized in that: The edge computing unit also has an abnormality detection function. When it monitors that the user's physiological indicators exceed the preset safety range, it can immediately take protective measures, such as stopping the operation of the exercise equipment or issuing an alarm.

4. The intelligent monitoring and training system suitable for clinical cardiovascular medicine according to claim 1, characterized in that: The cloud analysis platform uses advanced machine learning algorithms, including deep neural network DNN and convolutional neural network CNN, to perform pattern recognition and trend prediction on the collected data, thereby providing users with more accurate health management services.

5. The intelligent monitoring and training system suitable for clinical cardiovascular medicine according to claim 1, characterized in that: The mobile app has personalized settings options that allow users to set goals according to their own situation, adjust the frequency of reminders, and select the type of exercise they are interested in.

6. The intelligent monitoring and training system suitable for clinical cardiovascular medicine according to claim 1, characterized in that: The medical expert system is constructed based on the principles of evidence-based medicine and can continuously update and improve its internal knowledge base and decision-making logic according to the latest clinical guidelines and research results.

7. The intelligent monitoring and training system suitable for clinical cardiovascular medicine according to claim 1, characterized in that: It also includes a data security module to ensure that all transmitted and stored data is encrypted, complies with relevant laws and regulations, and protects the security of patients' personal information.

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