24 results about "Lower extremity joint" patented technology

The invention discloses a weight loss gait test evaluation and training device and method, and the device comprises a weight loss control module which is used for weighing the weight of a user in real time and automatically adjusting the air pressure of an air bag according to a set weight loss proportion; the gait information acquisition module is used for synchronously acquiring plantar pressure distribution, lower limb joint kinematics parameters and double-view video data; the multi-modal gait evaluation grading model module is used for processing plantar pressure distribution, lower limb joint kinematics parameters and double-view video data and outputting lower limb dyskinesia grades; and the training scheme generation model module is used for automatically generating a training scheme including a weight reduction proportion, a treadmill speed, single exercise time and training times per week according to the lower limb dyskinesia level and the personal information of the user.

The invention provides a bionic lower limb robot artificial limb test system and method. The system comprises a humanoid robot test main body, a load module, a support module and a data acquisition module, the humanoid robot testing main body at least comprises human lower limb joints and is used for simulating human lower limb walking; the human body lower limb joint comprises at least one of a knee joint, an ankle joint and a foot modularization, and at least part of the human body lower limb joint can be replaced by an artificial limb to-be-tested unit, so that the humanoid robot test main body can drive the artificial limb to-be-tested unit to carry out a walking test; the load module is arranged on the humanoid robot test main body and is used for providing a target load for the artificial limb to-be-tested unit; the supporting module is used for providing a walking road on which the humanoid robot testing main body can carry out a walking test; the data acquisition module is used for monitoring test parameters when the artificial limb to-be-tested unit is subjected to a walking test. According to the invention, a real use scene can be simulated, and accurate detection of the multi-dimensional performance of the artificial limb can be realized.

The invention relates to a multi-joint layered cooperative intelligent control method for a power-assisted exoskeleton, and belongs to the field of robot exoskeletons. Comprising the following steps: acquiring a real-time hip joint angle, updating an adaptive oscillator model based on the real-time hip joint angle, and obtaining a real-time gait phase; segmenting the real-time gait phase to obtain gait phases of a plurality of first sampling points; acquiring the height, the weight, the lower limb joint center and the stride frequency of the user to construct a power-assisted curve of the relation between the lower limb joint power-assisted torque and the gait phase; and acquiring the actual torque of the lower limb joint corresponding to each first sampling point, inputting the gait phase corresponding to each first sampling point into the power-assisted curve for updating to obtain an optimized power-assisted curve, and realizing power assistance of the lower limb joint based on the optimized power-assisted curve. According to the method, the hip joint angle and the moment thereof and the knee joint angle and the moment thereof are associated through the same gait phase, cooperative assistance of the hip joint and the knee joint is achieved, the effectiveness and smoothness of exoskeleton assistance are improved, and the user experience is improved.

This invention relates to an intelligent rehabilitation device and method based on machine vision and thermotherapy technology, belonging to the field of rehabilitation medicine and medical equipment technology. It includes: a multi-angle machine vision monitoring module; an intelligent positioning and temperature control module for the thermotherapy head, including a displacement adjustment mechanism, a thermotherapy head, and a temperature control system; an auxiliary flexion-extension mechanism and linkage control module, including a knee assistive support, a strap, and a drive assembly; and a real-time feedback and remote monitoring module. The multi-angle machine vision monitoring module, the intelligent positioning and temperature control module for the thermotherapy head, and the auxiliary flexion-extension mechanism and linkage control module achieve data fusion and closed-loop linkage control through a main control chip. This invention facilitates real-time and accurate monitoring of rehabilitation movements, intelligent positioning and dynamic temperature control of the thermotherapy head, quantitative evaluation of rehabilitation effects, and closed-loop optimization of training parameters, thereby improving the accuracy, safety, and patient compliance of lower limb joint rehabilitation treatment.

This invention provides a biomimetic lower limb robot prosthesis testing system and method, comprising: a humanoid robot testing body, a load module, a support module, and a data acquisition module; the humanoid robot testing body includes at least human lower limb joints for simulating human lower limb walking; the human lower limb joints include at least one of a knee joint, an ankle joint, and a foot module, and at least a portion of the human lower limb joints can be replaced with a prosthesis test unit, enabling the humanoid robot testing body to drive the prosthesis test unit for walking tests; the load module is disposed on the humanoid robot testing body for providing a target load to the prosthesis test unit; the support module provides a walking path for the humanoid robot testing body to perform walking tests; and the data acquisition module monitors the test parameters of the prosthesis test unit during walking tests. This invention can simulate real-world usage scenarios and achieve accurate testing of multi-dimensional prostheses.

The invention relates to the technical field of rehabilitation training, and relates to an evaluation and training method and system based on a lower limb joint rehabilitation apparatus, and the method comprises the steps: obtaining multi-dimensional motion data points of a target joint at each moment when a patient carries out training in a preset type of training mode; obtaining a first angle-angular velocity mapping curve and a second angle-angular velocity mapping curve according to the multi-dimensional action data points of the target joint from the first moment to the nth moment; constructing a time sliding window, and inputting the multi-dimensional action data points after the nth moment into the time sliding window; and calculating an evaluation coefficient of each moment after the (n + m) th moment, and determining a training mode of training the patient at each moment according to the evaluation coefficient of each moment. According to the invention, intelligent closed-loop regulation and control of the training difficulty are realized, safety risk and efficiency reduction caused by adjustment lag are avoided, and the automation level and the overall effect of rehabilitation training are remarkably improved.

The invention discloses a rehabilitation exoskeleton driving optimization method based on lower limb energy transfer characteristics, which comprises the following steps: firstly, acquiring and analyzing kinematics and dynamics data of a user during walking, and calculating lower limb joint torque, power and energy transfer efficiency between joints; secondly, constructing a high-fidelity man-machine coupling dynamic model fusing human muscle-bone and exoskeleton mechanisms and man-machine contact interaction; and finally, constructing a target function according to key indexes such as energy transfer efficiency and the like, and automatically generating an exoskeleton personalized driving strategy matched with the individual gait characteristics of the user through a simulation optimization algorithm. According to the method, the energy flow reference of the hip-knee-ankle joint of a normal person is established through calculation, the energy transfer deviation of an individual patient is analyzed, an exoskeleton driving curve is simulated and optimized based on man-machine coupling dynamics, the patient gradually recovers to be close to a normal energy transfer mode under the safety constraint, and the energy transfer efficiency is improved. Therefore, gait symmetry, propelling capability and comfort are improved.

The application provides a lower limb rehabilitation exoskeleton robot control method and system, which comprises the following steps: collecting joint torque, lower limb joint angle, joint angular velocity and plantar pressure data of a patient to calculate a rehabilitation state evaluation index; collecting the angle difference of left and right hip joints, identifying the current gait type and the expected trajectory under the corresponding gait based on the gait phase variable, and optimizing the expected trajectory based on the rehabilitation state evaluation index to obtain a target optimized trajectory; calculating the nominal torque based on the acceleration of the trajectory and the parameters of the dynamics model, designing a sliding surface through the implementation of monitoring trajectory tracking error, generating a compensation torque, and calculating a control torque vector. By identifying the gait type and generating a personalized trajectory, and then decomposing the nominal torque and the compensation torque through the U-K controller, high-precision tracking is realized while the model uncertainty disturbance is inhibited, and the naturalness of human-machine cooperation and the safety of rehabilitation training are significantly improved.

Individually adapted, rotatable footplate with inlays. In rowing and canoeing, the footplate is essential for transferring leg and overall body power, and is indispensable for stabilizing and thus propelling the boat. Conventional footplates do not accommodate the individual, genetically diverse physiques of each person, resulting in various disadvantages and problems during use. Furthermore, the joints of the lower extremities are not fully mobile. The innovative, rotatable footplate, optionally equipped with a tilting mechanism, is customized in material type, thickness, and stiffness to the user's foot position. Only with this rotatable footplate is safe use without risk of injury to the user's body possible.The rotating footplate is custom-made in various formats through milling, casting, and laminating of the respective materials, ensuring a perfect fit for each individual user. The rotating footplate provides safety and comfort, minimizes injuries, increases boat speed, and boosts the user's performance when rowing, canoeing, or using an ergometer. The individual adaptation of the rotating footplate reduces stress on the human body and prevents injury.

The application provides a sports action correction and monitoring system based on image recognition and big data, and relates to the technical field of artificial intelligence.The data synchronization and fusion module uses big data processing technology to integrate multi-source data, eliminate space-time differences, and improve the accuracy and reliability of analysis results.The biomechanics solving module uses Lagrange equation to calculate the lower limb joint torque vector in real time, and realizes instant monitoring of the joint torque.The load optimization module uses Adam optimization algorithm to optimize the stride width and knee flexion angle through gradient descent method, minimizes the maximum joint torque, reduces the joint load of athletes, and prevents potential harm.The feedback display module transmits the optimized action parameters to wearable devices in real time, guides athletes to adjust actions in real time, and ensures the efficiency and safety of training.

The invention relates to the field of medical treatment, and discloses an intelligent rehabilitation device for postoperative functional recovery of lower limb joints, the intelligent rehabilitation device comprises a bottom plate, the upper surface of the bottom plate is fixedly connected with a seat, the upper surface of the bottom plate is fixedly connected with a supporting block, and the upper surface of the bottom plate is slidably connected with a moving frame; a first supporting plate is fixedly connected to the upper surface of the movable frame, a pedal is fixedly connected to the upper surface of the first supporting plate, a strap is fixedly connected to the upper surface of the pedal, a first rack is fixedly connected to the inner top wall of the movable frame, and a first gear is fixedly connected to the inner bottom wall of the movable frame. When a user trains the lower limbs, the upper limbs of the user are also promoted to be synchronously matched for training, the synchronous training of the upper limbs and the lower limbs requires mutual matching and coordinated movement of all parts of the body, the balance ability and coordination of the body can be improved, the patient can be helped to more quickly adapt to various action requirements in daily activities, and the training efficiency is improved. And the risk of accidents such as falling is reduced.

This invention discloses a quick-release lower limb joint assistive exoskeleton, relating to the field of exoskeleton technology. The exoskeleton includes a lumbar fixation and adjustment component and an assistive component. The lumbar fixation and adjustment component comprises a back support, a waist belt, exoskeleton connectors, and a control power supply component. The back support is connected at both ends to two exoskeleton connectors via the waist belt, and the two connectors are symmetrically arranged. Each connector has a quick-release socket, and the assistive component has a quick-release plug that mates with the quick-release socket. The quick-release socket and plug enable a detachable mechanical fixation and electrical connection between the assistive component and the lumbar fixation and adjustment component. This invention, through the cooperation of the quick-release socket and plug, achieves simultaneous rapid mechanical fixation and electrical connection between the assistive component and the lumbar fixation and adjustment component, improving modularity and ease of use.

The invention relates to the technical field of lower limb recovery, and provides an orthopedic trauma recovery training device which comprises a height adjusting assembly, and the top of the height adjusting assembly is provided with a thigh cushion used for supporting the hip of a patient; the backrest assembly is rotationally connected to the rear end of the height adjusting assembly through a damping connector, and linkage control over the hip joint, the knee joint and the ankle joint is achieved through the arrangement of structures such as meshing transmission of a first driving gear and a second meshing gear and meshing transmission of a second driving gear and the second meshing gear; when the thigh supporting plate swings, gear transmission forcibly drives the shank supporting plate and the foot connecting rod to move cooperatively according to a preset track, the natural flexion and extension rhythm of lower limb joints when a human body walks is simulated truly, the problem of motion incoordination caused by single joint training is solved, and the problems of motion incoordination and insufficient adaptability in the prior art are solved.

This invention discloses an IMU-based method and system for predicting lower limb joint dynamic parameters. The method includes the following steps: acquiring kinematic data of key rigid bodies in the lower limb kinetic chain using four inertial measurement units (IMUs) configured at specific locations on the lower limb; preprocessing the kinematic data to construct a temporal input feature tensor; inputting the temporal input feature tensor into a pre-trained deep learning prediction model to obtain a fused feature vector; the deep learning prediction model performing split decoding on the fused feature vector, mapping it to different task branches; the multi-task branches simultaneously outputting the joint contact forces and torques of the hip, knee, and ankle joints; and the system integrating the aforementioned IMU-based method for predicting lower limb joint dynamic parameters. This invention achieves real-time, high-precision synchronous prediction of contact forces and torques of the hip, knee, and ankle joints using only IMU sensors, and is suitable for rehabilitation assessment and motion monitoring.

The invention provides a lower limb rehabilitation exoskeleton robot control method and system. The method comprises the following steps that the joint torque, the lower limb joint angle, the joint angular velocity and plantar pressure data of a patient are collected to calculate rehabilitation state evaluation indexes; the angle difference value of the left hip joint and the right hip joint is collected, the current gait type and the expected trajectory under the corresponding gait are recognized based on the gait phase variable, and the expected trajectory is optimized based on the rehabilitation state evaluation index to obtain a target optimized trajectory; and calculating a nominal torque based on the kinetic model parameters and the acceleration of the trajectory, designing a sliding mode surface by implementing a monitoring trajectory tracking error, generating a compensation torque, and calculating to obtain a control torque vector. The gait type is recognized, the personalized trajectory is generated, and the nominal torque and the compensation torque are decomposed through the U-K controller, so that the uncertainty disturbance of the model is inhibited while high-precision tracking is realized, and the naturalness of man-machine coordination and the safety of rehabilitation training are remarkably improved.

The invention relates to a multi-joint cooperative control system for a lower limb power-assisted exoskeleton, and belongs to the field of robot exoskeletons. Comprising a sensor used for acquiring a lower limb joint angle and interaction force between a lower limb and a lower limb exoskeleton in the movement process of a user and sending the interaction force to a wireless router; the communication unit is used for sending the received lower limb joint angle and the interaction force between the lower limb and the lower limb exoskeleton to the main control board; the main control board is used for outputting an instruction to the lower limb joint motor based on the received lower limb joint angle and the interaction force between the lower limb and the lower limb exoskeleton; and the lower limb joint motor is used for assisting the lower limbs according to the received instruction. According to the system, the real-time hip and knee joint assisting moments are obtained through the hip and knee joint assisting curves, the situation that the motion trend of a user is recognized through a sensor and then assisting is conducted is not needed, the effectiveness and smoothness of lower limb exoskeleton assisting are improved, and the user experience is improved.

The invention relates to a hemiplegic gait patient muscle strength grading method, which comprises the following steps: acquiring videos of walking, sitting up and standing up and standing with one foot of a patient, processing each frame in the videos by using a deep learning model, and calculating to obtain joint node data of the patient; inputting the joint node data obtained by calculation into a muscle-bone dynamics model to obtain kinematics data of lower limb joints; on the basis of the kinematics data of the patient, in combination with a foot-ground contact model, calculating muscle dynamics data and ground counter-acting force data of the lower limbs through a muscle recruitment method; and establishing an intelligent muscle strength grading algorithm for the hemiplegic patient, and performing grading evaluation on the lower limb muscle strength of the patient according to the calculated muscle dynamics data of the lower limbs of the patient and the kinematics data of the lower limb joints of the patient. The invention further relates to a hemiplegic gait patient muscle strength grading system. According to the method, kinematics, dynamics and muscle force conditions under the hemiplegic gait can be systematically evaluated, and accurate classification of the muscle force of the hemiplegic gait patient is achieved.

This invention discloses a method for estimating lower limb joint moments based on deep learning using physical information, belonging to the field of lower limb joint moment estimation technology. The method includes: acquiring data from three six-axis inertial measurement units (IMUs) set on the lower limb during movement and corresponding reference joint moment data based on an open-source lower limb biomechanical dataset; constructing a temporal input after preprocessing; building a TCN-BiLSTM model combining a temporal convolutional network and a bidirectional long short-term memory network; establishing a loss function containing physical information constraints based on prior knowledge of lower limb dynamics; training the model using the loss function; and simultaneously estimating the joint moments of the hip, knee, and ankle joints in the sagittal plane using the trained model. Compared with existing technologies, this invention can achieve high-precision estimation of lower limb multi-joint moments under various movement modes with a small amount of inertial sensor data input, improving the model's physical consistency, generalization ability, and ease of application.

The invention provides a lower limb rehabilitation exoskeleton on-demand power-assisted control method and system, and belongs to the technical field of rehabilitation robot and exoskeleton control, and the method comprises the steps: building a kinetic model through a Lagrange method, and forming a man-machine coupling model; designing a momentum observer, and estimating the lower limb joint torque of the patient; the estimated lower limb joint torque of the patient is subtracted from the expected joint torque, and the expected assisting torque of the lower limb rehabilitation exoskeleton is obtained; based on a spring damping man-machine interaction model, mapping the expected assisting torque into an equivalent expected joint track of the lower limb rehabilitation exoskeleton; a micro arc tangent function modeling actuator is adopted to input saturation, a state-related saturation gain matrix is obtained in combination with the Lagrange median theorem, and an input saturation prediction nonlinear fast terminal sliding mode controller is designed to track an expected trajectory to achieve power-assisted control. According to the method, the main power of a patient can be effectively estimated, the power assistance of the lower limb rehabilitation exoskeleton can be adaptively adjusted, and the input saturation and buffeting influence can be effectively inhibited.

The application discloses a kind of power-assisted exoskeleton devices, including: bottom plate, pedestal being arranged on the bottom plate, and seat cushion being fixed at the top of the pedestal;It further includes two groups of exoskeleton support structures arranged in the front side of the pedestal;The front end of each group of the exoskeleton support structure is further provided with pedal structure;It further includes meshing transmission assembly arranged between each group of the pedal structure and exoskeleton support structure.The application is realized by the exoskeleton support structure of two groups arranged, cooperate with the pedal structure arranged in the front end of exoskeleton support structure, to realize the support of patient lower limbs, and improve the power-assisted effect of hip, knee, ankle joint rigid support, and under the action of exoskeleton support structure, cooperate with meshing transmission assembly, further realize the range of motion training of patient lower limb joint, the device component structure is simple, and realizes the activity training of lower limb multi-joint, and the rehabilitation effect is remarkable, and practicality is high.

The application discloses a mobile lower limb rehabilitation exoskeleton robot, and relates to the technical field of automatic control.The mobile lower limb rehabilitation exoskeleton robot comprises a control unit, a mobile base, a handrail backrest part and an exoskeleton joint unit.The control unit is arranged above the mobile base.The handrail backrest part is arranged in front of the control unit.The exoskeleton joint unit comprises a left leg part, a right leg part, two hip joint motors and two knee joint motors.One hip joint motor and one knee joint motor are arranged on the left leg part, and the other hip joint motor and the other knee joint motor are arranged on the right leg part, which are used for driving the hip joint and the knee joint of a user to move respectively.The control unit is connected with servo drivers of the hip joint motors and the knee joint motors through an EtherCAT communication protocol, so that real-time cooperative control of lower limb joint movement is realized.The application can significantly shorten the response time from user intention to joint action, avoid gait instability or falling risk caused by delay, and improve gait coordination and safety.

The application provides a lower limb multi-joint angle prediction method, system, device and medium, the method comprises the following steps: collecting multi-modal data of a user, and preprocessing the multi-modal data to obtain a data set; the data set is divided into a training set and a test set, and the training set is embedded to obtain an embedded training set; using the embedded training set, a preset structure double tower model is trained to obtain a lower limb multi-joint angle prediction model; using the test set, the prediction result of the lower limb multi-joint angle prediction model is evaluated to obtain an evaluation result. The application provides a lower limb multi-joint angle prediction method based on a double tower Transformer and multi-modal data to solve the problem that the current lower limb joint angle prediction technology based on multi-modal data ignores muscle and joint coordination, and builds space-time features in the double tower Transformer architecture to improve the prediction performance of the model.

The utility model relates to the technical field of lower limb joint rehabilitation, in particular to a lower limb joint rehabilitation fixing device which comprises a groove body, an end plate connected with the groove body, a binding assembly connected with the groove body, a heating assembly detachably connected with the end plate and a filling assembly. The filling assembly is provided with a flexible working face and arranged in the through groove, the end plate is located at one end of the through groove, and the heating face of the heating assembly faces the through groove. The filling assembly is arranged in the through groove, the feet of a patient are directly placed on the filling assembly during use, direct rigid contact with the through groove is avoided, unsmooth blood circulation caused by extrusion of the feet of the patient is avoided, and the heating assembly is arranged to heat the feet of the patient under the condition that blood circulation of the feet of the patient is guaranteed through the filling assembly. Blood circulation of the feet of the patient is further promoted, and rehabilitation is promoted.

The invention relates to rehabilitation physiotherapy equipment, belongs to the technical field of rehabilitation training equipment, and provides rehabilitation physiotherapy equipment in order to solve the problems that in the prior art, rehabilitation training of ankle joints, leg muscles or lower limb joints cannot be met at the same time, and massage and heating devices are not arranged for improving the training rehabilitation effect. Comprising a height adjusting assembly, a seat assembly, a manual adjusting assembly and a lower limb fixing mechanism, and the lower limb fixing mechanism is composed of a shank fixing assembly and a foot fixing assembly. Meanwhile, officers and soldiers with injured leg muscles and joints or injured ankle joints can be independently trained or simultaneously trained, the muscles are massaged and heated in the training process, blood circulation is promoted, and the rehabilitation training effect is improved.