Knee osteoarthropathy AI acupoint electric diagnosis and treatment system

Abstract

The invention belongs to the technical field of medical instruments, and particularly relates to a knee osteoarthropathy AI acupoint electric diagnosis and treatment system which comprises a software architecture and a hardware architecture, the software architecture is composed of a medical platform, an applet and an equipment architecture, the software architecture further comprises a server, a front-end architecture, a background architecture, a data storage unit, a communication security unit, a data backup unit and a network connection unit, the hardware architecture comprises a system principle unit, a power management module, a man-machine interaction module, a driving algorithm unit and a structural design unit, and the software architecture is connected with the hardware architecture. According to the invention, a diagnosis and treatment scheme conforming to the patient is generated through the basic information and the disease information by using the independently researched and developed AI algorithm, and intelligent medical treatment is realized. All diagnosis and treatment schemes, patient information and disease features can be remotely stored, data information can be screened according to needs, doctors are helped to provide more comprehensive and detailed patient information, and therefore the treatment schemes can act on patients more directly and accurately, and efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of medical devices, and in particular relates to an AI acupoint electrical diagnosis and treatment system for knee osteoarthritis. Background Art

[0002] The knee joint is composed of the lower end of the femur, the upper end of the tibia and the patella. It is the largest and most complex joint in the human body and belongs to the trochlear joint. The knee joint is one of the largest joints in the body, composed of the femur, tibia and patella. It is the body's load-bearing joint and one of the most vulnerable joints. The knee joint is the joint with the highest incidence rate in the body. Knee joint pain not only involves various lesions within the joint, but is also often caused by various factors outside the joint. The symptoms produced by the knee joint are often not specific. Symptoms such as pain, weak legs, and joint locking can be caused by cruciate ligament and meniscus injuries, patellofemoral joint abnormalities, articular cartilage lesions, or even just due to the incarceration of abnormally proliferating synovium. Knee joint diseases mainly include: osteoarthritis, synovitis, patellar softening, meniscus injury, etc.

[0003] The current market quality of knee arthritis treatment devices are all stand-alone versions, and the treatment methods are nothing more than radio frequency, ultrasound and shock wave. This method requires professional medical staff to operate, the equipment is large, data information is stored locally, and it cannot provide diagnosis and treatment assistance and suggestions. In view of this, we provide an AI acupoint electrodiagnosis and treatment system for knee osteoarthritis to solve the above problems. Summary of the invention

[0004] The purpose of the present invention is to provide an AI acupoint electrical diagnosis and treatment system for knee osteoarthritis, aiming to solve the problem that in the prior art, the existing market for knee osteoarthritis is of single-machine version, and the treatment methods used are nothing more than radio frequency, ultrasound and shock wave, etc. This method requires professional medical staff to operate, the equipment is large in size, data information is stored locally, and it cannot provide diagnosis and treatment assistance and suggestions.

[0005] To achieve the above-mentioned objectives, the present invention provides the following technical solutions: an AI acupoint electrical diagnosis and evaluation treatment system for knee osteoarthritis, comprising a software architecture and a hardware architecture, wherein the software architecture is composed of a medical platform, a mini-program and a device architecture, wherein the software architecture also includes a server, a front-end architecture, a back-end architecture, data storage, communication security, data backup and network connection, wherein the hardware architecture includes a system principle, a power management module, a human-computer interaction module, a driving algorithm and a structural design, and the software architecture and the hardware architecture are connected.

[0006] As a preferred AI acupoint electrical diagnosis and evaluation treatment system for knee osteoarthritis of the present invention, the server adopts a Linux server, equipped with a Centos7.6 system, and adopts a 4-core 8G configuration, specifically a Linux system; CPU: 2 cores and above, memory: 8GB or above, storage: 400Mb or above; the front-end architecture adopts VUE and ElimentUI framework to achieve more humanized front-end interaction, and adopts axios encapsulation technology for stable data interaction; the back-end architecture is built with SpringBoot service, adopts front-end and back-end separation technology, and the interface adopts netty high-concurrency service design, supporting 10W concurrency.

[0007] As a preferred AI acupoint electrical diagnosis and evaluation treatment system for knee osteoarthritis of the present invention, the data storage adopts Mysql database for data storage, mature data scheduled backup and recovery solutions, and combines mongodb non-relational database to store user and device usage log information; the communication security and data backup adopt Https secure channel for data transmission, and adopts data encryption algorithm for secure encryption and backup.

[0008] As a preferred AI acupoint electrical diagnosis and evaluation treatment system for knee osteoarthritis of the present invention, the network connection adopts smart phones and other mobile devices and is connected and monitored by Bluetooth dynamic adjustment and is compatible with iOS and Android.

[0009] As a preferred AI acupoint electrical diagnosis and evaluation treatment system for knee osteoarthritis of the present invention, the system principle adopts pulse discharge combined with supercapacitor method to reduce energy consumption, increase equipment standby time, and integrate time-sharing multiplexing. The power management module adopts a multifunctional power management SOC with a boost converter, lithium battery charging management, and battery power indication. The human-computer interaction module adopts touch and LED display, wherein the touch has 3 touch buttons for detecting the touch action of a human hand on the external touch buttons. The driving algorithm adopts a fusion inversion algorithm and a current PID algorithm, and the structural design adopts an integrated circuit board.

[0010] As a preferred AI acupoint electrodiagnosis and evaluation treatment system for knee osteoarthritis of the present invention, the medical platform is composed of role permissions, equipment management, administrator management, consultation management, treatment records, user management, mode parameters, medical record management and treatment modes.

[0011] As a preferred AI acupoint electrodiagnosis and evaluation treatment system for knee osteoarthritis of the present invention, the mini-program consists of authorized login, electroacupuncture control, and treatment records.

[0012] As a preferred AI acupoint electrodiagnosis and evaluation treatment system for knee osteoarthritis of the present invention, the device architecture is composed of user authorization, device binding, device parameters, electroacupuncture control, treatment records and data synchronization.

[0013] As a preferred AI acupoint electrical diagnosis and evaluation treatment system for knee osteoarthritis of the present invention, the medical platform, mini-program and device architecture are connected by Bluetooth, and the mini-program is compatible with smartphones.

[0014] An AI acupoint electrical diagnosis and evaluation method for knee osteoarthritis comprises the following steps: S1. First, the patient information is entered into a medical platform, and a diagnosis and treatment plan matching the patient's symptoms is automatically generated through an AI algorithm; S2. Then, the patient enters the medical platform through a small program on a mobile phone, and can obtain the hospital's diagnosis and treatment plan by binding personal information; S3. Finally, the patient wears the device structure to the knee joint according to the obtained diagnosis and treatment plan, and issues diagnosis and treatment instructions through the small program. The knee chronic disease acupoint electrical stimulation therapeutic device uses electric current pulses to perform acupuncture stimulation treatment on various acupoints of the knee joint.

[0015] Compared with the prior art, the present invention has the following beneficial effects:

[0016] The present invention uses self-developed AI algorithms to generate treatment plans that meet the patient's needs through basic information and symptom information, thus realizing smart medical care. All treatment plans, patient information, and symptom characteristics can be stored remotely, and data information can be filtered as needed to help doctors provide more comprehensive and detailed patient information, so that the treatment plan can directly and accurately affect the patient and improve efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0018] Figure 1 It is a schematic diagram of the system structure of the present invention;

[0019] Figure 2 It is a schematic diagram of the structure of the medical platform of the present invention;

[0020] Figure 3 This is a schematic diagram of the structure of the applet of the present invention;

[0021] Figure 4 It is a schematic diagram of the device architecture structure of the present invention;

[0022] Figure 5 It is a schematic diagram of the system principle structure of the present invention;

[0023] Figure 6 It is a schematic diagram of the voltage reduction structure of the power management module of the present invention;

[0024] Figure 7 It is a schematic diagram of the boost structure of the power management module of the present invention;

[0025] Figure 8 Schematic diagram of the circuit structure of the human-computer interaction module of the present invention;

[0026] Fig. 9 It is a circuit structure schematic diagram of the human-computer interaction module of the present invention;

[0027] Fig.10 It is a schematic diagram of the structure of the fusion inversion algorithm of the driving algorithm of the present invention;

[0028] Fig.11 It is a schematic diagram of the circuit structure of the fusion inversion algorithm of the present invention;

[0029] Fig.12 It is a schematic diagram of the current PID algorithm flow structure of the driving algorithm of the present invention;

[0030] Fig.13 It is a schematic diagram of the structure of the PID adjustment algorithm formula of the present invention;

[0031] Fig.14 It is a schematic diagram of the current collection structure after the current PID algorithm of the driving algorithm of the present invention;

[0032] Fig.15 A schematic diagram of the circuit board structure designed for the structure of the present invention;

[0033] Fig.16 A schematic diagram of the role authority structure of the medical platform of the present invention;

[0034] Fig.17 A schematic diagram of the administrator management structure of the medical platform of the present invention;

[0035] Fig.18 It is a schematic diagram of the device management structure of the medical platform of the present invention;

[0036] Fig.19 It is a schematic diagram of the consultation management structure of the medical platform of the present invention;

[0037] Fig. 20 A schematic diagram of the user management structure of the medical platform of the present invention;

[0038] Fig.21 It is a schematic diagram of the treatment mode structure of the medical platform of the present invention;

[0039] Fig. 22 It is a schematic diagram of the mode parameter structure of the medical platform of the present invention;

[0040] Fig.23 It is a schematic diagram of the control panel structure of the applet of the present invention;

[0041] Fig.24 This is a schematic diagram of the authorization login structure of the mini program of the present invention;

[0042] Fig.25 This is a schematic diagram of the structure of the TCM intelligent electroacupuncture rehabilitation diagnosis and treatment device of the present invention;

[0043] Fig.26 It is a schematic diagram of the process structure of the present invention.

[0044] In the figure: 100, software architecture; 1001, medical platform; 1002, applet; 1003, device architecture; 101, server; 102, front-end architecture; 103, back-end architecture; 104, data storage; 105, communication security; 106, data backup; 107, network connection; 200, hardware architecture; 201, system principle; 202, power management module; 203, human-computer interaction module; 204, driving algorithm; 205, structural design. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] See also Figure 1-5 The present invention provides the following technical solutions: an AI acupoint electrical diagnosis and evaluation treatment system for knee osteoarthritis, including a software architecture 100 and a hardware architecture 200. The software architecture 100 is composed of a medical platform 1001, a mini-program 1002 and a device architecture 1003. The software architecture 100 also includes a server 101, a front-end architecture 102, a back-end architecture 103, data storage 104, communication security 105, data backup 106 and a network connection 107. The hardware architecture 200 includes a system principle 201, a power management module 202, a human-computer interaction module 203, a driving algorithm 204 and a structural design 205. The software architecture 100 and the hardware architecture 200 are connected.

[0047] Preferred: Server 101 uses Linux server, equipped with Centos7.6 system, 4-core 8G configuration, specifically Linux system; CPU: 2 cores and above, memory: 8GB or above, storage: 400Mb or above; front-end architecture 102 uses VUE and ElimentUI framework to achieve more user-friendly front-end interaction, and uses axios encapsulation technology for stable data interaction; back-end architecture 103 is built with SpringBoot service, using front-end and back-end separation technology, and the interface uses netty high-concurrency service design, supporting 10W concurrency.

[0048] In specific use, the front-end architecture 102 adopts the mainstream VUE and ElimentUI frameworks, designs and implements more user-friendly front-end interactions, and uses axios encapsulation technology for stable data interaction. The back-end architecture 103 is built based on SpringBoot services and adopts mainstream front-end and back-end separation technology. The interface adopts netty high-concurrency service design, supports 10W concurrency, and ensures stable user use.

[0049] Preferably: data storage 104 uses Mysql database for data storage, mature data scheduled backup and recovery solutions, and combines mongodb non-relational database to store user and device usage log information; communication security 105 and data backup 106 use Https secure channel for data transmission, and use data encryption algorithm for secure encryption and backup.

[0050] During specific use, data storage 104 is based on Mysql database for data storage, mature data scheduled backup and recovery solutions, and combined with mongodb non-relational database to store user and device usage log information. Communication security 105 and data backup 106 use Https secure channel for data transmission to ensure data integrity and security; and use a unique data encryption algorithm for secure encryption. At the same time, data backup 106 needs to perform multiple data backups on a daily basis to ensure data integrity and security, and has a mature data recovery solution.

[0051] Preferably, the network connection 107 uses smart phones and other mobile devices and is connected through Bluetooth dynamic adjustment and monitoring compatibility with iOS and Android.

[0052] During specific use, the network connection 107 uses smartphones and other mobile devices and connects and monitors compatibility with iOS and Android through Bluetooth dynamic adjustment, which makes it easy to understand the data of the medical platform 1001 and the use of the mini program 1002 and the device architecture 1003.

[0053] Preferred: System principle 201 adopts pulse discharge combined with supercapacitor method to reduce energy consumption, increase equipment standby time, and integrate time-sharing multiplexing mode. Power management module 202 adopts multifunctional power management SOC with boost converter, lithium battery charging management, and battery power indication. Human-computer interaction module 203 adopts touch and LED display, wherein the touch has 3 touch buttons for detecting the touch action of human hand on the external touch button. Drive algorithm 204 adopts fusion inverter algorithm and current PID algorithm. Structural design 205 adopts integrated circuit board.

[0054] When used specifically, the system principle 201 is composed of several main parts, including power supply, human-computer interaction, file management, time synchronization, electroacupuncture system, ARM, etc. The power supply part adopts precise power management, pulse discharge combined with supercapacitor method, reduces energy consumption, increases the standby time of the equipment, integrates time-sharing multiplexing, achieves three-channel output, greatly reduces the volume, is compatible with iOS and Android, and the Bluetooth connection adopts dynamic adjustment to ensure the stability of the dual system. Actively collect treatment data, analyze data, and form customized professional electronic prescriptions. The current PID algorithm automatically stabilizes the output current of the electrode sheet. Please refer to the attached manual Figure 5 ;

[0055] The power management module 202 integrates a multifunctional power management SOC with a boost converter, lithium battery charging management, and battery charge indication, providing a complete power solution for mobile power. The high integration and rich functions require only a few peripheral devices when applied, and effectively reduce the size of the overall solution and reduce the BOM cost. An inductor is required to achieve buck and boost functions. It can support low-cost inductors and capacitors. The synchronous boost system provides a maximum output current of 2.4A and a conversion efficiency of up to 92%. When not loaded, it automatically enters sleep mode and the quiescent current drops to 100uA. Using switching charging technology, it provides a maximum current of 2.1A and a charging efficiency of up to 91%. The built-in IC temperature and input voltage intelligently adjust the charging current; please refer to the attached manual Figure 6 and Figure 7 ;

[0056] The human-computer interaction module 203 includes touch and LED display; the touch has 3 touch buttons, which can be used to detect the touch action of human hands on the external touch buttons. The chip has a high degree of integration and only requires very few external components to realize the detection of touch buttons. It provides 3 direct output functions. The chip uses a special integrated circuit with a high power supply voltage suppression ratio, which can reduce the occurrence of key detection errors. This feature ensures that the chip still has high reliability in applications under adverse environmental conditions. This touch chip has automatic calibration function, low standby current, resistance to voltage fluctuations and other characteristics, and provides a simple and effective implementation method for various touch button + IO output applications. Please refer to the attached manual. Figure 8 and Fig. 9 ;

[0057] Driving algorithm 2041. The inverter mode can adjust the periodic exchange of electrode polarity to prevent single electrode sheet from burning the skin and reduce discomfort. In the circuit, 4 N-type MOS tubes are generally used to build it. The reason for not using 2 N-type MOS tubes + 2 P-type MOS tubes is that it is difficult to make P-type MOS tubes with high voltage and high current, and the on-resistance is large. For MOS with the same performance, N-type is cheaper than P-type. For NMOS, when the external gate-source Vgs voltage is greater than the Vgs threshold of the chip (mostly between 2V-10V), the drain D and the source S are directly connected. If the external Vgs voltage is less than the threshold, the drain D and the source S are cut off. Simply think of it as a switch controlled by the gate G voltage. Refer to the attached manual. Fig.10 ; Assume that the Vgs threshold of the N-MOS tube in the figure is 3V, and VCC = 24V. For the lower bridge arm Q2MOS tube, the chip pin can be used to directly control it, because the PWM high level is 3.3V, which is enough to turn on the N-MOS tube. The upper bridge arm Q1MOS tube cannot be directly turned on by the STM32 chip pin, because assuming that Q1 is turned on, the drain D and source S voltages are almost equal and Ros is very small, that is, VA = VCC, which requires Vg> = Va + Vgs. Simply put, if Vg is greater than the threshold, Q1 is turned on, and if it is less than the threshold, Q1 is turned off. Therefore, a circuit like this is needed: boost the 3.3VPWM signal. This circuit can be implemented using a bootstrap circuit. Refer to the attached manual. Fig.11 ; Upper bridge arm drive: bootstrap circuit Lower bridge arm drive: level control, in circuit design, Ves is generally set to a fixed threshold, because this ensures that the MOS tube is fully turned on. It should be noted that when the MOS tube is fully turned on, the internal resistance Rds of the MOS tube is generally small, at a few milliohms, which is equivalent to a wire. However, when the MOS tube is not fully turned on, that is, when Vgs is less than the turn-on voltage, the MOS is in an incompletely turned-on state, then the internal resistance of the MOS tube is relatively large, and the current of the motor drive board is also relatively large. Then the heat of the MOS will be very serious, and it is likely to burn out the chip.

[0058] 2. The current PID algorithm automatically stabilizes the output current of the electrode sheet. Set an output target. The feedback system transmits the output value back. If it is inconsistent with the target, there is an error. PID adjusts the input value according to this error until the output reaches the set value. Refer to the manual. Fig.12 ; then refer to Fig.13 The PID adjustment algorithm formula can be obtained, which can derive the relationship between e(t) and u(t): Where: Kp: proportional gain, which is an adjustment parameter; Ki: integral gain, which is also an adjustment parameter; Kd: differential gain, which is also an adjustment parameter; e: error = set value SP-feedback value PV; t: current time; refer to the manual for details. Fig.14It is the current acquisition DAC of the differential amplifier, and then combined with PID control, it outputs a stable intensity;

[0059] The structural design 205 is a device that integrates an inverter algorithm and an adjustable electrode polarity periodic exchange to prevent single electrode sheets from burning the skin and reduce discomfort reactions; it adopts precise power management, pulse discharge combined with supercapacitor method to reduce energy consumption and increase the standby time of the device; it integrates time-sharing multiplexing to achieve three-channel output, greatly reducing the volume; it is compatible with iOS and Android, and the Bluetooth connection uses a dynamic adjustment method to ensure the stability of the dual systems, actively collect treatment data, analyze data, and form customized professional electronic prescriptions; the current PID algorithm automatically stabilizes the output current of the electrode sheet; the operation safety redundancy combined with software and hardware ensures online and local operations, free switching, and improves operational reliability; the functions are compatible, except for chronic knee joint diseases, the main control can be used as an ordinary electroacupuncture device alone, refer to the instruction manual Fig.15 .

[0060] Preferably: the medical platform 1001 is composed of role authority, equipment management, administrator management, consultation management, treatment records, user management, mode parameters, medical record management and treatment mode.

[0061] When used specifically, role permissions are used to obtain 1001 permissions to log in to the medical platform; device management is used to maintain the system on a daily basis; administrator management is used to add, delete, modify, export and role status; consultation management is used to understand the consultation list of the day, patient information, first visit / re-visit channels, consultation records, treatment records and other information; treatment records are used to record patient consultation data; user management is used to register patient information; mode parameters are used to understand patient physical information; medical record management is used to store patient diagnosis and treatment data; treatment mode is used to give patient treatment plans. Figure 16-22 .

[0062] Preferably, mini-program 1002 is composed of authorization login, electroacupuncture control, and treatment record.

[0063] When used specifically, the authorized logged-in user obtains the patient's basic information, the electroacupuncture control is used to control the operation of the device architecture 1003, and the treatment record is used to store the patient's treatment information. Figure 23-24 .

[0064] Preferably: the device architecture 1003 is composed of user authorization, device binding, device parameters, electroacupuncture control, treatment records and data synchronization.

[0065] When used specifically, user authorization is used for patients to use the device, device binding is used to bind patients for use, device parameters are used to adjust when patients use them, electroacupuncture control is used to start the device, treatment records are used to store patients' treatment information, and data synchronization is used to synchronize to mini program 1002 and medical platform 1001. Fig.25 .

[0066] Preferably: the medical platform 1001, the mini program 1002 and the device architecture 1003 are connected by Bluetooth, and the mini program 1002 is compatible with smart phones.

[0067] An AI acupoint electrical diagnosis and evaluation method for knee osteoarthritis includes the following steps: S1. First, enter the patient information on the medical platform 1001, and automatically generate a diagnosis and treatment plan matching the patient's symptoms through an AI algorithm; S2. Then, the patient enters the medical platform 1001 through the small program 1002 on the mobile phone, and can obtain the hospital's diagnosis and treatment plan by binding personal information; S3. Finally, the patient wears the device architecture 1003 to the knee joint according to the obtained diagnosis and treatment plan, and issues diagnosis and treatment instructions through the small program 1002. The knee chronic disease acupoint electrical stimulation therapeutic instrument uses current pulses to perform acupuncture stimulation treatment on various acupoints of the knee joint.

[0068] It is necessary to add that: Reference Fig.26 This is a structural diagram of the intelligent electroacupuncture rehabilitation diagnosis and treatment device for traditional Chinese medicine. When in use, untie the strap 11, then tie the strap 11 on the knee joint, plug the electrode line through the device electrode output port 5, and pass it through the Yanglingquan electrode port 1, the Xiyangguan electrode port 3, the Yinlingquan electrode port 2, the Xuehai electrode port 4, and the Liangqiu electrode port 6 respectively; use the start / pause button & indicator 7 to start or pause, the increase button & indicator 8 to control the intensity to enhance the output, the weaken button & indicator 9 to weaken the output, and the Bluetooth indicator 10 indicates the network status.

[0069] Among them: 1. Yanglingquan electrode port; 2. Xiyangguan electrode port; 3. Yinlingquan electrode port; 4. Xuehai electrode port; 5. Liangqiu electrode port; 6. Equipment electrode output port; 7. Start / pause button & indication; 8. Increase button & indication; 9. Reduce button & indication; 10. Bluetooth indication; 11. Strap.

[0070] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An AI acupoint electrical diagnosis and treatment system for knee osteoarthritis, comprising a software architecture (100) and a hardware architecture (200), characterized in that: The software architecture (100) is composed of a medical platform (1001), a mini-program (1002) and a device architecture (1003), and the software architecture (100) also includes a server (101), a front-end architecture (102), a back-end architecture (103), data storage (104), communication security (105), data backup (106) and a network connection (107); The hardware architecture (200) includes a system principle (201), a power management module (202), a human-computer interaction module (203), a driving algorithm (204) and a structural design (205), and the software architecture (100) and the hardware architecture (200) are connected.

2. The AI ​​acupoint electrical diagnosis and treatment system for knee osteoarthritis according to claim 1 is characterized by: The server (101) adopts a Linux server, equipped with a Centos7.6 system, and adopts a 4-core 8G configuration, specifically a Linux system; CPU: 2 cores or above, memory: 8GB or above, storage: 400Mb or above; the front-end architecture (102) adopts VUE and ElimentUI frameworks to achieve more humanized front-end interaction, and adopts axios encapsulation technology for stable data interaction; the back-end architecture (103) is constructed using SpringBoot services, adopts front-end and back-end separation technology, and the interface adopts netty high-concurrency service design, supporting 10W concurrency.

3. The AI ​​acupoint electrical diagnosis and treatment system for knee osteoarthritis according to claim 1, characterized in that: The data storage (104) uses Mysql database for data storage, a mature data scheduled backup and recovery solution, and combines with mongodb non-relational database to store user and device usage log information; the communication security (105) and data backup (106) use Https secure channel for data transmission, and use data encryption algorithm for secure encryption and backup.

4. The AI ​​acupoint electrical diagnosis and treatment system for knee osteoarthritis according to claim 1, characterized in that: The network connection (107) uses smart phones and other mobile devices to connect and monitor in a dynamic adjustment manner via Bluetooth and is compatible with iOS and Android.

5. The AI ​​acupoint electrical diagnosis and treatment system for knee osteoarthritis according to claim 1, characterized in that: The system principle (201) adopts pulse discharge combined with supercapacitor method to reduce energy consumption, increase equipment standby time, and integrate time-sharing multiplexing mode. The power management module (202) adopts a multifunctional power management SOC with a boost converter, lithium battery charging management, and battery power indication. The human-computer interaction module (203) adopts touch and LED display, wherein the touch has 3 touch buttons for detecting the touch action of a human hand on the external touch button. The driving algorithm (204) adopts a fusion inversion algorithm and a current PID algorithm. The structural design (205) adopts an integrated circuit board.

6. The AI ​​acupoint electrical diagnosis and treatment system for knee osteoarthritis according to claim 1, characterized in that: The medical platform (1001) is composed of role authority, equipment management, administrator management, consultation management, treatment records, user management, mode parameters, medical record management and treatment mode.

7. The AI ​​acupoint electrical diagnosis and treatment system for knee osteoarthritis according to claim 1, characterized in that: The mini-program (1002) consists of authorization login, electroacupuncture control and treatment records.

8. The AI ​​acupoint electrical diagnosis and treatment system for knee osteoarthritis according to claim 1, characterized in that: The device architecture (1003) consists of user authorization, device binding, device parameters, electroacupuncture control, treatment records and data synchronization.

9. The AI ​​acupoint electrical diagnosis and treatment system for knee osteoarthritis according to claim 1, characterized in that: The medical platform (1001), the mini program (1002) and the device architecture (1003) are connected via Bluetooth, and the mini program (1002) is compatible with smart phones.

10. A method for AI acupoint electrical diagnosis and evaluation of knee osteoarthritis, characterized in that: The following steps are involved: S1. First, the patient information is entered into the medical platform (1001), and a diagnosis and treatment plan matching the patient's symptoms is automatically generated through an AI algorithm; S2. Then, the patient enters the medical platform (1001) through the mini program (1002) on the mobile phone and binds personal information to obtain the hospital's diagnosis and treatment plan; S3. Finally, the patient wears the device architecture (1003) to the knee joint according to the obtained diagnosis and treatment plan, and issues diagnosis and treatment instructions through the mini-program (1002). The knee joint chronic disease acupoint electrical stimulation therapeutic device uses electric current pulses to perform acupuncture stimulation treatment on various acupoints of the knee joint.

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