487 results about "Upper limb rehabilitation" patented technology

The invention discloses an upper limb exoskeleton rehabilitation robot control system and method, and relates to the technical field of rehabilitation robot upper limb control, and the method comprises the steps: collecting multi-modal data such as multi-channel myoelectricity, joint angles, angular velocity and interactive torque; constructing a sliding window feature vector, predicting a next joint angle increment through TCN and Bi-LSTM deep networks, and outputting intention confidence; and based on the confidence coefficient and the muscle fatigue factor, dynamically adjusting an impedance parameter, and combining an impedance control model to generate a power-assisted torque in real time so as to realize power-assisted torque output. By introducing an impedance adjustment mechanism of multi-modal perception, deep time sequence learning and myoelectricity driving, the bottleneck of a traditional upper limb rehabilitation robot in the aspects of intention prediction, parameter adjustment and training individuation is broken through, and the accuracy, safety and active participation degree in the rehabilitation training process are remarkably improved; wide clinical application prospects and industrial transformation values are realized.

The invention belongs to the field of cerebral apoplexy rehabilitation training, and provides a cerebral apoplexy upper limb dynamic rehabilitation method and system based on vagus nerve electrical stimulation, the excitement degree of a cortical spinal cord pathway of a patient is measured and evaluated by using motor evoked potential to obtain a motor function evaluation result, and an initial rehabilitation training task is set according to the motor function evaluation result; the training motion intention of the patient is determined by monitoring the electroencephalogram signal and the electromyographic signal of the patient, and percutaneous ear vagus nerve electrical stimulation is triggered; after percutaneous ear vagus nerve electrical stimulation, performing rehabilitation training analysis on basic clinical characteristics and multi-modal signals of the patient to determine intermuscular coordination, brain region connectivity and brain muscle coupling of the patient; the training condition of the patient is evaluated according to the rehabilitation training analysis result, and parameters of percutaneous ear vagus nerve electrical stimulation and training tasks are adjusted based on the evaluation result for iterative rehabilitation training; and stopping iteration until the rehabilitation training analysis result of the patient reaches a preset standard, and completing rehabilitation training.

The invention relates to the technical field of medical rehabilitation, and discloses a virtual fusion personalized upper limb rehabilitation training cloud platform and method. The platform is composed of a multi-source biological signal acquisition module, a motion function feature modeling module, a heterogeneous data fusion module, a rehabilitation knowledge graph construction module, a dynamic training planning module and the like. The method comprises the steps of collecting multi-source biological signals, carrying out hierarchical feature modeling, carrying out data fusion, constructing an atlas database, generating a personalized rehabilitation scheme and the like. In this way, individuation and precision of upper limb rehabilitation training are achieved. Patient data can be comprehensively collected, fusion rehabilitation state representation is generated, a double-layer atlas database is constructed to assist training planning, training safety is guaranteed, the rehabilitation effect is predicted, pertinence, scientificity and efficiency of rehabilitation training are effectively improved, and high-quality rehabilitation service is provided for upper limb dysfunction patients.

The invention discloses a fuzzy PID (Proportion Integration Differentiation) control method for an upper limb rehabilitation robot based on myoelectricity feedback. The fuzzy PID control method comprises the following steps: step 1, sampling surface myoelectricity signal data; 2, performing signal processing on the surface electromyogram signal data; 3, performing feature extraction on the surface electromyogram signal data after signal processing through a feature selection method so as to obtain a key feature set; 4, creating a fusion model, training the fusion model by using the fatigue state key feature set, and determining an optimal fusion model; detecting the fatigue state of the person to be detected in real time; and step 5, obtaining a fatigue state corresponding to the currently obtained surface electromyogram signal of the patient in real time, and dynamically adjusting a corresponding PID parameter in combination with a self-adaptive fuzzy PID controller so as to adapt to different fatigue states. Proportional, integral and differential parameters can be dynamically adjusted according to the real-time fatigue state of a patient; the method adapts to different fatigue levels of patients, and control flexibility and response speed are improved.

The invention discloses a multi-link collaborative evaluation and feedback system for upper limb rehabilitation training, and belongs to the technical field of medical rehabilitation, and the system comprises a data collection module which is used for obtaining the related data of the upper limb of a patient in the rehabilitation training process, and the related data comprises the motion posture, the muscle activity condition and the joint activity degree; the data processing module responds to the data acquisition module and is used for preprocessing the acquired related data, including filtering and denoising the related data, acquiring feature information in the preprocessed related data and sending the feature information to the data acquisition module; the feature information comprises movement tracks of joints, contraction intensity and time of muscles and coordination of upper limb movement. Multi-dimensional data such as action postures, muscle movement conditions and joint movement ranges in upper limb rehabilitation training are collected, preprocessing and feature extraction are carried out through the data processing module, the upper limb rehabilitation condition of a patient can be comprehensively and accurately evaluated, and a basis is provided for formulating a personalized rehabilitation scheme.

The invention discloses a cerebral apoplexy patient upper limb rehabilitation evaluation method based on electroencephalogram and electromyographic signals. The method specifically comprises the following steps that signals are collected and preprocessed; electroencephalogram and electromyographic signal decomposition; performing multi-scale processing; calculating transmission spectrum entropy; and upper limb rehabilitation grade evaluation: mapping a fitting relationship between the MSTSE significance area value of each patient and a Brunnstrom evaluation scale based on a Spearman correlation coefficient, analyzing an FCMC characteristic index and a change trend which are significantly related to the grade of the Brunnstrom evaluation scale, and performing quantitative evaluation on the disease grade of the stroke patient. According to the technical scheme, a binary variational mode decomposition-multi-scale transfer spectrum entropy method is used for representing the FCMC coupling relation between the brain motor cortex and the corresponding muscular tissue, and in combination with a Brunnstrom rating scale, objective quantitative evaluation of the rehabilitation level of the upper limbs of the stroke patient is achieved.

The invention relates to the technical field of cerebral apoplexy rehabilitation, in particular to a cerebral apoplexy patient upper limb rehabilitation evaluation system which comprises a motion capture module, an analysis module, a processing module, a training module, a feedback module, an optimization module and a sharing module. The analysis module performs analysis according to the data acquired by the motion capture module; the processing module formulates a training plan according to the analyzed illness state; the training module is used for training the patient according to the evaluation result; the feedback module is used for feeding back the training effect; according to the system, the training result of the patient can be comprehensively evaluated in real time, the training plan is adjusted in time according to the rehabilitation progress of the patient, the rehabilitation plan and the training mode are continuously optimized, the optimization module can gradually adapt to the individual difference and rehabilitation requirements of the patient, more accurate rehabilitation suggestions are provided, and the rehabilitation efficiency is improved. Therefore, the rehabilitation effect is obviously improved.

The invention discloses an upper limb rehabilitation control method and system based on a multimode coordination adaptive brain-computer interface, and belongs to the technical field of neural rehabilitation engineering and brain-computer interfaces. The system comprises a brain signal acquisition module, a self-adaptive residual filtering module, a feature extraction module, a predictive control module, an upper limb rehabilitation actuator and a self-adaptive updating module. The core is that a self-adaptive updating module constructs a composite error cost function by fusing kinematics errors of a physical layer and error correlation potentials of a neurocognitive layer, and on the basis of the composite error cost function, a front-end filtering weight and a network weight of a rear-end control model are synchronously adjusted, so that full-link parameter collaborative optimization from signal preprocessing to motion control is realized. According to the method, the framework limitation of single error feedback and independent parameter optimization of a traditional system is broken through, a closed-loop brain-computer interface system which can sense internal and external states and has system-level self-optimization capability is constructed, and the decoding robustness, the control precision and the practicability under long-term use are effectively improved.

The invention discloses an upper limb rehabilitation training method and system based on a human body motion model, and relates to the technical field of rehabilitation training. Constructing a human body motion model and outputting simulation data; calculating a physiological index coefficient, and further calculating the exercise intensity of each training action; calculating a motion mode complexity index of each training action so as to obtain and calculate the training duration of each training action; and calculating a motion deviation value, and further calculating a comprehensive dynamic deviation index. Presetting a threshold value and judging whether the rehabilitation training plan is suitable for the current state of the patient; whether a rehabilitation training plan needs to be changed; according to the method, the suitability of the rehabilitation training plan can be evaluated in real time, and the training scheme is dynamically adjusted; the training is always fit with the condition of the patient, and the rehabilitation efficiency and success rate are improved.

The invention discloses an upper limb rehabilitation intelligent self-adaptive system based on multi-modal fusion and MRD-FES cooperation. The system comprises a multi-modal signal acquisition module, a dynamic intention analysis module, a variable damping precise execution module, a neural remodeling strengthening module and a quantitative effect evaluation module. The tDCS-MRD-FES time sequence cooperation protocol is provided, the cortical excitability is improved through tDCS preprocessing, MRD drives training based on intention, FES closed loop strengthens muscle contraction, and vibration tactile feedback is assisted to strengthen sensory movement integration. And the quantitative effect evaluation module further combines a neuroplasticity index and clinical scale digitalization to realize dynamic optimization of training parameters.

The utility model provides an electric wheelchair with a rehabilitation function, which is used for upper limb rehabilitation exercise of a wheelchair user and comprises a touch sensor array arranged on the surface of an armrest of the electric wheelchair, and the touch sensor array comprises a plurality of touch sensors capable of being triggered by touch actions; when the touch sensor array is touched, the trigger state and the triggered sequence of each touch sensor are sent to the control module, so that the electric wheelchair moves according to the trigger state and the triggered sequence of each touch sensor in the touch sensor array; a wheelchair left side driving wheel is controlled by the touch action of the touch sensor array at the left armrest, and a wheelchair right side driving wheel is controlled by the touch action of the touch sensor array at the right armrest, so that a user can automatically judge the exercise amount of upper limb rehabilitation exercise according to the rotating direction and the moving distance of the electric wheelchair; according to the rehabilitation exercise device, convenient rehabilitation exercise can be provided for people with mobility difficulties, and a user can conveniently evaluate the rehabilitation exercise amount of the user.

The embodiment of the invention discloses a cerebral apoplexy upper limb rehabilitation training system and method based on dynamic reward feedback. A data acquisition module is used for acquiring physiological signals, motion signals, emotional state data and training performance data; the motion intention decoding module is used for performing motion intention feature extraction and reliability evaluation on the physiological signals according to an improved MREE-Net + + fusion algorithm, performing weighted fusion after feature weights are adjusted according to a reliability result, obtaining a unified motion intention feature vector, performing motion intention decoding, and obtaining a motion intention intensity index and a motion intention vector; the dynamic reward decision module is used for processing the facial micro-expression data according to an improved VGG-Face model to obtain an emotion titer, and obtaining an emotion awakening degree according to the voice signal; a reward action is generated according to an improved deep reinforcement learning algorithm; and the adaptive training regulation and control module is used for generating a personalized virtual training scene according to the generative adversarial network and regulating and controlling the training intensity according to the fatigue index. The rehabilitation training effect can be improved.

The utility model provides an upper limb rehabilitation training device which comprises a base, a seat is arranged at the upper end of the base, handrails are arranged on the two sides of the seat, a fixing block is arranged on the rear side of the seat, a training mechanism is arranged below the handrails, and the training mechanism comprises an installation block, a sliding rail, a sliding block, a lead screw, a hinge block, a hinge rod and a first motor. The handrails on the two sides can be controlled to conduct rehabilitation training of different degrees on the upper limbs, use is convenient, the structure is simple, the fixing mechanisms are arranged on the handrails, each fixing mechanism comprises a supporting plate, a fixing belt, a fixing buckle, a fixing hole and a handle, the supporting plates and the fixing belts are matched, the arms of a patient can be fixed and prevented from falling off, and the rehabilitation training effect is good. A lifting mechanism is arranged below the cushion and comprises a connecting plate, a guide pipe, a guide rod, a rotating rod, a gear and a second motor, so that the height of the cushion can be conveniently adjusted, and the situation that the patient feels uncomfortable when using the device and even the illness state of the patient is deepened due to the fact that the device is not matched with the body shape of the patient is avoided.

The desktop type upper limb rehabilitation robot comprises a shell structure with a bottom plate, a screw rod structure and a clamping seat penetrating through the bottom plate, the clamping seat is provided with a threaded hole and a clamping part which are located on the two opposite sides of the bottom plate respectively, the screw rod structure is in threaded connection with the threaded hole, one end of the screw rod structure abuts against the bottom plate, and the other end of the screw rod structure abuts against the clamping part. The clamping base can move linearly, and the clamping part and the bottom plate are matched to clamp the table top. According to the desktop type upper limb rehabilitation robot provided by the invention, the clamping seat and the screw rod structure are mounted on the bottom plate of the robot, that is, the desktop clamp is integrated in the robot and can be directly mounted on a desktop without additional clamps, so that the desktop type upper limb rehabilitation robot can be suitable for most desktops.

The invention discloses a double-upper-limb rehabilitation training management system which comprises a training management system, and the training management system comprises an intelligent rehabilitation platform, a modeling DFM platform, a bionic robot platform and a robot structure platform. Effective evaluation is carried out through a movement route of the system before training, a corresponding PNF upper limb training track is planned based on the functional level and the seat height posture of a patient, training imitating therapist skills is carried out, excitation and inhibition of main prime mover muscles and antagonistic muscles of the upper limb of the uninjured side of the patient are detected through surface myoelectricity, and the result serves as a normal standard. Myoelectricity detection is carried out on prime mover muscles and antagonistic muscles of the upper limb of the affected side, the effects of promoting excitation of the prime mover muscles and inhibiting the antagonistic muscles are carried out according to the state presented in the motion trail, and the excitation of the prime mover muscles is mainly promoted at the positions of muscle abdomens and muscle tendons in a tapping stimulation mode in an intermediate frequency therapeutic apparatus.

The invention discloses an upper limb rehabilitation training system and method for a stroke patient. Relates to the technical field of medical rehabilitation. According to the stroke upper limb rehabilitation training system and method, the limbs are driven by a machine to do repeated movement, a nervous system for controlling limb movement is stimulated and reconstructed, and therefore the movement function of the limbs is recovered, and the rehabilitation training effect of the limbs is improved. On the basis of an existing motion tracking and feedback technology, the system and the method are improved, real-time data analysis is carried out based on a sensor, a brain-computer interface technology and a cloud platform, influences of operation environment information and motion performance are considered in individualized requirements of patients, individual differences and environment variables are comprehensively considered in the rehabilitation process, and the rehabilitation effect is improved. A patient can perform rehabilitation training at any place, a rehabilitation physician, the patient and family members can check the rehabilitation condition of the patient at any time, and the precise training system and method suitable for various environments and changeable rehabilitation requirements are provided.

The invention belongs to the technical field of rope-driven robots, and particularly relates to a rope-driven upper limb rehabilitation robot and a control method thereof. The rope-driven upper limb rehabilitation robot comprises a rehabilitation rack, rehabilitation installation modules symmetrically installed on the rehabilitation rack and exoskeleton rehabilitation arms installed on the rehabilitation installation modules. The shoulder joint abduction / adduction rehabilitation mechanism, the shoulder joint inner side / outer side rehabilitation mechanism and the shoulder joint flexion / extension rehabilitation mechanism are in driving connection with the corresponding far-end driving modules through rope driving assemblies. The rope drive assembly comprises a first idle wheel, a drive guide wheel set, a second idle wheel and a steel wire rope. Transmission among the three rope drive assemblies is independent and matched with one another, automatic and accurate control is facilitated, shoulder joint abduction / adduction rehabilitation, shoulder joint inner side / outer side and shoulder joint flexion / extension flexible driving are achieved, meanwhile, dynamic inertia of the rehabilitation arm in the training process is effectively reduced, and the rehabilitation effect is improved. And the service life and the use stability of the motor and the rehabilitation arm are ensured.

The invention discloses a rehabilitation training upper limb movement measurement method based on depth trajectory coding, which comprises the following steps: acquiring movement data of an upper limb by using a sensor, processing the data by using an inertial navigation algorithm to obtain corresponding speed, direction and displacement, and further obtaining movement information of the upper limb in a three-dimensional space; performing speed correction and accumulative error correction on the motion information by using an AZVU method; coding the corrected motion information by using a track coding mapping technology to generate a track coding graph; and constructing a TEM-VGG model based on the pre-trained convolutional layer, inputting the trajectory coding graph into the model to obtain probability values corresponding to different upper limb motion posture categories, and completing measurement of the upper limb motion. The method has certain advantages on multiple indexes in an upper limb rehabilitation posture recognition task, the confusion condition during classification can be effectively reduced, the recognition accuracy is remarkably improved, and the method has excellent performance in a complex rehabilitation action recognition task.

The invention discloses a myoelectricity-driven multi-channel functional electrical stimulation upper limb rehabilitation platform and a method thereof. The platform comprises a myoelectricity acquisition device, a myoelectricity acquisition data processing system, an upper computer and an electrical stimulation system, the input end of the myoelectricity acquisition data processing system is connected with the myoelectricity acquisition device; the output end of the microprocessor is connected with the input end of the upper computer in a wireless or wired manner; the output end of the upper computer is connected with the electromyographic system and the electrical stimulation system in a wireless or wired mode. The myoelectricity acquisition device acquires myoelectricity signals on the surface of the healthy side limb of a patient; the myoelectricity collection data processing system is used for filtering the collected myoelectricity signals on the uninjured side of the patient to obtain myoelectricity data; the upper computer carries out gesture recognition processing according to the myoelectricity data to obtain electrical stimulation parameter configuration and sends the electrical stimulation parameter configuration to the electrical stimulation system; the electrical stimulation system outputs a matched waveform stimulation signal to the limb surface of the diseased side of the patient according to electrical stimulation parameter configuration; the affected side limbs are controlled through subjective movement of the healthy side limbs of the patient to achieve bilateral fine movement, and the rehabilitation process is accelerated.

The invention relates to the technical field of medical rehabilitation robots, in particular to a safe upper limb rehabilitation exoskeleton robot which comprises a fixing frame and a mechanical arm arranged on the fixing frame and used for assisting an arm of a patient to move. The mechanical arm comprises a shoulder joint vertical folding and unfolding module, a shoulder joint horizontal folding and unfolding module, a shoulder joint flexion and extension module, an elbow joint flexion and extension module, a wrist joint flexion and extension module and a forearm rotating module which are connected in sequence, and the mechanical arm can be suitable for a left arm or a right arm by switching a left state and a right state. Each module of the mechanical arm is provided with a mechanical limiting structure used for limiting the movement range of the corresponding module, and the mechanical limiting structures can be switched between the left state and the right state and used for synchronously switching when the mechanical arm is switched between the left state and the right state so as to guarantee the safety of a patient. By the adoption of the spring positioning pin for adjustable limiting, the left-right interchange function of the mechanical arm can be achieved, meanwhile, limit angle mechanical safety limiting of the two arms is guaranteed, and the safety of equipment is improved.

The invention discloses an upper limb rehabilitation safety nursing seat, and particularly relates to the technical field of rehabilitation nursing chairs, the upper limb rehabilitation safety nursing seat comprises a wheelchair body, the wheelchair body comprises a base, front wheels are symmetrically arranged on two sides of one end of the base, rear wheels are symmetrically mounted on two sides of the other end of the base, and a fixing frame is arranged at the top of the base; a cushion is connected to the top of the fixing frame, and a supporting frame is installed at the end, close to the rear wheel, of the top of the fixing frame. The supporting arms, the holding plates and the clamping seats are symmetrically arranged on the two sides of the wheelchair body, the upper limbs and arms of a patient can be put on the holding plates and embedded into the clamping seats, and under cooperation of the supporting plates, the supporting frames, the connecting blocks, the connecting rods and the driving assemblies, the driving assemblies can drive the supporting frames to move back and forth on the supporting plates; the connecting blocks can push and pull the two connecting rods to move back and forth, the connecting rods can drive the arms of the patient to rotate through the supporting arms and the holding plates, and therefore the upper limbs of the patient can be driven to continuously do front-back expansion movement.

The invention provides an upper limb rehabilitation device control method and device, a storage medium and electronic equipment, and the control method comprises the steps: carrying out analog simulation based on an upper limb model to obtain first motion information of an upper limb, and obtaining second motion information of the upper limb based on the first motion information and a surface electromyogram signal, the first motion information at least comprises a joint angle, a first muscle force, a first joint torque and a first muscle activation function; determining motion control information based on the first motion information and the second motion information; the rehabilitation device is controlled to act based on the motion control information, third motion information is obtained based on the surface electromyogram signals, and the third motion information at least comprises a third muscle activation function and third muscle force; an output of the muscle force is adjusted based on a comparison of the third muscle force and the first muscle force. By making the personalized musculoskeletal model, the personalized health plan is made for the patient, and the purpose of helping the patient recover the upper limb elbow joint flexion function is achieved.

The application discloses a rehabilitation robot control method based on multi-source information perception and electronic equipment, and the method comprises the following steps: acquiring upper limb modal signals of a patient without motor function, wherein the upper limb modal signals comprise electroencephalogram signals, and eye movement signals and / or electromyogram signals; for each kind of upper limb modal signal, using an intention recognition model to perform motor intention recognition on the upper limb modal signal to obtain a corresponding motor intention recognition result; acquiring a confidence degree corresponding to each kind of upper limb modal signal; determining the motor intention of the patient according to the motor intention recognition result corresponding to each kind of upper limb modal signal and the corresponding confidence degree; determining a motor control signal of an upper limb rehabilitation exoskeleton according to the motor intention; and controlling the upper limb rehabilitation exoskeleton to move according to the motor control signal. The application can improve the motor intention recognition accuracy of the patient without motor function in the upper limb rehabilitation training process.

The invention discloses an upper limb rehabilitation training device, method and system and a storage medium, and the method comprises the steps: constructing a virtual scene according to the rehabilitation condition of a patient, and combining rehabilitation paradigms from a paradigm library; high-channel electroencephalogram signals are collected, and real-time quality monitoring is conducted; extracting motor imagery features from the electroencephalogram signals and analyzing the motor imagery features into a motor intention; mapping the motion intention to a virtual limb to realize VR / AR body feedback; and behavior data such as concentration degree are calculated and displayed in real time, and personalized rehabilitation evaluation is completed. By the adoption of the technical scheme, the problems that in existing cerebral apoplexy rehabilitation treatment, the normal form has body deficiency, the training scene is single, medical intervention lacks real-time performance, rehabilitation evaluation is high in subjectivity, and individuation is insufficient are solved.

The invention discloses an upper limb rehabilitation training device, which relates to the technical field of medical instruments and comprises a workbench, a traction assembly and a support frame. The traction assembly comprises a first connecting rod, a second connecting rod, a third connecting rod, a fourth connecting rod and a sliding block, the sliding block is movably arranged on the workbench, one end of the first connecting rod is fixedly connected with the sliding block, the other end of the first connecting rod is rotatably connected with the second connecting rod, and the fourth connecting rod is rotatably arranged on the workbench and rotatably connected with the third connecting rod. The second connecting rod is rotatably connected with the third connecting rod. The supporting frame is located at the joint of the second connecting rod and the third connecting rod and used for placing the affected limb of the patient. According to the upper limb rehabilitation training device, the supporting frame is dragged to move through the first connecting rod, the second connecting rod, the third connecting rod, the fourth connecting rod and the sliding block, diversification of movement tracks of the supporting frame can be achieved, upper limb movement of a human body can be simulated more accurately, the operation process is more stable, and safety and comfort of rehabilitation training are improved.

The invention relates to the technical field of rehabilitation training, and discloses an electromyographic signal feedback-based upper limb rehabilitation training system, which comprises a main frame body, a training mechanism is mounted on the middle side in the main frame body, and the training mechanism comprises a flexion and extension assembly, a fixing assembly, a massage assembly and an auxiliary training assembly, and is used for carrying out rehabilitation training on arms of a user. An electromyographic signal collecting mechanism is installed on the middle side of the interior of the main frame body and used for collecting the training condition of a user, and a feedback display mechanism is installed on one side of the interior of the main frame body and used for feeding back collected data and displaying the training condition in real time. Through the feedback display mechanism, a user and medical staff can know the muscle activity condition in real time, automatic inflation or deflation is achieved through an air bag in the massage assembly, meanwhile, a vibration motor drives a massage plate and a circular massage block to vibrate, muscles and acupuncture points are stimulated, blood circulation is promoted, muscle fatigue and aching pain can be effectively relieved, and the rehabilitation effect is improved.

The invention discloses an upper limb rehabilitation exoskeleton with a shoulder-arm linkage mechanism, which belongs to the field of rehabilitation devices and comprises a supporting platform, the shoulder-arm linkage mechanism, a shoulder joint mechanism, a big arm and elbow joint mechanism and a front arm and hand mechanism. The shoulder-arm linkage mechanism is connected to the supporting platform in a sliding mode, the shoulder joint mechanism is connected to the free end of the shoulder-arm linkage mechanism, the large arm and elbow joint mechanism is connected to the free end of the shoulder joint, and the front arm and hand mechanism is connected to the free end of the large arm and elbow joint mechanism. A joint actuator is linked through parts such as a gear reduction box and a worm and gear reduction box, so that the rotation center of an exoskeleton shoulder joint can rotate around a set point on a frontal plane so as to shift along with the rotation center of the shoulder joint when the shoulder joint of the human body expands and contracts, and therefore, the dislocation of the upper limb of the human body when the upper limb of the human body moves along with the exoskeleton is reduced; and the wearing comfort of the exoskeleton is improved. The exoskeleton shoulder-arm linkage mechanism is simple in structure, reliable in movement and lower in cost compared with an active shoulder following mechanism driven by a motor.

The invention discloses passive upper limb weight reduction rehabilitation training equipment which comprises an equipment support and further comprises a first-degree-of-freedom movement assembly, a third-degree-of-freedom movement assembly and a hand supporting assembly, one end of the first-degree-of-freedom movement assembly is arranged on the equipment support and can rotate around a J1 shaft relative to the equipment support, and the other end of the first-degree-of-freedom movement assembly can rotate around a J2 shaft relative to the equipment support; one end of the third-degree-of-freedom movement assembly is arranged at the other end of the first-degree-of-freedom movement assembly, the third-degree-of-freedom movement assembly can rotate around a J3 shaft relative to the first-degree-of-freedom movement assembly, the J1 shaft is arranged in the vertical direction, the J3 shaft is arranged in the horizontal direction, and the hand supporting assembly is arranged at the other end of the third-degree-of-freedom movement assembly. According to the passive upper limb weight reduction rehabilitation equipment, driving equipment such as a servo motor does not need to be used, complex dynamic modeling is not needed, upper limb rehabilitation training can be achieved, the overall structure is simple, cost is low, rehabilitation training of shoulder joints and elbow joints can be achieved, driving motors are not needed, the overall structure is simple, and cost is low.

The invention discloses a breast cancer postoperative upper limb function rehabilitation assisting method and system, and the method achieves the precise rehabilitation through multi-dimensional data collection and intelligent scheme generation: collecting the joint movement range, muscle strength index, lymphedema data, VAS pain score and Borg fatigue index of the upper limb of a patient, and carrying out the fusion to generate an upper limb function feature set; dividing the rehabilitation process into four stages, and generating a rehabilitation target corresponding to each stage by means of a preset mapping mechanism based on the feature set; generating a candidate rehabilitation scheme by applying a rehabilitation scheme generation model based on machine learning according to the staged rehabilitation target; through a prediction model based on multi-dimensional evaluation, rehabilitation prediction scores are generated in combination with the upper limb function feature set and the candidate rehabilitation schemes, and the candidate scheme with the highest score is selected as the optimal rehabilitation scheme. Personalized and dynamic management of upper limb rehabilitation after the breast cancer operation is achieved, and adaptability and effectiveness of a rehabilitation scheme are improved.

The invention discloses upper limb rehabilitation training equipment capable of being mutually used by left and right arms, which comprises a small arm elbow joint training mechanism, a big arm shoulder joint training mechanism and a left and right reversing mechanism, and is characterized in that the small arm elbow joint training mechanism is connected with the front end of the big arm shoulder joint training mechanism in a foldable manner through a folding part; the rear end of the big arm shoulder joint training mechanism is connected with the left-right reversing mechanism, and the left-right reversing mechanism is used for driving the big arm shoulder joint training mechanism to rotate relatively. According to the upper limb rehabilitation training equipment capable of being used by the left arm and the right arm, the functions of being small in size, light and easy to use are achieved, the pull rope is used for power transmission, the overall size of the equipment is optimized, daily use is more convenient through the rotating clutch mechanism used by the left arm and the right arm, and the equipment is small in size, convenient to store, simple in structure, practical and easy to operate.