Gyromagnetic therapeutic machine control system based on Internet of Things

Abstract

The invention relates to the technical field of medical equipment, in particular to a gyromagnetic therapy machine control system based on the Internet of Things, and the system comprises a feature database; the data analysis module is used for generating a critical treatment index corresponding to a target treatment area based on the electronic medical archive of the target user, and determining initial working parameters of the gyromagnetic therapy machine and an optimal treatment distance between the gyromagnetic therapy machine and the target treatment area; the treatment control module is used for controlling the gyromagnetic treatment machine; the physical sign monitoring module is used for periodically collecting physical sign data of a target user in the process of using the gyromagnetic therapy machine and temperature data of a target treatment area; and the control adjustment module is used for judging whether abnormity occurs or not based on the physical sign data of the target user in the process of using the gyromagnetic therapy machine in the target time period and the temperature data of the target therapy area, and determining a control adjustment strategy based on a judgment result. The working parameters of the gyromagnetic therapy machine can be accurately formulated and adjusted, and the therapy experience of a user is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of medical devices, and particularly to a control system for a rotating magnetic therapy machine based on the Internet of Things. Background Art

[0002] A rotating magnetic therapy machine is a medical instrument that uses a magnetic field to perform physical therapy on the human body. Its working principle is based on the biological magnetic effect. By generating a magnetic field with a specific intensity and frequency and acting on human tissues, it can achieve auxiliary treatments such as promoting blood circulation, relieving various pains (including cancer pain), reducing swelling, promoting tissue repair, improving sleep and respiratory and digestive system functions; helping to eliminate fluid accumulation and edema; improving blood and immune system functions, and the softening and dispersing function of mild masses. It has a wide range of applications in many fields such as orthopedics, neurology, and rehabilitation medicine and is a commonly used auxiliary treatment tool. With the improvement of people's health awareness, the demand for home healthcare is increasing day by day. The rise of Internet of Things technology has made it possible for medical devices to be intelligent and remote. Incorporating it into a rotating magnetic therapy machine can meet the needs of professional medical care in a home scenario.

[0003] At present, the market for rotating magnetic therapy machines is developing steadily. Traditional devices are mostly used in medical institutions and are complex to operate and require medical staff guidance. Now, home rotating magnetic therapy machines are gradually emerging, but their degree of intelligence is low. They can only simply adjust the magnetic field intensity and frequency and cannot accurately set treatment parameters according to the individual health conditions of users. In terms of Internet of Things applications, although some medical devices are already connected to the Internet, the application in the field of rotating magnetic therapy machines is still shallow. Existing products can only remotely monitor the device status and need to be improved in terms of doctors' remote control and intelligent treatment based on health data.

[0004] The existing control systems for rotating magnetic therapy machines face many technical problems. In the home healthcare scenario, they lack the ability to formulate personalized treatment plans, there are deficiencies in data interaction between the device and users, the function of collecting physical signs data is imperfect, and they cannot accurately set the working parameters of the rotating magnetic therapy machine according to individual users, resulting in a relatively poor treatment experience for users. In addition, different users have different physical conditions, medical histories, and sensitivities to magnetic fields, and general parameters are difficult to meet the needs. For example, heart disease patients cannot tolerate too high a magnetic field intensity, and patients with bone diseases require sufficient magnetic field penetration depth. When doctors perform remote control, they cannot operate accurately in real time and it is difficult to adjust the working parameters of the rotating magnetic therapy machine in a timely manner according to the real-time feedback during the patient's treatment, which limits the effect of telemedicine. Summary of the Invention

[0005] Therefore, the present invention provides a control system for a rotating magnetic therapy machine based on the Internet of Things to overcome the problem in the prior art that the working parameters of the rotating magnetic therapy machine cannot be accurately formulated and adjusted, resulting in a relatively poor treatment experience for users.

[0006] To achieve the above object, the present invention provides an IoT-based control system for a spin magnetic therapy machine, including:

[0007] A feature database for storing user feature data of a target user, including the target user's electronic medical record, historical physical sign data, and spin magnetic therapy machine usage data;

[0008] A data analysis module connected to the feature database, for generating critical treatment indicators corresponding to a target treatment area based on the target user's electronic medical record, and determining initial working parameters of the spin magnetic therapy machine and the optimal treatment distance between the spin magnetic therapy machine and the target treatment area based on the critical treatment indicators and the spin magnetic therapy machine usage data;

[0009] A treatment control module connected to the data analysis module and the spin magnetic therapy machine respectively, for controlling the spin magnetic therapy machine based on the initial working parameters;

[0010] A physical sign monitoring module connected to the feature database, for periodically collecting physical sign data of the target user during the use of the spin magnetic therapy machine and temperature data of the target treatment area, and storing them in the feature database;

[0011] A control adjustment module connected to the spin magnetic therapy machine, the data analysis module, the physical sign monitoring module, and the feature database respectively, for determining whether an abnormality occurs based on the physical sign data of the target user during the use of the spin magnetic therapy machine and the temperature data of the target treatment area within a target time period, and determining a control adjustment strategy based on the determination result to control and adjust the spin magnetic therapy machine, including,

[0012] Determining a parameter adjustment coefficient corresponding to each of the working parameters based on the critical treatment indicators, and adjusting the working parameters of the spin magnetic therapy machine based on the parameter adjustment coefficient;

[0013] Or, adjusting the working parameters of the spin magnetic therapy machine based on the physical sign data and the temperature data of the target treatment area within the target time period.

[0014] Further, the data analysis module includes:

[0015] A medical data determination sub-module connected to the feature database, for determining target user medical data based on the target user's electronic medical record, and determining the treatment type of the target user and the target treatment area based on the target user medical data;

[0016] An index generation sub-module connected to the medical data determination sub-module, for generating critical treatment indicators corresponding to the target treatment area based on the treatment type and the target treatment area of the target user;

[0017] A parameter determination sub-module, which is respectively connected to the index generation sub-module and the feature database, and is used to determine the initial working parameters of the rotating magnetic therapy machine based on the critical treatment index corresponding to the target treatment area and the usage data of the rotating magnetic therapy machine;

[0018] A treatment distance determination sub-module, which is connected to the parameter determination sub-module, and is used to determine the optimal treatment distance between the rotating magnetic therapy machine and the target treatment area based on the initial working parameters.

[0019] Further, the index generation sub-module includes:

[0020] A treatment data storage unit, which is used to store the treatment data of the rotating magnetic therapy machine of several users, including the treatment type, treatment area and usage data of the rotating magnetic therapy machine of each user;

[0021] An index model construction unit, which is connected to the treatment data storage unit, and is used to construct a critical treatment index model based on the treatment data of the rotating magnetic therapy machine of each user;

[0022] An index generation unit, which is connected to the index model construction unit and the medical data determination sub-module, and is used to input the treatment type and target treatment area of the target user into the critical treatment index model to generate the critical treatment index corresponding to the target treatment area.

[0023] Further, the parameter determination sub-module includes:

[0024] A parameter analysis unit, which is connected to the feature database, and is used to determine the treatment progress of the target user based on the usage data of the rotating magnetic therapy machine of the target user;

[0025] A parameter determination unit, which is respectively connected to the parameter analysis unit and the index generation unit, and is used to determine the initial working parameters of the rotating magnetic therapy machine based on the critical treatment index corresponding to the target treatment area and the treatment progress of the target user.

[0026] Further, the control adjustment module includes:

[0027] A feature analysis sub-module, which is respectively connected to the physical sign monitoring module and the feature database, and is used to determine the physical sign representation value based on the physical sign data of the target user during the use of the rotating magnetic therapy machine within the target time period, and determine the temperature representation value based on the temperature data of the target treatment area;

[0028] An analysis and determination sub-module, which is connected to the feature analysis sub-module, and is used to determine whether an abnormality occurs based on the physical sign representation value and the temperature representation value;

[0029] A strategy determination sub-module, which is connected to the analysis and determination sub-module, is used to determine a control adjustment strategy based on the determination result.

[0030] Further, based on the determination result of no abnormality, the strategy determination sub-module determines the parameter adjustment coefficient corresponding to each working parameter based on the critical treatment index, and adjusts the working parameters of the rotating magnetic therapy machine based on the parameter adjustment coefficient.

[0031] Further, based on the determination result of abnormality, the strategy determination sub-module adjusts the working parameters of the rotating magnetic therapy machine based on the physical sign data within the target time period and the temperature data of the target treatment area.

[0032] Further, based on the determination result of abnormality, the strategy determination sub-module determines the physical sign sensitivity value of the target user based on the historical physical sign data of the target user, determines the physical sign adjustment coefficient based on the predicted physical sign data and the physical sign sensitivity value, and based on the temperature data of the target treatment area within the target time period, determines the temperature sensitivity value, determines the temperature adjustment coefficient based on the predicted temperature data and the temperature sensitivity value, and determines the key adjustment coefficient based on the physical sign adjustment coefficient and the temperature adjustment coefficient, and adjusts the working parameters of the rotating magnetic therapy machine based on the key adjustment coefficient.

[0033] Further, the treatment distance determination sub-module determines the optimal treatment distance between the rotating magnetic therapy machine and the target treatment area based on the comparison result between the initial working parameters and the working parameters during each use.

[0034] Further, the medical data determination sub-module extracts key diagnosis data based on the electronic medical record of the target user, and determines the medical data of the target user based on the correlation degree between the key diagnosis data and the rotating magnetic therapy machine.

[0035] Compared with the prior art, the beneficial effects of the present invention are as follows. The present invention sets up a feature database to provide data support for the subsequent precise control of the working parameters of the rotating magnetic field therapy machine for target users. It sets up a data analysis module to generate critical treatment indicators based on the electronic medical records, determine the initial working parameters and the optimal treatment distance, and can realize the personalized customization of the treatment plan of the rotating magnetic field therapy machine, improve the accuracy and effectiveness of the treatment, set the magnetic field intensity, magnetic field frequency and treatment duration according to the specific condition and physical characteristics of the user, and can improve the treatment effect and enhance the user's treatment experience. It sets up a treatment control module to control the rotating magnetic field therapy machine according to the initial working parameters provided by the data analysis module, ensure that the device operates according to the set working parameters, guarantee the stability of the treatment process, enable the treatment process to be precisely executed, and avoid the influence of improper user operation on the treatment effect. It sets up a physical sign monitoring module to periodically collect the user's physical sign data and the temperature data of the treatment area and store them, realizing the real-time monitoring of the treatment process. It sets up a control adjustment module to determine abnormalities based on the physical sign data and temperature data and determine the control adjustment strategy, improving the safety of the treatment process. By adjusting the parameters based on the critical treatment indicators or adjusting the working parameters according to the predicted data, the treatment plan can be dynamically optimized according to the real-time situation of the user during the use of the rotating magnetic field therapy machine, further improving the treatment effect and the safety of the user.

[0036] Furthermore, the data analysis module of the present invention sets up a medical data determination sub-module to determine the target user's medical data based on the target user's electronic medical record, and determine the target user's treatment type and target treatment area based on the target user's medical data, systematically analyzing and integrating the user's complex and diverse electronic medical records, accurately extracting key information that affects the formulation of the working parameters of the gyro-magnetic therapy machine, improving the accuracy of subsequent determination of working parameters. By determining the treatment type and target treatment area, the treatment becomes more targeted, improving the treatment effect and enhancing the patient's treatment experience. Set up an index generation sub-module to generate critical treatment indicators based on the target user's treatment type and target treatment area, setting reasonable parameter boundaries for the treatment with the gyro-magnetic therapy machine, which can ensure the safety and effectiveness of the treatment. Generating corresponding indicators according to different treatment types and treatment areas can ensure that the treatment process not only achieves the expected effect but also does not cause harm to the patient due to excessive parameters, improving the treatment effect and safety. Set up a parameter determination sub-module to determine the initial working parameters of the gyro-magnetic therapy machine based on the critical treatment indicators corresponding to the target treatment area and the usage data of the gyro-magnetic therapy machine, which can realize personalized customization of the working parameters, ensure that the working parameters are within a safe and effective range, and clarify the user's treatment progress in combination with the usage data of the gyro-magnetic therapy machine, making the initial working parameters more in line with the user's current actual treatment needs and further improving the treatment effect. Set up a treatment distance determination sub-module to determine the optimal treatment distance between the gyro-magnetic therapy machine and the target treatment area based on the initial working parameters. A suitable treatment distance can make the magnetic field act more effectively on the target treatment area, improving the effectiveness of the treatment. Different initial working parameters require matching treatment distances to ensure that the magnetic field energy can be accurately transmitted to the diseased area, avoiding the dispersion or excessive concentration of the magnetic field energy due to improper distance. Determining the optimal treatment distance can also reduce the unnecessary influence on the surrounding normal tissues, reducing the probability of adverse reactions, further ensuring the safety and treatment effect of the patient and enhancing the user's treatment experience.

[0037] Furthermore, the index generation sub-module of the present invention sets up a treatment data storage unit. By integrating the treatment data of multiple users, it helps to discover the potential relationships between different treatment types, treatment areas, and the use of the rotating magnetic therapy machine, providing data support for formulating treatment plans for new users. By setting up an index model construction unit, a critical treatment index model is constructed based on the treatment data of each user. Through in-depth mining and analysis of the treatment data, a model that can reflect the relationship between different treatment situations and critical treatment indicators is constructed, transforming complex clinical data into a quantifiable and referenceable index model, providing a scientific basis for generating individual critical treatment indicators, and further improving the treatment effect and treatment experience. By setting up an index generation unit, the treatment type and target treatment area of the target user are input into the critical treatment index model to generate corresponding critical treatment indicators, providing precise treatment guidance for the target user. It can fully consider the uniqueness of the user's individual condition, ensure the safety and effectiveness of the treatment process, and improve the user experience.

[0038] Furthermore, the parameter determination sub-module of the present invention determines the treatment progress of the target user through the parameter analysis unit based on the data of the rotating magnetic therapy machine used by the target user, which can accurately evaluate the progress of the user during the treatment with the rotating magnetic therapy machine, providing a theoretical basis for determining the working parameters of the rotating magnetic therapy machine in the future, and improving the pertinence and effectiveness of the treatment. By setting up a parameter determination unit to determine the initial working parameters of the rotating magnetic therapy machine based on the critical treatment indicators corresponding to the target treatment area and the treatment progress of the target user, it can closely combine the treatment indicators with the actual treatment progress of the user, realize the personalized customization of the working parameters of the rotating magnetic therapy machine, and ensure the treatment effect and treatment experience.

[0039] Furthermore, the control and adjustment module of the present invention sets up a feature analysis sub-module to determine the physical sign representation value and the temperature representation value. The physical sign representation value can quickly reflect the body's response of the user to the treatment, and the temperature representation value can timely reflect the thermal effect situation of the treatment area. By setting up an analysis and determination sub-module to determine whether there is an abnormality based on the physical sign representation value and the temperature representation value, it can improve the safety and effectiveness of the treatment, avoid potential safety risks, and ensure the treatment experience of the user. By setting up a strategy determination sub-module to determine the control and adjustment strategy based on the determination result, the control and adjustment strategies for the case of abnormality and non-abnormality are different, enabling the treatment plan to be precisely adjusted according to the real-time condition of the user, improving the treatment effect, and enhancing the treatment experience of the user. Description of the Drawings

[0040] Figure 1 It is the structural block diagram of the rotating magnetic therapy machine control system based on the Internet of Things according to the embodiment of the present invention;

[0041] Figure 2 It is the structural block diagram of the data analysis module according to the embodiment of the present invention;

[0042] Figure 3 It is a structural block diagram of the index generation sub-module according to an embodiment of the present invention;

[0043] Figure 4 It is a structural block diagram of the control and adjustment module according to an embodiment of the present invention. Detailed implementation manners

[0044] In order to make the objectives and advantages of the present invention clearer, the present invention will be further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0045] The preferred implementation manners of the present invention will be described below with reference to the accompanying drawings. Those skilled in the art should understand that these implementation manners are only used to explain the technical principles of the present invention and do not limit the protection scope of the present invention.

[0046] It should be noted that in the description of the present invention, the terms indicating directions or positional relationships such as "upper", "lower", "left", "right", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings. This is only for convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention.

[0047] In addition, it should also be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installation", "connection", and "connection" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0048] Please refer to Figure 1 as shown, which is a structural block diagram of the control system of a rotating magnetic field therapy device based on the Internet of Things according to an embodiment of the present invention; the embodiment of the present invention provides a control system of a rotating magnetic field therapy device based on the Internet of Things, including:

[0049] A feature database for storing user feature data of a target user, including the electronic medical record of the target user, historical physical sign data, and the usage data of the rotating magnetic field therapy device. Among them, the historical physical sign data includes general physical sign data and treatment physical sign data, the physical sign data includes blood pressure data, heart rate data, and body temperature data, and the usage data of the rotating magnetic field therapy device includes the usage time of the rotating magnetic field therapy device, the working parameters at each use, the treatment area temperature data, and the treatment distance between the rotating magnetic field therapy device and the treatment area;

[0050] It is understandable that the general physical sign data is the physical sign data of the target user when not using the rotary magnetic therapy machine, and the treatment physical sign data is the physical sign data of the target user during the treatment process using the rotary magnetic therapy machine. The electronic medical record includes basic information, medical history information, doctor's diagnosis and treatment information, etc. The basic information includes age, gender, height, weight, etc. The medical history information includes past medical history, such as chronic diseases like hypertension, diabetes, heart disease, etc., as well as past surgical history and hospitalization history. If the patient has a history of heart disease, during rotary magnetic therapy, too high a magnetic field intensity may affect heart function, and it is necessary to carefully set parameters such as magnetic field intensity and magnetic field frequency to avoid adverse effects. The doctor's diagnosis and treatment information includes the diagnosis result of the disease the patient currently has, the assessment of the severity of the condition, the ongoing treatment plan, medication situation, etc. If the patient has lumbar disc herniation, the doctor can determine whether the patient can receive rotary magnetic therapy and record it in the doctor's diagnosis and treatment information.

[0051] In practice, rotary magnetic therapy will have a certain impact on the electrophysiological activities of the heart, thereby causing changes in heart rate. When parameters such as magnetic field intensity and magnetic field frequency are set improperly, it will lead to abnormal heart rate. For example, too high a magnetic field intensity may stimulate the heart and cause a significant increase in heart rate; for some people with more sensitive bodies, even a normal-strength magnetic field may cause fluctuations in heart rate. After the magnetic field acts on the human body, it will affect the contraction and relaxation functions of blood vessels, thereby causing changes in blood pressure. During the treatment process, blood pressure may experience a short-term increase or decrease. For example, the magnetic field may cause blood vessels to dilate, resulting in a decrease in blood pressure. During the rotary magnetic therapy process, due to the thermal effect of the magnetic field and its impact on human metabolism, the body temperature of the treatment area will increase. If the temperature is too high and lasts for a long time, it may cause damage to tissues and also affect the body's metabolic function. Therefore, it is necessary to monitor physical sign data such as blood pressure, heart rate, and body temperature in real time and use this as a judgment basis.

[0052] The data analysis module, which is connected to the feature database, is used to generate the critical treatment indicators corresponding to the target treatment area based on the electronic medical record of the target user, and determine the initial working parameters of the rotary magnetic therapy machine and the optimal treatment distance between the rotary magnetic therapy machine and the target treatment area based on the critical treatment indicators and the rotary magnetic therapy machine usage data. The working parameters include magnetic field intensity, magnetic field frequency, and treatment duration. The critical treatment indicators are the critical working parameters for the target user to use the rotary magnetic therapy machine for the target treatment area, including the maximum working parameter and the minimum working parameter;

[0053] Please refer to Figure 2 as shown, which is the structural block diagram of the data analysis module of the embodiment of the present invention; specifically, the data analysis module includes:

[0054] A medical data determination sub-module, which is connected to the feature database, is used to determine the medical data of the target user based on the electronic medical record of the target user, and determine the treatment type and target treatment area of the target user based on the medical data of the target user;

[0055] Specifically, the medical data determination sub-module extracts key diagnostic data based on the electronic medical record of the target user, and determines the medical data of the target user based on the degree of association between the key diagnostic data and the rotating magnetic therapy machine.

[0056] In implementation, the electronic medical record of the target user is retrieved and classified according to disease diagnosis, examination and test, treatment and medication, etc., the imaging examination results and treatment and medication conditions are extracted, the main symptoms and complications are determined, and the key diagnostic data are determined according to the main symptoms of each main symptom and complication, such as the lesion location, scope, and severity of musculoskeletal diseases; the pain location, scope, etc. caused by the complications of cardiovascular diseases, and the correlation between the key diagnostic data and the rotating magnetic therapy using the rotating magnetic therapy machine is evaluated.

[0057] It can be understood that a correlation degree comparison table between various disease types and the rotating magnetic therapy machine can be set based on historical data or based on an expert system. For example, for musculoskeletal diseases, such as lumbar disc herniation and periarthritis of shoulder, the application of rotating magnetic therapy is common and the degree of association is high; for some infectious diseases, the degree of association is low. Or, the various diseases suitable for treatment by the rotating magnetic therapy machine are sorted according to the treatment cycle of the generated effect, the highest degree of association corresponds to the shortest treatment cycle, and the corresponding key diagnostic data are determined as the medical data of the target user.

[0058] It can be understood that the treatment type and target treatment area of the target user are determined based on the medical data of the target user. The treatment type includes pain relief, swelling reduction, promoting tissue repair, etc., and the target treatment area can be determined according to the specific lesion location.

[0059] An index generation sub-module, which is connected to the medical data determination sub-module, is used to generate a critical treatment index corresponding to the target treatment area based on the treatment type and target treatment area of the target user;

[0060] Please refer to Figure 3 shown, which is the structural block diagram of the index generation sub-module of the embodiment of the present invention; specifically, the index generation sub-module includes:

[0061] A treatment data storage unit, which is used to store the treatment data of the rotating magnetic therapy machine of several users, including the treatment type, treatment area and the usage data of the rotating magnetic therapy machine of each user;

[0062] An index model construction unit, which is connected to the treatment data storage unit and is used to construct a critical treatment index model based on the treatment data of the gyro-magnetic therapy machine of each user;

[0063] In implementation, a training data set is constructed according to the treatment types, treatment regions, and gyro-magnetic therapy machine usage data of each user, and the initial training model is trained based on the training data set to obtain a critical treatment index model. It can be understood that the model type of the initial training model is not specifically limited. For example, it can be a neural network model, a linear regression model, etc. This is prior art and will not be elaborated.

[0064] An index generation unit, which is connected to the index model construction unit and the medical data determination sub-module, and is used to input the treatment type and target treatment region of the target user into the critical treatment index model to generate the critical treatment index corresponding to the target treatment region.

[0065] In implementation, the critical treatment index is the critical working parameter of the gyro-magnetic therapy machine used by the target user for the target treatment region, including the maximum working parameter and the minimum working parameter, that is, the maximum magnetic field intensity, the minimum magnetic field intensity, the maximum magnetic field frequency, the minimum magnetic field frequency, the maximum treatment duration, and the minimum treatment duration.

[0066] The index generation sub-module of the present invention sets a treatment data storage unit. By integrating the treatment data of multiple users, it helps to discover the potential relationship between different treatment types, treatment regions, and the usage of the gyro-magnetic therapy machine, provides data support for formulating treatment plans for new users, sets an index model construction unit to construct a critical treatment index model based on the treatment data of each user, constructs a model that can reflect the relationship between different treatment situations and critical treatment indexes through in-depth mining and analysis of the treatment data, converts complex clinical data into a quantifiable and referenceable index model, provides a scientific basis for generating individual critical treatment indexes subsequently, and further improves the treatment effect and treatment experience. By setting an index generation unit, the treatment type and target treatment region of the target user are input into the critical treatment index model to generate the corresponding critical treatment index, providing precise treatment guidance for the target user, fully considering the uniqueness of the user's individual conditions, ensuring that the treatment process is both safe and effective, and improving the user experience.

[0067] A parameter determination sub-module, which is respectively connected to the index generation sub-module and the feature database, and is used to determine the initial working parameters of the gyro-magnetic therapy machine based on the critical treatment index corresponding to the target treatment region and the gyro-magnetic therapy machine usage data;

[0068] Specifically, the parameter determination sub-module includes:

[0069] A parameter analysis unit, which is connected to the feature database and is used to determine the treatment progress of the target user based on the data of the target user's rotary magnetic therapy machine usage;

[0070] In implementation, determining the treatment progress of the target user based on the rotary magnetic therapy machine usage time, working parameters during each use, and treatment area temperature data, including the initial stage of treatment, the middle stage of treatment, and the late stage of treatment. In the initial stage of treatment, to avoid strong reactions from the user, the working parameters during each use, such as magnetic field intensity and magnetic field frequency, are relatively small, the treatment duration is short, and the corresponding number of uses is 1 to 3 times. If, in the initial stage of treatment, the temperature in the treatment area can quickly reach the appropriate treatment range and remain stable, and at the same time, the patient's physical sign data shows no obvious abnormal fluctuations, it indicates that the initial stage of treatment progresses smoothly; on the contrary, if the temperature rises or drops abnormally, or the physical sign data shows large fluctuations, it may indicate that there are problems in the initial stage of treatment and it is impossible to enter the next stage. In the middle stage of treatment, as the number of treatments increases, parameters such as magnetic field intensity and frequency are gradually adjusted to a more suitable level for the patient. The magnetic field intensity and magnetic field frequency are relatively large, the treatment duration increases, and the patient's symptoms (such as pain level, activity limitation) improve, indicating that the treatment is developing in the expected direction. The corresponding number of uses is 4 to 8 times. If, in the middle stage of treatment, the temperature in the treatment area can quickly reach the appropriate treatment range and remain stable, it indicates that the middle stage of treatment progresses smoothly; on the contrary, if the temperature rises or drops abnormally, it may indicate that there are problems in the middle stage of treatment and it is impossible to enter the next stage. In the late stage of treatment, the treatment effect is stable, the user's condition improves, and each working parameter is stable. The magnetic field intensity and magnetic field frequency are relatively large (smaller than in the middle stage of treatment), and the treatment duration is short (longer than in the initial stage of treatment). The corresponding number of uses is more than 9 times. If, in the late stage of treatment, the temperature in the treatment area can quickly remain stable, it indicates that the late stage of treatment progresses smoothly and the treatment is approaching the completion stage.

[0071] A parameter determination unit, which is respectively connected to the parameter analysis unit and the index generation unit, and is used to determine the initial working parameters of the rotary magnetic therapy machine based on the critical treatment index corresponding to the target treatment area and the treatment progress of the target user.

[0072] In implementation, an intensity difference is determined based on the difference between the maximum magnetic field intensity and the minimum magnetic field intensity, a frequency difference is determined based on the difference between the maximum magnetic field frequency and the minimum magnetic field frequency, and a duration difference is determined based on the difference between the maximum treatment duration and the minimum treatment duration. The initial magnetic field intensity corresponding to the initial stage of treatment is set to the sum of the minimum magnetic field intensity and 1 / 5 to 1 / 6 times the intensity difference. The initial magnetic field frequency corresponding to the initial stage of treatment is set to the sum of the minimum magnetic field frequency and 1 / 5 to 1 / 6 times the frequency difference. The initial treatment duration corresponding to the initial stage of treatment is set to the sum of the minimum treatment duration and 1 / 5 to 1 / 6 times the duration difference. The initial magnetic field intensity corresponding to the middle stage of treatment is set to the sum of the minimum magnetic field intensity and 4 / 5 to 5 / 6 times the intensity difference. The initial magnetic field frequency corresponding to the middle stage of treatment is set to the sum of the minimum magnetic field frequency and 4 / 5 to 5 / 6 times the frequency difference. The initial treatment duration corresponding to the middle stage of treatment is set to the sum of the minimum treatment duration and 4 / 5 to 5 / 6 times the duration difference. The initial magnetic field intensity corresponding to the late stage of treatment is set to the sum of the minimum magnetic field intensity and 2 / 5 to 1 / 2 times the intensity difference. The initial magnetic field frequency corresponding to the late stage of treatment is set to the sum of the minimum magnetic field frequency and 2 / 5 to 1 / 2 times the frequency difference. The initial treatment duration corresponding to the late stage of treatment is set to the sum of the minimum treatment duration and 2 / 5 to 1 / 2 times the duration difference.

[0073] The parameter determination sub-module of the present invention can accurately evaluate the progress of the user during the treatment with the rotating magnetic field therapy machine by setting a parameter analysis unit to determine the treatment process of the target user based on the usage data of the rotating magnetic field therapy machine of the target user, providing a theoretical basis for determining the working parameters of the rotating magnetic field therapy machine subsequently, and improving the pertinence and effectiveness of the treatment. By setting a parameter determination unit to determine the initial working parameters of the rotating magnetic field therapy machine based on the critical treatment index corresponding to the target treatment area and the treatment process of the target user, the treatment index can be closely combined with the actual treatment process of the user, realizing the personalized customization of the working parameters of the rotating magnetic field therapy machine and ensuring the treatment effect and treatment experience.

[0074] A treatment distance determination sub-module, which is connected to the parameter determination sub-module, is used to determine the optimal treatment distance between the rotating magnetic field therapy machine and the target treatment area based on the initial working parameters.

[0075] Specifically, the treatment distance determination sub-module determines the optimal treatment distance between the rotating magnetic field therapy machine and the target treatment area based on the comparison result of the initial working parameters and the working parameters during each use.

[0076] In implementation, a sample data set is determined based on the working parameters during each use, and the treatment distance between the corresponding gyromagnetic therapy machine and the treatment area is used as a sample label to train a neural network model to obtain a target neural network model. The initial working parameters are input into the target neural network model to obtain the optimal treatment distance between the gyromagnetic therapy machine and the target treatment area output by the target neural network model.

[0077] The data analysis module of the present invention sets up a medical data determination sub-module to determine the target user's medical data based on the target user's electronic medical record, and determines the treatment type and target treatment area of the target user based on the target user's medical data. It systematically analyzes and integrates the complex and diverse electronic medical records of users, and accurately extracts the key information that affects the formulation of the working parameters of the gyromagnetic therapy machine, improving the accuracy of subsequent determination of working parameters. By determining the treatment type and target treatment area, the treatment becomes more targeted, improving the treatment effect and enhancing the patient's treatment experience. It sets up an index generation sub-module to generate critical treatment indicators based on the treatment type and target treatment area of the target user, setting reasonable parameter boundaries for the application of the gyromagnetic therapy machine for treatment, which can ensure the safety and effectiveness of treatment. Generating corresponding indicators according to different treatment types and treatment areas can ensure that the treatment process not only achieves the expected effect but also does not cause harm to the patient due to excessive parameters, improving the treatment effect and safety. It sets up a parameter determination sub-module to determine the initial working parameters of the gyromagnetic therapy machine based on the critical treatment indicators corresponding to the target treatment area and the usage data of the gyromagnetic therapy machine, which can realize personalized customization of the working parameters, ensure that the working parameters are within a safe and effective range, and combine the usage data of the gyromagnetic therapy machine to clarify the user's treatment process, making the initial working parameters more in line with the user's current actual treatment needs and further improving the treatment effect. It sets up a treatment distance determination sub-module to determine the optimal treatment distance between the gyromagnetic therapy machine and the target treatment area based on the initial working parameters. A suitable treatment distance can make the magnetic field act more effectively on the target treatment area, improving the effectiveness of treatment. Different initial working parameters require a matching treatment distance to ensure that the magnetic field energy can be accurately transmitted to the diseased part, avoiding the dispersion or over-concentration of the magnetic field energy due to improper distance. Determining the optimal treatment distance can also reduce the unnecessary influence on the surrounding normal tissues, reducing the occurrence probability of adverse reactions, further ensuring the safety and treatment effect of the patient, and enhancing the user's treatment experience.

[0078] The treatment control module is respectively connected to the data analysis module and the gyromagnetic therapy machine, and is used to control the gyromagnetic therapy machine based on the initial working parameters;

[0079] A physical sign monitoring module, which is connected to the feature database, is used to periodically collect the physical sign data of the target user during the use of the rotary magnetic therapy machine and the temperature data of the target treatment area, and store them in the feature database;

[0080] It can be understood that there are no specific restrictions on the devices and methods for collecting the physical sign data of the target user during the use of the rotary magnetic therapy machine and the temperature data of the target treatment area. This is the prior art and will not be elaborated here.

[0081] A control and adjustment module, which is respectively connected to the rotary magnetic therapy machine, the data analysis module, the physical sign monitoring module and the feature database, is used to determine whether there is an abnormality based on the physical sign data of the target user during the use of the rotary magnetic therapy machine within the target time period and the temperature data of the target treatment area, and determine a control and adjustment strategy based on the determination result to control and adjust the rotary magnetic therapy machine, including,

[0082] Determine the parameter adjustment coefficient corresponding to each working parameter based on the critical treatment index, and adjust the working parameters of the rotary magnetic therapy machine based on the parameter adjustment coefficient;

[0083] Or, adjust the working parameters of the rotary magnetic therapy machine based on the physical sign data and the temperature data of the target treatment area within the target time period.

[0084] Please refer to Figure 4 As shown, it is the structural block diagram of the control and adjustment module of the embodiment of the present invention; specifically, the control and adjustment module includes:

[0085] A feature analysis sub-module, which is respectively connected to the physical sign monitoring module and the feature database, is used to determine the physical sign representation value based on the physical sign data of the target user during the use of the rotary magnetic therapy machine within the target time period, and determine the temperature representation value based on the temperature data of the target treatment area;

[0086] In practice, determine the physical sign evaluation value of the corresponding physical sign based on the ratio of the difference between the mean value and the minimum value of the physical sign data within the target time period to the difference between the maximum value and the minimum value of the physical sign data of the target user during the use of the rotary magnetic therapy machine. For example, M is the maximum heart rate value, N is the minimum heart rate value, and P is the mean heart rate, then the physical sign difference corresponding to the heart rate is T =, and the physical sign evaluation value corresponding to the heart rate is Q = (P - N) / (M - N). In this way, determine the physical sign evaluation value corresponding to the blood pressure and the physical sign evaluation value corresponding to the body temperature, and determine the maximum value among the physical sign evaluation value corresponding to the heart rate, the physical sign evaluation value corresponding to the blood pressure, and the physical sign evaluation value corresponding to the body temperature as the physical sign representation value.

[0087] In implementation, a temperature characterization value is determined according to the ratio of the difference between the average temperature value and the minimum temperature value of the target treatment area to the difference between the maximum temperature value and the minimum temperature value of the target treatment area.

[0088] An analysis and determination sub-module, which is connected to the feature analysis sub-module, is used to determine whether an abnormality occurs based on the physical sign characterization value and the temperature characterization value;

[0089] In implementation, if the physical sign characterization value is less than a preset characterization value and the temperature characterization value is less than the preset characterization value, it is determined that no abnormality occurs; otherwise, it is determined that an abnormality occurs.

[0090] It can be understood that the actual implementer can set the preset characterization value based on the actual situation. Preferably, the value range of the preset characterization value is set to 1 / 2 to 2 / 3.

[0091] A strategy determination sub-module, which is connected to the analysis and determination sub-module, is used to determine a control adjustment strategy based on the determination result.

[0092] In the control adjustment module of the present invention, the feature analysis sub-module is set to determine the physical sign characterization value and the temperature characterization value. The physical sign characterization value can quickly reflect the user's body's response to the treatment, and the temperature characterization value can timely reflect the thermal effect situation of the treatment area. The analysis and determination sub-module is set to determine whether an abnormality occurs based on the physical sign characterization value and the temperature characterization value, which can improve the safety and effectiveness of the treatment, avoid potential safety risks, and ensure the user's treatment experience. The strategy determination sub-module is set to determine the control adjustment strategy based on the determination result. The control adjustment strategies for abnormality occurrence and non-occurrence are different, enabling the treatment plan to be accurately adjusted according to the user's real-time condition, improving the treatment effect, and enhancing the user's treatment experience.

[0093] Specifically, based on the determination result of determining no abnormality, the strategy determination sub-module determines the parameter adjustment coefficient corresponding to each working parameter based on the critical treatment index, and adjusts the working parameters of the rotary magnetic therapy machine based on the parameter adjustment coefficient.

[0094] In implementation, a parameter adjustment coefficient corresponding to the magnetic field intensity is determined based on the difference between the initial magnetic field intensity and the minimum magnetic field intensity and the difference between the maximum magnetic field intensity and the minimum magnetic field intensity, a parameter adjustment coefficient corresponding to the magnetic field frequency is determined based on the difference between the initial magnetic field frequency and the minimum magnetic field frequency and the difference between the maximum magnetic field frequency and the minimum magnetic field frequency, a parameter adjustment coefficient corresponding to the treatment duration is determined based on the difference between the initial treatment duration and the minimum treatment duration and the difference between the maximum treatment duration and the minimum treatment duration, an adjustment amount of each working parameter is determined based on the product of the parameter adjustment coefficient corresponding to each parameter and each initial working parameter, a corresponding candidate working parameter is determined based on the sum of each initial working parameter and the corresponding adjustment amount, and if the corresponding candidate working parameter meets the critical treatment index, the corresponding candidate working parameter is determined as the adjusted working parameter.

[0095] Specifically, based on the determination result of determining an abnormality, the strategy determination sub-module adjusts the working parameters of the rotary magnetic therapy machine based on the physical sign data within the target time period and the temperature data of the target treatment area.

[0096] Specifically, based on the determination result of determining an abnormality, the strategy determination sub-module determines the physical sign sensitivity value of the target user based on the historical physical sign data of the target user, determines the physical sign adjustment coefficient based on the predicted physical sign data and the physical sign sensitivity value, and based on the temperature data of the target treatment area within the target time period, determines the temperature sensitivity value, determines the temperature adjustment coefficient based on the predicted temperature data and the temperature sensitivity value, determines the key adjustment coefficient based on the physical sign adjustment coefficient and the temperature adjustment coefficient, and adjusts the working parameters of the rotary magnetic therapy machine based on the key adjustment coefficient.

[0097] In implementation, the standard physical sign data (standard blood pressure, standard body temperature, standard heart rate) of the target user is determined according to the mean value of the general physical sign data of the target user / the physical sign data with the most occurrences, the physical sign sensitivity value is determined according to the mean value of the ratio of the treatment physical sign data of the target user to the standard physical sign data. The larger the physical sign sensitivity value, the more sensitive the target user is to the use of the rotary magnetic therapy machine. The predicted physical sign degree value is determined based on the mean value of the ratio of the predicted physical sign data to the standard physical sign data, and the physical sign adjustment coefficient is determined based on the product of the physical sign sensitivity value and the predicted physical sign degree value.

[0098] In implementation, the temperature sensitivity value is determined based on the mean value of the ratio of the minimum temperature to the maximum temperature in the temperature data of the target treatment area collected each time within the target time period. The larger the temperature sensitivity value, the more sensitive the target treatment area is to the use of the rotary magnetic therapy machine. The predicted temperature degree value is determined based on the mean value of the ratio of the minimum temperature to the maximum temperature in each predicted temperature data within the future preset time period, and the temperature adjustment coefficient is determined based on the product of the predicted temperature degree value and the temperature sensitivity value.

[0099] It is understandable that the key adjustment coefficient is determined based on the product of the physical sign adjustment coefficient and the temperature adjustment coefficient, the adjustment amount of the corresponding working parameter is determined according to the product of the key adjustment coefficient and each initial working parameter. If the sum of each initial working parameter and the adjustment amount of the corresponding working parameter determines the corresponding alternative working parameter, and if each alternative working parameter meets the critical treatment index, then the corresponding alternative working parameter is determined as the adjusted working parameter.

[0100] In implementation, the actual implementer can set the target time period and the preset time period based on the actual situation. Preferably, the value range of the target time period is set to 20 min to 30 min, and the value range of the preset time period is set to 5 min to 10 min.

[0101] The present invention sets up a feature database to provide data support for the subsequent precise control of the working parameters of the rotary magnetic therapy machine for the target user, sets up a data analysis module, generates critical treatment indexes based on the electronic medical records, determines the initial working parameters and the optimal treatment distance, and can realize the personalized customization of the treatment plan of the rotary magnetic therapy machine, improve the precision and effectiveness of the treatment. By setting the magnetic field intensity, magnetic field frequency and treatment duration according to the specific condition and physical characteristics of the user, the treatment effect can be improved and the user's treatment experience can be enhanced. The treatment control module controls the rotary magnetic therapy machine according to the initial working parameters provided by the data analysis module to ensure that the device operates according to the set working parameters, guarantee the stability of the treatment process, enable the treatment process to be precisely executed, and avoid the influence of improper user operation on the treatment effect. The physical sign monitoring module periodically collects the user's physical sign data and the temperature data of the treatment area and stores them, realizing the real-time monitoring of the treatment process. The control adjustment module determines abnormalities based on the physical sign data and the temperature data and determines the control adjustment strategy, improving the safety of the treatment process. By adjusting the parameters based on the critical treatment index or adjusting the working parameters according to the predicted data, the treatment plan can be dynamically optimized according to the real-time situation of the user during the use of the rotary magnetic therapy machine, further improving the treatment effect and the safety of the user.

[0102] So far, the technical solution of the present invention has been described in conjunction with the preferred embodiments shown in the drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the protection scope of the present invention.

Claims

1. An IoT-based control system for a gyromagnetic therapy apparatus, characterized in that, Including: A feature database for storing user feature data of a target user, including the target user's electronic medical record, historical physical sign data, and the usage data of the spin magnetic therapy machine; A data analysis module connected to the feature database, configured to generate critical treatment indicators corresponding to a target treatment area based on the target user's electronic medical record, and determine the initial working parameters of the spin magnetic therapy machine and the optimal treatment distance between the spin magnetic therapy machine and the target treatment area based on the critical treatment indicators and the usage data of the spin magnetic therapy machine; A treatment control module connected to the data analysis module and the spin magnetic therapy machine respectively, configured to control the spin magnetic therapy machine based on the initial working parameters; A physical sign monitoring module connected to the feature database, configured to periodically collect the physical sign data of the target user during the use of the spin magnetic therapy machine and the temperature data of the target treatment area, and store them in the feature database; A control adjustment module connected to the spin magnetic therapy machine, the data analysis module, the physical sign monitoring module, and the feature database respectively, configured to determine whether an abnormality occurs based on the physical sign data of the target user during the use of the spin magnetic therapy machine and the temperature data of the target treatment area within a target time period, and determine a control adjustment strategy based on the determination result to control and adjust the spin magnetic therapy machine, including, Determining a parameter adjustment coefficient corresponding to each working parameter based on the critical treatment indicators, and adjusting the working parameters of the spin magnetic therapy machine based on the parameter adjustment coefficient; Or, adjusting the working parameters of the spin magnetic therapy machine based on the physical sign data and the temperature data of the target treatment area within a target time period.

2. The control system of the gyromagnetic therapy apparatus based on the Internet of Things according to claim 1, characterized in that, The data analysis module includes: A medical data determination sub-module connected to the feature database, configured to determine the target user's medical data based on the target user's electronic medical record, and determine the treatment type of the target user and the target treatment area based on the target user's medical data; An indicator generation sub-module connected to the medical data determination sub-module, configured to generate critical treatment indicators corresponding to the target treatment area based on the treatment type of the target user and the target treatment area; A parameter determination sub-module connected to the indicator generation sub-module and the feature database respectively, configured to determine the initial working parameters of the spin magnetic therapy machine based on the critical treatment indicators corresponding to the target treatment area and the usage data of the spin magnetic therapy machine; A treatment distance determination sub-module connected to the parameter determination sub-module, configured to determine the optimal treatment distance between the spin magnetic therapy machine and the target treatment area based on the initial working parameters.

3. The control system of the spin magnetic therapy machine based on the Internet of Things according to claim 2, wherein The indicator generation sub-module includes: A treatment data storage unit for storing the treatment data of the spin magnetic therapy machine of several users, including the treatment type, treatment area, and usage data of the spin magnetic therapy machine of each user; An indicator model construction unit connected to the treatment data storage unit, configured to construct a critical treatment indicator model based on the treatment data of the spin magnetic therapy machine of each user; An index generation unit, which is connected to the index model construction unit and the medical data determination sub-module, is used to input the treatment type and target treatment area of the target user into the critical treatment index model to generate the critical treatment index corresponding to the target treatment area.

4. The control system of the rotary magnetic therapy apparatus based on the Internet of Things according to claim 3, characterized in that, The parameter determination sub-module includes: A parameter analysis unit, which is connected to the feature database, is used to determine the treatment progress of the target user based on the data of the target user's use of the gyro-magnetic therapy machine. A parameter determination unit, which is respectively connected to the parameter analysis unit and the index generation unit, is used to determine the initial working parameters of the gyro-magnetic therapy machine based on the critical treatment index corresponding to the target treatment area and the treatment progress of the target user.

5. The control system of the spin magnetic therapy machine based on the Internet of Things according to claim 4, characterized in that, The control adjustment module includes: A feature analysis sub-module, which is respectively connected to the physical sign monitoring module and the feature database, is used to determine the physical sign representation value based on the physical sign data of the target user during the use of the gyro-magnetic therapy machine within the target time period, and determine the temperature representation value based on the temperature data of the target treatment area. An analysis and determination sub-module, which is connected to the feature analysis sub-module, is used to determine whether an abnormality occurs based on the physical sign representation value and the temperature representation value. A strategy determination sub-module, which is connected to the analysis and determination sub-module, is used to determine the control adjustment strategy based on the determination result.

6. The control system of the gyromagnetic therapy apparatus based on the Internet of Things according to claim 5, characterized in that, Based on the determination result of no abnormality, the strategy determination sub-module determines the parameter adjustment coefficient corresponding to each working parameter based on the critical treatment index, and adjusts the working parameters of the gyro-magnetic therapy machine based on the parameter adjustment coefficient.

7. The control system of the spin magnetic therapy machine based on the Internet of Things according to claim 6, characterized in that, Based on the determination result of abnormality, the strategy determination sub-module adjusts the working parameters of the gyro-magnetic therapy machine based on the physical sign data within the target time period and the temperature data of the target treatment area.

8. The control system of the spin magnetic therapy machine based on the Internet of Things according to claim 7, characterized in that Based on the determination result of abnormality, the strategy determination sub-module determines the physical sign sensitivity value of the target user based on the historical physical sign data of the target user, determines the physical sign adjustment coefficient based on the predicted physical sign data and the physical sign sensitivity value, and determines the temperature sensitivity value based on the temperature data of the target treatment area within the target time period, determines the temperature adjustment coefficient based on the predicted temperature data and the temperature sensitivity value, and determines the key adjustment coefficient based on the physical sign adjustment coefficient and the temperature adjustment coefficient, and adjusts the working parameters of the gyro-magnetic therapy machine based on the key adjustment coefficient.

9. The control system of the spin magnetic therapy machine based on the Internet of Things according to claim 8, characterized in that, The treatment distance determination sub-module determines the optimal treatment distance between the gyro-magnetic therapy machine and the target treatment area based on the comparison result of the initial working parameters and the working parameters at each use.

10. The control system of the rotating magnetic therapy apparatus based on the Internet of Things according to claim 9, characterized in that, The medical data determination sub-module extracts the key diagnostic data based on the electronic medical record of the target user, and determines the medical data of the target user based on the correlation degree between the key diagnostic data and the gyro-magnetic therapy machine.

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