Intelligent balance bar rehabilitation training device

Abstract

The invention relates to the technical field of rehabilitation medical treatment and intelligent control, and provides an intelligent balance bar rehabilitation training device. Existing rehabilitation training equipment is single in adjustment mode, difficult to adapt to individual requirements of different patients, lack of intelligent control and limited in training effect. According to the invention, through cooperative work of the intelligent control system, the sensor group, the Transform model and the PID control algorithm, dynamic adjustment and personalized training of equipment are realized. A sensor collects motion state data of a patient in real time, and an optimal training target state is calculated through a Transform model. The system calculates deviation based on a target state, generates an adjustment signal by using a PID control algorithm, and drives a motor control knob to realize accurate adjustment of the height of the equipment. According to the device, the intelligent level of rehabilitation training is improved, the accuracy and adaptability of the training effect are enhanced, and the device is suitable for scenes such as postoperative rehabilitation, balance training of old people and sports injury recovery.

Description

Technical Field

[0001] The present invention relates to the technical field of rehabilitation equipment, and particularly to an intelligent balance bar rehabilitation training device and its intelligent control system. Background Art

[0002] With the continuous development of rehabilitation medicine and intelligent control technology, intelligent rehabilitation equipment, as an important tool to improve the rehabilitation effect of patients, has received increasing attention. As a common rehabilitation training equipment, the intelligent balance bar plays an important role in helping patients restore their balance ability and enhance their physical strength. However, there are still many deficiencies in the existing intelligent balance bar technology in practical applications, mainly reflected in inaccurate training effects, difficult equipment adjustment, and insufficient comfort and safety during use.

[0003] Traditional balance bar rehabilitation equipment usually relies on mechanical structures to adjust the angle and stability of the equipment. However, during operation, there are often problems such as limited adjustment range and cumbersome operation, resulting in patients being unable to carry out personalized rehabilitation training according to their own needs. At the same time, most of the existing equipment adopts a fixed structure design, lacking intelligent feedback and real-time adjustment functions, and it is difficult to make dynamic adjustments according to the real-time motion state of patients, which limits the improvement of training effects.

[0004] In addition, most of the mechanical systems of existing equipment adopt traditional motor and gear transmission methods, resulting in high noise and friction during operation, affecting the user experience of patients. Especially during long-term use, the problems of equipment wear and aging are more prominent, further affecting the stability and service life of the equipment.

[0005] In recent years, with the development of artificial intelligence and sensor technology, more and more intelligent control systems have been introduced into rehabilitation training equipment, which can provide real-time feedback and adjustment according to the motion data of patients. Nevertheless, there are still significant gaps in the fusion processing of multi-point feedback data, dynamic adjustment control algorithms, and mechanical design optimization in the existing technology, and it is unable to meet the requirements for high-precision and high-stability equipment.

[0006] Therefore, it has become an urgent need to develop an intelligent balance bar rehabilitation training device that can combine an intelligent control system and adjust the angle and stability of the equipment in real time to improve the rehabilitation effect and equipment performance. Summary of the Invention

[0007] The object of the present invention is to provide an intelligent balance bar rehabilitation training device and its intelligent control system. By integrating advanced sensor technology, artificial intelligence algorithms, and motor control systems, it realizes real-time dynamic adjustment, personalized training program generation, and highly precise device adjustment during the balance training of patients, and solves the problems of inaccurate training effects, difficult device adjustment, and insufficient comfort and safety during use in the prior art.

[0008] To achieve the above object, the present invention provides an intelligent balance bar rehabilitation training device, including an intelligent control system, a support rod, and a rod base.

[0009] The intelligent control system includes a memory and a processor. The memory contains an intelligent control system program. When the intelligent control system program is executed by the processor, it includes: obtaining real-time sensor data; using a Transformer model to generate a target state; adjusting the mechanical structure according to the target state; device height adjustment, adjusting the height of the device according to the generated target height to ensure that the patient is in the most suitable training state; performing dynamic adjustment according to the deviation value calculated in real time and applying a PID control algorithm.

[0010] A support rod is fixedly connected to the base. A connecting plate is provided at the bottom end of the support rod. Two connecting rods are slidably connected to the connecting plate. The same connecting block is fixedly connected to the bottoms of the two connecting rods. The connecting block is connected to a second fixator. A connecting belt is fixedly connected to the bottom end of the second fixator. One end of the connecting belt away from the second fixator is fixedly connected to a first fixator. A positioning hole is provided on one of the two connecting rods close to the support rod. A fixing plate is provided inside the connecting plate. A first spring is fixedly connected to the fixing plate. A movable plate is fixedly connected to the side of the first spring away from the fixing plate. A positioning pin is fixedly connected to the side of the movable plate away from the first spring. The positioning pin is slidably connected to the positioning hole. A gear is rotatably connected inside the connecting plate. Teeth adapted to the gear are provided at the bottom of the movable plate, and the movable plate meshes with the gear. A second pulley group is provided inside the support rod. A first pulley group is provided inside the connecting plate. One pulley of the first pulley group is fixedly connected to the gear, and the other pulley is fixedly connected to the second pulley group. A helical gear group is fixedly connected to the pulley located below in the second pulley group. A fixed block is fixedly connected to the support rod. A rotating shaft is rotatably connected inside the fixed block. One end of the rotating shaft is fixedly connected to the helical gear group, and the other end is fixedly connected to a second spring and is provided with a tooth groove. A knob is slidably connected to the fixed block. The knob is fixedly connected to the second spring, and teeth adapted to the tooth groove are provided at the end of the knob close to the rotating shaft.

[0011] The adjustment mechanical structure described above includes equipment height adjustment. According to the deviation between the target height and the current height of the equipment, the height of the equipment is precisely adjusted using the motor control knob.

[0012] The specific steps for the Transformer model to generate the target state include: data input and processing, and target state generation.

[0013] Target state generation includes a feedback mechanism. The specific steps include: calculating the deviation in real time and feeding it back. Each time the sensor data is updated, the system calculates the deviation between the current position and the target state in real time; the calculation of the deviation is through the difference function between the real-time sensor data and the target state value; the deviation value includes parameters such as position, angle, and speed. The specific calculation formula is:

[0014]

[0015] Among them, δ position , δ angle and δ velocity are the position deviation, angle deviation, and speed deviation respectively.

[0016] 5. An intelligent balance bar rehabilitation training device according to claim 1, characterized in that

[0017] The specific steps of the PID control and motor adjustment include: calculating the deviation and generating a control signal. When the target state is determined, the PID control algorithm calculates the adjustment signal in real time according to the deviation between the current equipment state and the target state, and adjusts the angle and height of the equipment. The specific control formula is:

[0018]

[0019] Among them, u(t) is the control signal, K p is the proportionality coefficient, δ position (t) is the current position deviation, K i is the integral coefficient, τ is the integral variable, K d is the differential coefficient, is the rate of change of the position deviation.

[0020] The bottom surface of the base is fixedly connected with a number of universal wheels. Metal plates are fixedly connected to the outer sides of the first fixator and the second fixator, and a number of sensors are connected to the metal plates.

[0021] Through the above technical solutions, the present invention effectively improves the accuracy and effect of the intelligent balance bar in the patient's balance training. At the same time, through the optimized design of the intelligent control system, the flexibility and stability of the equipment are improved, meeting the needs of modern rehabilitation medicine for efficient and personalized training equipment.

[0022] The present invention conducts multi-level optimizations on the overall performance and functional requirements of the intelligent balance bar rehabilitation training device to ensure its efficient and stable operation during the patient's rehabilitation training.

[0023] To improve the stability and adjustment effect of the device, the support rod and the connection system adopt high-strength alloy materials and wear-resistant designs. The surface hardness and abrasion resistance are enhanced through heat treatment processes. Sealed bearings are built into the connection parts, and an automatic lubrication device is equipped to ensure that the mechanical system can maintain stability for a long time under high-load operation, reducing wear and resistance. The precise fit between the support rod and the connection system can effectively prevent structural offset of the device during training.

[0024] Furthermore, the surface of the knob of the device adopts high-strength composite materials, which have high wear resistance and are designed with anti-slip textures to enhance the stability of knob operation and avoid adjustment errors caused by improper operation. The integrated design of the motor control system and the mechanical transmission structure of the knob can accurately transmit adjustment signals and improve the adjustment efficiency of the device.

[0025] To ensure the intelligent control accuracy and adaptability of the device, the sensor system integrates multiple groups of high-sensitivity acceleration sensors and pressure sensors. These sensors are installed at key force-bearing positions of the device and perform real-time data acquisition and analysis through a signal processing module. The signal processing module adopts high-frequency filtering technology and combines fuzzy logic algorithms to filter out environmental noise interference and achieve high-precision measurement of the patient's motion state. The sensor data can be transmitted to the intelligent control system in real time for dynamic adjustment during the training process.

[0026] Preferably, the support system adopts a modular structure design. The functional components are fixed through bolt connections and positioning pins, which can not only ensure the strength of the overall framework but also facilitate the transportation, installation, and maintenance of the device. The device frame material is selected as lightweight high-strength steel alloy, and the structure is optimized through finite element analysis to ensure the stability and anti-deformation ability of the frame during operation.

[0027] Furthermore, the adjustment system of the device realizes precise control through the intelligent control system and motor drive. The motor is equipped with a high-precision position sensor, which can monitor the position and angle of the device in real time to ensure the safety and stability of the patient during training. During the training process, the device adjusts the angles and support forces of each part according to real-time data feedback to achieve the best training effect.

[0028] Through the above design optimizations, the intelligent balance bar rehabilitation training device of the present invention can significantly improve the accuracy and efficiency of the rehabilitation training process, enhance the stability and adaptability of the device, and meet the requirements of modern rehabilitation medicine for high-efficiency and intelligent training devices. Brief Description of the Drawings

[0029] To more clearly illustrate the technical solutions in the embodiments or exemplifications of the present invention, the following will briefly introduce the drawings required for use in the embodiments or exemplifications. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to the ones shown in these drawings.

[0030] Figure 1 It is a schematic external view of an intelligent balance bar rehabilitation training device

[0031] Figure 2 It is a schematic structural view of an intelligent balance bar rehabilitation training device

[0032] Figure 3 It is an enlarged view of part A of the schematic structural view of an intelligent balance bar rehabilitation training device

[0033] Figure 4 It is an enlarged view of part B of the schematic structural view of an intelligent balance bar rehabilitation training device

[0034] Figure 5 It is a topological structure diagram of an intelligent balance bar rehabilitation training device

[0035] Figure 6 It is a data flow diagram of an intelligent balance bar rehabilitation training device

[0036] Figure 7 It is a timing diagram of an intelligent balance bar rehabilitation training device

[0037] Legend Explanation

[0038] In the figure: 1. Support rod; 2. Base; 3. Universal wheel; 4. First fixator; 5. Sensor; 6. Connecting belt; 7. Second fixator; 8. Connecting block; 9. Connecting rod; 10. Positioning hole; 11. Positioning pin; 12. Helical gear; 13. Movable plate; 14. First spring; 15. Gear; 16. First pulley group; 17. Second pulley group; 18. Second spring; 19. Knob.

[0039] The realization of the purpose, functional features and advantages of the present invention will be further described in combination with the embodiments with reference to the drawings. Specific Embodiments

[0040] The following will further describe the present invention in combination with the drawings and embodiments.

[0041] It should be noted that the following detailed description is exemplary and is intended to provide further description of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present application belongs.

[0042] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular forms are also intended to include the plural forms. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they specify the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0043] Refer to Figure 1-4 , Figure 1 The device shown is for one side of the balance bar. When using this device, first place the equipment on a stable ground and ensure that the universal wheels 3 of the base are locked to prevent sliding during training. The patient stands in the designated area of the equipment and relies on the first fixator 4 or the second fixator 7 to provide basic support. The pressure sensors on the fixators will monitor the patient's support force distribution in real time to ensure the accuracy of data collection. After the equipment is started, the intelligent control system begins to work. First, it obtains the patient's real-time motion data through sensors, including information such as standing posture angle, support force distribution, and body tilt state, and inputs this data into the Transformer model for calculation to generate the target state that is most suitable for the patient at present. After the target state is determined, the intelligent control system calculates the deviation between the current position and the target state, and generates an adjustment signal through the PID control algorithm. The motor drives the knob 19 for height adjustment to gradually approach the optimal training height of the equipment. At the same time, the mechanical transmission system optimizes the equipment angle and support force according to the calculation results of the intelligent control system. Specifically, the knob 19 drives the rotating shaft to rotate through the internal gear transmission mechanism of it. The rotating shaft is connected to a set of bevel gears 12 to transmit the power to the first pulley set 16. At the same time, the pulley 16 is connected to the second pulley set 17 to make the entire adjustment mechanism move synchronously, thereby precisely controlling the angle and support force of the equipment to meet the different training needs of the patient. During the training process, the equipment will continuously obtain sensor data and calculate the deviation value in real time. If the patient's training state changes, the intelligent control system will re-evaluate the target state and dynamically adjust the equipment parameters to ensure that the patient is always in the best training state. After the training is completed, the equipment will automatically adjust back to the initial position, and all training data will be stored in the memory for the patient or rehabilitation physician to analyze.

[0044] Refer to Figure 5 , which is a schematic diagram of the system architecture of the intelligent balance bar rehabilitation training device of the present invention, showing the overall working framework of the device. The device mainly consists of an intelligent control system, a sensor group, a Transformer model, and a balance bar entity.

[0045] The sensor group includes multiple sensors, which are installed on the fixed structure of the device, the patient contact part and the key components of the equipment, and are used to collect the patient's motion state data in real time. The data of these sensors is transmitted to the intelligent control system. The processor in the intelligent control system analyzes the data and calls the Transformer model stored in the memory. This model analyzes the patient's training state based on the sensor data and calculates the optimal target training state. Subsequently, the intelligent control system generates corresponding control instructions and adjusts the height, angle and support force of the balance bar entity through control signals to ensure that the equipment always meets the patient's training needs. Through this system architecture, the equipment can achieve data-driven dynamic adjustment, combine artificial intelligence calculation to personalize the rehabilitation training parameters, and improve the scientificity and accuracy of rehabilitation training.

[0046] Refer to Figure 6 , which is the software flow chart of the intelligent balance bar rehabilitation training device of the present invention and describes the operation logic of the software system. The core software modules of this system include: sensor data acquisition, data input and processing, target state generation, feedback mechanism, real-time calculation of deviation, PID control algorithm, control signal generation, motor adjustment and equipment state adjustment.

[0047] During the software operation, first, the real-time data of the sensors is acquired, and the data is formatted and noise-filtered. Subsequently, the data is input into the Transformer model to calculate the optimal training target state of the patient. After the target state is determined, the system enters the feedback mechanism to calculate the deviation between the current equipment state and the target state. The PID control algorithm dynamically adjusts the deviation and generates corresponding control signals to adjust the motor. After the motor executes the control signal, it drives the mechanical structure to complete the automatic adjustment of the equipment height, angle and support force to ensure that the equipment meets the patient's current training needs. This software process adopts a closed-loop control architecture, combines artificial intelligence prediction and PID real-time adjustment to ensure the accuracy and stability of equipment adjustment.

[0048] Refer to Figure 7, which is the timing diagram of the intelligent balance bar rehabilitation training device of the present invention, and details the data interaction and operation sequence among the system modules. First, the patient initializes the sensor through the device and stands on the device. Subsequently, the system starts to collect real-time sensor data and transmits the data to the intelligent control system. The intelligent control system preprocesses the data and calls the Transformer model to calculate the target state. After the target state calculation is completed, the system compares it with the current device state, calculates the error, and uses the PID control algorithm to optimize and adjust the parameters. During the device adjustment process, the system continuously performs state feedback. If it detects a change in the patient's motion state, the system will recalculate the data and adjust the control parameters to enable the device to adapt to the new training requirements. Throughout the process, all modules work together to achieve data-driven intelligent adjustment, providing precise and personalized rehabilitation training support for the patient. This timing diagram intuitively reflects the operation sequence and interaction relationship of each module, ensuring the high efficiency and stability of the system operation.

Claims

1. An intelligent balance bar rehabilitation training device, including an intelligent control system, a support rod (1) and a base (2), characterized in that: The intelligent control system includes a memory and a processor. The memory contains an intelligent control system program. When the intelligent control system program is executed by the processor, it includes: acquiring real-time sensor data; using a Transformer model to generate a target state; adjusting the mechanical structure according to the target state; adjusting the device height, adjusting the height of the device according to the generated target height to ensure that the patient is in the most suitable training state; dynamically adjusting according to the deviation value calculated in real time; applying a PID control algorithm; The base (2) is fixedly connected with a support rod (1). A connecting plate is provided at the bottom end of the support rod (1). Two connecting rods (9) are slidably connected to the connecting plate. The bottoms of the two connecting rods (9) are fixedly connected to the same connecting block (8). The connecting block (8) is connected to a second fixator (7). The bottom end of the second fixator (7) is fixedly connected to a connecting belt (6). One end of the connecting belt (6) far from the second fixator (7) is fixedly connected to a first fixator (4). A positioning hole (10) is provided on one of the two connecting rods (9) close to the support rod. A fixing plate is provided in the connecting plate. A first spring (14) is fixedly connected to the fixing plate. A movable plate (13) is fixedly connected to the side of the first spring (14) far from the fixing plate. A positioning pin (11) is fixedly connected to the side of the movable plate (13) far from the first spring (14). The positioning pin (11) is slidably connected to the positioning hole (10). A gear (15) is rotatably connected in the connecting plate. Teeth adapted to the gear (15) are provided at the bottom of the movable plate (13), and the movable plate (13) meshes with the gear (15). A second pulley group (17) is provided in the support rod (1). A first pulley group (16) is provided in the connecting plate. One pulley in the first pulley group (16) is fixedly connected to the gear (15), and the other pulley is fixedly connected to the second pulley group (17). A set of helical gears (12) is fixedly connected to the pulley located below in the second pulley group (17). A fixed block is fixedly connected to the support rod (1). A rotating shaft is rotatably connected in the fixed block. One end of the rotating shaft is fixedly connected to the set of helical gears (12), and the other end is fixedly connected to a second spring (18) and is provided with a tooth groove. A knob (19) is slidably connected to the fixed block. The knob (19) is fixedly connected to the second spring (18), and teeth adapted to the tooth groove are provided at one end of the knob (19) close to the rotating shaft.

2. The intelligent balance bar rehabilitation training device according to claim 1, wherein, The adjusted mechanical structure includes: adjusting the device height, and precisely adjusting the height of the device by using a motor to control the knob (19) according to the deviation between the target height and the current height of the device.

3. An intelligent balance bar rehabilitation training device according to claim 1, characterized in that, The specific steps for the Transformer model to generate the target state include: data input and processing, and target state generation.

4. The intelligent balance bar rehabilitation training device according to claim 3, wherein, The generation of the target state includes a feedback mechanism, and the specific steps are as follows: calculating the deviation in real time and feeding it back. Each time the sensor data is updated, the system calculates the deviation between the current position and the target state in real time; the calculation of the deviation is through the difference function between the real-time sensor data and the target state value; the deviation value includes position, angle, and speed, and the specific calculation formula is: Among them, δ position , δ angle and δ velocity are the position deviation, the angle deviation, and the speed deviation respectively.

5. An intelligent balance bar rehabilitation training device according to claim 1, characterized in that, The specific steps of the PID control and motor adjustment are as follows: calculating the deviation and generating a control signal. After the target state is determined, the PID control algorithm calculates the adjustment signal in real time according to the deviation between the current device state and the target state, and adjusts the angle and height of the device; the specific control formula is: where u(t) is the control signal, K p is the proportional coefficient, δ position (t) is the current position deviation, K i is the integral coefficient, τ is the integral variable, K d is the differential coefficient, is the rate of change of the position deviation.

6. The intelligent balance bar rehabilitation training device according to claim 1, wherein, A plurality of universal wheels (3) are fixedly connected to the bottom surface of the base (2), and a locking device is provided on the universal wheel (3).

7. An intelligent balance bar rehabilitation training device according to claim 1, characterized in that, Metal plates are fixedly connected to the outsides of the first fixer (4) and the second fixer (7), and a plurality of sensors (5) are connected to the metal plates.

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