Traction bed for bone fracture rehabilitation

Abstract

The invention provides a traction bed for bone fracture rehabilitation, which comprises a traction data acquisition unit, a traction compensation determination unit and a traction control unit, and is characterized in that the traction data acquisition unit acquires traction data of flexible traction when a patient uses the traction bed to perform bone fracture rehabilitation training; the traction compensation determining unit obtains a traction track of a patient during rehabilitation training, determines static traction force according to the traction track and traction zero position information of a traction bed during static continuous traction, and performs traction compensation on matching degree information of traction tension during rehabilitation training of the patient according to the static traction force. And the traction control unit performs self-adaptive traction control on the traction bed for bone fracture rehabilitation training according to the adjusted reciprocating degree of freedom and the matching degree information after traction compensation. According to the scheme, the traction bed for bone fracture rehabilitation is adjusted based on self-adaptive traction control, and the traction effect of the traction bed in the rehabilitation training process can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of medical equipment, and more specifically, to a traction bed for bone injury rehabilitation. Background Art

[0002] Medical devices refer to various equipment, instruments, tools or systems used to prevent, diagnose, treat, monitor, rehabilitate or alleviate diseases or injuries. They are designed and manufactured to assist different links in the medical process and do not rely on pharmacological, immunological or metabolic pathways to produce their main effects. Medical devices cover a wide range, ranging from simple physical tools (such as thermometers, sphygmomanometers) to complex electronic devices (such as magnetic resonance imaging devices, surgical robots), as well as equipment for rehabilitation (such as traction beds, rehabilitation training systems). They provide support during the medical process and improve the health and quality of life of patients through physical means or mechanical actions.

[0003] Existing traction beds for bone injury rehabilitation are mainly used for the rehabilitation process after bone injury treatment. Through mechanical traction, the patient's bones and soft tissues are continuously and controlled stretched to help restore the normal position and function of the bones. The traction bed often has multiple functions, including angle adjustment, timed traction, automatic release, etc. It can also be equipped with sensors to monitor the patient's traction status in real time to avoid damage to bones or soft tissues caused by excessive traction. Through regular traction training, the traction bed can help patients improve the stability of the injured part. However, during the rehabilitation training process, the existing traction bed for bone injury rehabilitation cannot collect the patient's participation in the traction training in real time, lacks dynamic adjustment of the required traction force size boundary and intelligent feedback mechanism, resulting in a matching hysteresis between the traction force and the patient's actual rehabilitation needs, making it impossible to achieve accurate personalized rehabilitation training control, thereby reducing the traction effect. Therefore, how to achieve accurate personalized rehabilitation training control under the influence of the matching hysteresis between the traction force of the traction bed and the patient's actual rehabilitation needs to improve the traction effect of the traction bed during the rehabilitation training process is a problem faced by the industry. Summary of the invention

[0004] The present application provides a traction bed for bone injury rehabilitation, which can achieve accurate personalized rehabilitation training control under the influence of matching hysteresis between the traction force of the traction bed and the actual rehabilitation needs of the patient, so as to improve the traction effect of the traction bed during the rehabilitation training process.

[0005] In order to solve the above technical problems, the present application provides a traction bed for bone injury rehabilitation, which includes a traction data acquisition unit, a traction data processing unit, a reciprocating adjustment unit, a traction compensation determination unit and a traction control unit: The traction data acquisition unit is used to collect traction data of flexible traction when the patient uses the traction bed for bone injury rehabilitation training; The traction data processing unit is used to extract the active participation index of the patient during rehabilitation training from the traction data, and determine the traction force value of the patient during traction training according to the active participation index; The reciprocating adjustment unit is used to determine the traction force range of the reciprocating traction movement of the traction bed during the bone injury rehabilitation training, and determine the dynamic traction flexion angle of the traction bed in the traction direction according to the traction force range and the traction force value, and then adjust the reciprocating degree of freedom of the patient during the rehabilitation training according to the dynamic traction flexion angle; The traction compensation determination unit is used to obtain the traction trajectory of the patient during rehabilitation training, determine the static traction force according to the traction trajectory and the traction zero position information of the traction bed during static continuous traction, and perform traction compensation on the matching degree information of the traction tension during rehabilitation training of the patient according to the static traction force; The traction control unit is used to perform adaptive traction control on the traction bed used for bone injury rehabilitation training according to the adjusted reciprocating degree of freedom and the matching degree information after traction compensation.

[0006] In some embodiments, the traction data acquisition unit acquires traction data of flexible traction when a patient uses a traction bed for bone injury rehabilitation training through a force sensor and a displacement sensor.

[0007] In some embodiments, the traction data processing unit is also used to determine the force level of the traction action during the patient's rehabilitation training based on the traction data; obtain the active stretching data of the patient during rehabilitation training; and determine the active participation index of the patient during rehabilitation training based on the force level and the active stretching data.

[0008] In some embodiments, the traction data processing unit is also used to determine the traction amplitude of the patient during traction training according to the active participation index; determine the traction movement trajectory of the patient during rehabilitation traction; and determine the traction force value of the patient during traction training according to the traction amplitude and the traction movement trajectory.

[0009] In some embodiments, the reciprocating adjustment unit is also used to determine the traction compensation coefficient of the reciprocating traction motion during bone injury rehabilitation training guided by the traction bed; determine the traction force tracking amount of the reciprocating traction motion during bone injury rehabilitation training; and determine the traction force range of the reciprocating traction motion based on the traction compensation coefficient and the traction force tracking amount.

[0010] In some embodiments, the reciprocating adjustment unit is also used to extract the traction action distribution entropy of the traction bed during traction from the traction force range; determine the traction feedback vector of the traction bed in the traction direction according to the traction force value; and determine the dynamic traction flexion angle of the traction bed in the traction direction through the traction action distribution entropy and the traction feedback vector.

[0011] In some embodiments, the traction compensation determination unit is also used to determine the static traction trend amount when the traction bed pulls the patient according to the traction trajectory; determine the traction zero position information of the traction bed during static continuous traction; determine the traction force source control value of the traction bed according to the traction zero position information; determine the static traction force according to the static traction trend amount and the traction force source control value.

[0012] In some embodiments, the flexible traction adopts flexible steel wire rope traction.

[0013] In some embodiments, the traction data acquisition unit, the traction data processing unit, the reciprocating adjustment unit, the traction compensation determination unit and the traction control unit are integrated into a traction bed controller for bone injury rehabilitation.

[0014] In some embodiments, the traction data includes traction force data and displacement data.

[0015] The technical solution provided by the embodiments disclosed in this application has the following beneficial effects: In the traction bed for bone injury rehabilitation of the present application, the traction data of the flexible traction of the patient when using the traction bed for bone injury rehabilitation training is collected by the traction data collection unit, the traction data can be collected in real time, and detailed traction process information can be obtained, so as to provide an accurate data basis for subsequent analysis. This data-driven method can achieve more efficient rehabilitation training and ensure data transparency and traceability during the treatment process; secondly, in order to ensure the personalization and adaptability of traction, the patient's active participation index data is extracted by the traction data processing unit to quantify the patient's initiative in the rehabilitation process, so as to dynamically adjust the traction force value according to the actual situation; thirdly, the reciprocating adjustment unit determines the dynamic traction index by determining the dynamic traction index. The flexion angle is guided to accurately control the posture and direction of the traction bed during the traction process, which effectively improves the flexibility and stability of the traction; then, the traction compensation determination unit analyzes the traction trajectory and the static traction force, so that the traction bed can achieve accurate traction tension matching in different rehabilitation stages, which is helpful to improve the effectiveness of traction, and traction compensation is performed on the matching degree information of the traction tension during the patient's rehabilitation training according to the static traction force; finally, the traction control unit performs adaptive traction control on the traction bed used for bone injury rehabilitation training according to the adjusted reciprocating degree of freedom and the matching degree information after traction compensation, thereby adjusting the traction parameters of the traction bed in real time through adaptive traction control.

[0016] To sum up, the technical solution adopted in this application can realize accurate personalized rehabilitation training under the influence of matching hysteresis between the traction force of the traction bed and the actual rehabilitation needs of the patient, so as to improve the traction effect and rehabilitation efficiency of the traction bed during the rehabilitation training process. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a module structure diagram of the traction control of the traction bed for bone injury rehabilitation provided by the present application; Figure 2 is a schematic diagram of a traction bed cable length model according to some embodiments of the present application; Figure 3 is a schematic diagram of a flexible cable traction model of a traction bed for bone injury rehabilitation training according to some embodiments of the present application; Figure 4 It is a schematic diagram of an exemplary process of determining the static traction force by the traction compensation determination unit shown in some embodiments of the present application. DETAILED DESCRIPTION

[0018] In order to better understand the technical solution of the present application, the technical solution of the present application will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0019] refer to Figure 1 , which is a module structure diagram of the traction bed for bone injury rehabilitation provided by the present application to realize traction control. Specifically, the traction bed for bone injury rehabilitation of the present application includes: a traction data acquisition unit 100, a traction data processing unit 200, a reciprocating adjustment unit 300, a traction compensation determination unit 400 and a traction control unit 500, which are respectively described as follows: The traction data acquisition unit 100 in the present application is mainly used to collect traction data of flexible traction when the patient uses a traction bed for bone injury rehabilitation training.

[0020] In specific implementation, the force sensor can be installed at the connection between the flexible element (such as a flexible steel wire rope) and the traction bed in the flexible traction to ensure that it can measure the traction force exerted on the flexible element in real time. For example, the force sensor can be directly integrated into the fixed end of the flexible element or the pulley system to detect the force change of the flexible element during each traction process. Then, the displacement sensor should be installed on the traction bed, specifically set at one end connected to the flexible element, to measure the actual movement distance of the flexible element. In specific implementation, a guide pulley can be installed to record the displacement of the flexible element in combination with the displacement sensor. Then, the collected traction force data and displacement data are transmitted to the controller of the traction bed through a wired (such as USB, serial port) or wireless (such as Wi-Fi, Bluetooth) method. That is, the traction data acquisition unit 100 can collect the traction data of the flexible traction when the patient uses the traction bed for bone injury rehabilitation training through the force sensor and the displacement sensor. The traction data mainly includes two types of information, namely, traction force data and displacement data. In other embodiments, other methods can also be used to collect the traction data of the flexible traction when the patient uses the traction bed for bone injury rehabilitation training, which is not limited here.

[0021] It should be noted that the traction data in the present application represents the traction force data and displacement data of the flexible element of the flexible traction collected by the sensor during the traction process. The traction force data includes the magnitude and direction of the traction force and the law of change of the traction force over time. The displacement data includes the displacement of the flexible element of the flexible traction during the traction process. The role of the traction data in the present application is to provide accurate data information for the traction intensity, motion trajectory and training effect in rehabilitation training.

[0022] In addition, the traction data processing unit 200 in the present application can be used to extract the active participation index of the patient during rehabilitation training from the traction data, and determine the traction force value required for the patient during traction training according to the active participation index.

[0023] In some embodiments, the flexible element of the flexible traction can be a flexible steel wire rope or a flexible rope, Figure 2 As shown in the figure, this figure is a schematic diagram of the cable length model shown in some embodiments of the present application. The cable is connected to an electric control device at one end through a pulley fixed on the traction bed bracket, and the other end is connected to a rehabilitation traction platform. The electric control device is used to pull and contract the cable, so that the rehabilitation traction platform can be raised, lowered or the inclination angle can be adjusted through the other end of the pulley.

[0024] In some embodiments, reference Figure 3 As shown, this figure is a schematic diagram of a flexible cable traction model for bone injury rehabilitation training shown in some embodiments of the present application. The bone injury rehabilitation patient undergoes rehabilitation training in a passive state, that is, he is pulled by a traction bed. The rehabilitation traction platform in the traction bed is driven by four flexible cables to complete the traction degree required for rehabilitation traction. One end of the four flexible cables is connected to the rehabilitation traction platform, and the other end passes through four fixed pulleys on the traction bed bracket and is connected to a motor in an electric control device installed on the traction bed. After the motor receives the control command of the electric control device, it runs to drive the flexible cables to move, thereby completing the traction. When the patient undergoes rehabilitation training, the part that needs rehabilitation training, such as the leg, is placed on the traction rehabilitation traction platform. The driving motor receives the control signal of the host computer and starts working. The rehabilitation traction platform realizes actions such as lifting, lowering, tilting left or right, thereby completing the rehabilitation traction training of the bone injury rehabilitation patient.

[0025] In addition, it should be noted that in order to extract the active participation index during rehabilitation training from the traction data, the traction data processing unit 200 in the present application is also used to determine the force level of the traction action during the patient's rehabilitation training based on the traction data; obtain the active stretching data of the patient during rehabilitation training; and determine the active participation index of the patient during rehabilitation training based on the force level and the active stretching data.

[0026] In specific implementation, first, the traction data processing unit 200 can classify the traction action according to the change of the traction force over time to obtain different force levels (for example, mild, moderate, and severe). The classification can be based on a preset standard traction force value range. For example, the traction force between 10-20N is mild, 20-30N is moderate, and more than 30N is severe. The force level in the rehabilitation training process can be determined by analyzing the average force value, maximum force value, and fluctuation range of the traction action; then, the displacement sensor and force sensor can be used to detect the force and movement amplitude generated autonomously by the patient to obtain the active stretching data of the patient during rehabilitation training, that is, according to the displacement of the flexible printing element (such as a flexible cable or a flexible steel wire rope) of the flexible traction and the force applied by the patient, it can be judged whether the patient is actively cooperating with the traction. If it is detected that the patient applies a force opposite to the set traction force during the traction process, or a displacement different from the external traction is detected in the displacement data, it is judged as the patient's active stretch. By comparing with the standard stretching pattern, the patient's active stretching part is extracted. For example, if it is detected that the movement frequency of the flexible element is inconsistent with the traction frequency applied by the system, it indicates the patient's willingness and degree of active stretching; finally, if the system detects that the patient's active stretching data matches the force level (that is, the patient's active force is equivalent to the traction force set by the system), it indicates that the patient's active participation index is high. On the contrary, if the patient's active force is small, the active participation index is low. The active participation index can be determined in the following way, namely: active participation index = patient's active force / system set traction force*100%, which will not be repeated here.

[0027] It should be noted that the force level in this application represents the level of grading the movements in rehabilitation training according to the size of the traction force, which is used to quantify the intensity of rehabilitation training; the active stretching data represents the stretching force and range of motion applied autonomously by the patient in rehabilitation training, which is used to evaluate the patient's active participation in the rehabilitation process; the active participation index represents the proportion of the force applied autonomously by the patient in the rehabilitation training process to the overall traction force, which is used to evaluate the patient's degree of active cooperation in training during the rehabilitation process.

[0028] In some embodiments, in order to determine the traction force value during traction training according to the active participation index, the traction data processing unit 200 of the present application can determine the traction amplitude of the patient during traction training according to the active participation index; and then determine the traction movement trajectory of the patient during rehabilitation traction; finally, determine the traction force value required for the patient during traction training according to the traction amplitude and the traction movement trajectory.

[0029] In specific implementation, first, when the traction data processing unit 200 determines the traction amplitude, it can be controlled by adjusting the length or angle of the displacement of the flexographic element of the flexible traction. For example, when the patient's active participation index is high, the displacement of the flexible element of the flexible traction can be increased to increase the traction amplitude, thereby enhancing the stretching effect; when the active participation index is low, the traction amplitude can be appropriately reduced to avoid the risk caused by excessive stretching. In addition, the traction amplitude can be determined according to a preset formula or parameter. For example, the change in traction amplitude is determined by setting different participation thresholds, that is: traction amplitude = f (active participation index), where f can be a linear or nonlinear function, which is specifically set according to the rehabilitation goal and the patient's condition; then, during the rehabilitation training process, the traction amplitude data can be combined to determine the specific movement direction and path of the patient during traction. This process not only records linear displacement, but may also include arcs, angles or complex multi-dimensional displacements. The traction trajectory is a three-dimensional trajectory, especially when the patient's rehabilitation involves multi-directional stretching. The traction trajectory data can be used to evaluate whether the patient has performed the rehabilitation movements correctly by comparing the actual trajectory with the standard trajectory. For example, the patient's traction trajectory can be displayed in real time through a graphical interface, allowing the rehabilitation therapist to judge whether the patient's movements deviate from the predetermined rehabilitation goals; finally, the size of the traction amplitude determines the required traction force. For example, the larger the traction amplitude, the greater the traction force applied to ensure the stretching effect. At the same time, the complexity of the traction motion trajectory and the speed of the movement will also affect the calculation of the traction force. Therefore, the required traction force is calculated based on these factors to ensure the accuracy of the training, that is, traction force value = f (traction amplitude, traction trajectory), where f can be a linear or nonlinear function, which is specifically set according to the rehabilitation goals and patient conditions. By updating the traction amplitude and trajectory data in real time, the traction force is dynamically adjusted to achieve accurate rehabilitation training.

[0030] It should be noted that the traction amplitude in the present application represents the displacement range or angle of the traction movement in rehabilitation training, which is used to adjust the rehabilitation intensity by controlling the stretching amplitude of the traction; the traction movement trajectory represents the displacement path of the flexible element of the patient during the rehabilitation training process, which is used to monitor whether the patient's traction movement meets the preset rehabilitation goals, and evaluate the rehabilitation effect through the trajectory; the traction force value represents the traction force that the system needs to apply in rehabilitation training, which is used to provide sufficient force to complete the stretching training while ensuring safety and rehabilitation effect.

[0031] In addition, the reciprocating adjustment unit 300 of the present application is mainly used to determine the traction force range of the reciprocating traction movement when the traction bed guides bone injury rehabilitation training, and determine the dynamic traction flexion angle of the traction bed in the traction direction according to the traction force range and the traction force value, and then adjust the reciprocating degree of freedom of the patient during rehabilitation training according to the dynamic traction flexion angle.

[0032] In some embodiments, in order to determine the traction force range of the reciprocating traction motion when the traction bed guides bone injury rehabilitation training, the reciprocating adjustment unit 300 of the present application is also used to determine the traction compensation coefficient of the reciprocating traction motion when the traction bed guides bone injury rehabilitation training; determine the traction force tracking amount of the reciprocating traction motion during bone injury rehabilitation training; determine the traction force range of the reciprocating traction motion based on the traction compensation coefficient and the traction force tracking amount.

[0033] In specific implementation, firstly, during the actual use of the traction bed, the traction force may deviate due to factors such as the elasticity of the flexible element of the flexible traction, the patient's movement interference or the friction of the device itself. Therefore, the reciprocating adjustment unit 200 calculates the compensation demand for the traction force by monitoring these variables in real time, and sets the compensation coefficient according to these variables. The current traction force is detected by the sensor and compared with the preset standard value. If the detected traction force is insufficient or too high, the compensation coefficient is adjusted according to the error amplitude. For example, if the error is large, the compensation coefficient is increased accordingly, otherwise it is reduced. Then, the reciprocating adjustment unit 300 can collect and calculate the compensation coefficient at different times. The traction force at the point is measured, and a curve of the traction force changing with time is constructed. The maximum slope of the curve is used as the traction force tracking amount. The fluctuation of the traction force is tracked through this curve to ensure the smooth change of the traction force. It will not be repeated here. Finally, the reciprocating adjustment unit 300 can determine the traction force range of the reciprocating traction motion in the following manner, that is, the traction force range = (target traction force ± △ compensation + traction force tracking amount), wherein △ compensation is the adjustment amount of the compensation coefficient, and the traction force tracking amount is used to detect the fluctuation of the traction force. When the traction force exceeds the predetermined range, the system will sound an alarm or automatically adjust the traction force to avoid injury to the patient due to excessive traction.

[0034] It should be noted that the traction compensation coefficient in the present application represents an adjustment coefficient for correcting the difference between the actual traction force and the preset target traction force, and is used to ensure the accuracy and effect of training by adjusting the traction force in real time; the traction tracking amount represents the system's real-time monitoring and recording of the change in traction force over time during rehabilitation training, and is used to ensure the continuity and stability of the traction force output; the traction force range represents the maximum and minimum allowable range of traction force in reciprocating traction motion, and is used to ensure the safety and effectiveness of traction during rehabilitation training.

[0035] In some embodiments, in order to determine the dynamic traction flexion angle of the traction bed in the traction direction according to the traction force range and the traction force value, the reciprocating adjustment unit 300 of the present application also extracts the traction action distribution entropy of the traction bed during traction from the traction force range; determines the traction feedback vector of the traction bed in the traction direction according to the traction force value; and determines the dynamic traction flexion angle of the traction bed in the traction direction through the traction action distribution entropy and the traction feedback vector.

[0036] In specific implementation, first, the distribution entropy of the traction action can be quantified through the calculation formula of information entropy. The larger the entropy value, the more complex the change of the traction action and the higher the uncertainty. Conversely, the entropy value is smaller. When the reciprocating adjustment unit 300 extracts the distribution entropy of the traction action, it collects the traction force data at different stages of the traction process, analyzes the distribution pattern of these data, and calculates the entropy value of the traction force. The entropy value can be used to judge the balance or intensity of the force distribution during the traction process; then, the reciprocating adjustment unit 300 calculates the traction feedback vector in real time according to the magnitude of the traction force value and the traction direction of the flexible element of the flexible traction. The traction feedback vector not only contains the magnitude information of the force, but also describes the directional distribution of the force. The feedback data of the patient in rehabilitation training is obtained through a force sensor or an acceleration sensor, and combined with the traction The force value is used to dynamically adjust the feedback vector. For example, when the traction force deviates during training, the direction and magnitude of the traction force can be corrected according to the information of the feedback vector, which will not be repeated here. Finally, according to the distribution entropy of the traction action, it is judged whether the force distribution during the traction process is uniform. If the distribution entropy value of the traction force is high (that is, the force changes greatly), it is necessary to consider adjusting the flexion angle accordingly to reduce or increase the bending of the flexible element of the flexible traction to better adapt to the patient's physical condition. At the same time, the reciprocating adjustment unit 300 can calculate the resultant force of the traction force in different directions through the traction feedback vector, and adjust the flexion angle of the traction bed accordingly to ensure that the traction direction and flexion angle match. For example, if the feedback vector shows that the traction force is biased to one side, the system automatically adjusts the flexion angle of the traction bed to ensure a balanced distribution of force and traction effect.

[0037] It should be noted that the traction action distribution entropy in the present application represents a measure of the uncertainty or complexity of the traction action during the traction process, and is used to measure the distribution characteristics and complexity of the traction force; the traction feedback vector represents a vector used to describe the magnitude and direction of the traction force during the traction process, and is used to dynamically adjust the direction of application of the traction force to ensure the accuracy and effectiveness of the force in rehabilitation training; the dynamic traction flexion angle represents that the traction bed dynamically adjusts the degree of bending of the flexible element of the flexible traction in the traction bed according to the changes in the traction force and direction during the traction process. By adjusting the flexion angle of the traction, the traction angle and amplitude can be optimized to ensure the accuracy and safety of the rehabilitation training.

[0038] In specific implementation, the dynamic traction flexion angle can be used to adjust the reciprocating degree of freedom of the patient during rehabilitation training in the following manner, namely: the reciprocating degree of freedom refers to the amplitude and direction of reciprocating motion that the patient's limbs or joints can perform during rehabilitation training, and the initially set reciprocating degree of freedom is based on the patient's rehabilitation status, injury and training goals; first, according to the doctor's advice and rehabilitation plan, the initial motion range suitable for the patient is first determined, usually based on the patient's current joint motion range. For example, assuming the target patient's knee joint rehabilitation training, the initial setting may be a flexion range of motion of the knee joint from 30 degrees to 90 degrees, that is, the reciprocating degree of freedom of the patient during rehabilitation training is obtained; then, according to the real-time calculated dynamic traction flexion angle, the system can adjust the initially set reciprocating degree of freedom to ensure that the motion amplitude of the traction bed during rehabilitation training adapts to the patient's rehabilitation needs, that is, the bending angle of the flexible component of the traction bed can be dynamically adjusted according to the dynamic traction flexion angle, thereby Change the restricted range of patient limb movement. For example, if the dynamic traction flexion angle shows that the flexion angle needs to be increased, the system will expand the range of motion of the patient's knee joint accordingly, thereby increasing the training range. Conversely, if the traction flexion angle decreases, the system will reduce the range of motion to avoid overstretching. Finally, the adjustment process is based on the patient's real-time feedback data (such as traction force, feedback vector, etc.). The system continuously monitors the patient's status during training to ensure that the reciprocating degree of freedom is adjusted accurately, dynamically and timely. In addition, the patient's status and reciprocating motion are continuously monitored through the real-time feedback mechanism to determine whether the reciprocating degree of freedom needs to be further adjusted. For example, the system detects that the patient's traction force has increased, indicating that the patient's participation has increased. The system can appropriately relax the reciprocating degree of freedom. If it is detected that the patient overreacts or the traction force is uneven, the system will shrink the range of motion accordingly, and continuously adjust the flexion angle and reciprocating degree of freedom adaptively according to the feedback information to ensure that the patient performs rehabilitation training within a safe range.

[0039] In addition, the traction compensation determination unit 400 of the present application is mainly used to obtain the traction trajectory of the patient during rehabilitation training, determine the static traction force according to the traction trajectory and the traction zero position information of the traction bed during static continuous traction, and perform traction compensation on the matching degree information of the traction tension during rehabilitation training of the patient according to the static traction force.

[0040] In specific implementation, the traction compensation determination unit 400 obtains the traction trajectory of the patient during rehabilitation training in the following manner, namely: accurately monitor the patient's motion trajectory through multiple sensors, the sensors may include position sensors, acceleration sensors, angle sensors, and force sensors, etc., which are installed on the flexible elements of the traction bed or the key joints of the patient. The position sensor mainly records the patient's motion displacement, the acceleration sensor records the change in motion speed, the angle sensor detects the angle change of the limb, and the force sensor monitors the size and direction of the traction force. During the rehabilitation training process, the sensor collects data in real time and transmits it to the control system wirelessly or wired. The control system forms a preliminary model of the patient's motion trajectory based on these sensor data. The trajectory modeling method includes multi-segment linear interpolation or spline curves. These algorithms can smoothly connect various data points to generate a more continuous and realistic motion trajectory. The traction trajectory during rehabilitation training can be output through the preliminary model of the patient's motion trajectory. In other embodiments, other methods can also be used to obtain the traction trajectory during rehabilitation training, which is not limited here.

[0041] It should be noted that the traction trajectory in this application refers to the movement path of the patient's body or limbs in space under the traction of a traction bed or similar equipment during rehabilitation training. The path includes dynamic information such as the patient's displacement, angle change, speed and acceleration under the action of traction.

[0042] refer to Figure 4 The figure is a schematic diagram of an exemplary process of determining the static traction force by the traction compensation determination unit in some embodiments of the present application. In this embodiment, the traction compensation determination unit can determine the static traction force by the following steps: In step 401, a static traction trend amount when the traction bed tractions the patient is determined according to the traction trajectory; In step 402, the traction zero position information of the traction bed during static continuous traction is determined; In step 403, a traction force source control value of the traction bed is determined according to the traction zero position information; In step 404, the static traction force is determined according to the static traction tendency amount and the traction force source control value.

[0043] In specific implementation, first, by extracting the trend of the patient's movement from the traction trajectory, the system can determine whether the patient's traction trajectory shows a static trend in which the traction force tends to be stable and the patient's movement amplitude decreases. For example, when the patient's traction trajectory shows a small displacement and the acceleration gradually decreases, the system can infer that the traction process has entered a static stage, and calculate a trend quantity, and use the trend quantity as the static traction trend quantity during traction in the current traction state; then, the position data of the traction bed when it is stationary or unloaded is recorded by the sensor, and the system can set a reference point (zero position) as a reference for subsequent traction force measurement and control. When the traction bed is in a static state, the system will automatically capture the current device position and traction state to form traction zero position information, which is usually obtained through the reference of the sensor or control system. The traction source control value is obtained by calibration, which will not be repeated here; then, the traction source control value is a feedback control parameter. Based on the deviation between the traction zero position and the current traction demand, the system adjusts the traction source (such as a motor, a hydraulic device) to provide appropriate traction. The traction source control value can be calculated according to the zero position information and the traction trajectory by the control algorithm of the traction system, such as proportional integral differential control (PID), which will not be repeated here; finally, the system calculates the static traction force that the current traction bed needs to apply according to the static traction trend amount and the traction source control value, wherein the calculation of the static traction force is combined with the movement trend in the traction trajectory, the output of the current traction source, and the individual differences of the patient, and an optimal traction force value is output through linear fitting, multi-value fitting, etc., and the traction force value is used as the static traction force.

[0044] It should be noted that the static traction trend quantity in the present application represents a numerical indicator of the traction force tending to be stable during the traction process; the traction zero position information represents the initial position and state of the traction bed when no traction force or the minimum traction force is applied, that is, the position and state of the traction bed when it is static and no external force is applied, which is the basis for subsequent traction force adjustment and monitoring; the traction force source control value represents the force control value output according to the patient's demand feedback when the traction bed is tractioned, which is used to adjust the output of the traction force source to maintain a reasonable traction force; the static traction force represents the force that the traction bed needs to maintain in the current stable rehabilitation state to ensure the continuity and effectiveness of the patient's traction process.

[0045] In specific implementation, traction compensation can be performed according to the matching degree information of traction tension during rehabilitation training of the patient based on the static traction force, which can be achieved in the following manner, namely: first, the static traction force previously determined by the static traction trend quantity and the traction source control value is obtained, which is the traction force applied by the traction bed during the current rehabilitation training and has reached a stable state; then, the patient's own traction tension is calculated by analyzing the patient's muscle activity and soft tissue feedback during rehabilitation training, that is, the patient's body response to the traction force during the traction process can be obtained through sensors or biofeedback devices on the patient's limbs, reflecting the patient's muscle traction or passive resistance. For example, an electromyography (EMG) sensor can record the patient's muscle electrical activity level during the traction process, thereby estimating the patient's traction tension; then, the obtained static traction force is compared with the patient's traction tension to determine the matching degree between the two. If the difference between the two is within the set threshold range, it means that the traction tension and the static traction force are well matched. If the difference is large, it means that the matching degree is insufficient. The matching degree information can be obtained by comparing the obtained static traction force with the patient's traction tension. The matching degree can be determined in the following manner, namely: the matching degree can be obtained by subtracting the static traction force from the traction tension and then obtaining the quotient of the static traction force, and then obtaining the difference between "1" and the absolute value of the quotient, and the difference is used as the matching degree information. When the matching degree is high, it means that the patient's traction tension is close to the static traction force applied by the system, and the rehabilitation process is relatively balanced. A low matching degree indicates that compensation is required. Finally, according to the matching degree information, if the matching degree is low (that is, the static traction force differs greatly from the patient's traction tension), the system will compensate according to the unmatched part. The compensation process includes automatically adjusting the traction force of the traction bed to reduce the difference and improve the matching degree. The traction compensation mechanism can be implemented by an adaptive control algorithm, such as proportional integral differential control (PID control). The algorithm can adjust the traction force in real time so that the traction force output by the system gradually approaches the traction tension of the patient. For example, if the patient's traction tension is low, the system can reduce the output of the traction source and reduce the static traction force. On the contrary, if the patient's traction tension is high, the system can increase the traction force to ensure that the rehabilitation training achieves the expected stretching effect.

[0046] It should be noted that the traction tension in this application refers to the resistance or response force generated by the muscles or soft tissues to the external traction force during the patient's traction rehabilitation process, which reflects the patient's rehabilitation progress and physical tolerance.

[0047] In addition, the traction control unit 500 of the present application is mainly used to perform adaptive traction control on the traction bed used for bone injury rehabilitation training according to the adjusted reciprocating degree of freedom and the matching degree information after traction compensation.

[0048] In specific implementation, the traction control unit 500 in the present application performs adaptive traction control on the traction bed for bone injury rehabilitation training according to the adjusted reciprocating degrees of freedom and the matching degree information after traction compensation, which can be achieved in the following manner: First, the adjusted reciprocating degrees of freedom are determined by the dynamic traction flexion angle adjustment and traction compensation process of the traction bed. For example, based on the patient's fracture site and recovery progress, the system may increase or decrease the degrees of freedom to ensure that the patient can perform traction training within a safe range. The matching degree information after traction compensation reflects the difference between the traction force and the patient's actual bearing capacity. When the matching degree is high, it means that the traction force is suitable for the patient's current recovery state, and the system can maintain the current traction force; when the matching degree is low, the system will further compensate the traction force, increase or decrease the traction intensity, until the matching degree reaches the set standard; then, during the adaptive traction control process, the system uses a variety of sensors to The traction bed uses sensors (such as displacement sensors, force sensors, and angle sensors) to monitor the movement state of the traction bed and the patient's response in real time. The traction bed will record the traction force, displacement, speed, and patient feedback (such as muscle activity or pain threshold), and feed this information back to the control system. Through monitoring data, the system can timely detect abnormalities in the traction process, such as displacement beyond the range of reciprocating degrees of freedom or sudden increases and decreases in traction force. According to real-time data, the system can make rapid adjustments to ensure that the traction bed operates within a safe and effective range; finally, according to the adjustment results of the reciprocating degrees of freedom and traction force, the traction bed can dynamically modify the traction path, that is, the traction bed not only adjusts the traction force, but also optimizes its motion trajectory according to the patient's recovery, traction direction requirements, and muscle status. At the same time, the system will optimize the traction direction, amplitude, and speed in real time according to the dynamic traction flexion angle, traction force feedback, and changes in the patient's traction trajectory.

[0049] It can be seen that in the adaptive traction control of the traction bed used for bone injury rehabilitation training, the present application, firstly, by collecting traction data in real time, can obtain detailed traction process information, thereby providing an accurate data basis for subsequent analysis, and the data-driven method can achieve more efficient rehabilitation training and ensure data transparency and traceability during the treatment process; secondly, to ensure the personalization and adaptability of traction, the active participation index is extracted so that the therapist can quantify the patient's initiative in the rehabilitation process, thereby dynamically adjusting the traction force value according to the actual situation; thirdly, by determining the dynamic traction flexion angle, the posture and direction of the traction bed during the traction process can be accurately controlled, which effectively improves the flexibility and stability of the traction and ensures the safety of the treatment process; then, the traction trajectory and static traction force are analyzed, so that the traction bed can achieve accurate traction tension matching in different rehabilitation stages, which helps to improve the effectiveness of traction; finally, the traction parameters of the traction bed are adjusted in real time through adaptive traction control.

[0050] To sum up, the technical solution adopted in this application can realize accurate personalized rehabilitation training under the influence of matching hysteresis between the traction force of the traction bed and the actual rehabilitation needs of the patient, so as to improve the traction effect and rehabilitation efficiency of the traction bed during the rehabilitation training process.

[0051] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0052] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0053] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0054] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0055] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of protection of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A traction bed for bone injury rehabilitation, characterized in that: The traction bed for bone injury rehabilitation includes a traction data acquisition unit, a traction data processing unit, a reciprocating adjustment unit, a traction compensation determination unit and a traction control unit; The traction data acquisition unit is used to collect traction data of flexible traction when the patient uses the traction bed for bone injury rehabilitation training; The traction data processing unit is used to extract the active participation index of the patient during rehabilitation training from the traction data, and determine the traction force value required for the patient during traction training according to the active participation index; The reciprocating adjustment unit is used to determine the traction force range of the reciprocating traction movement of the traction bed during the bone injury rehabilitation training, and determine the dynamic traction flexion angle of the traction bed in the traction direction according to the traction force range and the traction force value, and then adjust the reciprocating degree of freedom of the patient during the rehabilitation training according to the dynamic traction flexion angle; The traction compensation determination unit is used to obtain the traction trajectory of the patient during rehabilitation training, determine the static traction force according to the traction trajectory and the traction zero position information of the traction bed during static continuous traction, and perform traction compensation on the matching degree information of the traction tension during rehabilitation training of the patient according to the static traction force; The traction control unit is used to perform adaptive traction control on the traction bed used for bone injury rehabilitation training according to the adjusted reciprocating degree of freedom and the matching degree information after traction compensation.

2. The traction bed for bone injury rehabilitation according to claim 1, characterized in that: The traction data acquisition unit acquires traction data of flexible traction of a patient using a traction bed for bone injury rehabilitation training through a force sensor and a displacement sensor.

3. The traction bed for bone injury rehabilitation according to claim 1, characterized in that: The traction data processing unit is also used to determine the force level of the traction action during the patient's rehabilitation training based on the traction data; obtain the active stretching data of the patient during the rehabilitation training; and determine the active participation index of the patient during the rehabilitation training based on the force level and the active stretching data.

4. The traction bed for bone injury rehabilitation according to claim 1, characterized in that: The traction data processing unit is also used to determine the traction amplitude of the patient during traction training according to the active participation index; determine the traction movement trajectory of the patient during rehabilitation traction; and determine the traction force value required for the patient during traction training according to the traction amplitude and the traction movement trajectory.

5. The traction bed for bone injury rehabilitation according to claim 1, characterized in that: The reciprocating adjustment unit is also used to determine the traction compensation coefficient of the reciprocating traction motion when the traction bed guides bone injury rehabilitation training; determine the traction force tracking amount of the reciprocating traction motion during bone injury rehabilitation training; and determine the traction force range of the reciprocating traction motion based on the traction compensation coefficient and the traction force tracking amount.

6. The traction bed for bone injury rehabilitation according to claim 1, characterized in that: The reciprocating adjustment unit is further used to extract the traction action distribution entropy of the traction bed during traction from the traction force range; determine the traction feedback vector of the traction bed in the traction direction according to the traction force value; and determine the dynamic traction flexion angle of the traction bed in the traction direction through the traction action distribution entropy and the traction feedback vector.

7. The traction bed for bone injury rehabilitation according to claim 1, characterized in that: The traction compensation determination unit is also used to determine the static traction trend amount when the traction bed pulls the patient according to the traction trajectory; determine the traction zero position information of the traction bed during static continuous traction; determine the traction force source control value of the traction bed according to the traction zero position information; determine the static traction force according to the static traction trend amount and the traction force source control value.

8. The traction bed for bone injury rehabilitation according to claim 1, characterized in that: The flexible traction adopts flexible steel wire rope traction.

9. The traction bed for bone injury rehabilitation according to claim 1, characterized in that: The traction data acquisition unit, the traction data processing unit, the reciprocating adjustment unit, the traction compensation determination unit and the traction control unit are integrated in a traction bed controller for bone injury rehabilitation.

10. The traction bed for bone injury rehabilitation according to claim 1, characterized in that: The traction data includes traction force data and displacement data.

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