A smart management system for rehabilitation training based on dual-end collaboration

Abstract

This utility model discloses a rehabilitation training intelligent management system based on dual-end collaboration, including rehabilitation training equipment and medical care management equipment, as well as patient-end training monitoring equipment and communication connection equipment. The patient-end training monitoring equipment is connected to the medical care management equipment through the communication connection equipment and is also connected to the rehabilitation training equipment. The patient-end training monitoring equipment includes sensor groups for the affected and healthy sides, and a synchronization device that connects all sensors and signal processing units through a synchronization signal interface to construct hardware-level synchronization timing. The main controller connects the synchronization device, signal processing unit, wireless communication unit, and equipment control device to form a complete control link. This utility model, through its unique hardware connection architecture, realizes synchronous acquisition of multi-source physiological signals, remote data transmission, and precise equipment control, effectively solving the problem of inaccurate data timing and providing a reliable hardware foundation for remote collaborative rehabilitation.

Description

Technical Field

[0001] This utility model relates to the field of rehabilitation training equipment, specifically to a rehabilitation training intelligent management system based on dual-end collaboration. Background Technology

[0002] With the accelerating aging of society and the rising incidence of cardiovascular and cerebrovascular diseases, the number of patients with motor dysfunction such as hemiplegia and sequelae of stroke continues to increase. Traditional rehabilitation treatment mainly relies on one-on-one guidance from physicians, which suffers from problems such as strained medical resources, long rehabilitation cycles, and a lack of professional guidance for home rehabilitation. Currently available rehabilitation training technologies have the following limitations: First, at the data acquisition level, existing systems generally lack effective multi-source signal synchronization mechanisms. Most devices use software post-processing to time-align the data from each sensor, but because electromyography, angle, and force sensors have different sampling frequencies and transmission delays, there is a significant timing discrepancy (usually >10ms) between the acquired data from the affected and healthy sides. This timing misalignment introduces errors into the phase comparison analysis of bilateral movements, failing to meet the accuracy requirements for data synchronization in rehabilitation assessments.

[0003] Secondly, in terms of system architecture, existing solutions often design functional modules such as sensing acquisition, signal processing, and device control in a decentralized manner, lacking an effective coordination mechanism. This decentralized architecture leads to increased system response latency, making it difficult to achieve adaptive adjustment of training parameters based on real-time physiological signals. Furthermore, the lack of a unified time reference between modules further exacerbates the data synchronization problem.

[0004] Furthermore, there are shortcomings in reliability design. Traditional equipment lacks a robust power management mechanism, and power outages during training may lead to data loss or equipment malfunction, affecting training safety and continuity. Especially in home rehabilitation scenarios, a stable power supply is often difficult to guarantee, which places higher demands on the system's power redundancy design.

[0005] In summary, existing rehabilitation training systems suffer from technical bottlenecks in areas such as multi-source signal synchronous acquisition, real-time control response, and system reliability, hindering the development of precise rehabilitation training. Therefore, there is a need for an intelligent rehabilitation management system that can solve the signal synchronization problem at the hardware level and possesses reliable power supply and rapid response capabilities. Utility Model Content

[0006] The purpose of this invention is to overcome the shortcomings of the existing technology and provide a rehabilitation training intelligent management system based on dual-end collaboration, including rehabilitation training equipment, medical staff management equipment, and patient-end training monitoring equipment and communication connection equipment. The communication connection device is connected to the patient-side training and monitoring device and the medical staff-side management device. The patient-side training and monitoring device is connected to the rehabilitation training device. The patient-side training and monitoring device includes a sensor group on the affected side, a sensor group on the healthy side, a synchronization device, a signal processing unit, a main controller, a wireless communication unit, a device control device, and a power module. The synchronization device, signal processing unit, wireless communication unit, and device control device are respectively connected to the main controller; the affected side sensor group, the healthy side sensor group, and the signal processing unit are respectively connected to the synchronization device; the device control device is connected to the rehabilitation training device; and the wireless communication unit is connected to the communication connection device. The affected-side sensor group includes a first electromyography (EMG) sensor, a first angle sensor, and a first force sensor, which are respectively connected to the synchronization device. The healthy side sensor group includes a second electromyography (EMG) sensor, a second angle sensor, and a second force sensor, which are respectively connected to the synchronization device. The synchronization device includes a clock source, a pulse generator, a timestamp encoder, and a synchronization signal interface. The pulse generator, timestamp encoder, and main controller are respectively connected to the clock source. The pulse generator and timestamp encoder are respectively connected to the main controller. The signal processing unit, pulse generator, timestamp encoder, first electromyography sensor, first angle sensor, first force sensor, second electromyography sensor, second angle sensor, and second force sensor are respectively connected to the synchronization signal interface. The main controller includes a microcontroller and a storage component. The wireless communication unit, clock source, pulse generator, timestamp encoder, device control device, and storage component are respectively connected to the microcontroller.

[0007] Preferably, the power module includes a rechargeable battery, a power converter, and a charging interface. The charging interface is connected to the rechargeable battery for charging the rechargeable battery. The rechargeable battery, a first electromyography sensor, a first angle sensor, a first force sensor, a second electromyography sensor, a second angle sensor, a second force sensor, a clock source, a pulse generator, a timestamp encoder, a signal processing unit, a microcontroller, a storage component, a wireless communication unit, and a device control device are respectively connected to the power converter.

[0008] Preferably, the patient-side training monitoring device further includes a UPS and a power switching controller. The input terminal of the UPS is connected to an external AC power source, and the output terminal is connected to the first input terminal of the power switching controller. The rechargeable battery is connected to the second input terminal of the power switching controller, and the output terminal of the power switching controller is connected to the power converter. Preferably, the signal processing unit includes a filter, a signal amplifier, and an analog-to-digital converter. The signal amplifier is connected to the filter and the analog-to-digital converter, the analog-to-digital converter is connected to the storage component, and the filter is connected to the synchronization signal interface.

[0009] Preferably, the main controller uses an STM32H743 microprocessor, and the storage component uses a UC260 flash memory chip.

[0010] Preferably, the first and second electromyography (EMG) sensors are both ADS1298 EMG sensors, the first and second angle sensors are both MPU-6050 angle measuring devices, and the first and second force sensors are both LSB200 or LSB500 miniature force sensors.

[0011] Preferably, the clock source is a crystal oscillator, and the timestamp encoder is an encoder of model EL5102.

[0012] Preferably, the wireless communication unit uses a Bluetooth 5.0 chip with a built-in PCB antenna, and the communication connection device includes a Bluetooth gateway, which is connected to the Bluetooth 5.0 chip with the built-in PCB antenna via the BLE protocol.

[0013] Preferably, the device control unit includes a control component and an execution component. The main controller and the execution component are connected to the control component, and the execution component is connected to the rehabilitation training equipment.

[0014] Preferably, the control component uses a DC servo driver of model MADDT1207003, and the execution component uses a DC servo motor of model MSMD022G1V.

[0015] The beneficial effects of this utility model are: 1. Achieving high-precision synchronous acquisition of multi-source signals: Through a hardware-level synchronization device, a unified clock reference is provided for all sensors, enabling microsecond-level synchronous acquisition of electromyography, angle, and force signals on the affected and healthy sides, fundamentally eliminating data timing errors and ensuring the accuracy of motion phase analysis.

[0016] 2. Redundant power supply ensures continuous system operation: Through the dual power supply design of rechargeable battery and UPS, and with the power switching controller, automatic and seamless switching is performed when the main power supply is abnormal, ensuring continuous power supply to core modules such as clock source and main controller, avoiding data loss and control interruption; 3. Enhance system integration and remote collaboration capabilities: Through optimized hardware architecture and professional component selection, achieve efficient collaboration among multiple modules; combine with low-power wireless communication solutions to establish a stable and reliable data link, providing technical support for remote rehabilitation assessment and guidance. Attached Figure Description

[0017] Figure 1 This is a system architecture block diagram of an intelligent management system for rehabilitation training based on dual-end collaboration. Figure 2 This is a schematic diagram of an embodiment of an intelligent management system for rehabilitation training based on dual-end collaboration; Figure 3 This is a schematic diagram of another embodiment of a rehabilitation training intelligent management system based on dual-end collaboration. Detailed Implementation

[0018] The technical solution of this utility model is described in further detail below with reference to the accompanying drawings, but the scope of protection of this utility model is not limited to the following description.

[0019] The features and performance of this utility model will be further described in detail below with reference to the embodiments.

[0020] In some embodiments, such as Figure 1 As shown, a smart rehabilitation training management system based on dual-terminal collaboration includes rehabilitation training equipment, medical staff management equipment, and patient-side training monitoring equipment and communication connection equipment. The communication connection device is connected to the patient-side training and monitoring device and the medical staff-side management device; the patient-side training and monitoring device is connected to the rehabilitation training device. The patient-side training and monitoring device includes a sensor group on the affected side, a sensor group on the healthy side, a synchronization device, a signal processing unit, a main controller, a wireless communication unit, a device control device, and a power module. The synchronization device, signal processing unit, wireless communication unit, and device control device are respectively connected to the main controller; the affected side sensor group, the healthy side sensor group, and the signal processing unit are respectively connected to the synchronization device; the device control device is connected to the rehabilitation training device; and the wireless communication unit is connected to the communication connection device. The affected-side sensor group includes a first electromyography (EMG) sensor, a first angle sensor, and a first force sensor, which are respectively connected to the synchronization device. The healthy side sensor group includes a second electromyography (EMG) sensor, a second angle sensor, and a second force sensor, which are respectively connected to the synchronization device. The synchronization device includes a clock source, a pulse generator, a timestamp encoder, and a synchronization signal interface. The pulse generator, timestamp encoder, and main controller are respectively connected to the clock source. The pulse generator and timestamp encoder are respectively connected to the main controller. The signal processing unit, pulse generator, timestamp encoder, first electromyography sensor, first angle sensor, first force sensor, second electromyography sensor, second angle sensor, and second force sensor are respectively connected to the synchronization signal interface. The main controller includes a microcontroller and a storage component. The wireless communication unit, clock source, pulse generator, timestamp encoder, device control device, and storage component are respectively connected to the microcontroller.

[0021] The intelligent rehabilitation training management system based on dual-end collaboration provided in this embodiment achieves efficient and precise rehabilitation training management by constructing a hierarchical and closely collaborative hardware architecture. Specifically, the system takes the patient-end training monitoring device as its core, and connects it to the sensor groups (both including electromyography, angle, and force sensors) on the affected and healthy sides through its internal synchronization device (integrating a clock source, pulse generator, and timestamp encoder), ensuring microsecond-level synchronization and timestamp consistency of bilateral physiological and motor signal acquisition. This synchronized data is sent to the main controller (microcontroller and storage components) via the signal processing unit, and all synchronized data is uploaded to the medical staff-end management device in real time through the wireless communication unit and communication connection device.

[0022] The patient-side training and monitoring device is further configured to: receive control commands from the medical care management device via the wireless communication unit; and adjust the operating parameters of the rehabilitation training device via the device control device according to the received commands. Thus, the patient-side training and monitoring device protected in this embodiment, through its unique hardware structure, constitutes a complete physical entity with high-precision synchronous data acquisition, remote data transmission, and remote command execution capabilities, providing a hardware foundation for remote, collaborative, and precise rehabilitation training management.

[0023] In some embodiments, the power module includes a rechargeable battery, a power converter, and a charging interface. The charging interface is connected to the rechargeable battery for charging the rechargeable battery. The rechargeable battery, a first electromyography sensor, a first angle sensor, a first force sensor, a second electromyography sensor, a second angle sensor, a second force sensor, a clock source, a pulse generator, a timestamp encoder, a signal processing unit, a microcontroller, a storage component, a wireless communication unit, and a device control device are respectively connected to the power converter.

[0024] In this embodiment, the power module adopts a complete power solution including a rechargeable battery, a power converter, and a charging interface, providing a unified and stable power supply to all core units of the system through a centralized power supply topology. This design has dual advantages: firstly, the rechargeable battery and charging interface ensure the portability and mobile operation of the patient-end monitoring device in various rehabilitation scenarios such as home and community, meeting the core requirement of rehabilitation training for device flexibility; secondly, the centralized power supply architecture of a single power converter eliminates the potential difference and common-mode noise problems inherent in multi-power supply systems at the source, providing a clean power environment for the acquisition of high-precision bioelectrical signals such as electromyography signals, angle data, and force signals, significantly improving the accuracy and signal-to-noise ratio of data acquisition, and laying a solid foundation for subsequent signal processing and synchronous analysis.

[0025] In some embodiments, such as Figure 2 As shown, the patient-side training and monitoring device also includes a UPS and a power switching controller. The input terminal of the UPS is connected to an external AC power source, and the output terminal is connected to the first input terminal of the power switching controller. The rechargeable battery is connected to the second input terminal of the power switching controller, and the output terminal of the power switching controller is connected to the power converter.

[0026] In this embodiment, a hierarchical redundant power supply system is constructed by introducing a UPS and a power switching controller, forming a dual power supply guarantee mechanism of "rechargeable battery-UPS". This design further enhances the system's fault tolerance and continuous operational reliability on the basis of the original centralized power supply. When the rechargeable battery is unexpectedly disconnected or depleted, the power switching controller can automatically and seamlessly switch to the UPS power supply link, ensuring that the two most core functional units, the clock source and the microcontroller, operate uninterruptedly. This redundancy design achieves two key protections: first, it maintains the core time reference of the system's high-precision synchronization mechanism without loss, ensuring the continuity of data acquisition time; second, it prevents system crashes, data loss, or abnormal shutdowns caused by sudden power outages of the microcontroller, ensuring the integrity of training data and the safety of system operation. This protection mechanism built at the power supply level fundamentally improves the reliability and patient safety of the entire rehabilitation training management system in real-world usage environments.

[0027] In some embodiments, such as Figure 3 As shown, the signal processing unit includes a filter, a signal amplifier, and an analog-to-digital converter. The signal amplifier is connected to the filter and the analog-to-digital converter. The analog-to-digital converter is connected to the storage component. The filter is connected to the synchronization signal interface.

[0028] In this embodiment, a signal processing pipeline consisting of filters, signal amplifiers, and analog-to-digital converters (ADCs) is constructed to achieve precise conditioning and efficient digitization of the original sensor signals. Specifically, the filters first remove environmental noise and power frequency interference from the signal; the signal amplifier amplifies the amplitude of the purified useful signal; and finally, the ADC converts the analog signal to a digital signal and writes it to the storage unit. First, through the synergistic effect of filtering and amplification, the signal-to-noise ratio and fidelity of electromyography, angle, and force sensor signals are significantly improved, providing a high-quality data foundation for subsequent analysis. Second, the entire processing flow begins with a direct connection to the synchronization signal interface, ensuring that all processed signals are included in unified timing management from the entry point, guaranteeing precise synchronization of data in the time dimension. Finally, through the direct interface between the ADC and the storage unit, the standardized storage of the conditioned digital signal is achieved, providing real-time and reliable data support for the subsequent device control of the microcontroller. From the three levels of quality, synchronization, and availability, a solid data foundation is laid for the precise monitoring and intelligent control of the entire rehabilitation training system.

[0029] In some embodiments, the main controller employs an STM32H743 microprocessor, and the storage component uses a UC260 flash memory chip. The STM32H743 features a high-performance ARM Cortex-M7 core and rich peripheral interfaces, providing powerful computing capabilities to support complex real-time signal processing and multi-task collaboration. Simultaneously, the UC260 flash memory chip offers large capacity and high read / write speeds, providing stable and reliable storage for the massive amounts of synchronous data generated during long-term training, thus jointly ensuring the real-time performance and reliability of the system's data processing and response.

[0030] In some embodiments, both the first and second electromyography (EMG) sensors are ADS1298 EMG sensors, which have the advantages of high integration, low noise, and multi-channel synchronous sampling capability, enabling accurate acquisition of weak EMG signals. Both the first and second angle sensors are MPU-6050 angle measuring devices, which integrate a three-axis gyroscope and a three-axis accelerometer, enabling real-time and high-precision capture of joint angle changes and motion postures. Both the first and second force sensors are LSB200 or LSB500 miniature force sensors, which feature a miniaturized design and high sensitivity, allowing direct and accurate measurement of the mechanical load applied during training. This synergistic configuration of specialized sensors provides the system with a highly reliable, multimodal foundation for physiological and motor signal acquisition, thereby ensuring the accuracy and comprehensiveness of rehabilitation training assessment and control.

[0031] In some embodiments, the clock source is a crystal oscillator, and the timestamp encoder is an EL5102 encoder. The advantage is that the crystal oscillator can provide a high-precision, high-stability reference clock signal, establishing a unified time reference for the entire system. Simultaneously, the EL5102 encoder possesses professional high-resolution time stamping and synchronization management capabilities. Working together, these two technologies can achieve microsecond-level precise synchronization of all sensor data at the hardware level, thereby avoiding errors in the timeline of multi-source data streams and providing a precise time reference for subsequent device control. In some embodiments, the wireless communication unit employs a Bluetooth 5.0 chip with a built-in PCB antenna, and the communication connection device includes a Bluetooth gateway. The Bluetooth gateway connects to the Bluetooth 5.0 chip with the built-in PCB antenna via the BLE protocol. The advantage is that this combination fully utilizes the low power consumption, strong anti-interference capability, and high transmission rate characteristics of Bluetooth 5.0 technology, and the built-in PCB antenna simplifies the hardware design. By connecting to a dedicated gateway via the BLE protocol, a stable, efficient, and low-latency wireless data link can be established in complex home or clinical environments, thereby reliably uploading real-time monitoring data from the patient to the medical staff, meeting the stringent requirements of remote monitoring for communication quality and continuity.

[0032] In some embodiments, the device control unit includes a control component and an execution component. The main controller and the execution component are connected to the control component, and the execution component is connected to the rehabilitation training device. The advantage of this hierarchical control architecture is that it achieves a clear division of functions: the control component acts as the command center, responsible for parsing the logical commands of the main controller; the execution component acts as the power output, directly driving the rehabilitation device. This setup enables effective electrical isolation and power amplification between the main controller and the high-power actuator, protecting the core controller while ensuring that control commands are executed accurately and powerfully, thus improving the safety and reliability of the entire system.

[0033] In some embodiments, the control component uses a DC servo driver of model MADDT1207003, and the execution component uses a DC servo motor of model MSMD022G1V. The advantage is that the MADDT1207003 driver can provide precise current and position loop control, while the MSMD022G1V motor has high torque density and fast dynamic response characteristics. The deep matching of the two can realize extremely precise, smooth and rapid control of the speed, position and output torque of the rehabilitation training equipment, thereby directly ensuring the accuracy of the rehabilitation training action execution and the safety of the patient.

[0034] The above description is only a preferred embodiment of the present utility model. It should be understood that the present utility model is not limited to the form disclosed herein. The number of sensors or the communication method can be adjusted according to actual rehabilitation needs. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present utility model should be included within the protection scope of the present utility model.

Claims

1. A double-end cooperative-based intelligent management system for rehabilitation training, comprising a rehabilitation training device and a medical care end management device, characterized in that, It also includes patient-side training and monitoring equipment, and communication connection equipment. The communication connection device is connected to the patient-side training and monitoring device and the medical staff-side management device; the patient-side training and monitoring device is connected to the rehabilitation training device. The patient-side training and monitoring device includes a sensor group on the affected side, a sensor group on the healthy side, a synchronization device, a signal processing unit, a main controller, a wireless communication unit, a device control device, and a power module. The synchronization device, signal processing unit, wireless communication unit, and device control device are respectively connected to the main controller; the affected side sensor group, the healthy side sensor group, and the signal processing unit are respectively connected to the synchronization device; the device control device is connected to the rehabilitation training device; and the wireless communication unit is connected to the communication connection device. The affected-side sensor group includes a first electromyography (EMG) sensor, a first angle sensor, and a first force sensor, which are respectively connected to the synchronization device. The healthy side sensor group includes a second electromyography (EMG) sensor, a second angle sensor, and a second force sensor, which are respectively connected to the synchronization device. The synchronization device includes a clock source, a pulse generator, a timestamp encoder, and a synchronization signal interface. The pulse generator, timestamp encoder, and main controller are respectively connected to the clock source. The pulse generator and timestamp encoder are respectively connected to the main controller. The signal processing unit, pulse generator, timestamp encoder, first electromyography sensor, first angle sensor, first force sensor, second electromyography sensor, second angle sensor, and second force sensor are respectively connected to the synchronization signal interface. The main controller includes a microcontroller and a storage component. The wireless communication unit, clock source, pulse generator, timestamp encoder, device control device, and storage component are respectively connected to the microcontroller. 2.The dual-end collaborative rehabilitation training intelligent management system according to claim 1, characterized in that, The power module includes a rechargeable battery, a power converter, and a charging interface. The charging interface is connected to the rechargeable battery for charging the rechargeable battery. The rechargeable battery, a first electromyography sensor, a first angle sensor, a first force sensor, a second electromyography sensor, a second angle sensor, a second force sensor, a clock source, a pulse generator, a timestamp encoder, a signal processing unit, a microcontroller, a storage component, a wireless communication unit, and a device control device are all connected to the power converter. 3.The dual-end collaborative rehabilitation training intelligent management system according to claim 2, characterized in that, The patient-side training and monitoring device also includes a UPS and a power switching controller. The input of the UPS is connected to an external AC power source, and the output is connected to the first input of the power switching controller. The rechargeable battery is connected to the second input of the power switching controller, and the output of the power switching controller is connected to the power converter. 4.The dual-end collaborative rehabilitation training intelligent management system according to claim 1, characterized in that, The signal processing unit includes a filter, a signal amplifier, and an analog-to-digital converter. The signal amplifier is connected to the filter and the analog-to-digital converter, the analog-to-digital converter is connected to the storage component, and the filter is connected to the synchronization signal interface.

5. The intelligent management system for rehabilitation training based on double-end cooperation according to claim 1, characterized in that, The main controller uses an STM32H743 microprocessor, and the storage component uses a UC260 flash memory chip.

6. The intelligent management system for rehabilitation training based on dual-end collaboration according to claim 1, characterized in that, Both the first and second electromyography (EMG) sensors are ADS1298 EMG sensors, both the first and second angle sensors are MPU-6050 angle measuring devices, and both the first and second force sensors are LSB200 or LSB500 miniature force sensors.

7. The intelligent management system for rehabilitation training based on dual-end collaboration according to claim 1, characterized in that, The clock source uses a crystal oscillator, and the timestamp encoder uses an encoder of model EL5102.

8. The intelligent management system for rehabilitation training based on dual-end collaboration according to claim 1, characterized in that, The wireless communication unit uses a Bluetooth 5.0 chip with a built-in PCB antenna, and the communication connection device includes a Bluetooth gateway, which is connected to the Bluetooth 5.0 chip with the built-in PCB antenna via the BLE protocol.

9. The intelligent management system for rehabilitation training based on dual-end collaboration according to claim 1, characterized in that, The equipment control device includes a control component and an execution component. The main controller and the execution component are connected to the control component, and the execution component is connected to the rehabilitation training equipment.

10. The intelligent management system for rehabilitation training based on dual-end collaboration according to claim 9, characterized in that, The control component uses a DC servo driver of model MADDT1207003, and the execution component uses a DC servo motor of model MSMD022G1V.

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