133 results about "Lower limb exercises" patented technology

The invention discloses a lower limb muscle fatigue assessment method and system based on multi-modal physiological signals, and relates to the technical field of biomedical engineering, target muscles are selected, sEMG signals, AUS signals and respiratory flux VE data are synchronously collected, and RPE is recorded; preprocessing various signals to remove interference and abnormal points; extracting sEMG time-frequency domain features and AUS muscle thickness features; fusing features and constructing vectors in a standardized manner; dividing five fatigue grades; and a data set is divided according to stratified sampling, a model is optimized through five-fold cross validation, and real-time features are input to output a fatigue level. Multi-modal physiological signals are fused, fatigue evaluation accuracy is improved, different fatigue stages are finely adapted, muscle load and energy consumption are reduced through personalized adaption and a dynamic adjustment strategy, rehabilitation training safety and comfort are improved, and efficient recovery of lower limb movement functions is assisted.

The invention discloses a method and a related device for closed-loop optimization of a lower limb motor imagery experiment normal form through dynamic mind training, and relates to the field of rehabilitation medicines.The method comprises the steps that electroencephalogram signals of a testee when the testee executes a mind fusion lower limb motor imagery task are collected and preprocessed, and preprocessed electroencephalogram signal data are obtained; based on a dynamic feature extraction technology of a sliding window, calculating electrophysiological indexes in real time; performing weighted fusion on the motor imagery definition, the concentration degree and the correctness degree through predefined weights to generate a comprehensive state score; on the basis of the comprehensive state score, dynamically adjusting a normal feeling and task stimulation parameter applied to the testee; based on the collected electroencephalogram signals, extracting optimal perception motion rhythm and cross-frequency coupling characteristics; and inputting into the trained two-dimensional time convolution network decoding model to obtain the lower limb motor imagery intention of the testee. According to the method, the evoked rate and the stability of the electroencephalogram characteristics of the stroke patient in the lower limb motor imagery task can be improved.

The invention belongs to the technical field of smart old-age care product behavior debugging, and particularly discloses a smart old-age care product behavior dynamic adjustment method based on interactive data perception. According to the method, a sole mechanical fragment, a lower limb movement fragment and a heart rate fragment are extracted based on gait cycle alignment, gait stability, gait coordination and physiological conformity indexes are calculated, and coupling sensing of user movement behaviors and physiological states in the dynamic walking assisting process is achieved; the gait stability and the physiological conformity are fused to construct a gait physiological synchronism criterion, a hierarchical adaptive control strategy is implemented accordingly, and the limitation that a traditional supporting robot only depends on kinematics feedback control is broken through, so that on the premise that the user safety is guaranteed, response type physical and mental collaborative intelligent assistance is achieved, and the user experience is improved. And the risk prevention and control capability of rehabilitation training is effectively improved.

The invention discloses a control method, and the method comprises the steps: collecting the data of a centroid state and an MPC optimal ground acting force in a plurality of motion states of a robot, designing a full-connection residual network, taking the centroid state information as the input, taking the ground acting force as the output, and designing a loss function based on priority. Upper and lower bounds of a friction cone and a sole reaction force are constrained, and the network is trained offline to fit MPC optimization quantity, so that an efficient mode of online reasoning is realized; the joint angle and the angular velocity are fused with the action at the previous moment, the centroid linear velocity and the angular velocity and the foot-ground acting force fitted through a residual network, a bionic reference trajectory is generated through a human motion public data set, different weights are given to a reward function group according to a dominant function value obtained through calculation, and the control performance is improved; symmetrical loss constraint is added to lower limb movement, and the algorithm convergence speed is increased. And finally, training to obtain a whole-body control strategy based on model priori knowledge and a human motion reference trajectory.

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.

Disclosed in the present invention is a lower-limb-powered exoskeleton device for rehabilitation assistance, comprising ankle-joint sagittal-plane driving units, knee-joint sagittal-plane driving units, hip-joint sagittal-plane driving units, a hip-joint horizontal-plane driving unit, a joint driver connecting frame, a lower-limb fixing support, sensors, a controller and a power supply. Antagonistic-drive-type linear driving units are used in the sagittal plane of a hip joint so as to enable the bending and extension movements of the hip joint, and a linear driving unit having the function of self-locking when powered off is used in the horizontal plane of the hip joint so as to enable the turning movements of the exoskeleton; and a linear driving unit in cooperation with a magnetorheological brake is used in the sagittal plane of each knee joint, thereby significantly reducing the power consumption of a knee-joint driver while lowering the control difficulty. The powered exoskeleton device can help patients with an impaired lower-limb motor function to carry out walking rehabilitation training.

The invention discloses a multi-sensor motion evaluation method and system for special training of lower limbs. The method comprises the following steps: step S100, collecting data of various sensors of the lower limbs; step S200, based on the collected data, carrying out gait and support state identification; step S300, judging the state of foot varus and valgus; step S400, calculating a foot stability index; step S500, calculating a lower limb exercise ability index; step S600, carrying out special exercise evaluation; and step S700, generating training feedback. Compared with an optical system, the core advantages of the system in training are reflected in that the system can be used for real training instead of a forced performance type test; the device is suitable for long-distance and continuous special training; the technical stability and injury risk can be directly reflected; and the training evaluation cost and the use threshold are obviously reduced.

The invention relates to a lower limb motor function recovery system and method based on a motor imagery brain-computer interface, and the system comprises a noninvasive electroencephalogram signal collection module which is used for collecting an electroencephalogram signal when a patient carries out a lower limb motor imagery task; the signal processing and intention recognition module is used for carrying out feature extraction and classification recognition on the collected electroencephalogram signals and outputting the motor imagery intention of the patient; the multi-sensory feedback module is used for providing multi-sensory feedback information including visual sense, auditory sense, tactile sense and proprioceptive sense for the patient; the lower limb rehabilitation training module is used for executing lower limb rehabilitation training actions corresponding to the motor imagery intention; the central control module is configured to receive the recognition result of the motor imagery intention and generate a control instruction according to the recognition result to drive the multi-sensory feedback module and the lower limb rehabilitation training module to work cooperatively. According to the system, a multi-sensory collaborative feedback mode is adopted to simulate multi-sensory interaction, and the identification degree and training compliance of a motor imagery task of a patient are improved.

The invention discloses a multi-modal sensing data automatic labeling method and system for gait assessment, and the system comprises a sensing collection module which comprises two paths of pressure sensors and a six-axis IMU sensor; the two paths of pressure sensors are used for acquiring plantar pressure data; the six-axis IMU sensor is used for acquiring lower limb movement data; the wireless transmission module is used for uploading the collected plantar pressure data and lower limb movement data to a cloud Internet of Things platform; the cloud data processing module is used for receiving and storing the plantar pressure data and the lower limb movement data; the data labeling module is used for automatically recognizing a gait cycle and carrying out multi-dimensional score labeling; and the user interaction module is used for interacting with the data annotation module and the cloud data processing module and displaying gait evaluation related data and results. According to the invention, a multi-mode sensing PCB is self-developed, a closed-loop system of collection, cloud loading, labeling and display is constructed, and accurate, continuous and remote evaluation of gaits of children with cerebral palsy is realized.

The invention relates to a closed-loop control method suitable for personalized lower limb exercise training, belongs to the technical field of exercise rehabilitation, and designs a closed-loop control method for dynamically adjusting lower limb training load according to muscle activation degree by combining surface myoelectricity characteristics with a personalized training model and a closed-loop control algorithm. According to the method, the resistance load can be adjusted in real time according to the muscle state, and finally the muscle activation level in the training process is maintained in an expected range. In the pre-training stage, sEMG data are collected to establish a personalized mapping model, and response characteristics of individual muscles are quantified; in the formal training stage, the muscle state is monitored in real time, the reference load is predicted through the model, and a closed-loop control algorithm is adopted to generate dynamic adjustment amount to adjust resistance output in real time. The invention further provides a closed-loop control system suitable for personalized lower limb exercise training.

The invention discloses a lower limb multi-joint torque intelligent prediction method and related equipment, and relates to the technical field of joint torque prediction.The method comprises the steps that original surface electromyography sEMG, kinematics data and ground reaction data of a subject under different lower limb movements are collected; kinematics data and ground reaction force data are used as input, and multi-degree-of-freedom angle data and moment data of three joints of the lower limb are obtained through inverse kinematics and inverse dynamics calculation; constructing a lower limb multi-joint torque prediction model through a deep learning technology, and performing model training by using the training set; and inputting the test sample set into the trained lower limb multi-joint torque prediction model to obtain a joint torque prediction result of the subject. According to the method, the problems of low joint torque prediction precision, high calculation cost and the like in the prior art are solved, the method has the advantages of being easy to implement, high in generalization, capable of processing large-scale data and the like, and prediction results are expected to be applied to three-dimensional compliance and modular control of the exoskeleton robot.

The present disclosure provides a movement system. The movement system includes a foot-plate exercise machine and a chair. The foot-plate exercise machine implements repetitive lower limb movement accompanied by extension and flexion of at least a knee joint and a hip joint. The chair is a component for a user to sit on while the user uses the foot-plate exercise machine to perform the lower limb movement. The chair has a seating portion for the user to sit on, and a support mechanism that supports the seating portion in a manner that allows the seating portion to rock laterally. By the seating portion rocking laterally during the lower limb movement, a movement chain of the lower limb and the torso is generated.

The invention discloses lower limb dyskinesia adjusting equipment and a gait adjusting method, and the equipment comprises a wearing part which comprises a housing matched with a lower limb; the projection module comprises a projector arranged on the shell, and the projection angle of the projector is adjustable; the control unit comprises a control mainboard arranged in the shell and an acquisition module communicating with the control mainboard, and the acquisition module is configured to acquire gait data of the wearing piece in real time; the projector communicates with the control mainboard, and the control mainboard is configured to control and adjust the projection angle of the projector based on the gait data acquired by the acquisition module. The lower limb dyskinesia adjusting device prompts gait disorders by using vision, and the mechanism is that the lower limb dyskinesia adjusting device can provide external sensory cues for the patient and stimulate the visual system of the patient, so that neural activity of the premotor area is activated. Visual information is used for guiding gaits, and the deficiency of internal movement rhythm caused by basal ganglion dysfunction is made up.

The invention relates to the technical field of training instruments, in particular to an intelligent heart rehabilitation training assisting device which comprises a supporting frame, a first supporting rod is fixedly connected to the top of the supporting frame, a second supporting rod is fixedly connected to the right side of the supporting frame, and a cushion is fixedly connected to the upper end of the second supporting rod. A lower limb exercise mechanism is arranged in the supporting frame, an upper limb exercise mechanism is arranged in the first supporting rod, and a linkage assembly is arranged between the lower limb exercise mechanism and the upper limb exercise mechanism. Through the arrangement of the linkage assembly, the exercise requirement is small in the initial rehabilitation stage of a patient, lantern rings at the positions of connecting ropes can be connected to clamping grooves of a handle and a pedal in a sleeving mode, combined training is achieved between the lower limb exercise mechanism and the upper limb exercise mechanism, physical output is reduced, and therefore the more effective recovery effect is achieved on rehabilitation training of the heart of the patient; by arranging the adjusting assembly, the resistance is increased, the exercise amount is increased, and the exercise intensity of the patient is adjusted.

The invention discloses a motion intention recognition method based on multi-modal enhanced comparative learning, and the method achieves the precise motion intention recognition based on any single mode through systematic fusion of multi-modal physiological signals and an innovative comparative learning architecture. Intention perception contrast learning: constructing positive and negative sample pairs enhanced by a multi-modal time sequence and optimizing contrast loss, so that the discrimination capability of the model in dynamic intention transfer is remarkably improved; according to many-for-one cross-modal prediction, multi-modal identification performance under single-modal input is realized through semantic alignment and a knowledge migration mechanism. After pre-training joint optimization, training and reasoning can be completed only through single-modal data, and data dependence is remarkably reduced while the advantage of multi-modal performance is kept. According to the technical scheme, the accuracy and robustness in lower limb movement intention recognition in the brain-computer interaction field are effectively improved, and an innovative technical solution is provided for a movement auxiliary rehabilitation system.

This invention belongs to the technical field of rehabilitation robots, specifically relating to a continuous phase control method for a lower limb rehabilitation exoskeleton that adapts to user gait. It employs a multi-task learning model, simultaneously outputting user identity probability and movement pattern probability to generate a probability map representing the similarity between the current gait and a certain movement pattern of a sample user in a sample database. A gait phase variable parameter prediction model is used to predict gait phase variable parameters, employing angular velocity data from the initial stage of the current gait cycle and the matched movement pattern to predict the gait phase variable parameters for the current cycle. Finally, a pre-constructed relational constraint model corresponding to the matched sample user and their movement pattern is used to obtain the desired joint angles from the real-time gait phase, and the exoskeleton is tracked and controlled via a PD controller. This invention can adaptively adjust the exoskeleton's motion assistance mode according to the user's gait characteristics, and is suitable for rehabilitation training of patients with lower limb motor dysfunction.

The application provides a flexible assisted lower limb motion robot, and relates to the field of motion robots, which comprises a thigh motion assembly, a shank motion assembly and a foot connecting assembly, the shank motion assembly is located below the thigh motion assembly, and the foot connecting assembly is located below the shank motion assembly, the motor in the thigh motion assembly controls the contraction and release of each rope, cooperates with the tensioning mechanism, realizes the lifting and lowering of the thigh belts on both sides, and assists in motion; the driving muscle in the shank motion assembly simulates the natural motion process, provides power, and drives the shank belt to move through the rope, so that the shank motion is realized; through the cooperation of the rope and the pulley set in the shank assembly, the distance between the sliding table and the sliding table support is adjusted, the freedom degree in the lower limb motion can be met to a large extent, and through the flexible connection of the spring and the foot connecting frame, the flexible adaptation of the foot to the leg during walking is realized.

A method for measuring motion postures of lower limbs of an automobile collision dummy continuously collects lower limb images of the automobile collision dummy during a collision in a real automobile collision test; identifies an edge contour in each lower limb image; samples a plurality of points from the edge contours for fitting to obtain a lateral thigh expression, a lower medial thigh expression, a lateral lower leg expression, and a lower medial leg expression respectively; determines various bone positions, various joint positions, and various bone angles of each lower limb; and associates the various bone positions, the various joint positions, and an included angle between two ends of each joint in the plurality of lower limb images in a chronological order to form a series of two-dimensional human rod-shaped model diagrams.

The utility model discloses a kind of electric wheelchair with auxiliary lower limb exercise function, it is related to electric wheelchair technical field, including electric wheelchair body, further include placing plate, placing plate is fixedly installed below electric wheelchair body, the front side of electric wheelchair body is rotatably installed with two supporting leg plates, the double legs of user who is sat on electric wheelchair body can be supported by supporting leg plate, reciprocating component for driving supporting leg plate to move is installed between placing plate and supporting leg plate, two supporting leg plates can be driven by reciprocating component with its and electric wheelchair body rotatable installation place as center synchronous or asynchronous swing, so as to drive the double legs of user can be in use electric wheelchair body Also can realize the activity exercise of lower limb, so as to can reduce the electric wheelchair body in prior art in the complication of lower limb muscle atrophy, joint stiffness and blood circulation disorder and muscle degradation etc. caused by user long-term sitting in use.

The present application relates to the technical field of rehabilitation equipment control, and particularly relates to a control method and system of a lower limb movement rehabilitation training machine. The method comprises the following steps: starting the brushless motor lower limb movement rehabilitation training machine, collecting the force detection parameters of the user's stepping and the operation feedback parameters of the brushless motor in real time; sending the resistance adaptation instruction to the brushless motor of the lower limb movement rehabilitation training machine based on the force detection parameters and in combination with the operation feedback parameters, and real-time regulating and controlling the output impedance of the brushless motor; detecting the posture signal of the lower limb movement rehabilitation training machine in real time during the continuous operation of the output impedance regulation and control of the brushless motor; and triggering the emergency stop instruction of the brushless motor immediately when the abnormal posture signal is detected. The present application adopts the brushless motor, combines the standby protection countdown with the zoned, angularly linked collection of the force parameters and the dynamic impedance regulation and control, so as to realize the portable and silent operation of the equipment and the personalized resistance adaptation, and to enhance the operation stability and the training adaptation accuracy.

The utility model discloses a lower limb exercise device for orthopedic nursing, which relates to the technical field of orthopedic nursing and comprises a base, a support rod is fixedly mounted on the upper surface of the base, a bedplate is fixedly mounted at the top of the support rod, a training component and an adjusting component are arranged on one side of the bedplate, and the training component comprises a groove formed in one side of the bedplate. A rotating plate is rotationally connected into the groove through a rotating shaft, an opening is formed in one side of the rotating plate, two rotating plates are rotationally connected into the opening through rotating shafts, and a fixing belt is fixedly installed on one side of each rotating plate. According to the lower limb exercising device for orthopedic nursing, the training assembly is arranged, the tension training strength between the two legs can be adjusted in the using process, therefore, the tension of the legs can be conveniently adjusted in the using process, muscles on the inner sides of the thighs are prevented from being damaged in the training process, and the training effect of the lower limb exercising device is improved. Meanwhile, the training intensity can be adjusted according to training effect requirements.

The computing device relating to one aspect includes at least one memory and at least one processor, the processor recognizes the body shape of a user housed in the massage device, divides the user's body into multiple parts based on the recognition result, promotes blood circulation in the lower limbs among the multiple parts, controls the leg massage unit included in the massage device so that multiple acupuncture points included in the lower limbs are stimulated, controls the leg massage unit to guide the user to perform a predetermined movement with respect to the lower limbs, and controls the leg massage unit so that the lower limbs move in a predetermined direction and position.

This invention relates to the field of motion correction technology, specifically to a method for lower limb motion correction that integrates angle and pressure data. The method includes acquiring real-time angle and pressure data during lower limb movement and establishing an angle-pressure time-series matrix; identifying the phase difference distribution pattern between angle and pressure feature points based on the matrix; comparing the phase difference distribution pattern with an individual's standard motion pattern; generating targeted motion correction commands when abnormal phase relationships are detected; and dynamically optimizing the individual's standard motion pattern based on the execution effect of the motion correction commands. This invention achieves cross-modal fusion of motion control signals and external reaction force signals. This fusion enhances the comprehensiveness of motion anomaly detection and improves the sensitivity of identifying subtle motion imbalances or phase misalignments, making it suitable for identifying problems that conventional models struggle to capture, such as gait deviations and incorrect force application sequences.

This invention relates to the field of lower limb rehabilitation data recognition and monitoring technology, specifically disclosing a method for recognizing lower limb rehabilitation movement postures and an intelligent ankle bracelet for preventing VTE, comprising: Step 1, real-time acquisition of three-dimensional spatial motion data and recognition of lower limb motion data, extracting kinematic parameter features; Step 2, identification of movement types based on kinematic parameter features, acquisition of movement pattern consistency scores, and determination of whether rehabilitation training is qualified; Step 3, acquisition of surface electromyographic signals of the rehabilitation participant's leg-raising force exertion movement during rehabilitation training and simultaneous acquisition of lower limb motion data, extraction of force exertion data, evaluation and analysis to generate a muscle activation efficiency score; Step 4, establishment of a mapping model based on historical hemodynamic data, inputting the extracted force exertion data into the mapping model to output a VTE prevention efficiency score; Step 5, calculation of the movement pattern consistency score, muscle activation efficiency score, and VTE prevention efficiency score through movement evaluation analysis to generate a movement evaluation quality coefficient.

This invention relates to the field of brain-computer interface (BCI) technology, specifically to a monitoring method and system for a lower limb feedback training and adjustment device using a BCI. The method includes: real-time acquisition of EEG signals related to the patient's lower limb movement intention via an EEG signal acquisition unit, combined with lower limb movement posture data obtained via a posture sensing module, and synchronous transmission to a data processing center; the data processing center performs fusion analysis on the EEG signals and posture data to identify the accuracy of movement intention, compliance of movement execution, and muscle load status; based on the analysis results, real-time feedback instructions are generated, and multimodal feedback information is output to the patient through a feedback adjustment unit to dynamically adjust the parameters of the training device; abnormal data is monitored throughout the training process, triggering corresponding safety warnings and emergency adjustment mechanisms. This invention improves the accuracy, safety, and effectiveness of lower limb rehabilitation training through the coordinated monitoring of EEG signals and movement postures, multi-dimensional data fusion analysis, and real-time feedback adjustment.

The application belongs to the technical field of wearable exoskeleton devices, and provides a wearable exoskeleton device suitable for rehabilitation training of infants with congenital cerebral palsy and an exoskeleton control method. The device comprises a wearable exoskeleton device main body, hip joint drives symmetrically arranged on the left and right sides, knee joint drives, ankle joint drives, a controller and multiple groups of sensors. The controller stores joint target trajectory data corresponding to multiple training modes, retrieves corresponding trajectory data based on the selected training mode and generates control instructions to actively drive the affected lower limbs to move. The multiple groups of sensors comprise electromyography sensors, inertial measurement units and pressure sensors. The controller identifies abnormal movement modes such as combined responses and extensor spasticity based on sensor signals and dynamically reduces the drive control gain to release abnormal stress in a compliant manner. The application realizes multi-mode active guidance training and asymmetric assistance for infants with congenital cerebral palsy, and has the ability of abnormal mode identification and safe compliant response.

The invention belongs to the technical field of patient rehabilitation auxiliary equipment, and particularly relates to a stroke patient limb rehabilitation activity auxiliary device which comprises a first U-shaped hollow metal frame and a second U-shaped hollow metal frame, the outer wall of the first U-shaped hollow metal frame is fixedly connected with an L-shaped hollow rod, and the outer side end of the L-shaped hollow rod is fixedly connected with a check block. The limb rehabilitation activity assisting device for the stroke patient not only has the function of accurate height adjustment, but also can be accurately matched with the height of the stroke patient, can avoid various discomfort of the patient during exercise, has the ability of alternate movement, can continuously support and assist the stroke patient who performs lower limb exercise, and is convenient to use. The function of improving the stability of rehabilitation exercise of the lower limbs of the stroke patient is achieved, the situation of injury caused by falling down is avoided, the use reliability of the device can be improved, and the safety and effect of the rehabilitation exercise of the limbs of the stroke patient can also be improved.

This application relates to the field of interdisciplinary technology, and in particular to a stroke rehabilitation training system based on a mixed reality digital human. The system includes: a data acquisition module configured to: acquire multimodal data of the subject performing standard movement tasks under the guidance of the rehabilitation therapist's digital human; the multimodal data includes: visual data, electromyographic data, and inertial data; perform perception and heterogeneous spatial registration on the multimodal data; and drive the subject's mirror digital human for synchronous display in real time; and a processing module configured to: identify the subject's movement intentions, assess upper limb motor function, detect compensatory movements, and assess lower limb motor function based on the multimodal data; and generate real-time prompts, visual feedback, and training reports, thus achieving an integrated closed loop of stroke rehabilitation training, functional assessment, and feedback adjustment. It is applicable to stroke rehabilitation training, functional grading assessment, and home-based continuous rehabilitation intervention.

This invention discloses a lower limb motion mechanism for a wheeled humanoid robot, belonging to the field of wheeled humanoid robots. Through the coordinated use of linear motion modules and various rotary joint modules, it achieves lightweight and miniaturized lower limb structure, resulting in more flexible and free leg movement, thus improving the working range and efficiency of the wheeled humanoid robot. It mainly includes a wheeled chassis, on which the lower limb motion mechanism is mounted. The lower limb motion mechanism includes fixed bases symmetrically mounted on the wheeled chassis. The top of the fixed bases is connected to the power output end of the bottom rotary joint module, which is fixedly mounted within leg links. Linear motion modules are located within both leg links on either side, situated above the bottom rotary joint module. The power output ends of both linear motion modules are connected to the power output ends of the leg rotary joint modules. This invention is primarily used in wheeled humanoid robots.

The application provides a neurosurgical limb rehabilitation training device, which comprises a bed plate and a supporting leg; the bed plate is provided with an upper limb exercise mechanism and a lower limb exercise mechanism; the upper limb exercise mechanism comprises a supporting frame, a main pulley and a guide pulley; the main pulley and the guide pulley are provided with a pull rope, and the other end of the pull rope is connected with a first linkage mechanism; the lower limb exercise mechanism is detachably connected with the first linkage mechanism; a leg supporting frame is driven by the pull rope and the first linkage mechanism to make a leg lifting movement; a driving device for driving the leg supporting frame to make a leg flexion movement is arranged in the box; the upper surface of the bed plate is provided with a back lifting mechanism; the lower end of the back lifting mechanism is connected with one end of a second linkage mechanism; when the driving device drives the leg supporting frame to make a flexion movement, the back lifting mechanism is driven by the second linkage mechanism and the driving device to make a back lifting movement. The application can exercise the upper and lower limbs simultaneously, increase the limb coordination, combine the active exercise with the passive exercise, be suitable for different patients, increase the back massage and be high in interesting.