428 results about "Plantar pressure" 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 a teenager physical exercise real-time monitoring system, and relates to the technical field of intelligent monitoring. An individualized health assessment model is constructed through space-time alignment processing of joint three-dimensional movement, electromyographic signals and plantar pressure and a bone age dynamic matching technology. Time sequence deviation is eliminated through unified clock marking and interpolation compensation, parameters such as bone stress deviation degree, muscle synergy asymmetry degree and plantar pressure unbalance degree are extracted, and comprehensive health indexes are generated through weighting. And in combination with a preset training path model, analyzing a health index trend in real time and triggering a grading adjustment instruction, dynamically optimizing training intensity, interval and action schemes, and correcting path model parameters through a closed-loop feedback mechanism to realize adaptive updating. The defects that traditional teenager physique monitoring data fusion is large in deviation and static evaluation hysteresis is high are overcome, real-time accurate monitoring and personalized training optimization of teenager physique exercise are achieved, and the sport injury risk is effectively reduced.

The invention relates to the technical field of biological feature recognition, and discloses a neural reflex motion feature extraction and quantitative evaluation method, which comprises the following steps that: multi-modal behavior data of a premature infant are synchronously acquired through a sensor array, and the multi-modal behavior data comprise a motion inertia signal, optical tracking data and plantar pressure distribution data; preprocessing the multi-modal behavior data, and performing dynamic feature fusion on the preprocessed multi-modal data to generate a joint feature vector; extracting a motion symmetry index and a reflection intensity grade from the joint feature vector; and inputting the joint feature vector, the motion symmetry index and the reflection intensity level into a hierarchical rule engine, and executing risk judgment of a behavior pattern. The invention also provides a neural reflex motion feature extraction and quantitative evaluation system. According to the invention, the accuracy of neural reflex motion feature extraction and quantitative evaluation can be improved.

The invention provides a stroke patient gait walking analysis method and device. The stroke patient gait walking analysis method comprises the steps that pressure data and inertial data generated in the gait walking process of a patient are collected based on a plantar pressure sensing module and an inertial measurement module; performing data preprocessing on the pressure data and the inertial data; constructing a double-flow neural network to respectively extract pressure features and inertial features of the pressure data and the inertial data, performing feature fusion, and calculating step length, stride frequency, gait asymmetry index and gait stability index key indexes based on the fused features so as to realize gait evaluation; an evaluation result is transmitted to the flexible OLED touch screen, and gait parameters, rehabilitation progress, abnormal early warning and training guidance information are displayed in real time through the flexible OLED touch screen. According to the method, the end-to-end process from original sensor data to clinical application is realized, manual monitoring is avoided, the accuracy and clinical practicability of evaluation are improved, and the method is particularly suitable for family rehabilitation monitoring of stroke patients and precise rehabilitation evaluation of medical institutions.

The invention discloses a pneumatic-biological signal feedback cooperative control method based on an anti-gravity rehabilitation treadmill, and the method comprises the steps: synchronously collecting sEMG, IMU and plantar pressure signals, and completing the time-space registration through clock synchronization, time warping and extended Kalman filtering; muscle activation degree, pressure center offset and joint angular velocity are extracted to construct multidimensional features, and gait phase switching is predicted through LSTM-CNN; the TS fuzzy system generates a preliminary control instruction according to expert rules, and Q-learning takes pressure balance and motion smoothing as reward functions to optimize the weight reduction proportion and the treadmill speed online; a waist annular air cavity is driven to be inflated to form a pressure supporting field so as to lift a pelvis and guide a lower limb gait mechanical mode, so that the muscle activation degree, the joint angular motion trail and the pressure center migration characteristic are dynamically influenced, a servo motor tracks phase nodes in a feedforward-feedback mode, and risk early warning and training parameter self-adaptive closed-loop rehabilitation are achieved.

The invention provides an intelligent wearable rehabilitation monitoring and evaluation device after anterior cruciate ligament injury, and relates to the technical field of exercise rehabilitation and intelligent medical monitoring, the device comprises a sensor acquisition module, a signal processing module, a compensation determination module, a difference determination module and an evaluation analysis module, a force-electricity coupling flexible sensor, an IMU and a pressure sensor, the method comprises the following steps: synchronously collecting a muscle force signal, a surface electromyogram signal, an attitude signal and a plantar pressure signal at the same position, performing dynamic filtering, confidence enhancement and personalized compensation processing, extracting a difference feature vector, inputting the difference feature vector into a muscle force prediction model, and outputting a quantitative evaluation result. The portable wearable long-term dynamic monitoring is realized, the core indexes of muscles, joints and gaits are covered in multiple dimensions, the assessment is accurate and real-time, the rehabilitation scheme can be optimized, the risk of re-injury is reduced, and the rehabilitation effect and compliance of a patient are improved.

According to the human body activity distinguishing device and method, through an intelligent insole system integrating an inertial sensor and a plantar pressure sensor and in combination with a multi-scale time window analysis method, gait data of a user are accurately collected and processed, daily activity modes such as walking, running and going upstairs and downstairs and changes of the modes are recognized, and the human body activity distinguishing effect is achieved. And real-time health feedback and rehabilitation support are provided. The intelligent insole system comprises an upper computer system, sensor integrated insole hardware and a module communicating with a user terminal and a cloud server. According to the system, multi-modal data is collected through an inertial sensor and a plantar pressure sensor, data processing is achieved in combination with data fusion and a multi-scale sliding time window method, finally, a random forest classifier is used for classifying activity modes, and the functions of health monitoring, posture improvement suggestion, falling risk assessment and the like are achieved. The exercise performance of the user is improved, and personalized health management is provided.

The invention discloses an unmarked motion capture system integrating a pressure sensor array and a depth camera, which belongs to the field of computer vision and comprises a depth camera module, a plantar pressure sensor array module, a data summarization module, a joint point calibration module, a three-dimensional force prediction module and a posture simulation module. The system collects and summarizes positions of human body joint points and pressure distribution data of planta pedis, extracts foot feature points, calibrates the human body joint points to obtain kinematics data, predicts ground reaction force in combination with planta pedis pressure distribution, and uses the calibrated kinematics data and predicted three-dimensional ground reaction force data to predict the three-dimensional ground reaction force. And carrying out human kinematics and dynamics simulation. The system provided by the invention can accurately position the spatial position of the human body joint point, accurately collect the pressure distribution and the ground reaction force in the human body movement process, and improve the accuracy of kinematics and dynamics analysis of the human body.

The invention relates to the technical field of biomechanical analysis, in particular to a health data input method and system and a storage medium. The method comprises the following steps: collecting multi-modal data of a subject, and carrying out gait event recognition to obtain a gait event mark; bilateral gait synchronous alignment is carried out according to the gait event marks, bilateral gait cycle data are obtained, and the bilateral gait cycle data comprise plantar pressure data, ground force data, joint angle data and motion state data; plantar pressure power processing is carried out according to the plantar pressure data and the ground force data, and plantar power parameters are obtained; estimating body segment inertial parameters of the subject; joint torque energy processing is carried out according to the body segment inertial parameters and the joint angle data, and joint power parameters are obtained; and performing gait acceleration calculation according to the motion state data to obtain a gait stability index. The accuracy, comprehensiveness and convenience of gait analysis are remarkably improved through a biomechanical analysis technology.

The invention provides a gait analysis method and an early warning system based on multi-source data fusion, three types of original signals are collected through a wearable inertial sensor, a plantar pressure insole and an edge calculation camera, and multi-dimensional motion characteristic parameters are fused through wavelet denoising, low-pass filtering, interpolation alignment and data consistency correction, so that the gait analysis method based on multi-source data fusion is realized. And constructing a user individualized gait feature prototype library. The method further adopts a dynamic causal graph network to model a motion relation between joints, determines an abnormal coupling mode based on causal weight and historical reference, and combines activity context and Bayesian rules to generate a dynamic threshold value to realize risk grading early warning, so that heterogeneous data collaborative analysis precision and abnormal gait detection sensitivity are improved, and the method is suitable for large-scale popularization and application. And support is provided for gait health monitoring and personalized risk management and control under multiple scenes.

The invention relates to the field of gait analysis, and discloses a gait analysis method and system based on intelligent shoes, and the method comprises the steps: obtaining pressure distribution data captured by a plantar pressure sensor, dividing gait stages according to a pressure mode, and recognizing gait phases; the method comprises the following steps: acquiring three-dimensional acceleration, angular velocity and magnetic field data of an inertial measurement unit, and converting the three-dimensional acceleration data from an IMU coordinate system to an earth coordinate system; performing integral calculation on the three-dimensional acceleration data based on the earth coordinate system to obtain speed data; describing the time stage of the gait through the pressure mode of the pressure distribution data, detecting to obtain a zero speed moment, correcting the speed data by applying a zero speed updating algorithm according to the zero speed moment to obtain the corrected speed data, and further performing integral calculation to obtain the motion trail of the foot; through a principal component analysis algorithm, decoupling the displacement in the step length direction and the step width direction in the foot motion trail so as to obtain step length and step width parameters; the plantar pressure distribution data cloud picture and the foot movement track are combined and visualized, visual reproduction of the foot posture in the gait process is completed, and a convenient mode is provided for a patient to monitor and evaluate the gait health condition of the patient.

The invention discloses a psychological state assessment method and device. The method comprises the steps that firstly, based on a sensor group and a camera module, electrocardio information, face information, gait information and plantar pressure information of a target are obtained; then constructing an input feature vector based on the electrocardio information, the face information, the gait information and the plantar pressure information; and finally, inputting the input feature vector into a preset model to obtain an evaluation result. According to the embodiment of the invention, the multi-dimensional feature data can be processed, so that the psychological state is evaluated by using the multi-dimensional feature data to obtain the evaluation score, and the evaluation accuracy can be improved.

The invention discloses a cognitive movement dual-task intelligent testing and training system. The system comprises a three-dimensional rotating platform, a door frame type auxiliary frame, a plantar pressure film, a head top scanning radar, a tension traction component and a dual-screen display control unit. The plantar pressure film is laid on the upper surface of the three-dimensional rotating platform; the overhead scanning radar, the tension traction part and the double-screen display control unit are installed on the door frame type auxiliary frame. The three-dimensional rotating platform provides a three-dimensional non-linear unstable motion environment with presettable difficulty for a patient, the double-screen display control unit provides cognitive recognition information, and the head top scanning radar, the plantar pressure film and the tension traction component collect body posture data of the patient. According to the invention, a cognitive motion dual-task evaluation and training means based on a three-dimensional nonlinear unstable motion environment is provided for doctors and physicians, so that the evaluation accuracy and the training pertinence are remarkably improved.

The invention discloses a wearable plantar pressure and three-dimensional gait analysis system, and relates to the technical field of gait analysis, the system comprises a wearable in-shoe plantar pressure analysis subsystem and a three-dimensional gait analysis subsystem; the wearable in-shoe plantar pressure analysis subsystem comprises a pressure sensor module, a pressure integration module, an intelligent transmission module, a detection software module, a power supply module, an instantaneous pressure and balance detection module, a standing balance detection module, a balance and gait detection module and a cloud server; the three-dimensional gait analysis subsystem comprises a hardware unit and a software unit; according to the invention, a wearable plantar pressure and three-dimensional gait analysis collaborative system is constructed, bidirectional verification compensation is realized by means of data fusion of two subsystems, and traditional single-dimensional limitation is broken; pressure sensing and a double-view reconstruction technology are fused, data are dynamically captured, and bidirectional error correction is carried out; the limitation of traditional equipment is solved, the evaluation accuracy and robustness are improved, and a quantitative basis is provided for clinical diagnosis, rehabilitation and the like.

The invention relates to the technical field of medical assistance, and discloses a flatfoot sole model generation system and device, which comprises a plurality of air bag elements, a pressure data acquisition module, a motion capture module, a static data processing module, a dynamic data processing module, an execution control module and a model generation module, through the synergistic effect of the air bag element, the pressure data acquisition module and the static and dynamic data processing module, in combination with real-time inflation adjustment and foot arch state judgment, the plantar model adaptive to the foot characteristics of the user is dynamically generated, plantar pressure distribution can be monitored and adjusted in real time, the plantar model is dynamically generated according to the foot motion state of the user, and the user experience is improved. The method has the advantage of improving the flatfoot correction effect and the user experience.

The invention is suitable for the technical field of medical instruments, and provides a pneumatic global self-adaptive ankle-foot artificial limb which comprises a rear sole and a front sole which are connected through a front and rear foot connecting piece. The pressure response assemblies are located at the bottoms of the rear sole and the front sole, and pressure changes after bearing; and the ankle self-adaption assembly is connected with the pressure response assembly through a valve communication assembly and drives the ankle to do eversion, centering and introversion motions based on pressure changes. According to the embodiment of the invention, an ankle joint inward and outward turning automatic adjusting mechanism directly driven by plantar pressure change can enable the artificial limb to adapt to complex terrains such as uneven road surfaces and lateral slopes in real time, an inward and outward turning motion mode of a physiological ankle joint in the walking process is simulated, and the gait of a user is smoother and more natural; the pure pneumatic control structure is relatively simple and light, and an external power supply pressure driving pump or a complex sensor is not needed.

The invention relates to a gait monitoring system of a multi-mode flexible wearable device, and belongs to the field of medical instruments. The insole body of the wearable device comprises an embedded layer and an FPCB, wherein the embedded layer is in contact with the foot end and used for embedding a data acquisition unit and an electrical stimulation unit, and the FPCB is attached to the embedded layer. A through hole is formed in the embedding layer so as to embed and fix the acquisition unit; an interface is arranged at a position corresponding to the through hole in the FPCB and is connected with the acquisition unit; the insole main body is simple to prepare, practical and portable; a flexible sensor is adopted to adapt to the fluctuation of the sole surface, and a good working state is kept; according to the gait monitoring system, data of multiple data acquisition units are fused, so that various data types are displayed in a multi-modal monitoring system; plantar pressure, temperature, center-of-gravity shift and acceleration information are monitored in real time, and support is provided for sports health monitoring and foot disease prevention; gait data in a real dynamic scene is displayed, electrical stimulation is given to positions with abnormal foot temperature, and foot diseases are prevented and improved.

The invention provides a skiing posture correction method and device, and relates to the technical field of skiing teaching, and the method comprises the steps: synchronously collecting plantar pressure distribution characteristic data and ankle joint inclination data of a skier; when the plantar pressure distribution data and / or the ankle inclination data meet the preset unbalance judgment condition, an unbalance adjusting signal is triggered; the imbalance adjustment signal includes at least one of a haptic alert signal related to a severity of the imbalance, a dynamic visual signal including a pressure distribution characteristic, and a sound indication signal having a joint angle quantitative indicator. According to the invention, the skiing posture of the skier can be intelligently and accurately corrected, and the correction efficiency of the skiing posture is improved.

The invention belongs to the technical field of physical ability analysis and diagnosis, and particularly relates to a latent variable fusion modeling method and system for old people weakness trajectory prediction based on biomechanics. According to the method, the plantar pressure, the joint angle and the electromyographic signal in the gait process of the elderly are collected through wearable sensing equipment, multi-dimensional structured feature parameters are extracted, and a key index group reflecting the weakness degree is generated based on preset weight fusion. And in combination with time sequence fitting and variation trend analysis, dynamic evaluation and risk level judgment of the weakness state of the old people are realized. The system comprises a data acquisition module, a feature extraction module, an index fusion module, a trend analysis module and a result output module, has the characteristics of high accuracy, strong real-time performance, good interpretability and the like, and is suitable for weakness risk screening and rehabilitation intervention guidance.

The invention provides an exercise load multi-objective optimization method based on an anti-gravity rehabilitation treadmill. The exercise load multi-objective optimization method comprises the steps of obtaining gait kinematics data, plantar pressure distribution data, electromyographic signal data and pain scores of lower limbs of a patient; based on the data, a gait asymmetry index and a myoelectricity activation sequence consistency index are screened out, the gait asymmetry index and the myoelectricity activation sequence consistency index are combined with pain scores to serve as key features, and a function grading model is constructed to obtain function grades; establishing a multi-objective optimization problem by taking minimization of a pain score, maximization of joint activity and electromyographic activation sequence consistency and minimization of muscle fatigue as objectives and taking non-overrun of articular cartilage contact stress as a constraint; an NSGA-III algorithm is adopted to solve the problem, and a Pareto optimal solution set of the weight reduction proportion and the speed of the treadmill is obtained; through a PPO reinforcement learning strategy network, taking the real-time state of a patient as input, and selecting and dynamically adjusting treadmill parameters in a Pareto solution set; and issuing the adjusted parameters to a treadmill execution mechanism in real time.

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 belongs to the field of medical equipment, and particularly relates to a lower limb intelligent feedback training system and method with balance training, and the method comprises the steps that a pressure feedback system monitors the pressure applied by a left foot and a right foot to corresponding pedals in the stepping training process of a patient, and sends the obtained pressure value to an electric control system; the execution mechanism realizes height lifting, lying standing, foot plate stretching and backrest posture adjustment of the bed body according to a control instruction of the electric control system, and meanwhile, controls left and right pedal plates to execute reciprocating motion; the electric control system receives training control parameters issued by the upper computer and controls the execution mechanism to execute corresponding motion; the running state of the training motor, the running state of each push rod, the training coordination of the left leg and the right leg and the collected pressure value are sent to an upper computer in real time; and meanwhile, the information is displayed on the man-machine interaction system. By detecting the plantar pressure in the walking process of the two feet, balance analysis is carried out when the left foot and the right foot walk, and abnormal gaits are prevented from being generated after walking is recovered.

The invention discloses a composite type four-foot wall climbing robot integrating a fish suction cup adsorption mechanism and lizard crawling characteristics. The problems that a traditional wall climbing robot is poor in adsorption stability and insufficient in moving flexibility on uneven and wet wall surfaces are solved. The core structure of the robot comprises an adsorption sole assembly, a multi-degree-of-freedom leg joint, a bionic spine, a micro air pump and a sole pressure sensor, and the adsorption sole assembly controls an air bag through the air pump to generate negative pressure to adapt to various wall surfaces; multiple joints of the legs are matched with the spherical joints to achieve multi-angle attachment of the foot sole, the bionic spine can be bent and buffered, lizard diagonal gaits are adopted, the rotation angle of the joints is adjusted in combination with a sensor, self-adaptive movement on the wall with the inclination angle ranging from 0 degree to 90 degrees is achieved, and the efficiency is improved by 30% or above compared with a traditional robot. The robot breaks through the limitation of a single bionic mechanism, can be applied to complex high-altitude scenes such as building outer wall detection, and reduces the manual operation risk.

The invention discloses a badminton player action posture analysis system and method based on multi-sensor fusion, and relates to the technical field of athletic training auxiliary systems.The system comprises a wearable sensing subsystem, an environment sensing subsystem and a central processing and feedback subsystem; the wearable sensing subsystem is arranged on an inertia measurement unit and a pressure sensing insole of a body to collect movement inertia and plantar pressure data; the environment perception subsystem collects global videos through multiple cameras. The central processing and feedback subsystem performs synchronous processing on multi-source data, adopts a hierarchical fusion algorithm, restrains inertia integral drift by utilizing a plantar contact state, reconstructs a three-dimensional skeleton posture and a motion trail in combination with visual key points and skeleton restraint, drives a digital twin model, compares with a standard motion model, and performs three-dimensional motion control on the three-dimensional skeleton posture and the motion trail. Quantitative evaluation results such as joint angle deviation, time sequence difference and pressure center track are generated, and visual feedback is performed through a display device and an augmented reality terminal for badminton training evaluation and technical deviation correction.

The invention discloses a diabetic shoe system for plantar pressure monitoring and pressure reduction of a diabetic patient, relates to the technical field of diabetic foot monitoring and rehabilitation, and provides the following scheme that the diabetic shoe system comprises a monitoring shoe, and a plantar pressure monitoring mechanism is laid on the upper surface of the interior of the monitoring shoe; a plantar pressure distribution and pressure reduction mechanism is arranged on the upper surface of the plantar pressure monitoring mechanism, and a bridle mechanism is arranged above the plantar pressure distribution and pressure reduction mechanism. According to the technical scheme, the sole pressure distribution and pressure reduction mechanism composed of the multiple array type air bags is arranged on the sole, the pressure of the sole is monitored by means of the multiple flexible pressure sensors arranged in an array mode, the sole is controlled to incline forwards or backwards or be horizontal by means of different expansion degrees of the multiple air bag sets while the pressing force of the sole is monitored, and therefore the comfort degree of the sole is improved. In a mode of transferring the gravity center of the sole, the pressure is transferred to the heel when the stress of the sole is large, so that ulcer caused by overlarge stress of the half sole of the diabetic foot is prevented.

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 discloses a whole body posture estimation method and system based on a pressure sensor and an inertial sensor, relates to a human body posture reconstruction technology, and provides the scheme for solving the problems of low technology fusion and the like in the prior art. The three inertial sensors are used for generating real IMU data; according to the human body posture reconstruction algorithm, real IMU data and virtual IMU data are fused, and whole body posture estimation is carried out through the following steps that S1, pressure-based biological estimation is carried out, wherein pressure distribution is obtained through a pressure sensor so as to estimate ground counter-acting force GRF and the pressure center CoP; and S2, estimating the body posture in combination with the ground reaction force GRF and the pressure center CoP. The method has the advantages that only three inertial sensors are combined with plantar pressure data, so that complex human motion can be accurately captured. By combining the virtual IMU data with the actually collected IMU data, a larger-scale data set is constructed, and the method can be applied to multiple human body research fields.

The invention relates to the technical field of pressure monitoring, and discloses a method and system for motion state analysis according to plantar pressure, and the method comprises the steps: receiving multi-modal biomechanical data related to a landing event; extracting a corresponding motion feature vector from the multi-modal biomechanical data; and inputting the motion feature vector into a motion state analysis model for identification to obtain a corresponding damage risk index, and outputting the corresponding damage risk index. By receiving pressure distribution data detected by the plantar pressure sensing array, shear force data detected by the shear force measuring and calculating module and a kinematics data sequence detected by the inertial measurement unit, biomechanical information in the movement process can be comprehensively captured from multiple dimensions; compared with a single data acquisition mode, the fusion of the multi-modal data can reflect the real state of the human body in motion more accurately, and a richer and more accurate data basis is provided for subsequent motion state analysis.

The invention provides a knee joint dyskinesia function evaluation method and system. The method comprises the following steps: by collecting lower limb kinematics parameters, plantar pressure distribution data and gait rhythm parameter groups of a subject in a standard gait test, generating a knee joint motion trail map comprising sagittal plane, coronal plane and rotation trail components, dividing a dynamic phase window based on the gait rhythm parameters, calculating a fluctuation feature vector of a sagittal plane track component, performing nonlinear decomposition on a coronal plane and a rotation track component to separate an adduction and abduction motion principal component and a rotation coupling component, constructing a joint stability quantitative index, and performing dynamic space registration on a bilateral knee joint track map to obtain a joint stability quantitative index; and calculating a three-dimensional trajectory similarity weight matrix, and calculating a dynamic symmetry index in combination with the cross-side difference coefficient of the joint stability quantitative index. According to the technical scheme provided by the invention, a scientific basis is provided for personalized rehabilitation treatment.

The invention provides a method for evaluating the correction effect of an ankle-foot orthosis on abnormal plantar stress, and the method comprises the steps: obtaining target pressure detection data of a plurality of plantar sites of a target user, the target user having a symptom of abnormal plantar stress and having worn the ankle-foot orthosis; generating a target pressure change curve corresponding to the sole site according to the target pressure detection data; according to the target pressure change curve, extracting plantar pressure curve characteristic parameters; and performing correction effect evaluation according to the plantar pressure curve characteristic parameters to obtain an evaluation result. By implementing the method disclosed by the invention, the correction effect of the ankle-foot orthosis can be objectively and accurately evaluated based on the pressure detection data of the sole after the user wears the ankle-foot orthosis, so that reliable reference information is provided for optimization of the orthosis.