Wearable mirror image rehabilitation system based on force feedback

Abstract

The invention belongs to the field of rehabilitation medical instruments, and provides a wearable mirror image rehabilitation system based on force feedback, which is used for bilateral coordination rehabilitation training of stroke hemiplegic patients. The system is composed of a wearable rehabilitation manipulator end, a mirror image glove end and a driving control and acquisition integrated module. The mirror image glove collects an uninjured side muscle force value, drives the injured side rehabilitation manipulator to do mirror image motion, and dynamically adjusts the rotating speed of a motor through a fuzzy PID double-closed-loop control algorithm, so that the difference value between the injured side muscle force and the uninjured side is stabilized within the range of 0.5-3N. Innovation points comprise that a force feedback mechanism is adopted to evaluate the active participation degree, and the rehabilitation effect is quantified through the muscle force difference of the affected and healthy side; a double-closed-loop control algorithm is combined with gravity compensation, so that the accuracy of auxiliary force is improved; the visualization module displays a muscle force comparison histogram and a historical data broken line graph in real time, and supports a personalized training scheme. The system is integrated on the STM32U575 single-chip microcomputer, the size is reduced, and delay is reduced. Compared with traditional angle sensor rehabilitation equipment, the degree of participation of active training is enhanced through force feedback, the rehabilitation effect is optimized in combination with dynamic data monitoring, and the device has the advantages of being portable and intelligent.

Description

Technical Field

[0001] The present invention relates to the field of rehabilitation medical devices, and particularly to a wearable mirror rehabilitation system based on force feedback. Background Art

[0002] Stroke is an acute cerebrovascular disease, and its pathogenic mechanism is that the blood vessels in the brain are blocked or ruptured during blood circulation, causing damage to brain tissues and nerves. According to the latest epidemiological survey data, the number of newly added stroke patients in China each year is 2.8 million, and the number of patients who died due to stroke is close to 1.5 million. Hemiplegia is a common sequela after stroke, manifested as the asymmetry of the motor function of the bilateral limbs of the patient. The injury of the residual limb may lead to the disorder of the bilateral hand coordination function, and further affect the functional balance between the cerebral hemispheres. At present, most of the existing rehabilitation robots adopt a passive training mode, and the movement guidance for patients is completely provided externally, and patients rarely participate in the whole treatment process. This passive training mode not only limits the initiative of patients, but also may lead to an increase in the dependence of patients on the rehabilitation process, thereby affecting their rehabilitation effect. At the same time, in bilateral rehabilitation training, angle sensors are usually relied on for mirror simulation to collect the bending information of the patient's hand. However, this method can only reflect the movement angle of the limb and cannot comprehensively evaluate the patient's active participation degree and muscle state. Summary of the Invention

[0003] The purpose of the present invention is to overcome the above-mentioned disadvantages of the prior art and disclose a wearable mirror rehabilitation system based on force feedback. The mirror glove end is worn on the healthy hand of the patient, and the wearable rehabilitation manipulator end is worn on the affected hand. The acquisition module collects the muscle strength values of the affected and healthy hands in real time. When the patient moves, his movement intention is sensed, and the driving module controls the movement of the motor according to the muscle strength value information of the healthy side, so that the corresponding affected fingers of the wearable rehabilitation manipulator mirror-simulate the movement of the healthy fingers to help the patient carry out rehabilitation training. At the same time, the muscle strength signals of the affected and healthy sides are fed back to the control module, and through a double closed-loop control algorithm, the inner-loop motor speed is dynamically adjusted according to the muscle strength difference between the outer-loop affected and healthy sides to ensure that the muscle strength of the affected fingers is closely combined with the muscle strength of the healthy fingers. The muscle strength data of the patient is sent to the visualization module through wireless communication to provide visual feedback for it, and at the same time, the historical data is transmitted to the medical staff for providing movement guidance.

[0004] The technical solution of the present invention is a wearable mirror rehabilitation system based on force feedback, including a wearable rehabilitation manipulator end, a mirror glove end, and a driving control acquisition integrated module;

[0005] Preferably, both the mirror glove end and the wearable rehabilitation robot end have five built-in thin film force sensors, which are attached to the front of the thumb, index finger, middle finger, ring finger and little finger respectively. When the hand starts to make movements such as grasping, the acquisition module collects muscle strength data of the affected side and the healthy side respectively through the thin film pressure sensors.

[0006] Preferably, the initial state of the wearable rehabilitation robot end is finger extension. When the acquisition module detects a force value on the healthy side, the drive module starts to drive the motor forward, and the corresponding mechanical finger bends; on the contrary, when the acquisition module detects a force value on the healthy side, the drive module drives the motor in reverse, and the corresponding mechanical finger extends, mirroring the movement of the healthy side finger.

[0007] Preferably, the control module adopts fuzzy PID double closed-loop control algorithm, and the muscle force value F of the affected side collected by the film force sensor a and the muscle strength value F of the healthy side d As the input value and feedback value of the outer loop PID closed loop control algorithm, and according to the muscle strength difference F between the affected side and the healthy side e Sum and difference rate of change Dynamically adjust PID control parameters; the actual speed of the motor n a and ideal speed n d As the input value and feedback value of the inner loop PID closed loop control algorithm, it is also based on the speed difference n of the motor. e Sum and difference rate of change Dynamically adjust PID control parameters.

[0008] Preferably, the ideal speed n of the motor in the control algorithm is d is the difference in muscle strength between the affected and healthy sides of the outer ring, F e The numerical value is converted and the actual speed of the motor is adjusted by n a To regulate the assistive force of the rehabilitation manipulator; at the same time, gravity compensation G is introduced to take into account the influence of gravity on the patient's hand and the rehabilitation manipulator; this process is combined with the force feedback mechanism to achieve mirror control, ensuring that the muscle force of the robotic finger dynamically fits the muscle force changes of the healthy side finger to promote the patient's bilateral coordination training; in addition, the muscle force difference range is set between 0.5-3N to ensure that the system operates within a reasonable force feedback range.

[0009] Preferably, the visualization module is developed in the Visual Studio environment using the C# language, and uses a muscle strength bar graph to intuitively display muscle strength data, thereby providing mirrored visual feedback to the patient and allowing the patient to actively engage in rehabilitation training. The module not only provides a bar graph comparing the muscle strength of the ten fingers, but also displays a disk graph of the average muscle strength of the left and right hands, so that a personalized interface can be customized according to the patient's needs. At the same time, a MySQL database can be used to save dynamic line graphs of ten sets of muscle strength historical data, so that medical staff can provide corresponding guidance and effect evaluation based on the patient's rehabilitation status. 2. A wearable mirror rehabilitation system based on force feedback according to claim 1, characterized in that the patient's muscle strength data is sent to the visualization module via wireless communication to provide visual feedback, and the historical data is transmitted to medical staff to provide exercise guidance.

[0010] Preferably, the present invention further includes a visualization module, and the drive control and acquisition integrated module sends the patient's muscle strength data to the visualization module via wireless communication to provide visual feedback, and at the same time transmits historical data to medical staff to provide exercise guidance.

[0011] Preferably, the drive control and acquisition integrated module is integrated on a single-chip microcomputer with STM32U575 as the main control. In this integrated module, the drive module is responsible for starting, stopping and changing the speed of the motor, and the acquisition module collects muscle strength data in real time to ensure that effective muscle strength data is fed back to the control module.

[0012] Compared with the prior art, the present invention has the following beneficial technical effects:

[0013] 1. The present invention utilizes an acquisition module to acquire real-time muscle strength values from the affected and unaffected hands via a thin-film force sensor. The drive module controls motor movement based on the unaffected hand's muscle strength values. The corresponding fingers on the affected side of the wearable rehabilitation manipulator mirror the movements of the unaffected fingers, assisting the patient in rehabilitation training. Simultaneously, the muscle strength signals from both sides are fed back to the control module. A fuzzy PID double-closed-loop algorithm dynamically adjusts the motor speed, altering the assistive force of the rehabilitation manipulator to achieve the same output muscle strength values on both sides. By dynamically adjusting the PID control parameters, the control effect can be optimized in real time, improving the accuracy and effectiveness of rehabilitation training. The patient's muscle strength data is then transmitted to a visualization module via Bluetooth communication and converted into a bar chart comparing ten finger muscle strengths and a disc chart of the average muscle strength of the left and right hands, which are then fed back to the patient, allowing for a customized interface tailored to their needs. To facilitate real-time monitoring and analysis of muscle strength data trends by patients and medical staff, the system also utilizes a MySQL database to store ten sets of historical muscle strength data and generate a dynamic line chart. This design not only enhances the effectiveness of rehabilitation assessments but also strengthens patients' sense of engagement in their rehabilitation process.

[0014] 2. In the bilateral rehabilitation training of the present invention, mirror simulation is carried out by obtaining the muscle strength data of the patient. This index can evaluate the active participation degree and bilateral limb coordination through the difference in muscle strength between the affected side and the healthy side. If the muscle strength value of the affected side gradually approaches that of the healthy side, it indicates that the patient's active participation degree and limb coordination are improving. In addition, the system can also identify the progress or bottleneck of the patient during training by analyzing the change trend of the muscle strength difference. This feedback mechanism not only helps the patient understand their own rehabilitation progress, but also provides important data support for medical staff to adjust the training plan in a timely manner to ensure the personalization and effectiveness of the rehabilitation training.

[0015] 3. The present invention integrates the drive control acquisition integrated module on a single-chip microcomputer with STM32U575 as the main control. In this integrated module, the drive module is responsible for starting, stopping and changing the speed of the motor, and the acquisition module real-time acquires the muscle strength data to ensure that effective muscle strength data is fed back to the control module. This design reduces the signal transmission delay and improves the response speed of automatic adjustment, enabling the patient to obtain a more accurate rehabilitation experience. At the same time, this design reduces the volume and cost, enhances the reliability of the system, is more inclined to productization, and effectively improves the intelligent level of the rehabilitation equipment. Brief Description of the Drawings

[0016] Figure 1 Flowchart of the wearable mirror rehabilitation manipulator system based on force feedback.

[0017] Figure 2 Block diagram of the wearable mirror rehabilitation manipulator system based on force feedback.

[0018] Figure 3 Control strategy diagram of the wearable mirror rehabilitation manipulator system based on force feedback.

[0019] Figure 4 Visualization interface diagram of the wearable mirror rehabilitation manipulator system based on force feedback. Detailed Embodiment

[0020] Such as Figure 1 And Figure 2As shown, the present invention proposes a wearable mirror rehabilitation system based on force feedback, including a wearable rehabilitation manipulator, a mirror glove, a drive control and acquisition integrated module, and a visualization module. Five thin film force sensors are built into the thumb, index finger, middle finger, ring finger, and little finger of the mirror glove and the wearable rehabilitation manipulator, and the wearable rehabilitation manipulator is driven by five DC push rod motors with encoders, wherein the encoders are installed at the tail of the DC push rod motors to detect the motor speed. The thin film force sensors and the DC push rod motors with encoders are connected to the drive control and acquisition integrated module via data cables. The drive control and acquisition integrated module is integrated into a microcontroller with STM32U575 as the main control and is powered by a 15V lithium-ion battery.

[0021] like Figure 1 and Figure 3 As shown in the figure, the mirror glove end is worn by the patient's healthy hand, and the wearable rehabilitation robot end is worn by the affected hand. The initial state of the wearable rehabilitation robot end is that the fingers are extended. Two objects are placed in front of the patient. When the patient's healthy hand starts to grasp the objects, the acquisition module detects the healthy side muscle force value F in real time through the thin film force sensors attached to the five fingers. a At this time, the driving module starts to drive the motor to rotate forward, the corresponding mechanical finger bends, and the patient wearing the rehabilitation robot starts to grasp the object on the affected side, mirroring the movement of the healthy side finger; and the healthy side muscle force value F a and the muscle strength value F on the affected side d As the input value and feedback value of the control module, the motor speed n is dynamically adjusted through the fuzzy PID double closed-loop control algorithm i , thereby regulating the assistive force of the rehabilitation robot; in addition, due to the influence of gravity on the patient's hand and the rehabilitation robot, a gravity compensation mechanism is adopted to make the bilateral muscle force output the same, ensuring that the muscle force difference is stable between 0.5-3N, ensuring that the patient will not suffer discomfort due to insufficient or excessive assistive force during rehabilitation training.

[0022] like Figure 1 and Figure 4 As shown, the patient's muscle strength data is then sent to the visualization module via low-power Bluetooth communication. The visualization module is developed in the Visual Studio environment and uses a bar chart comparing the muscle strength of ten fingers and a disc chart of the average muscle strength of the left and right hands to provide real-time visual feedback to the patient. At the same time, the MySQL database can be used to save dynamic line charts of ten sets of historical muscle strength data, making it convenient for patients and medical staff to monitor and analyze muscle strength data trends in real time.

[0023] The above are the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements are also regarded as the protection scope of the present invention.

Claims

1. A force-feedback-based wearable mirror rehabilitation system, characterized in that It includes a wearable rehabilitation robotic hand end, a mirror glove end, and a driving, controlling, and data acquisition integrated module. The wearable rehabilitation robotic hand end consists of a wearable rehabilitation robotic hand, and thin-film force sensors and DC pushrod motors with encoders respectively arranged at the positions of the thumb, index finger, middle finger, ring finger, and little finger on the wearable rehabilitation robotic hand. The mirror glove end consists of a mirror glove and thin-film force sensors respectively arranged at the positions of the thumb, index finger, middle finger, ring finger, and little finger on the mirror glove. The method is as follows: The mirror glove end is worn on the healthy hand of the patient, and the wearable rehabilitation robotic hand end is worn by the affected hand. The driving, controlling, and data acquisition integrated module real-time collects the hand muscle strength values. When the patient moves, their movement intention is sensed. The driving, controlling, and data acquisition integrated module controls the movement of the motor according to the healthy-side muscle strength value information, and the corresponding affected-side fingers of the wearable rehabilitation robotic hand mirror and simulate the movement of the healthy-side fingers to help the patient carry out rehabilitation training. At the same time, the muscle strength signals of the affected side and the healthy side are fed back to the driving, controlling, and data acquisition integrated module. The integrated drive control and acquisition module adopts the fuzzy PID double closed-loop control algorithm, and the muscle strength value F of the affected side collected by the thin-film force sensor a and the muscle strength value F of the healthy side d are used as the input value and feedback value of the outer-loop PID closed-loop control algorithm, and the PID control parameters are dynamically adjusted according to the muscle strength difference F e between the affected and healthy sides and the difference change rate; The specific formula is as follows: F e = F a -F d (1) Among them, F a is the input force value, F d is the feedback force value, F o is the output force value, F e is the error force value, G is the gravity compensation (generally taken as 2 - 4N according to actual measurement), K po 、K io 、K do are the initial parameters of the PID outer loop control, ΔK po 、ΔK io 、ΔK do are the change parameters calculated by the outer loop fuzzy controller. The actual speed n of the motor a and the ideal speed n d As the input value and feedback value of the inner-loop PID closed-loop control algorithm, and also based on the speed difference n of the motor e and the rate of change of the difference dynamically adjust the PID control parameters; n e = n a -n d (3) Among them, n i is the output speed value, and n e is the error speed value. K pi , K ii , and K di are the initial parameters of the PID inner loop control, and ΔK pi , ΔK ii , and ΔK di are the change parameters calculated by the outer loop fuzzy controller. Dynamically adjust the motor speed according to the difference in muscle strength between the affected side and the healthy side to ensure that the muscle strength of the fingers on the affected side is closely combined with that on the healthy side. Therefore, the ideal speed n of the inner loop of the fuzzy PID double closed-loop control algorithm d is the numerical conversion of the difference in muscle strength F between the affected and healthy sides of the outer loop e ; And by adjusting the output speed n of the motor i to regulate the assisting force of the rehabilitation manipulator; introducing gravity compensation G to consider the gravity influence of the patient's hand and the rehabilitation manipulator; this process combines a force feedback mechanism to achieve mirror control, ensuring that the muscle strength of the mechanical finger dynamically fits the muscle strength change of the healthy finger to promote the bilateral coordination training of the patient; the muscle strength difference range is set between 0.5 - 3N to ensure that the system operates within a reasonable force feedback range.

2. The wearable mirror rehabilitation system based on force feedback according to claim 1, wherein It further includes a visualization module. The driving, controlling, and data acquisition integrated module sends the patient's muscle strength data to the visualization module through wireless communication to provide visual feedback for it. At the same time, the historical data is transmitted to medical staff for providing movement guidance.

3. A force-feedback-based wearable mirror rehabilitation system according to claim 1 or 2, characterized in that The driving, controlling, and data acquisition integrated module is integrated on a single-chip microcomputer with STM32U575 as the main control. The data acquisition module sends the patient's muscle strength data to the visualization module through low-power Bluetooth communication. In this integrated module, the driving module is responsible for starting, stopping, and speed-changing of the motor, and the data acquisition module real-time collects the muscle strength data to ensure that effective muscle strength data is fed back to the driving, controlling, and data acquisition integrated module.

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