716 results about "Muscle strength" patented technology

The invention discloses a peripheral nerve stimulation system based on muscle fatigue prediction and compensation, which is used for acquiring electromyographic signals and predicting muscle fatigue states during nerve stimulation, and timely warning and adjusting stimulation to ensure the stability of muscle strength, and comprises a stimulation output module used for stimulating target nerves to activate target muscles according to stimulation parameters; the acquisition and analysis module is used for synchronously acquiring electromyographic signals of target muscles, preprocessing the electromyographic signals and extracting electromyographic signal features; the fatigue prediction module is used for predicting the fatigue state of the muscle according to the electromyographic signal characteristics; the compensation control module is used for adjusting stimulation parameters according to the fatigue state of the muscle and sending the stimulation parameters to the stimulation output module to ensure that the muscle strength is stable in the stimulation process; and the user interaction module is used for performing stimulation control and setting in real time and displaying the stimulation effect and the muscle fatigue state. Muscle fatigue and strength attenuation in the peripheral nerve stimulation process can be dynamically predicted and compensated in time, and the safety, accuracy and reliability of nerve stimulation are improved.

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 relates to a muscle strength and muscle fatigue prediction algorithm based on surface electromyogram signals, which comprises the following steps of: (1) acquiring the surface electromyogram signals of a measured muscle area by using a non-invasive sensor, and acquiring muscle mechanics parameters at the same time; (2) carrying out filtering, amplification and noise reduction preprocessing on the collected surface electromyogram signals to eliminate interference and enhance signal quality; and (3) extracting multi-dimensional features from the preprocessed surface electromyogram signals and muscle mechanics parameters, establishing a frequency domain data set by using the feature values, and calibrating the muscle mechanics parameters. The method has the advantage that the prediction accuracy and reliability are enhanced. Muscle strength and muscle fatigue states of different individuals can be reflected more accurately, and accurate prediction of individual differences is realized. The adopted surface electromyogram signal acquisition mode is non-invasive, and a plug-in electrode is not needed, so that the test discomfort is reduced, and the acceptability and participation degree of a testee are increased; by establishing an individual model and combining with real-time signal acquisition, real-time monitoring and prediction of muscle strength and muscle fatigue can be realized, and a user can obtain feedback of a muscle state at any time, so that the exercise intensity, posture and training plan are adjusted, and the training effect is optimized.

The invention discloses a muscle strength prediction method and device based on fusion of a physical model and deep learning, and the method comprises the steps: taking the physical information of neuromusculoskeletal as the soft constraint of a data-driven model, fully considering the dynamic time relation of muscle strength distribution, converting the time series input data into time slice data, and carrying out the prediction of the muscle strength. Kinematic data and EMG signals are used as input, advanced features are automatically extracted through a deep learning algorithm, the relation between the input signals and muscle force is established, muscle force prediction meeting a kinematic equation is achieved, and the defect that an existing model for muscle force calculation generally does not contain definite physical modeling for the potential neuromechanical process, and the calculation accuracy is poor is overcome. And the physical mechanism in the joint movement process is not reflected.

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 invention discloses a system for achieving linear constant-speed muscle force test training through a portal frame. The system is suitable for common muscle test training and linear constant-speed muscle test training. The device comprises a portal frame, a barbell rod arranged on the portal frame, and a force measuring table arranged on the portal frame and used for testing the force applied by a trainee, the portal frame is provided with two linear sliding tables connected with the barbell rod and used for generating the movement of the barbell rod, and each linear sliding table is provided with a locking structure used for locking the barbell rod. The portal frame is further provided with a control mechanism connected with the force measuring table, the linear sliding table and the locking structure. When the barbell rod is not locked with the linear sliding table, the barbell rod can be connected with a barbell disc for common muscle test training, and the training function of a universal barbell stand is compatible; when the barbell rod is locked with the linear sliding table through the locking structure, the barbell rod does not need to be connected with barbell discs, the vertical moving speed and direction of the barbell rod are directly adjusted through the linear sliding table, and then linear constant-speed muscle testing training is achieved.

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 a preparation method of a hydrogel film sensor for muscle force prediction and the sensor. The method comprises the following steps: selecting a material ratio of a hydrogel precursor according to a sensitivity parameter and a mechanical stress parameter of the sensor; preparing a hydrogel film, and symmetrically arranging electrodes on the left side and the right side of the hydrogel film in the length direction to form a hydrogel film sensing structure; acquiring the change of the resistance value of the hydrogel film sensing structure, and forming a one-to-one correspondence relationship with the strain value of the sensor for calibration; and carrying out strength test on the target muscle group, measuring the resistance value of the hydrogel film sensing structure tightly attached to the skin surface, and associating a strength test result with the resistance change of the hydrogel film sensing structure to form a muscle strength prediction model. According to the scheme, the accuracy of muscle force testing can be greatly improved.

The invention relates to the field of physical training and testing equipment, in particular to a training and testing device for multiple muscles on the sole and a using method of the training and testing device. Comprising a supporting frame horizontally placed on the ground; the sensor is mounted on the supporting frame; a plurality of stress pieces with different shapes are connected with the sensor and aim at muscles of different parts, the stress pieces are selected according to the muscles of different parts trained by a tester and are hooked on the feet, and the muscles of the designated area are trained by exerting force through the muscles of the feet and acting on the stress pieces. Meanwhile, the magnitude of the muscle strength obtained by monitoring the stress piece through the sensor. The foot training device has the advantages that by arranging the stress parts, a tester can use the proper stress parts for training when training muscles of different parts, muscle training is more targeted, meanwhile, the foot training effect can be better monitored based on the magnitude of foot muscle strength, and the training effect is better. The influence of long-term wearing of different shoes on foot muscle functions is avoided, and a certain thought is provided for optimizing the design of soles and insoles of running shoes 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 utility model discloses a lip muscle strength training device, including movable plate, locating plate, pressure monitoring mechanism, host and feedback panel, movable plate and locating plate are respectively arranged on the same side of host and can be close to each other when being pressed, pressure monitoring mechanism is installed between movable plate and locating plate, and feedback panel is installed on the host. The feedback panel is arranged on the outer wall of the main machine and provided with a voice prompt module and / or a visual prompt module capable of prompting lip muscle strength training, and the main machine is electrically connected with the pressure monitoring mechanism and the feedback panel. The lip strength training device has the advantages that the lip strength training device is suitable for lip strength training of dysarthria or dysphagia, pronunciation clarity can be improved, salivation can be avoided, and swallowing efficiency can be 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.

Provided is a muscle strength evaluation device that includes a data acquisition unit that acquires feature quantity data including a feature quantity used for estimation of a muscle strength of an evaluation target muscle related to a fall risk, the feature quantity data being extracted from sensor data related to movement of a user's foot, a storage unit that stores an estimation model that outputs a muscle strength index of the evaluation target muscle according to an input of the feature quantity data, an evaluation unit that inputs the acquired feature quantity data to the estimation model and evaluate a muscle strength of the evaluation target muscle of the user according to the muscle strength index output from the estimation model, and an output unit that outputs information regarding an evaluation result related to the muscle strength of the evaluation target muscle of the user.

The invention relates to a pelvic floor muscle test data evaluation method, system and equipment, and the method comprises the steps: obtaining test data of pelvic floor muscle in a test period, presetting a boundary value, obtaining a first reference image related to first-class muscle fibers of the pelvic floor muscle, and obtaining a second reference image related to second-class muscle fibers of the pelvic floor muscle, based on the first-class muscle fiber test section and the second-class muscle fiber test section, respectively constructing a first-class muscle test curve and a second-class muscle test curve, and combining the first reference image, the second reference image, the first-class muscle test curve and the second-class muscle test curve to obtain a first-class muscle test curve and a second-class muscle test curve; and first-class muscle strength grading, first-class muscle fatigue degree calculation, second-class muscle strength grading and second-class muscle fatigue degree calculation are carried out respectively. The system and the equipment are used for executing the method. According to the method, muscle strength grading and fatigue calculation can be accurately and quickly performed on the pelvic floor muscle data, human subjective influences are reduced, and the accuracy and efficiency of pelvic floor muscle test data evaluation are improved.

The invention relates to the technical field of pelvic floor muscle pressure assessment, in particular to a pelvic floor muscle pressure assessment method and system.The pelvic floor muscle pressure assessment method comprises the steps that pressure values generated when a user makes assessment actions in a plurality of sampling periods are obtained, and the pressure values form a plurality of corresponding data sets according to the sampling periods, the evaluation action is composed of pelvic floor muscle contraction and pelvic floor muscle relaxation. According to data collected in the pelvic floor muscle contraction process, the muscle strength and fatigue degree corresponding to # imgabs0 # muscle are automatically calculated, meanwhile, in order to guarantee the accuracy of a calculation result in the calculation method, nonstandard contraction in pelvic floor contraction is considered, for example, the phenomena that the pelvic floor contraction is not kept after contraction, and secondary contraction is conducted are considered, and the calculation accuracy is improved. According to the method, on one hand, a multi-averaging method is adopted to eliminate abnormal points, and on the other hand, whether the abnormal points are extreme values in a rising trend process or not is judged, so that a non-standard shrinkage method is eliminated. And the accuracy of the final evaluation result is improved.

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.

A muscular strength assisting apparatus includes a muscular strength assisting portion that assists a user's muscular strength and a first connecting link including one side connected to one side of the muscular strength assisting portion and an opposite side rotatable relative to a shoulder of the user about a first rotation axis. The muscular strength assisting portion includes an upper arm module that assists muscular strength of an upper arm of the user and a link assembly including one side connected to one side of the upper arm module to be rotatable about a second rotation axis non-parallel to the first rotation axis and an opposite side disposed adjacent to a portion of a body of the user to be supported on the user.

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.