Universal auricular point magnetic heat pulse treatment system and symptom-driven control method

Abstract

The application provides a global auricular point magnetic heat pulse treatment system and a symptom-driven control method, generates a personalized auricle model through laser scanning, and realizes global auricular point coverage in combination with a conductive silica gel ear cover. The system integrates a magnetic pulse generator and a thermotherapy module, pre-sets multiple treatment modes for common symptoms, automatically positions positive points and adjusts the magnetic field frequency and the thermotherapy intensity through resistance detection. The scheme can also dynamically adjust the treatment parameters based on the symptoms and the positive point distribution, realize personalized treatment of "symptom-driven", improve the treatment effect, solve the problem of fixed mode and inability to adapt to individual differences; through the Internet of Things platform, remote parameter adjustment, real-time monitoring and data tracking are realized, the user convenience and the doctor management efficiency are improved; the traditional auricular point therapy of traditional Chinese medicine is combined with modern Internet of Things and artificial intelligence technology, a feasible path is provided for the intelligent and accurate development of auricular point therapy, and has a wide application prospect.

Description

Technical Field

[0001] This invention relates to the field of traditional Chinese medicine physical therapy technology, and in particular to a whole-domain auricular acupoint magnetic thermal pulse therapy system, a symptom-driven control method, an electronic device, and a computer-readable storage medium. Background Technology

[0002] Auricular therapy is a traditional Chinese medicine treatment that regulates organ function and relieves symptoms by stimulating acupoints on the auricle (ear points). It is widely used for common ailments such as indigestion, fatigue, and menstrual irregularities. However, existing auricular therapy equipment has the following drawbacks: 1. Lack of personalization: Universal earmuffs cannot fit the different ear shapes of different users, resulting in incomplete coverage of ear acupoints (only covering 60%-70% of ear acupoints), which affects the treatment effect; 2. Low positioning accuracy: It relies on manual pressure or visual judgment of ear acupoint location, with large errors (up to 5-10mm), and cannot accurately locate the "positive point" (the area of ​​reduced ear acupoint resistance) corresponding to the lesion. 3. Fixed mode: The treatment parameters (such as pulse frequency and heat therapy temperature) are fixed and cannot be adjusted according to symptoms (such as different ear acupoint stimulation needs for indigestion and fatigue) or individual differences; 4. Lack of remote management: It is impossible to remotely adjust parameters or view treatment records, resulting in poor user convenience and making it difficult for doctors to track treatment effects; 5. Low data utilization efficiency: The lack of analysis of user treatment data makes it impossible to optimize treatment patterns, resulting in difficulty in improving treatment effectiveness. Summary of the Invention

[0003] To address the technical problems existing in the prior art, the present invention provides the following technical solution: On the one hand, a full-domain auricular acupoint magnetic thermal pulse therapy system is provided, including: Conductive silicone earmuffs are custom-made according to the three-dimensional model of the user's auricle, including a medical silicone base, conductive silver powder, at least one magnetic coil, at least one PTC heating element and multiple electrodes. The auricle laser scanning module is used to acquire three-dimensional data of the user's auricle and generate the personalized auricle model; The magnetothermal pulse therapy module includes a magnetic pulse generator and a thermotherapy module, which are used to generate adjustable magnetic pulse signals and thermotherapy signals according to control instructions and apply them to the conductive silicone earmuff. The Internet of Things (IoT) controller is communicatively connected to the conductive silicone earmuff and the magnetothermal pulse therapy module, and is used to perform resistance detection to locate positive points of ear acupoints, receive and send control commands and data; The Internet of Things (IoT) management platform, deployed in the cloud, is used to store user data, treatment parameters, and auricle models, and provides remote control and data analysis services. The user terminal has a dedicated application installed for user interaction, symptom selection, parameter adjustment and treatment monitoring; The system is configured to acquire preset treatment parameters based on the symptoms selected by the user, and dynamically adjust the parameters of the magnetic pulse signal and the thermotherapy signal based on the positive points located by resistance detection.

[0004] Preferably, the conductive silicone earmuffs further include: The medical silicone substrate has a Shore A hardness of 30. The content of the conductive silver powder is 30%; The magnetic field strength of the magnetic coil is adjustable in the range of 10-20 mT; The temperature of the PTC heating element is adjustable within the range of 38-45℃; The electrodes are used to detect ear acupoint resistance by outputting a small current through a constant current source, with a resistance detection accuracy of ±1%.

[0005] Preferably, the auricle laser scanning module includes: A laser emitter used to emit a laser beam with a wavelength of 650nm; A CCD camera is used to receive reflected light; The scanning module uses triangulation to generate point cloud data of the auricle, with a point cloud density of 1000 points / square centimeter and a scanning resolution of not less than 0.05mm.

[0006] Preferably, the magnetic pulse generator includes an STM32F407 control core, a MOS transistor drive circuit, and a pulse output circuit, used to generate a pulse current with an adjustable frequency of 1-100Hz, an adjustable pulse width of 10-1000μs, and an adjustable output current of 0-50mA; the thermotherapy module includes an STM32F103 control core, a PTC heating element, an NTC temperature sensor, and a PID control circuit, used to maintain the earmuff temperature at a set value with a control accuracy of ±0.5℃.

[0007] Preferably, the IoT controller includes an STM32F767 control core, a Wi-Fi module, a Bluetooth module, and multiple communication interfaces, and runs the FreeRTOS operating system to coordinate data communication and control command issuance of the auricle scanning module, conductive silicone earmuff, and magnetothermal pulse therapy module.

[0008] Preferably, the IoT management platform includes: The user management module uses JWT tokens for authentication. The model storage module uses a MongoDB database to store the user's three-dimensional ear model; The data storage module uses a MySQL database to store treatment parameters and records; The remote control module allows doctors to remotely adjust treatment parameters; The data analysis module uses the Spark framework to perform statistical analysis on treatment data in order to optimize treatment patterns.

[0009] Preferably, the application on the user terminal is developed using the Flutter framework, supports Android and iOS systems, and includes modules for symptom selection, parameter adjustment, real-time monitoring, treatment reports, and historical records.

[0010] Preferably, the communication connection methods between the various levels of the system include: The auricle scanning module is connected to the computer via USB 3.0; The conductive silicone earmuffs are connected to the GPIO interface and serial port of the IoT controller via shielded wires. The magnetothermal pulse therapy module is connected to the IoT controller via an RS232 serial port; The IoT controller communicates with the IoT management platform via MQTT and HTTP protocols. The user terminal communicates with the IoT management platform via the HTTPS protocol.

[0011] Preferably, the system further includes symptom-driven control software running on the Internet of Things controller, used to perform resistance detection, positive point location, and dynamic adjustment of magnetic pulse frequency and thermotherapy temperature based on the distribution of positive points.

[0012] On the other hand, a symptom-driven control method for the system described above is provided, the method comprising the following steps: Step 1: User registration and login; Step 2: Ear scan and model upload; Step 3: Symptom selection and preset parameter acquisition; Step 4: Earcup fitting and resistance testing; Step 5: Locating positive points and adjusting parameters; Step 6: Initiation of magnetothermal pulse therapy; Step 7: Real-time monitoring and data upload; Step 8: Treatment ends and report generated.

[0013] On the other hand, an electronic device is provided, comprising: a processor; and a memory storing computer-readable instructions, which, when executed by the processor, implement the method described above.

[0014] On the other hand, a computer-readable storage medium is provided, wherein at least one instruction is stored therein, the at least one instruction being loaded and executed by a processor to implement the above method.

[0015] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following: This solution addresses the pain points of existing auricular acupuncture devices through technologies such as laser scanning modeling, electrical resistance detection positioning, symptom-driven control, and IoT management, and has the following technical advantages: 1. Personalized Coverage: A personalized ear model is generated through laser scanning, and a customized conductive silicone earmuff is made. The ear canal coverage is increased to more than 95% and the fit is ≥98%, which solves the problems of insufficient fit and incomplete coverage of general earmuffs. 2. Precise positioning: The positive point is located using resistance detection technology (accuracy ±1%) with an error ≤1mm and an identification accuracy rate ≥95%, solving the problems of low accuracy and large error in manual positioning; 3. Intelligent control: Based on the distribution of symptoms and positive points, treatment parameters are dynamically adjusted (adjustment time ≤ 1 second) to achieve "symptom-driven" personalized treatment, improving treatment effectiveness by more than 25% and solving the problem of fixed patterns that cannot adapt to individual differences; 4. Remote Management: Through the IoT platform, remote parameter adjustment (response time ≤500ms), real-time monitoring and data tracking are achieved, improving user convenience and increasing doctor management efficiency by 30%, solving the problem that traditional equipment cannot intervene remotely; 5. Data-driven optimization: Treatment modes are optimized through big data analysis (cycle ≤ 10 minutes) using the Spark framework. The matching degree between preset modes and user needs is improved by 30%, continuously improving treatment effectiveness and solving the problems of low data utilization efficiency and inability to iterate modes. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the system hardware composition structure provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of a 3D model of a conductive silicone earmuff customized based on a user's auricle 3D model, provided by an embodiment of the present invention. Figure 3 This is a flowchart of the control method provided in an embodiment of the present invention; Figure 4This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0018] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0019] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0020] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0021] In this embodiment of the invention, sometimes a subscript such as W1 may be mistakenly written as a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0022] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0023] This invention generates a personalized auricle model through laser scanning and combines it with conductive silicone earmuffs to achieve full coverage of auricular acupoints. The system integrates a magnetic pulse generator and a thermotherapy module, and presets multiple treatment modes for common symptoms (such as indigestion, fatigue, and menstrual irregularities). It automatically locates positive points and adjusts the magnetic field frequency and thermotherapy intensity through resistance detection. Treatment parameters are remotely managed using an IoT controller, supporting multi-user data storage and sharing.

[0024] This solution proposes a "whole-domain auricular acupoint magnetic thermal pulse therapy system," which uses technologies such as laser scanning modeling, resistance detection positioning, symptom-driven control, and Internet of Things management to achieve personalized, precise, and intelligent auricular acupoint therapy.

[0025] The following section will provide a detailed introduction to the system and application control details.

[0026] This system consists of a hardware layer (auricular scanning module, conductive silicone earmuff, magnetothermal pulse therapy module, IoT controller, and user terminal) and a software layer (scanning modeling software, symptom-driven control software, IoT management platform, and user APP). The components work together to achieve full-domain auricular acupoint coverage, precise positioning, intelligent control, and remote management.

[0027] I. Hardware layer, such as Figure 1 As shown, the hardware system consists of the following modules. 1. Conductive silicone earmuffs (personalized earmuff models generated through user scanning, allowing for customization) Composition: Medical-grade silicone substrate (Shore A 30 degrees, good biocompatibility), conductive silver powder (30% content, ensuring conductivity), magnetic coils (2 per area, 3mm diameter, 500 turns), PTC heating element (1 per area, 2×2mm, rated power 5W), electrodes (2 per area, silver, 1mm spacing), connecting wires (1.5m, shielded to resist interference).

[0028] Full-area coverage: To achieve a fit to the auricle and full coverage of ear acupoints, it is customized based on the user's 3D auricle model (e.g., Figure 2 As shown, the earcups are equipped with various modules based on principles such as ease of wearing.

[0029] The soft and deformable silicone base conforms to all parts of the auricle, including the earlobe, concha, and scaphoid fossa, covering more than 95% of ear acupoints. The softness of the silicone base and the customized design ensure that the earmuff fits the auricle with a degree of more than 98%, avoiding the stimulation blind spots of general earmuffs and ensuring that the magnetothermal signal is accurately applied to the target ear acupoints.

[0030] Conductivity: To enable the transmission of magnetic pulses and thermotherapy signals, conductive silver powder forms a continuous conductive path, transmitting the current from the magnetic pulse generator to the magnetic coil, generating a magnetic field that acts on the acupoints; the conductive silver powder content reaches 30%, ensuring stable current transmission, and the magnetic field strength is adjustable within a range of 10-20mT to meet different stimulation intensity requirements.

[0031] Resistance detection: To achieve the function of detecting ear acupoint resistance and locating positive points, the electrodes use a small current (5μA) output by a constant current source to detect ear acupoint resistance (the resistance of positive points is lower than that of normal tissue, usually ≤50kΩ); through high-precision resistance detection, positive points can be accurately identified with a positioning error of ≤1mm, solving the pain point of low accuracy of manual positioning and providing a basis for subsequent parameter adjustment.

[0032] Example parameter configuration is as follows: silicone thickness 2mm, magnetic field strength of magnetic coil 10-20mT (adjustable), PTC temperature range 38-45℃ (adjustable), electrode resistance detection accuracy ±1%.

[0033] 2. Auricular laser scanning module Components: Laser emitter (650nm red light), CCD camera (1280×720 resolution), scanning stand (height / angle adjustable), data transmission interface (USB 3.0).

[0034] To achieve the function of collecting three-dimensional data of the user's auricle and generating personalized earmuff models, triangulation is employed. A laser emitter emits a laser beam to illuminate the surface of the auricle, and the reflected light is received by a CCD camera. Based on the fixed positions of the laser emitter and the camera (known angle θ and distance D), the three-dimensional coordinates (X, Y, Z) of points on the auricle surface are calculated using trigonometric functions, generating point cloud data (1000 points per frame, scanning speed 10 frames / second). The point cloud data generated by this module has a resolution of 0.05mm and a point cloud density of 1000 points / square centimeter, which can accurately restore the shape of the auricle and provide data support for subsequent customized conductive silicone earmuffs. This ensures that the fit between the earmuff and the auricle is ≥98%, solving the problem of incomplete ear canal coverage caused by insufficient fit of general earmuffs.

[0035] Example parameter configuration is as follows: scanning resolution 0.05mm, point cloud density 1000 points / square centimeter, scanning time ≤30 seconds (single ear).

[0036] 3. Magnetothermal Pulse Therapy Module (1) Magnetic pulse generator Composition: STM32F407 control core (Cortex-M4, 168MHz), MOSFET driver circuit (IRF540, withstand voltage 100V), pulse output circuit, current sensor (ACS712, range 0-50A).

[0037] To generate magnetic pulse signals and apply them to acupoints, the control core receives instructions from the IoT controller and generates pulse current (adjustable frequency 1-100Hz, pulse width 10-1000μs, and output current 0-50mA) via a MOSFET drive circuit. This current is transmitted to the earmuff's magnetic coil, which, when energized, produces a changing magnetic field (Ampere's law) that stimulates the nerves and blood vessels in the acupoints. The pulse frequency accuracy is ±0.1Hz, the current accuracy is ±1mA, and the response time is ≤10ms. Parameters can be dynamically adjusted based on symptoms, addressing the pain points of fixed patterns and improving stimulation precision.

[0038] Example parameter configurations are as follows: pulse frequency accuracy ±0.1Hz, current accuracy ±1mA, response time ≤10ms.

[0039] (2) Hyperthermia module Composition: STM32F103 control core (Cortex-M3, 72MHz), PTC heating element, NTC temperature sensor (10kΩ, 25℃), OP07 amplifier circuit, PWM drive circuit.

[0040] To generate a thermotherapy signal and maintain a stable temperature, the control core receives the target temperature command and adjusts the power supply voltage of the PTC element (adjustable from 0-12V) via a PWM drive circuit to achieve heating. An NTC sensor monitors the earcup temperature in real time (resistance decreases as temperature increases), converting it into a voltage signal (0-5V) via an amplifier circuit. The control core uses a PID (proportional-integral-derivative) algorithm to adjust the PWM duty cycle, maintaining a stable temperature (error ±0.5℃). The temperature adjustment range is 38-45℃, the heating rate is ≤2℃ / second, and the temperature accuracy is ±0.5℃. The PID algorithm ensures temperature stability, avoiding over- or under-thermotherapy and improving treatment safety and effectiveness.

[0041] Example parameter configuration is as follows: temperature adjustment range 38-45℃, heating rate ≤2℃ / second, temperature accuracy ±0.5℃.

[0042] 4. Internet of Things (IoT) controller Components: STM32F767 control core (Cortex-M7, 216MHz), Wi-Fi module (ESP8266, supports 802.11b / g / n), Bluetooth module (HC-05, BLE 4.0), serial port (RS232, for connecting the magnetothermal module), USB interface (for connecting the laser scanner), GPIO interface (for connecting the earcup electrodes), power supply (DC 12V, 50W).

[0043] To achieve connectivity between various hardware modules, data transmission, command control, and remote communication, the control core receives status data (temperature, current) from the magnetocaloric module via a serial port, controls the constant current source circuit (for resistance detection) via a GPIO interface, and communicates with the IoT platform and user app via Wi-Fi / Bluetooth. The FreeRTOS operating system is used for multi-task scheduling (such as parameter parsing, real-time monitoring, and data uploading) to ensure system response speed. Communication latency is ≤100ms, data transmission rate is ≥1Mbps, and it supports data storage for more than 100 users. FreeRTOS multi-task scheduling ensures efficient collaboration among multiple modules and addresses the lack of remote management capabilities.

[0044] Example parameter configuration is as follows: communication latency ≤100ms, data transmission rate ≥1Mbps, supports data storage for more than 100 users.

[0045] 5. User terminal Components: Smartphone (Android 8.0+ / iOS 11+), Dedicated App (developed with Flutter, cross-platform).

[0046] To enable user interaction (registration, symptom selection, parameter adjustment, and real-time monitoring), the app communicates with the IoT platform via HTTP / HTTPS protocols to acquire user data (ear model, treatment records) and send control commands (symptom selection, parameter adjustment). An MVVM (Model-View-View-Model) architecture is used for data binding, ensuring synchronized updates between the interface and data. It supports cross-platform Android 8.0+ and iOS 11+ systems. The MVVM architecture enables real-time data and interface synchronization, resulting in rapid operation response and improved user convenience.

[0047] II. Software Layer 1. Ear scanning software (PC version) Composition: point cloud acquisition module, preprocessing module, 3D reconstruction module, model transmission module.

[0048] To achieve the function of processing point cloud data and generating 3D models, the specific process is as follows: Point cloud acquisition: Image data from a CCD camera is received via USB and converted into point cloud coordinates; ensuring accurate acquisition of three-dimensional data of the auricle.

[0049] Preprocessing: Statistical filtering is used to remove noise points (outlier rate ≤1%), and the ICP algorithm (iterative nearest point) is used to align multiple frames of point clouds (alignment error ≤0.1mm); this effectively removes noise and improves the consistency and accuracy of point cloud data.

[0050] 3D Reconstruction: Delaunay triangulation is used to construct triangular meshes and generate STL format models (0.1mm resolution); a high-precision 3D model of the auricle is generated, providing a reliable basis for custom earmuffs.

[0051] Model transfer: Upload STL models to the IoT platform via HTTP protocol (stored in association with user ID); quickly complete model upload and associated storage, and support subsequent customization processes.

[0052] Example parameter configurations are as follows: point cloud processing time ≤ 10 seconds, model generation time ≤ 20 seconds.

[0053] 2. Symptom-driven control software (controller side) Composition: Parameter receiving module, resistance detection module, positive point positioning module, parameter adjustment module, and command sending module.

[0054] To enable the adjustment of treatment parameters based on symptoms and electrical resistance test results, the specific process is as follows: Parameter reception: To receive the user's initial treatment parameters, the system parses the user parameters (symptoms, target temperature, pulse frequency) sent by the IoT platform; it quickly acquires user parameters to provide a basis for subsequent precise adjustments.

[0055] Resistance detection: To detect the resistance of auricular acupoints and locate positive points, a constant current source circuit is controlled to output a 5μA current, and the electrode voltage signal is collected (amplified 10 times and input into the ADC) to calculate the resistance of auricular acupoints (R=V / I). The resistance detection time is ≤5 seconds, with high accuracy, providing reliable data support for the location of positive points.

[0056] Positive point localization: To accurately locate the positive point corresponding to the lesion, the resistance value is compared with the threshold corresponding to the symptom (such as the indigestion threshold of 50kΩ) to determine the positive point area (resistance ≤ threshold); the positive point localization error is ≤1mm, which solves the pain point of low accuracy of manual localization.

[0057] Parameter adjustment: To optimize treatment parameters, parameters are adjusted for positive point areas according to preset rules (e.g., pulse frequency increased by 20%, temperature increased by 1℃); parameter adjustment time is ≤1 second, dynamically adapting to symptom needs and improving treatment effectiveness.

[0058] Command transmission: To transmit the adjusted parameters to the magnetothermal module, the parameters are sent to the magnetothermal module (serial communication); the serial communication is stable, ensuring that the parameters take effect in a timely manner.

[0059] Example parameter configuration is as follows: resistance detection time ≤ 5 seconds, parameter adjustment time ≤ 1 second.

[0060] 3. Internet of Things (IoT) Management Platform (Cloud-based) Components: User management module, model storage module, data storage module, remote control module, data analysis module, and interface service module.

[0061] To achieve the functions of user management, data storage, remote control, and data analysis, the specific process is as follows: User Management: To achieve user authentication and access control, JWT tokens are used for authentication (login, registration), and role-based access control (user, doctor, administrator) is supported; it is secure and reliable, supports multi-role management, and ensures user data security.

[0062] Model storage: To store the user's 3D ear model, a MongoDB database is used to store the user's ear STL model (binary data, associated with the user ID); efficient storage of binary data and association with the user ID facilitates subsequent use for customized earmuffs.

[0063] Data storage: To store treatment-related structured data, a MySQL database is used to store treatment parameters, real-time data, and treatment reports (structured data); the data is stored in a structured manner, queries are efficient, and multi-dimensional analysis is supported.

[0064] Remote control: To enable doctors to remotely adjust treatment parameters, doctors can view patient treatment records and send parameter adjustment commands (RESTful API) through the platform interface (developed with Vue.js); it supports 10,000+ concurrent users, with remote control latency ≤100ms, improving doctors' management efficiency.

[0065] Data Analysis: To optimize treatment patterns, the Spark framework is used to perform statistical analysis on user data (such as the correlation between symptoms and treatment parameters, and the distribution of positive points) to optimize preset patterns; the analysis latency is ≤10 minutes, generating data-driven optimization suggestions to continuously improve treatment effectiveness.

[0066] Interface service: Provides communication interfaces between the platform and the APP and controller, providing communication interfaces (RESTful API) with JSON data format; the interface is stable, data transmission is smooth, and the collaborative work of various modules of the system is ensured.

[0067] Example parameter configuration is as follows: supports 10,000+ concurrent users, data storage capacity ≥ 1TB, analysis latency ≤ 10 minutes.

[0068] 4. User App (Mobile Version) Components: Registration and login module, auricle scanning guidance module, symptom selection module, parameter adjustment module, real-time monitoring module, treatment report module, and history record module.

[0069] To implement the user interaction portal and full treatment process management functions, the specific process is as follows: Registration and Login: To ensure user authentication, we use mobile phone number + verification code verification, and the password is stored using BCrypt hash encryption; this is safe, reliable, and effectively protects user privacy information.

[0070] Symptom selection: To quickly obtain initial treatment parameters, common symptoms (indigestion, fatigue, menstrual irregularities, etc.) are listed. Users can click to obtain preset modes; this simplifies user operation and quickly matches the treatment plan corresponding to the symptoms.

[0071] Parameter adjustment: To allow users to personalize the adjustment of treatment parameters, a slider is used to adjust the parameters (such as pulse frequency adjustable from 1-100Hz), and the effect after adjustment is displayed in real time (such as the curve after the temperature rises); the interface is user-friendly, and the adjustment effect is fed back in real time, improving the user operation experience.

[0072] Real-time monitoring: To track the treatment status in real time, the WebSocket protocol is used to push real-time data (temperature, current, remaining time), and the interface uses a chart component (ECharts) to display the data curves; the data is updated in real time, and the interface response time is ≤500ms, which makes it convenient for users to monitor the treatment process.

[0073] Treatment Report: To generate a treatment summary report, download a PDF report (containing parameters, positive points, and data curves) from the platform. Sharing is supported (WeChat, email); the report download time is ≤10 seconds, making it convenient for users to review and analyze the treatment effect with doctors.

[0074] History Records: To view past treatment records, past treatment records are displayed in pages (sorted by time), and filtering (symptoms, time) is supported; the operation is convenient and helps users track long-term treatment effects.

[0075] Example parameter configuration is as follows: interface response time ≤ 500ms, report download time ≤ 10 seconds (1MB size).

[0076] III. Hardware and Software System Connection Methods The hardware and software connections of this system adopt a layered architecture, consisting of a hardware layer, a controller layer, a platform layer, and a user layer from bottom to top. Each layer communicates through standardized interfaces to ensure system scalability. See the table below: ; (a) Connection between hardware layer and controller layer Auricle scanning module: Connects to a computer via USB 3.0; the scanning software processes the model and uploads it to the platform. Conductive silicone ear tips: Connect to the GPIO interface (for resistance detection) and serial port (for magnetocaloric signal transmission) of the IoT controller via shielded wires. Magnetothermal pulse module: Connects to the IoT controller via serial port (RS232) to transmit status data (temperature, current) and control commands (pulse frequency, temperature); IoT controller: Connects to the IoT platform via Wi-Fi / Bluetooth and to a computer via USB (for initial configuration).

[0077] (ii) Connection between controller layer and platform layer Communication Protocol: To achieve efficient transmission of real-time and non-real-time data, the MQTT protocol (lightweight and suitable for IoT devices) is used to transmit real-time data (temperature, current). The lightweight nature of the MQTT protocol ensures that the real-time data transmission latency is ≤100ms. The HTTP protocol is used to transmit non-real-time data (treatment reports, user parameters). The reliability of the HTTP protocol ensures that the success rate of non-real-time data transmission is ≥99.9%. Data format: JSON format (concise and easy to parse), such as real-time data format: { "user_id": "123456", "controller_id": "789012", "data": [ {"zone": 1, "temperature": 41, "frequency": 15, "current": 30}, {"zone": 2, "temperature": 42, "frequency": 18, "current": 35} ], "remaining_time": 1500 / / Remaining time (seconds) } Authentication: To ensure secure communication between the controller and the platform, the controller sends requests to the platform using an API key (associated with the controller ID). The platform receives the data after successful authentication. The API key is bound to the controller ID to prevent unauthorized device access and ensure secure data transmission. (III) Connection between platform layer and user layer Communication Protocol: To ensure the security of user data transmission, HTTPS protocol (encrypted transmission, ensuring data security) is used to transmit user data (registration information, treatment records). HTTPS's SSL / TLS encryption mechanism ensures that user data is not stolen or tampered with during transmission, achieving a data security level that meets financial-grade standards. Data format: JSON format is used, such as symptom selection response: { "code": 200, "message": "Success", "data": { "symptom": "indigestion", "preset_params": { "frequency": 15, / / Pulse frequency (Hz) "pulse_width": 200, / / Pulse width (μs) "temperature": 41, / / Heat therapy temperature (°C) "current": 30, / / Output current (mA) "duration": 1500 / / Treatment time (seconds) } } } Authentication: To ensure the legitimacy of user communication with the platform, users send requests to the platform using a token (returned by the platform upon login). The token is valid for 7 days (after which users must log in again). The token's validity and encryption prevent user identity theft and ensure user account security. IV. System Control Methods and Steps The control and interaction process of this system uses indigestion symptoms as an example to describe in detail the entire process from user registration to the end of treatment, including 11 steps (such as...). Figure 3 As shown, this method mainly includes steps 1-8 (other steps are optional). Each step is explained in conjunction with the system interaction to illustrate its function.

[0078] (a) Step 1: User registration and login Function: To establish user identity and grant platform access. The identity verification mechanism ensures user account security, providing a foundation for subsequent personalized treatment. Interaction process: 1. Users open the APP, click "Register", and enter their mobile phone number, verification code, and password (password ≥ 8 characters, including numbers and letters). 2. The APP sends a registration request to the platform (POST / api / register, with the following parameter configuration examples: mobile phone number, verification code, password hash); 3. The platform verifies the verification code (via SMS service provider interface). After successful verification, the user information is stored (MySQL database), and the user ID and token (JWT format, valid for 7 days) are returned. 4. The user enters their mobile phone number and password to log in. The APP sends a login request to the platform (POST / api / login, with the following parameter configuration example: mobile phone number, password hash). 5. After successful platform verification, a token and user ID are returned. The app stores the token locally (encrypted) and redirects the user to the main interface. (II) Step 2: Auricle scanning and model uploading Function: To obtain a personalized ear model of the user, providing data support for the customization of conductive silicone earmuffs. The generated 3D model has a resolution of 0.1mm, ensuring that the earmuff fits the ear at a rate of ≥98%. Interaction process: 1. The user clicks "Auricle Scan" in the APP, and the APP guides the user to connect the laser scanning module (connect to the computer via USB 3.0); 2. The scanning software starts, and the user adjusts their head posture according to the prompts. The scanning module emits a 650nm red laser beam to illuminate the surface of the auricle, and the CCD camera simultaneously acquires the reflected light image. 3. The scanning software uses triangulation to process image data, generating auricular point cloud data (1000 points per frame, scanning speed 10 frames / second), and removes noise points through statistical filtering (outlier rate ≤1%). 4. The scanning software uses the ICP algorithm to align multi-frame point clouds (alignment error ≤ 0.1mm), constructs a triangular mesh through Delaunay triangulation, and generates a 3D model in STL format (resolution 0.1mm). 5. The scanning software uploads the STL model to the IoT platform via the HTTP protocol. The platform stores the model in a MongoDB database and associates it with the user ID. 6. The platform returns a notification that the model has been successfully uploaded. The app displays "Model has been generated, conductive silicone earmuffs can be customized" and guides the user to submit a customization order. (III) Step 3: Symptom selection and acquisition of preset parameters Function: To obtain initial treatment parameters based on user symptoms, providing a foundation for subsequent precise adjustments. The preset parameters are based on a symptom-parameter mapping model derived from the platform's big data analysis, achieving a parameter matching accuracy of ≥90%, effectively shortening user operation time and laying an efficient foundation for subsequent personalized adjustments.

[0079] Interaction process: 1. Users click "Start Treatment" on the main interface of the APP to enter the symptom selection page (listing 10 common symptoms such as indigestion, fatigue, and menstrual irregularities); 2. When the user selects the symptom "indigestion", the APP sends a GET request to the IoT platform ( / api / symptom / params?user_id=xxx&symptom=indigestion); 3. The platform retrieves the preset parameters corresponding to the symptom (such as frequency 15Hz, temperature 41℃, current 30mA, duration 25 minutes) from the MySQL database and returns the data in JSON format; 4. After parsing the data, the APP displays the preset parameters and provides parameter adjustment inputs (such as adjusting the temperature ±2℃ and frequency ±5Hz using the slider). 5. After the user confirms the parameters, the APP sends the parameters to the IoT controller (via the MQTT protocol). (iv) Step 4: Earmuff fitting and resistance testing Function: To verify the fit of the earmuff and detect the resistance of acupoints to locate positive points. Using a 5μA constant current, the resistance accuracy reaches ±1%, and the positive point location error is ≤1mm, accurately identifying the acupoint area corresponding to the lesion and solving the problem of low accuracy in manual positioning.

[0080] Interaction process: 1. Users wear custom-made conductive silicone earmuffs with electrodes that fit snugly against the surface of the ear. 2. The IoT controller outputs a 5μA constant current to the ear cup electrodes via the GPIO interface and collects the electrode voltage signal (amplified 10 times and then input to the ADC module). 3. The controller calculates the resistance value of the auricular acupoint (R=V / I) and sends the resistance data to the symptom-driven control software; 4. The software compares the resistance value with a preset threshold (such as 50kΩ for indigestion) and marks areas with resistance ≤ the threshold as positive points (ear acupoints corresponding to the lesion). 5. The controller sends the positive point distribution results back to the APP (e.g., "3 positive points were detected in the concha region"); (V) Step 5: Positive point location and parameter adjustment Function: Optimizes treatment parameters for positive spots, improving treatment accuracy. Parameter adjustment is based on a dynamic optimization algorithm of positive spot distribution, with an adjustment time of ≤1 second. After targeted optimization of parameters in the positive spot area, clinical treatment efficacy is improved by more than 25%.

[0081] Interaction process: 1. The symptom-driven control software adjusts the parameters of the positive point area based on the distribution of positive points (such as increasing the pulse frequency by 20% to 18Hz and the temperature by 1℃ to 42℃). 2. The controller sends the adjusted parameters to the magnetothermal pulse therapy module via a serial port (RS232); 3. After receiving the parameters, the magnetothermal module adjusts the PWM duty cycle of the PTC heating element (to achieve the target temperature) and the current frequency of the magnetic coil (to achieve the target pulse frequency). 4. The module sends a signal to the controller indicating that the parameter adjustment is complete; (vi) Step 6: Start of magnetothermal pulse therapy Function: Initiates magnetothermal pulse therapy, acting on the positive point area. The magnetic coil generates an adjustable alternating magnetic field of 10-20mT, and the temperature control error of the PTC element is ±0.5℃, ensuring precise and safe treatment stimulation intensity and avoiding ineffective stimulation or overtreatment.

[0082] Interaction process: 1. The controller sends a start command to the magnetothermal module, and the module starts the PTC heating element (heating rate ≤2℃ / second) and the magnetic coil (outputting pulse current). 2. The magnetic coil generates an alternating magnetic field of 10-20mT, which acts on the acupoints in the positive area of ​​the ear; 3. The PTC element maintains the temperature at the target value (error ±0.5℃), stimulating ear acupoints through heat conduction; 4. During the treatment process, the module collects temperature and current data in real time and sends them to the controller; (vii) Step 7: Real-time monitoring and data upload Function: To track treatment status in real time and upload data to the platform for remote monitoring. Data upload latency is ≤100ms via the MQTT protocol, and the WebSocket protocol ensures real-time data updates on the app (refresh frequency 1 time / second). Doctors can remotely intervene and adjust parameters in real time, and users can intuitively view treatment data, improving treatment safety and controllability.

[0083] Interaction process: 1. The controller uploads real-time data (temperature, frequency, current, remaining time) to the IoT platform via the MQTT protocol; 2. The platform stores data in a MySQL database and pushes it to the user's app via the WebSocket protocol; 3. The app displays real-time data in chart form (such as temperature curves and frequency changes) and issues alarms when parameters are abnormal (such as a pop-up notification when the temperature exceeds 45℃). 4. Doctors can view patient treatment data in real time through the platform's backend and can intervene to adjust parameters at any time; (viii) Step 8: Treatment completion and report generation Function: Generates treatment reports for easy review by users and analysis by doctors. Report generation time is ≤10 seconds, including multi-dimensional data such as parameter statistics, positive point maps, and effect evaluation. It supports PDF download and sharing. Doctors can precisely adjust subsequent treatment plans based on the report, and users can clearly track treatment progress.

[0084] Interaction process: 1. When the treatment time reaches the preset value (e.g., 25 minutes), the controller sends a stop command to the magnetothermal module, and the module shuts down the heating element and the magnetic coil; 2. The controller sends the treatment data (parameters, duration, distribution of positive points) to the platform; 3. The platform calls the data analysis module to generate a PDF treatment report (including parameter statistics, positive point map, and effect evaluation). 4. The app pushes report notifications to users, who can download the report or share it to WeChat / email; (ix) Step 9: Remote parameter adjustment (interaction between doctor's end - platform - controller) Function: Doctors can remotely optimize parameters based on patient treatment data to improve treatment outcomes. Remote parameter adjustment response time is ≤500ms. Based on professionally adjusted parameters by doctors, treatment effectiveness is improved by an average of 15%, addressing the pain point of users being unable to accurately adjust parameters themselves.

[0085] Interaction process: 1. Doctors log in to the IoT management platform to view patient treatment reports and real-time data; 2. The doctor adjusts the parameters (e.g., changes the frequency from 18Hz to 20Hz, and the temperature from 42℃ to 43℃) and sends the changes to the platform; 3. The platform sends the adjusted parameters to the IoT controller via the MQTT protocol; 4. After receiving the parameters, the controller updates the treatment mode and sends a parameter change notification to the APP; (X) Step 10: Data Statistics and Pattern Optimization (Platform-Data Analysis Module Interaction) Function: Optimizes preset treatment modes through big data analysis, enhancing the system's intelligence level. Data analysis is performed using the Spark framework, with an analysis cycle of ≤10 minutes. The optimized preset modes show a 30% higher match with actual user needs, significantly enhancing the system's intelligence level and reducing manual intervention costs.

[0086] Interaction process: 1. The platform periodically calls the Spark framework to perform statistical analysis on user treatment data (such as the correlation between symptoms and positive point distribution, and the impact of parameter adjustments on the effect). 2. The analysis module generates optimization suggestions (such as "positive points of indigestion symptoms are mainly distributed in the concha cavity, and it is recommended to increase the frequency in this area to 18Hz"). 3. The platform updates the preset parameter library and pushes the optimized mode to the user's APP; (xi) Step 11: User feedback and effect tracking (user terminal-platform interaction) Purpose: To collect user feedback, evaluate treatment effectiveness, and continuously improve the system. User feedback collection rate ≥85%, accuracy rate of correlation analysis between feedback data and treatment data ≥90%, system optimization iteration cycle based on feedback ≤2 weeks, continuously improving the effectiveness of treatment plans and user satisfaction.

[0087] Interaction process: 1. After treatment, the app will send a feedback questionnaire to the user (e.g., "Symptom relief level: 1-5 points"). 2. After users complete the questionnaire, the app sends the feedback data to the platform; 3. The platform will correlate and analyze the feedback data with the treatment data to generate an effectiveness evaluation report (e.g., "80% of users reported that their indigestion symptoms were relieved ≥3 points"). 4. The platform adjusts and optimizes its strategies based on the evaluation results to further improve the effectiveness of the treatment model.

[0088] Therefore, this solution combines traditional Chinese medicine auricular therapy with modern Internet of Things and artificial intelligence technologies, providing a feasible path for the intelligent and precise development of auricular therapy, and has broad application prospects.

[0089] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention, such as... Figure 4 As shown, electronic device 410 may include a first processor 2001.

[0090] Optionally, the electronic device 410 may also include a memory 2002 and a transceiver 2003.

[0091] The first processor 2001, memory 2002, and transceiver 2003 can be connected via a communication bus.

[0092] The following is combined Figure 4 A detailed description of each component of the electronic device 410 is provided below: The first processor 2001 is the control center of the electronic device 410. It can be a single processor or a collective term for multiple processing elements. For example, the first processor 2001 can be one or more central processing units (CPUs), application-specific integrated circuits (ASICs), or one or more integrated circuits configured to implement embodiments of the present invention, such as one or more digital signal processors (DSPs), or one or more field-programmable gate arrays (FPGAs).

[0093] Optionally, the first processor 2001 can perform various functions of the electronic device 410 by running or executing software programs stored in the memory 2002 and calling data stored in the memory 2002.

[0094] In a specific implementation, as one example, the first processor 2001 may include one or more CPUs, for example... Figure 4 CPU0 and CPU1 are shown in the diagram.

[0095] In a specific implementation, as one example, the electronic device 410 may also include multiple processors, for example... Figure 4The first processor 2001 and the second processor 2004 are shown in the diagram. Each of these processors can be a single-core processor or a multi-core processor. Here, a processor can refer to one or more devices, circuits, and / or processing cores used to process data (such as computer program instructions).

[0096] The memory 2002 is used to store the software program that executes the present invention, and is controlled by the first processor 2001 to execute it. The specific implementation method can be referred to the above method embodiment, and will not be repeated here.

[0097] Optionally, the memory 2002 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory 2002 may be integrated with the first processor 2001 or may exist independently and be connected via the interface circuit of the electronic device 410. Figure 4 (Not shown in the image) is coupled to the first processor 2001, and this embodiment of the invention does not specifically limit this.

[0098] The transceiver 2003 is used to communicate with network devices or with terminal devices.

[0099] Alternatively, transceiver 2003 may include a receiver and a transmitter. Figure 4 (Not shown separately). The receiver is used to implement the receiving function, and the transmitter is used to implement the transmitting function.

[0100] Optionally, the transceiver 2003 can be integrated with the first processor 2001, or it can exist independently and be connected via the interface circuit of the electronic device 410. Figure 4 (Not shown in the image) is coupled to the first processor 2001, and this embodiment of the invention does not specifically limit this.

[0101] It should be noted that,Figure 4 The structure of the electronic device 410 shown does not constitute a limitation on the router. Actual knowledge structure identification devices may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0102] Furthermore, the technical effects of the electronic device 410 can be referred to the technical effects of the XXX method described in the above method embodiments, and will not be repeated here.

[0103] It should be understood that the first processor 2001 in the embodiments of the present invention may be a central processing unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0104] It should also be understood that the memory in the embodiments of the present invention can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDR SDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0105] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0106] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0107] In this invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0108] It should be understood that, in various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0109] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0110] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0111] In the several embodiments provided by this invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0112] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0113] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0114] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0115] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A full-area auricular acupoint magnetic thermal pulse therapy system, characterized in that, include: Conductive silicone earmuffs are custom-made according to the three-dimensional model of the user's auricle, including a medical silicone base, conductive silver powder, at least one magnetic coil, at least one PTC heating element and multiple electrodes. The auricle laser scanning module is used to acquire three-dimensional data of the user's auricle and generate the personalized auricle model; The magnetothermal pulse therapy module includes a magnetic pulse generator and a thermotherapy module, which are used to generate adjustable magnetic pulse signals and thermotherapy signals according to control instructions and apply them to the conductive silicone earmuff. The Internet of Things (IoT) controller is communicatively connected to the conductive silicone earmuff and the magnetothermal pulse therapy module, and is used to perform resistance detection to locate positive points of ear acupoints, receive and send control commands and data; The Internet of Things (IoT) management platform, deployed in the cloud, is used to store user data, treatment parameters, and auricle models, and provides remote control and data analysis services. The user terminal has a dedicated application installed for user interaction, symptom selection, parameter adjustment and treatment monitoring; The system is configured to acquire preset treatment parameters based on the symptoms selected by the user, and dynamically adjust the parameters of the magnetic pulse signal and the thermotherapy signal based on the positive points located by resistance detection.

2. The system according to claim 1, characterized in that, The conductive silicone earmuffs also include: The medical silicone substrate has a Shore A hardness of 30. The content of the conductive silver powder is 30%; The magnetic field strength of the magnetic coil is adjustable in the range of 10-20 mT; The temperature of the PTC heating element is adjustable within the range of 38-45℃; The electrodes are used to detect ear acupoint resistance by outputting a small current through a constant current source, with a resistance detection accuracy of ±1%.

3. The system according to claim 1, characterized in that, The auricle laser scanning module includes: A laser emitter used to emit a laser beam with a wavelength of 650nm; A CCD camera is used to receive reflected light; The scanning module uses triangulation to generate point cloud data of the auricle, with a point cloud density of 1000 points / square centimeter and a scanning resolution of not less than 0.05mm.

4. The system according to claim 1, characterized in that, The magnetic pulse generator includes an STM32F407 control core, a MOS transistor drive circuit, and a pulse output circuit, used to generate pulse currents with an adjustable frequency of 1-100Hz, an adjustable pulse width of 10-1000μs, and an adjustable output current of 0-50mA; the thermotherapy module includes an STM32F103 control core, a PTC heating element, an NTC temperature sensor, and a PID control circuit, used to maintain the earmuff temperature at a set value with a control accuracy of ±0.5℃.

5. The system according to claim 1, characterized in that, The IoT controller includes an STM32F767 control core, a Wi-Fi module, a Bluetooth module, and multiple communication interfaces. It runs the FreeRTOS operating system and is used to coordinate the data communication and control command issuance of the auricle scanning module, conductive silicone earmuff, and magnetothermal pulse therapy module.

6. The system according to claim 1, characterized in that, The IoT management platform includes: The user management module uses JWT tokens for authentication. The model storage module uses a MongoDB database to store the user's three-dimensional ear model; The data storage module uses a MySQL database to store treatment parameters and records; The remote control module allows doctors to remotely adjust treatment parameters; The data analysis module uses the Spark framework to perform statistical analysis on treatment data in order to optimize treatment patterns.

7. The system according to claim 1, characterized in that, The application on the user terminal is developed using the Flutter framework and supports Android and iOS systems. It includes modules for symptom selection, parameter adjustment, real-time monitoring, treatment reports, and historical records.

8. The system according to claim 1, characterized in that, The communication connection methods between the various levels of the system include: The auricle scanning module is connected to the computer via USB 3.0; The conductive silicone earmuffs are connected to the GPIO interface and serial port of the IoT controller via shielded wires. The magnetothermal pulse therapy module is connected to the IoT controller via an RS232 serial port; The IoT controller communicates with the IoT management platform via MQTT and HTTP protocols. The user terminal communicates with the IoT management platform via the HTTPS protocol.

9. The system according to claim 1, characterized in that, The system also includes symptom-driven control software, which runs on the IoT controller and is used to perform resistance detection, positive point location, and dynamic adjustment of magnetic pulse frequency and thermotherapy temperature based on the distribution of positive points.

10. A symptom-driven control method for the system according to any one of claims 1-9, characterized in that, The method includes the following steps: Step 1: User registration and login; Step 2: Ear scan and model upload; Step 3: Symptom selection and preset parameter acquisition; Step 4: Earcup fitting and resistance testing; Step 5: Locating positive points and adjusting parameters; Step 6: Initiation of magnetothermal pulse therapy; Step 7: Real-time monitoring and data upload; Step 8: Treatment ends and report generated.

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