1950 results about "Lower limb" patented technology

The invention relates to the technical field of medical rehabilitation, and discloses a lower limb weight-bearing gait rehabilitation training system which comprises a data acquisition module, a data processing and analysis module, a patient individualized modeling module, an intelligent decision and control module, a rehabilitation execution module and a man-machine interaction and medical information interface module which are in communication connection through a network. The data acquisition module is used for acquiring multi-modal data of a patient in real time, and the multi-modal data comprises static sign data, dynamic physiological parameters, kinematics and dynamics parameters and non-motion physiological and psychological state data; and the data processing and analysis module is used for carrying out preprocessing, feature extraction and deep analysis on the original data, and outputting a structured patient individualized feature vector and an evaluation result. According to the invention, a patient three-dimensional skeletal muscle digital twinborn model is constructed through the patient individualized modeling module, and in combination with a continuous learning intelligent model library, body sign differences of different patients can be accurately adapted.

The invention provides an artificial intelligence auxiliary diagnosis method and system for a knee joint, and the method comprises the steps: synchronously collecting a multi-angle dynamic X-ray image and six-degree-of-freedom contact force distribution data in an articular cavity, dynamically tracking a patella sliding track, and generating a mechanical phase track; a personalized knee joint model is constructed in combination with the biological parameters of the lower limbs of the patient, the mechanical phase trajectory and the contact force data vector are superposed to generate a dynamic mechanical fingerprint, and then the dynamic mechanical fingerprint is mapped into a biomechanical attribute map; electromyographic signal time-frequency characteristics and tibia rotation angles in the movement process are collected, an electromyographic activation mode is constructed, and the electromyographic activation mode and a biomechanical attribute map are subjected to characteristic fusion to form a joint dynamics comprehensive contour; analyzing a stress wave conduction path by using a joint anomaly dynamic propagation model to identify a compensatory injury mode; a diagnosis map is generated according to the recognition result, a preset biomechanical constraint condition is matched to correct the diagnosis map, and an individualized rehabilitation strategy is formulated. The treatment effect is improved, and the recovery speed of a patient is increased.

The invention discloses an intelligent training method for preventing lower limb thrombus and a related device, and the method comprises the steps: inputting the physiological parameters of a patient, the initial exercise ability evaluation information and the personalized rehabilitation target information into a DQN multi-mode fusion model, and generating an ankle pump exercise training scheme meeting the rehabilitation demands of the patient; monitoring ankle pump motion execution information of the patient in real time through wearable equipment; according to the ankle pump motion training scheme and the ankle pump motion execution information of the patient, a lower limb thrombus training effect evaluation result of the patient is calculated, and the lower limb thrombus training effect evaluation result comprises the blood circulation improvement degree, the joint motion range and the gait characteristics; according to a lower limb thrombus training effect evaluation result of the patient, predicting lower limb thrombus potential recovery disorder and a falling risk level of the patient, and starting a grading alarm program according to the potential recovery disorder and the falling risk level. The training effect is comprehensively evaluated through the multi-modal data fusion training method, and the lower limb thrombus rehabilitation efficiency is improved.

The invention discloses a multifunctional leg sleeve for auxiliary treatment of lower limb lymphedema, which comprises a leg sleeve body, a pressure sensing unit, a temperature and humidity sensing unit, an air bag pressure unit, a heating unit, an electrical stimulation unit, an impedance measuring unit and a portable force-electricity-heat cooperative intervention controller, the leg sleeve is characterized in that the pressure sensor and the temperature and humidity sensor monitor internal environment parameters of the leg sleeve body, drive the air bag pressure unit to perform self-adaptive pressurization, and drive the heating element and the electrical stimulation electrode to perform intelligent heating medicine application and muscle stimulation at the same time; the main control unit is driven to adjust the pressure, the temperature and the stimulation intensity of the air bag pressurizing unit, the heating unit and the electrical stimulation unit; in the wearing period, the device uploads data to a mobile phone and a cloud server terminal for data analysis, optimal pressure, temperature and electrical stimulation regulation prescriptions are provided for a user, and a good treatment effect is achieved.

The invention relates to the technical field of rehabilitation medical treatment, and discloses a muscle group stress analysis method and device, a terminal and a storage medium, and the method comprises the steps: respectively obtaining motion data collected by inertial measurement units arranged on the body of a user, and recognizing gait events based on the motion data corresponding to the inertial measurement units of the lower limbs, dividing the continuous motion data into a plurality of gait cycles according to the gait event; fusing the motion data acquired by each inertial measurement unit to obtain a three-dimensional posture of each preset segment of the body, and constructing a three-dimensional motion track of the spine area of the user in combination with a human kinematics chain model; processing the three-dimensional motion track and the known muscle group stress data by adopting a singular value decomposition embedding regression method to obtain a preliminary target muscle group stress curve of each gait cycle; and correcting the initial target muscle group stress curve based on a human body multi-rigid-body dynamic model in combination with a control cost function to obtain a final target muscle group stress curve.

The invention relates to the technical field of intelligent wearable devices, and discloses a multi-modal sensing and motion state recognition method and device for an intelligent wearable device, and the method comprises the steps: carrying out the anatomical coordinate transformation of original motion data collected by a wrist wearable device, and obtaining an acceleration sequence and an angular velocity sequence; performing sliding window segmentation and multi-scale wavelet packet decomposition to obtain a potential conversion period window set and corresponding multi-scale time-frequency features; constructing a conversion period feature vector for describing a conversion relation between the wrist movement and the whole body movement; inputting the conversion period feature vector into a hierarchical conversion identification model for processing to obtain a conversion type label and a conversion confidence coefficient; body part association mapping and lower limb action state inference are executed, a lower limb state sequence and a whole body action conversion type in the conversion process are obtained, real-time efficient recognition of action conversion is achieved, limitation of a single model is avoided, and the high recognition rate under low calculation complexity is kept.

The invention belongs to the field of computer vision, and discloses a method, a system, equipment and a medium for recognizing whole-body actions of a three-dimensional skeleton human body based on a multi-style topological matrix and refined skeleton features, and the method comprises the following steps: firstly, acquiring skeleton action sequence data containing multi-frame three-dimensional coordinates of human body articulation points; constructing a multi-style topological structure composed of three local adjacent matrixes of the head, the trunk and the lower limbs and a global adjacent matrix; after spatio-temporal feature extraction is carried out through a graph convolutional network, refining processing is carried out on output features to generate local and global feature representations, and corresponding prediction probability distribution is calculated; and training the network by using a combined loss function of global and local prediction probability distribution joint optimization, and finally outputting an action classification result. According to the method, the joint relation is captured through effective skeleton topological representation, local and global feature refined learning is combined, and the three-dimensional skeleton human body action recognition performance is improved.

The invention relates to the technical field of robots, and discloses an electro-hydraulic hybrid driving and driven humanoid robot lower limb and waist assembly which serves as a connection foundation of lower limbs and a robot trunk. The near ends of the thigh assemblies are connected with the waist assembly through hip joints; the near end of the shank assembly is connected with the far end of the thigh assembly through a knee joint; the foot component is connected with the far end of the shank component through an ankle joint; the hip joint is provided with three rotational degrees of freedom, the knee joint is provided with one rotational degree of freedom, and the ankle joint is provided with two rotational degrees of freedom; the rotational degree of freedom of each joint in a sagittal plane is driven by an active hydraulic actuator and a passive hydraulic actuator; the rotational degree of freedom of each joint in a horizontal plane and a coronal plane is driven by a motor joint module; the advantages of electric drive and hydraulic drive are brought into full play, and the problems of high power consumption in the negative work stage, complex traditional hydraulic drive pipelines and the like are solved by adopting an active and passive combined distributed hydraulic drive technology.

The invention discloses a double-clutch variable-stiffness knee joint exoskeleton, and relates to the technical field of wearable lower limb exoskeletons.The double-clutch variable-stiffness knee joint exoskeleton comprises a gait sensing module arranged outside and a limb connecting arm module used for being connected with a human body, and an energy storage module is installed on one side of the limb connecting arm module; a sensor module is mounted on the other side of the limb connecting arm module; the limb connecting arm module comprises a limb connecting arm assembly I used for being connected with the thigh of the human body and a limb connecting arm assembly II used for being connected with the shank of the human body, the limb connecting arm assembly I and the limb connecting arm assembly II are each provided with a clutch unit, and the core speed increaser is installed between the limb connecting arm assembly I and the limb connecting arm assembly II. The energy storage module and the sensor module are arranged on the two sides of the core speed increaser, and the core speed increaser is connected with the energy storage module. The device has the advantages of compact structure, variable rigidity bandwidth and good motion adaptability, can realize high energy recovery efficiency in a multi-gait mode, and reduces the metabolic consumption of a human body.

A prosthetic foot includes a base spring, a top spring assembly, a connector assembly, and a heel cushion. The top spring assembly includes first and second spring members, and first and second bond connections. The second spring member extends parallel with and spaced apart from the first spring member. The first bond connection is between distal ends of the first and second spring members, and the second bond connection is between a distal end of the second spring member and a top surface of the base spring. The top spring assembly has a first portion arranged horizontally, and a second portion arranged vertically. The connector is connected to a proximal end of the top spring assembly to connect the prosthetic foot to a lower limb prosthesis. The heel cushion is mounted to the base spring at a location spaced forward of a heel end of the base spring.

The invention provides a sports action correcting and monitoring system based on image recognition and big data, relates to the technical field of artificial intelligence, and integrates multi-source data, eliminates space-time differences and improves the accuracy and reliability of an analysis result through a data synchronization and fusion module by using a big data processing technology; the biomechanical solving module calculates a lower limb joint torque vector in real time based on a Lagrange equation, and real-time monitoring of the joint torque is achieved; the load optimization module adopts an Adam optimization algorithm, optimizes the stride width and the knee joint buckling angle through a gradient descent method, minimizes the maximum value of the joint torque, reduces the joint load of an athlete, and prevents potential injury; the feedback display module transmits the optimized action parameters to the wearable device in real time, the athlete is guided to adjust the action in real time, and the high efficiency and safety of training are ensured.

The gait assistance mechanism according to one example of the present invention may comprise one or more tendons connecting an upper limb, a trunk, and a lower limb of a wearer and a fixing part fixing the one or more tendons to the body of the wearer, and the one or more tendons may comprise a driving tendon connecting the lower limb and the upper limb on the same side of the wearer.

The invention relates to the technical field of wearable exoskeleton assistance, in particular to a lower limb exoskeleton knee joint assistance control method and system. The lower limb exoskeleton comprises a pair of swing arms respectively connected with thighs and shanks and an actuator, and the method comprises the following steps: processing data of a motion parameter sensor, acquiring detection data input by the motion parameter sensor arranged on the lower limb exoskeleton, and processing the detection data to extract motion features; gait phase detection is conducted, the current gait phase is determined according to the motion characteristics, the gait phase comprises a supporting phase and a swinging phase, the supporting phase corresponds to the state that the lower limb touches the ground, and the swinging phase corresponds to the state that the lower limb leaves the ground; activity identification: motion features are extracted in the supporting phase to determine activity types, and the activity types comprise at least one of flat walking, upward walking, downward walking, running, squatting, backward walking and unknown; according to the control strategy, the corresponding control strategy is selected according to the gait phase and the activity type so as to control an actuator.

The invention relates to the field of pelvic floor muscle recovery treatment, in particular to a female pelvic floor muscle recovery treatment device and an adjusting structure thereof.The female pelvic floor muscle recovery treatment device comprises a movable base, a control box is arranged on the surface of the movable base, a hydraulic rod is installed on one side of the control box, and a recovery supporting plate is installed at the top of the hydraulic rod; a massage repairing device capable of massaging female pelvic floor muscles is installed on the upper surface of the repairing supporting plate, a movable structure is installed in the repairing supporting plate, and a lifting adjusting structure capable of freely moving is arranged above the repairing supporting plate. The top of the lifting adjusting structure is provided with an abdomen repairing structure capable of repairing female abdomen muscle tissue, and the matrix type layout of the massage vibrators can stimulate pelvic floor muscle groups in a partitioned mode, so that the biological feedback effect is enhanced. The leg repairing structure drives a sliding ball to move in an arc groove through an electric telescopic rod, switching between resistance training and passive stretching is achieved, and lower limb venous thrombosis is effectively prevented.

The invention discloses a lower limb exoskeleton control system and method based on phase recognition and model prediction control. The system comprises a kinematics modeling module, a gait database module, a data processing and feature extraction module, a gait phase recognition module, a dynamics modeling module, a model prediction controller and an actuator control unit. By recognizing the gait phase and dynamically adjusting and controlling the target, precise assistance of the natural gait of the wearer is achieved. The system calculates the trajectory of the ankle joint relative to the hip joint in real time based on a kinematic model, and constructs a database in combination with gait data collected under multiple working conditions to provide an expected trajectory and reference parameters for control. In the dynamic modeling process, motor driving torque and man-machine interaction torque are introduced, a system dynamic model is established in a unified mode, and control characteristics under different gait phases are reflected.

The present application relates to the field of medical devices, and provides a back plate adjustable exoskeleton, comprising: a column structure and a control module, the column structure is slidably connected with a back plate mechanism, and a lower limb exoskeleton connected with the back plate mechanism, and the back plate mechanism is provided with a back plate which can move up and down relative to the back plate mechanism; further comprising: a binding device arranged on the lower limb exoskeleton and a foot bottom exoskeleton, the foot bottom exoskeleton is provided with a pressure sensor. When the human body wears the exoskeleton and changes from a sitting posture to a standing posture, the back plate mechanism adjusts the back plate mechanism along the column structure to the height matched with the user according to different body shapes of the user; and when the user changes the posture in the walking process in the standing posture, the foot bottom exoskeleton detects the change of the foot bottom pressure, so that the control module can control the up and down movement of the back plate relative to the back plate mechanism according to the foot bottom pressure to adjust the human body posture.

The invention relates to the technical field of robots, and discloses an electro-hydraulic hybrid drive active and passive humanoid robot which is characterized in that a head assembly adopts pure electric drive configuration, and three-degree-of-freedom rotation of a neck is realized through driving of a parallel-series hybrid mechanism; the upper limb assembly is purely electrically driven and comprises a two-degree-of-freedom waist joint driven by a differential parallel transmission mechanism and a seven-degree-of-freedom mechanical arm driven by a near-end motor through a spherical parallel mechanism, a four-bar mechanism and the differential parallel transmission mechanism; the lower limb assembly adopts mixed configuration of active and passive hydraulic main drive and motor auxiliary drive, the single leg has six degrees of freedom, sagittal plane degrees of freedom of hip joints, knee joints and ankle joints are driven by active and passive hydraulic actuators, and other degrees of freedom are driven by a motor joint module; high-dynamic, high-outbreak, high-energy-efficiency, large-load and impact-resistant operation of the upper limbs is achieved while high-dynamic, large-load, high-rigidity and high-precision operation of the upper limbs is guaranteed, and the movement, operation and cruising ability of the whole machine is remarkably improved.

The invention provides an ankle foot orthosis parameter adjusting method based on a digital model, and the method comprises the steps: constructing a first fusion model which comprises a lower limb three-dimensional model of a target user and an initial orthosis three-dimensional model of an initial orthosis, and the target user has a lower limb abnormal symptom; a first parameter value, corresponding to the target walking parameter, of the target user wearing the initial ankle foot orthosis in the walking process is detected and obtained; orthosis parameter adjustment is conducted on the first fusion model according to the first parameter value, and a second fusion model is obtained; performing walking parameter prediction based on a second fusion model to obtain a second parameter value corresponding to the target walking parameter; and determining a target orthosis parameter according to the second parameter value. By implementing the method disclosed by the invention, on-line adjustment of related parameters of the ankle foot orthosis and accurate evaluation of the orthopedic effect after adjustment can be realized based on the digital model, so that the adaptation efficiency of the orthosis is improved while the adaptation cost of the orthosis is reduced.

The invention relates to the technical field of image processing, in particular to a lower limb fracture image high-precision segmentation method and system based on artificial intelligence, and the method comprises the steps: obtaining a plurality of initial extension bone lines in a leg connected domain; according to the distance between each initial extension bone line and the comparison edge, obtaining the texture degree of each initial extension bone line, screening out a plurality of initial extension bone lines, and obtaining a bone connected domain in the leg connected domain; according to the difference between the gradient difference of the central pixel point and the gradient difference of the to-be-grown pixel points, obtaining a growth coefficient between the central pixel point and each to-be-grown pixel point in the corresponding eight neighborhoods; growing to obtain a plurality of growth lines; according to the unevenness and the included angle of each growth line and the minimum distance between the growth line and the edge line of the bone connected domain, all the bone fracture lines are obtained, and observation and treatment of a doctor are assisted through all the bone fracture lines. The accuracy of high-precision segmentation of the lower limb fracture is improved.

The invention relates to an early screening method and system for abnormal spinal curvature based on multi-modal data fusion, and the method comprises the steps: carrying out the fusion of space-time sequence features based on obtained multi-modal data, and carrying out the three-dimensional biomechanical modeling, and obtaining a spine-pelvis-lower limb dynamic coupling network; carrying out weighted calculation on the key mechanical transmission path through a graph attention mechanism based on a dynamic coupling network to obtain a path strengthening feature vector; performing multi-modal risk quantitative modeling based on the path strengthening feature vector to obtain a multi-dimensional risk index; and based on multi-dimensional risk indexes, carrying out grading early warning decision making through threshold value comparison and dynamic risk layering so as to realize early screening of spinal curvature abnormity. By implementing the scheme, the early screening accuracy of the abnormal spinal curvature can be improved.

The invention relates to the technical field of lower limb rehabilitation training, and discloses an intelligent load lower limb rehabilitation training system fused with a multi-source sensor. The system comprises a multi-source sensing module, a motion intention recognition module, a self-adaptive track generation module, a real-time load regulation and control module and an actuator driving module. The multi-source sensing module synchronously collects plantar pressure, joint angles and electromyographic signals during training of a user through a plantar pressure sensor array, a knee joint angle sensor and a surface electromyographic sensor; the motion intention recognition module extracts time domain and frequency domain features from the multi-source data, and obtains a real-time motion intention through classification; the self-adaptive track generation module generates an exclusive three-dimensional motion track in combination with the real-time intention and historical rehabilitation data of the user; the real-time load regulation and control module generates a self-adaptive load control signal through a fuzzy decision algorithm; the actuator driving module adjusts the magnetic powder brake through PWM current, outputs corresponding real-time resistance torque, and assists in optimizing the rehabilitation training effect.

The invention provides a compact lower limb exoskeleton hip pitching degree-of-freedom joint assembly which comprises a hip motor fixing plate and a hip motor, the hip motor is installed on the hip motor fixing plate through a hip motor fixing piece, the hip motor fixing plate is connected with a hip joint upper connecting plate and a hip joint lower connecting plate, and the hip joint upper connecting plate is connected with the hip joint lower connecting plate. A stable supporting structure is formed; a motor flange plate is mounted at the output end of the hip motor, and a motor output shaft is fixed on the motor flange plate to transmit torque generated by the motor; the other end of the motor output shaft is connected with a knee joint motor, and meanwhile the motor output shaft transmits power to the thigh rod connecting piece through a transmission bolt.

The invention relates to the technical field of finite element modeling, in particular to a kinematics and dynamics index output method based on a human body model, which comprises the following steps of: S1, establishing acceleration modules at the head, the chest, the hip and the lower limbs of the human body model for global and local acceleration and angular velocity output; s2, building displacement modules at the chest, abdomen, knee joints and achilles tendons of the human body model, wherein the displacement modules are used for outputting the compression amount and the elongation amount; and S3, establishing section force modules at the spine, crista iliaca, femur and tibia of the human body model for outputting local force and torque. According to the scheme, the technical problem that kinematics and dynamics indexes of the human body model cannot be effectively extracted in the prior art can be solved, the obtained kinematics and dynamics indexes can be compared with data collected by various sensors in a real physical test, and biological fidelity verification of the human body model is facilitated.

The invention provides a pelvis inclination and lower limb posture anomaly detection method based on a body measurement all-in-one machine, and the method comprises the steps: collecting an original image of the body shape of a detected person through a multi-view camera array, carrying out the brightness adjustment and contrast enhancement, obtaining an image fuzzy index, judging the image fuzzy degree through a preset brightness comparison threshold value, and obtaining a detection result. Evaluating to obtain initial ambiguity and setting ambiguity tolerance; if the initial ambiguity exceeds a preset ambiguity threshold, increasing an edge enhancement coefficient to a specified range to obtain an enhanced first image data set; and extracting a pelvic front rake value and a left-right tilt offset from the smoothed angle data, performing vectorization to obtain a feature vector, determining a pelvic tilt state category according to the feature vector, and obtaining a preliminary pelvic tilt state evaluation result.

According to the technical scheme, the four-limb joint supporting structure comprises an upper supporting part, a lower supporting part and a connecting part, and the upper supporting part and the lower supporting part can be bent to be in an arc surface shape from the two sides and are used for being attached to the upper limb and the lower limb at the joints of a patient; the two ends of the connecting part are connected to the upper supporting part and the lower supporting part respectively and used for being attached to the joint position, and the width of the connecting part is smaller than that of the upper supporting part and that of the lower supporting part so that two grooves can be formed between the connecting part and the upper supporting part and between the connecting part and the lower supporting part. The utility model has the beneficial effects that the connecting part is formed between the upper supporting part and the lower supporting part through the groove, the connecting part is bent and attached to the joint, the generation of a break angle is avoided, the bending can be extremely simplified, no matter whether the material has enough ductility or not, the requirements can be met, the structure is simple, the complexity degree is low, the production process is simple, and the operability is high; the device is suitable for shoulder joints, elbow joints, ankles and the like, and the structural design has certain universality.

The present invention provides a fracture reduction device, which relates to the technical field of medical devices. The fracture reduction device includes: a fixing frame, a driving mechanism, a proximal traction mechanism and a distal traction mechanism, wherein the proximal traction mechanism and the distal traction mechanism are used to be connected to the proximal end and the distal end of the broken bone respectively; the driving mechanism is connected to the fixing frame; one of the proximal traction mechanism and the distal traction mechanism is connected to the fixing frame, and the other is connected to the movable end of the driving mechanism, and the driving mechanism is used to drive the proximal traction mechanism or the distal traction mechanism connected thereto to move, so that the distance between the distal traction mechanism and the proximal traction mechanism changes. The above device is used to assist in the traction and stretching of the broken bone, and only one operator is required to complete the traction reduction work; when the broken bone is stretched by the driving mechanism, the stretching action is smooth, and the length of the lower limb after reduction can be stably maintained.

The invention discloses a hip replacement lower limb equal-length control system and method based on individualized three-dimensional modeling. The hip replacement lower limb equal-length control system comprises a data preprocessing module, a medical image processing module, a dynamic implantation simulation module, a biomechanical analysis module, a guide plate generation module and a postoperative evaluation module. The method comprises the following steps: acquiring bilateral lower limb CT data and carrying out multi-modal registration; segmenting a skeleton structure by using a deep learning model, and constructing a three-dimensional model; reconstructing a complete sphere through affected side femoral head multi-plane fitting, and determining a target femoral head center in combination with uninjured side mirror image data; dynamically adjusting the space posture of the prosthesis to enable the center of the prosthesis head to coincide with the center of the target; performing finite element analysis to optimize stress distribution; and generating a 3D printing file of the individualized osteotomy guide plate and the positioning pointer. According to the method, preoperative accurate planning, intraoperative real-time control and postoperative quantitative evaluation are achieved, the operation precision is effectively improved, and complications of unequal lengths of lower limbs are avoided.

The invention relates to the technical field of medical supplies, in particular to an intelligent medical compression sock which comprises an elastic sock cylinder, a multi-mode sensor array module and a control host, the elastic sock cylinder is constructed to cover at least one part of a foot, a shank and a thigh, and toes are exposed out of the tail end of the elastic sock cylinder; the multi-modal sensor array module is integrated on the inner surface of the side, tightly attached to leg muscles, of the stretch sock leg, the multi-modal sensor array module comprises a plurality of micro pressure sensors, and the micro pressure sensors are non-uniformly arranged according to a lower limb vein anatomy distribution path and are mainly distributed in a great saphenous vein walking area and a gastrocnemius muscle belly area; the control host is externally arranged at the position, close to a sock inlet, of the rear side of the stretch sock leg, and a microprocessor, a communication module and a power supply module are arranged in the control host. The problems that an existing medical stretch sock is non-adjustable in pressure, single in function and lack of monitoring are effectively solved, and treatment individuation, datamation and intelligentization are achieved.

The invention discloses a lightweight multi-mode lower limb motion intention recognition method and system, and relates to the technical field of biomedicine. The method comprises the steps that multi-channel surface electromyogram signals sEMG of a target lower limb and joint angle signals and joint torque signals of lower limbs on the same side are synchronously collected; performing feature extraction by using a double-branch structure to obtain muscle-related deep time sequence features and joint-related high-level semantic features; performing feature fusion through a bidirectional cross attention mechanism to obtain cross attention fusion features; and performing flattening, nonlinear mapping, regularization and Softmax classification on the cross attention fusion features, and outputting the motion intention of the target lower limb. Through double-branch input, depth feature extraction and a bidirectional cross attention mechanism, on the premise of ensuring recognition precision, a lightweight attention module, a residual structure and a cross-modal interaction mechanism are introduced, and the parameter quantity and calculation overhead are reduced.

The invention relates to the field of lower limb hip and knee data analysis, and discloses a user feature data effective acquisition and analysis method for lower limb hip and knee rehabilitation, which comprises the following steps: acquiring related data for movement at the kitchen hip and knee of a user and performing data preprocessing; meanwhile, a convolutional neural network is used for conducting modeling analysis on the preprocessed related data, and a multi-channel sequence gait detection algorithm model is designed and constructed and used for presetting the next movement of the lower limbs, the hips and the knees of the user. And finally, performing model loss training optimization on the multi-channel sequence gait detection algorithm model, and introducing a scoring mechanism to enable the multi-channel sequence gait detection algorithm model to perform gait scoring on the target user. According to the invention, simultaneous input of multiple channel data can be realized, detection of the current state and gait of the human body can be realized, and the effect of still keeping recognition without switching modes under the condition that the channel data is missing can also be realized.