499 results about "Muscle strength" patented technology

The invention discloses an intelligent orthopedic rehabilitation self-adaptive evaluation method and device based on multi-modal physiological feedback. The method comprises the steps that multi-modal physiological data including electromyographic signals, knee joint three-dimensional motion trails, plantar pressure distribution and cognitive input degree of a subject are synchronously collected; constructing a three-dimensional baseline vector according to the MMT muscle force test, knee joint ROM measurement and VAS pain score of the subject; inputting the multi-modal physiological data and the three-dimensional baseline vector into a personalized orthopedic rehabilitation model, and outputting a knee joint function index prediction value and personalized rehabilitation adjustment parameters; dynamically adjusting electrical stimulation parameters according to rehabilitation adjustment parameters output by the personalized orthopedic rehabilitation model; if the cognitive load index exceeds the early warning line, the electrical stimulation intensity is reduced; otherwise, activating the hippocampus body wave stimulation mode. Adjustment is carried out according to the real-time state of the subject, blindness and subjectivity in the rehabilitation process are avoided, and the rehabilitation efficiency and success rate are improved.

The invention discloses an intelligent wearable exoskeleton self-adaptive auxiliary regulation and control method and an intelligent wearable exoskeleton system.The intelligent wearable exoskeleton self-adaptive auxiliary regulation and control method comprises the steps that a motion data sample of human walking is obtained, and a human motion model is constructed based on a man-machine closed-chain motion model according to the motion data sample; collecting multi-modal data of the target user when the target user wears the exoskeleton in real time; calling a human body motion model and a man-machine closed-chain motion model, and generating an exoskeleton control instruction of man-machine motion cooperation according to the multi-modal data; and dynamically adjusting motion control parameters of the exoskeleton according to the control instruction. According to the method, the precise human body motion model is constructed based on the man-machine closed-chain motion model, the man-machine motion cooperative exoskeleton control instruction is generated in combination with the model, the exoskeleton motion control parameters are dynamically adjusted according to the instruction, the body type difference, the muscle strength level and the motion habit of different users can be precisely matched, and the wearing comfort and safety are effectively improved.

The invention relates to the technical field of medical health information, and particularly discloses a heart rehabilitation training control method based on muscle force and electrocardiosignal real-time monitoring, which comprises the following steps: firstly, calculating real-time myoelectricity intensity to quantify muscle load, synchronously analyzing electrocardiosignals and respiratory frequency to obtain a cardiopulmonary state, and correcting physiological indexes in combination with a trunk motion state; then, a multi-parameter fusion result is generated through a weighted fusion algorithm, and the relevance between the muscle force load and the heart response is comprehensively reflected; then, the system judges the training intensity through a preset threshold model, generates a voice feedback instruction in real time to adjust the action of the patient, and adaptively updates training parameters to match the rehabilitation progress of the individual; meanwhile, the system continuously monitors multi-parameter changes, and automatically triggers an early warning mechanism when abnormal risks are detected, so that training safety is ensured. According to the method, the limitation that a traditional scheme depends on a single index is overcome, and personalized and dynamic heart rehabilitation training closed-loop control is achieved.

The invention discloses a high-compliance impedance training method and system based on self-adaptive visual servo control and application of the high-compliance impedance training method and system. The training method comprises the steps that historical pose data and historical contact stress data are collected; performing feature processing to obtain stress pose information and generate a corresponding pose mapping relation; constructing a dynamic mapping model associated with the muscle force, the contact stress, the training track and the impedance parameters in combination with the stress pose information and the pose mapping relation; acquiring rehabilitation training information of a current patient, and generating and optimizing a preliminary expected trajectory; calculating deviation data of the real-time trajectory and the expected training trajectory; and an impedance adjusting model is constructed, the input of the impedance adjusting model comprises the deviation data and the real-time contact stress data, and the output of the impedance adjusting model is the impedance adjusting quantity. According to the invention, through visual real-time feedback, fuzzy PID adaptive adjustment and multi-feature fusion modeling, impedance adjustment training with better dynamic adaptability, higher safety, higher flexibility and high personalized precision can be realized.

The invention discloses a respiratory therapy system and method based on biofeedback, and belongs to the field of medical instruments, and the therapy method comprises the following specific steps: S1, collecting and recording multiple paths of user physiological parameters; s2, respiratory rhythm extraction is carried out according to the characteristics of the multi-path data; s3, analyzing each piece of feature data to obtain the confidence coefficient of each piece of data, calculating the total confidence coefficient, and rejecting non-ideal data; according to the invention, by realizing coordination of electrical stimulation between diaphragm and abdominal muscles, the effect of synchronizing with breathing of a user is achieved, the expiration ability is improved, the recovery of respiratory muscle functions of a patient is promoted, the muscle strength and endurance are gradually improved, the dyspnea symptom is relieved, the exercise ability and exercise endurance are improved, and the life quality of the patient is improved.

The invention provides an ankle rehabilitation exercise intelligent management system and method based on multi-modal data fusion, and relates to the technical field of medical rehabilitation, and the method comprises the steps: collecting sole state data and electromyographic signal data of a patient end through a sensor network; determining a target gait mode and gait parameters according to the sole state data, and summarizing to obtain real-time gait data; determining muscle strength and muscle coordination degree according to the electromyographic signal data, and summarizing to obtain muscle state data; constructing an ankle motion function abnormity prediction model, and determining an ankle fault score according to the real-time gait data and the muscle state data; the ankle fault grade is judged according to the ankle fault score, and a personalized ankle rehabilitation strategy is made based on the ankle fault grade and sent to the visual display terminal, so that the ankle movement data can be accurately collected, a personalized rehabilitation exercise scheme is customized, the rehabilitation effect of a patient is improved in combination with an exercise auxiliary structure, and the rehabilitation effect of the patient is improved. The rapid recovery of the ankle function is promoted.

The present invention relates to a wearable robot for assisting back muscle strength, comprising: an upper wearing part worn on the upper body; a back muscle strength assisting part that can be fixed to the upper wearing part; and a lower wearing part connected to a lower end portion of the back muscle strength assisting part, wherein the back muscle strength assisting part comprises a housing that can be fixed to the upper wearing part, a plurality of elastic members arranged in series or parallel within the housing, a moving part connected to the bottom of the elastic members and connected to the lower wearing part so as to slide up and down, and a rigidity control part that adjusts the rigidity of the elastic members.

The invention discloses an active reminding type wearable device for scoliosis correction, which belongs to the technical field of scoliosis and comprises a monitoring regulator and a plurality of reminders. The monitoring regulator is composed of an angle sensing module, a horizontal detection module and a logic processing module and used for detecting angle changes of the shoulder and back detection line and the crista iliaca detection line and comparing the angle with a target range. When deviation is detected, the logic processing module sends a signal to the reminder through the communication module, and the reminder feeds back in a vibration or low-frequency stimulation mode to induce the wearer to actively adjust the body position. The device overcomes the defects of passive correction, enhances the correction effect, has static and dynamic correction functions, and monitors the posture change of a patient in a motion state in real time. The portable design improves the wearing comfort and compliance, is suitable for patients with mild scoliosis and poor postures, is especially suitable for children groups, helps to correct the posture, enhance the muscle force and form good posture habits, and significantly improves the treatment effect.

The invention provides an unmarked action acquisition and analysis method and system, and the method comprises the steps: recognizing static and dynamic 2D key points according to the static and dynamic image data of a tester, and reconstructing the static and dynamic 2D key points into static and dynamic 3D key points; based on the static 3D key points, calculating and optimizing the skeleton length, and performing scaling adjustment on the standard skeleton and muscle model to obtain a static skeleton and muscle model of the testee; estimating skeleton motion attitude information according to the original and optimized dynamic 3D key points, and matching the skeleton motion attitude information to a static skeleton and muscle model of a tester to perform inverse kinematics analysis; estimating ground support force GRF of left and right feet by using an inverse kinematics analysis result based on a dynamic balance relationship of human motion; on the basis of an inverse kinematics analysis result and ground support force GRF estimated values of the left and right feet, counter-acting force and torque required by each joint of the human body are calculated frame by frame by adopting an inverse kinematics method of a rigid body system, and then muscle strength and activation degree are calculated. According to the invention, unmarked action acquisition and analysis can be carried out.

An embodiment provides an industrial muscle-strength assistive robot, including: a wearing part; a pair of arm muscle-strength assistive parts connected to the upper body wearing member so as to be adjacent to the shoulders of the user and movable along an upper part of the upper body wearing member; a wire part connecting the pair of arm wearing members and the pair of arm muscle-strength assistive parts; a fixing part coupled to the upper body wearing member so as to be positioned at a bottom part of the pair of arm muscle-strength assistive parts; an auxiliary muscle strength conversion part coupled to the upper body wearing member so as to be positioned at a bottom part of the fixing part and selectively assisting one of waist muscle strength and arm muscle strength of the user; and a string twist driving part coupled to the waist wearing member.

The invention discloses bifidobacterium animalis subsp. Lactis and application thereof in a product for enhancing athletic ability, and relates to the technical field of microorganisms. The invention provides an animal bifidobacterium subsp. Lactis MUS < + >, and the preservation number of the animal bifidobacterium subsp. Lactis MUS < + > is CGMCC (China General Microbiological Culture Collection Center) No.35626. The invention also provides a preparation method of the animal bifidobacterium subsp. Lactis MUS < + >. The animal bifidobacterium subsp. Lactis MUS + provided by the invention can increase the length of surrounding motor nerves and promote the development of the motor nerves; the total exercise distance is increased, and the exercise ability and endurance are promoted; body length or height development is promoted; muscle fibers are thickened, the muscle fiber density is increased, muscle fiber gaps are reduced, and muscle development is promoted; and the method has a very good application prospect in preparation of products for improving athletic ability or increasing muscle.

The invention relates to the technical field of medical rehabilitation equipment, in particular to a surgical postoperative rehabilitation nursing auxiliary device and method based on the Internet of Things, and the device comprises a bearing part, a driving part, a base, a monitoring part and a remote interaction part, the driving part comprises a first driving assembly for providing relative resistance for a using object and a second driving assembly for driving the thigh and the shank to move relatively. The method comprises the steps that in a single training period, the passive muscle activation degree and the active muscle activation degree are determined to determine the rehabilitation degree of the muscle function of a using object; according to the limb movement track and the muscle strength balance condition of the feature movement part, the movement control ability of the using object is determined, and a rehabilitation training scheme of the using object is adjusted according to the rehabilitation degree or the movement control ability. According to the invention, comprehensive monitoring and remote transmission of the rehabilitation process of the use object are realized, and the rehabilitation process can be accurately controlled by medical personnel.

The invention discloses a sarcopenia patient self-health intervention management system, which comprises a system overall architecture module, a personalized scheme generation module, a monitoring and feedback module, an evaluation and adjustment module and a data storage and analysis module, and is characterized in that the output end of the system overall architecture module is electrically connected with the input end of the personalized scheme generation module; the invention relates to the technical field of medical health management. According to the self-health intervention management system for the patients with sarcopenia, factors of different age groups, genders, physical conditions, personal preferences and the like are comprehensively considered, exercise and nutrition intervention are organically combined, personalized exercise and nutrition plans are generated, and the self-health intervention management system for the patients with sarcopenia is provided for the patients with sarcopenia. The limitation of single movement or nutrition intervention and lack of personalized schemes in the prior art is overcome, the prognosis condition of the patient with sarcopenia can be more effectively improved, and the patient is comprehensively assisted to improve the muscle quality, enhance the muscle strength, improve the body function and the like.

The invention discloses an active constant-speed treatment and training method for patients with neurodegenerative diseases and myasthenia, and the method comprises the steps: promoting nerve remodeling through active constant-speed training, enabling the patients to use active constant-speed training equipment, and adjusting the training speed, the angle range and the impedance torque. The device activates a specific muscle group in a safe and controllable environment through an adaptive impedance training technology, gradually enhances training impedance to improve muscle strength, enhances muscle contraction efficiency through targeted training, promotes neural pathway reconstruction and improves nerve-muscle cooperative control ability, and thus achieves neural function recovery and improvement. Therefore, drug therapy provides neuroprotection and muscle function support for a patient, active constant-speed training further promotes the rehabilitation progress through accurate control and real-time feedback, and meanwhile, the flexibility and individuation of training are improved through the multi-mode man-machine interaction and cloud remote guidance functions, so that the rehabilitation effect of the patient is improved. And the treatment effect and life quality of patients with neurodegenerative diseases and myasthenia are improved.

The invention discloses an anti-resistance exercise training system for old people based on intelligent wearable equipment, and relates to the technical field. The problems that in the prior art, a dynamic action monitoring error correction mechanism is lacked, exercise intensity adjustment is not personalized and real-time, interaction and data feedback functions do not exist, and equipment portability and wearing adaptability are insufficient are solved. The system collects data in real time through the whole body position intelligent wearable device, corrects non-standard actions through the action recognition feedback module, dynamically regulates the intensity through the exercise intensity evaluation module, reduces the risks of muscle strain, cardiovascular burden and the like, takes standardized action guidance, personalized intensity adaptation and data visualization as the core, ensures target muscle activation, and improves the training efficiency. The training effect is quantified, the operation is simple, the use threshold is reduced through voice guidance, the boring feeling is relieved through personalized plans and summary reports, the training achievement feeling and compliance of the old people are enhanced, the muscle strength can be improved through whole body position training, and the anti-resistance exercise requirement of the old people is met.

The invention discloses an intelligent lower limb rehabilitation training device based on multi-modal feedback. Comprising an adjustable exoskeleton support capable of dynamically adjusting exoskeleton driving torque, and a multi-mode feedback system installed outside the adjustable exoskeleton support and capable of capturing the motion intention of a patient. The central controller can calculate the optimal motion trail of the patient according to the data fed back by the multi-mode feedback system; the force feedback actuator can provide assistance or resistance in real time according to the muscle force of the patient; by arranging the multi-mode feedback system, the action starting of a patient can be predicted, and the action intention and the muscle activation intensity of a user can be recognized; the hip, knee and ankle joint angles and plantar pressure of the patient during movement are measured in real time, the training intensity is dynamically adjusted according to the muscle force state and the movement intention of the patient, and the training individuation is optimized; compared with traditional single-machine training, the device can avoid secondary injury of muscles and reduce the risk of muscle injury.

The utility model relates to an arm strength exerciser which comprises a spring tube and two grab handles. The bourdon tube is a cylindrical spiral bourdon tube with a certain length and comprises a middle main body part with a larger diameter and two end parts which are positioned at two ends of the middle main body part and have smaller diameters; and the two grab handles are respectively and fixedly sleeved on the two end parts. The main body is the cylindrical spiral bourdon tube, the grab handles are arranged at the two ends of the cylindrical spiral bourdon tube respectively, the two hands grasp the grab handles to elastically bend the bourdon tube during exercise, so that the muscle strength of the arms is exercised, and the bourdon tube has the advantages of being simple in structure and convenient to use.

The invention relates to the technical field of foot health and motion monitoring, in particular to a multi-motion-scene-oriented foot motion data acquisition and intelligent analysis guidance method, which comprises the following steps of: acquiring foot three-dimensional static form and plantar pressure data through a foot correction shaping box, and establishing a foot geometric model with an anatomical mark; then, a nine-axis inertial measurement unit and a pressure sensor at a shoelace knob in the shoe are used for collecting time sequence foot motion data of multiple motion scenes; extracting multi-modal features after fusion, inputting the multi-modal features into a pre-training multi-task model, and outputting exercise habit classification, technical action scoring and injury risk assessment; finally, a sports biomechanics knowledge base is adjusted, and personalized suggestions of posture correction, muscle strength training and equipment adjustment are generated. The method is suitable for various exercise scenes, accurate in data acquisition, comprehensive in analysis dimension and high in guidance suggestion pertinence, the exercise normalization of the user can be effectively improved, and the exercise injury risk can be reduced.

The invention relates to a labiolingual muscle mechanical characteristic acquisition and analysis system, and the system comprises a fixing part which is combined with an oral appliance so as to be fixed in the oral cavity of a user; the acquisition piece is used for acquiring a lip mechanical signal generated by the lip and / or a palate side mechanical signal generated by the tongue muscle; and the analysis part is used for identifying tongue muscle strength information and / or lip muscle strength information of the user according to the lip mechanical signal and / or the palate side mechanical signal, and generating patient evaluation information of the user according to the tongue muscle strength information and / or the lip muscle strength information. The embodiment of the invention is combined with a corresponding oral appliance to be fixed in the oral cavity to monitor the strength of the tongue muscle and the lip muscle of a patient in real time, so that the strength of the tongue muscle and the lip muscle of the patient during training and non-training periods can be monitored, the patient and a doctor can check the conditions of the tongue muscle and the lip muscle of the patient in real time, and the user experience is improved through information processing and analysis of a terminal system. And the condition of the patient is correspondingly evaluated, so that the patient is reminded and guided.

The invention discloses a muscle state analysis method for analyzing muscle strength based on electromyographic signals, belongs to the technical field of neuromuscular physiology and data processing, and solves the problem that traditional electromyographic analysis lacks activation degree and fatigue degree multi-dimensional dynamic evaluation ability. Through multi-channel electromyographic signal collection and feature extraction and in combination with a calculation model, the muscle activation degree and the fatigue state are accurately evaluated. The functional state of the target muscle under the specific action can be dynamically monitored, and a reliable scientific basis is provided for movement safety; and moreover, the defects in the aspect of muscle state analysis in the prior art are overcome, and the method has important clinical application value in the aspect of improving exercise rehabilitation and training effects.

The utility model discloses a joint torque measuring device, which comprises a base provided with a slide rail and used for bearing a force measuring unit and abutting against a static limb joint of a joint to be measured; the force measuring unit is mounted on the sliding rail in a sliding manner and is used for receiving and measuring the acting force of a movable limb joint of the joint to be measured; and the displacement measuring unit is arranged on the base and is used for measuring the displacement of the force measuring unit. The device can be used for measuring torques of joints of all positions of a human body, such as joints of upper and lower limbs or fingers, the muscle strength and motion function conditions of the joints can be evaluated only by adjusting the sizes of all parts of the device to be matched with the sizes of the corresponding joints and limbs, and basis is provided for formulation and adjustment of rehabilitation treatment when the device is applied to the rehabilitation treatment; accordingly, a corresponding rehabilitation training scheme is designed, and the patient is helped to recover muscle strength and motion functions.

The invention discloses a lower limb rehabilitation robot control method and system based on electromyographic signals, and belongs to the technical field of medical rehabilitation instruments.The method comprises the steps that the electromyographic signals of lower limb muscles of all parts of a user when the user uses a lower limb rehabilitation robot are collected in real time, and the electromyographic signals are preprocessed; the electromyographic signal features of the electromyographic signals are input into the trained DE fused GA-SVM algorithm classification and recognition model, the gait cycle stage is determined, main force exerting muscles in the gait cycle stage are selected, and the muscle force level, needing to be compensated, of the main force exerting muscles is output. According to the method, the problem that the lower limb muscle activation levels of different gait phases are different is considered, the current gait cycle stage of a user is judged firstly, muscle force compensation is conducted on the muscles mainly exerting force at different stages, a patient can conduct active rehabilitation training, the muscle force training efficiency of the patient can be improved, and the rehabilitation training efficiency of the patient is improved. And a better rehabilitation training effect is achieved.

The invention relates to the technical field of rehabilitation medicine, and discloses an array type pneumatic contact lower limb movement function identification and evaluation device which comprises a base, an adjustable seat is arranged at the top of the base, a fixed seat is fixedly connected to the top of the base, an auxiliary mechanism is arranged at the top of the fixed seat, an identification mechanism is arranged at the top of the base, and a pneumatic contact is arranged at the top of the identification mechanism. The identification mechanism comprises mounting boxes, the bottoms of the two mounting boxes are fixedly connected to the top of the base, follow-up assemblies are arranged in the mounting boxes, the other ends of the follow-up assemblies are rotationally connected with fixing rings, hook-and-loop fasteners are arranged at the two ends of the fixing rings, and a plurality of air cylinders are fixedly connected to the interiors of the fixing rings. According to the invention, through the design of the array type pneumatic contacts, the detection precision is improved, errors caused by looseness or missing detection of the contacts are avoided, and making of a personalized rehabilitation scheme, such as targeted training for a patient with asymmetrical muscle strength, is supported.

The invention discloses a smart home type remote rehabilitation assessment training system, and the system comprises a data collection module which is used for continuously collecting health index data and rehabilitation training data of a patient; the index evaluation plate is used for determining indexes such as the joint motion range, the muscle strength, the balance capacity, the Cobb angle and the pelvic inclination angle of the patient through index evaluation necessary characteristics, and then the next rehabilitation target of the patient is determined; the AI processing module is used for dividing the processed rehabilitation data and the obtained index data into a training set and a test set, establishing an AI model based on a machine learning algorithm and a deep learning algorithm, inputting the training set and the test set into the AI model to achieve training and testing of the model, and obtaining the rehabilitation data of the patient according to the features and data of the patient through the trained AI model. And performing a pattern recognition or evaluation task. According to the system, more convenient household training guidance can be realized, the body movement condition of a patient can be more accurately known through AI model index evaluation, and a personalized rehabilitation scheme is formulated.

The invention provides a virtual reality-based joint movement injury rehabilitation mode generation method and a virtual reality-based joint movement injury rehabilitation mode generation system, and relates to the technical field of virtual reality, and the method comprises the following steps: analyzing a rehabilitation path according to movement joint injury data of a user; performing rehabilitation limb posture decomposition based on the rehabilitation analysis path to generate a rehabilitation analysis view; a multi-modal sensor unit is used for collecting rehabilitation feedback actions of a user, and matching recognition of physiological parameters and rehabilitation constraints is carried out in a rehabilitation analysis view; and according to the posture deviation feedback, performing amplitude and muscle power guidance feedback of the rehabilitation limb posture, and synchronously performing virtual reality visual display. The technical problem that in the prior art, most VR rehabilitation systems mainly pay attention to visual feedback, so that only the motion appearance can be evaluated, and the compensatory motion mode cannot be recognized is solved, real-time monitoring and guidance on the force exerting correctness are achieved through combination of posture decomposition and physiological parameter projection, and the effect that the correctness of force exerting is improved is achieved. Therefore, the compensatory motion mode is effectively blocked.

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 present invention relates to a method for rapid stroke identification combining TOPSIS and artificial intelligence. First, the existence of unilateral muscle strength decline is judged by the degree of horizontal raising of the user's arms, and the muscle strength difference is graded by the angle between the arms; then the degree of slurred speech of the user is analyzed by artificial intelligence speech recognition and combined with the error word rate calculation method; then the position coordinates of the facial feature points are detected by the artificial intelligence facial feature point recognition model, the degree of facial droop is calculated by the TOPSIS method, and finally the risk degree of stroke is rapidly identified by the TOPSIS method by comprehensively grading the muscle strength difference, the degree of slurred speech and the degree of facial droop. The present invention can enable patients and their families to effectively and quickly identify stroke symptoms at home, and automatically shunt stroke patients to corresponding stroke centers for treatment according to different severity of stroke, thereby improving the emergency rescue efficiency and quality of emergency medical rescue services.

The embodiment of the invention provides a limb constant-speed motion control method and system based on surface myoelectricity triggering, and belongs to the technical field of constant-speed equipment. The method comprises the following steps: acquiring data of surface myoelectricity; calculating the strength of the electromyographic signals according to the surface electromyographic data to obtain analysis data of muscle activity; adjusting and driving the limbs according to the analysis data of the muscle activity and the data of the surface myoelectricity to obtain activity data; the training condition is analyzed according to the activity data, and limb constant-speed movement control information is obtained. Residual strength of muscles can be fully utilized to actively participate in exercise, and the requirements of users in different rehabilitation stages are met.

This utility model discloses a rehabilitation device for lower limb dysfunction with adjustable angle, relating to the field of rehabilitation technology. It includes a base frame and a computer operating unit. The computer operating unit is installed on the top of the base frame, which has an adjustable support unit on top and a body support unit on top of the adjustable support unit. The device utilizes four square blocks on both sides inside the foot pedal. Two of the blocks have Velcro fasteners (first type) on top, and the other two have Velcro fasteners (second type) on top. During use, the patient places their foot on the foot pedal, and the Velcro fasteners (first and second types) securely fix the foot to the pedal. This effectively prevents the foot from slipping or becoming unstable on the foot pedal due to weakened muscle strength or poor balance during rehabilitation training, thus ensuring the smooth progress and safety of rehabilitation training.

The application discloses a lower limb venous thrombosis prevention training device and particularly relates to the field of training devices. The device comprises a support frame, both sides of the bottom of the support frame are provided with placing grooves, a sliding block is slidably connected to the support frame, a limiting groove is fixedly connected with the sliding block and slidably connected to the support frame, two driving racks are symmetrically arranged on the two sides of the sliding block and fixedly connected with the sliding block, two first driving gears are respectively engaged with the corresponding driving racks, each first driving gear is rotatably connected to the support frame, two flexible shoes are symmetrically arranged and each flexible shoe can be detachably connected with the limiting groove and the first driving gear, and a driving assembly can be driven by a user to move the sliding block. The application solves the problem that the existing prevention training device is not suitable for the elderly patients with insufficient muscle strength and improves the initiative of patient training.