47 results about "Rehabilitation engineering" patented technology

The invention provides an electroencephalogram-myoelectricity collaborative limb movement intention decoding method and system based on a symmetric cross-modal attention network, and belongs to the technical field of neural rehabilitation engineering and movement intention decoding. Comprising the following steps: acquiring an electroencephalogram signal and an electromyographic signal to be decoded; inputting the electroencephalogram signals into an electroencephalogram channel specificity feature extraction network, and extracting multi-scale space-time oscillation features; the electromyographic signals are input into an electromyographic channel specificity feature extraction network, and dynamic time sequence mode features are extracted; inputting the electroencephalogram features and the myoelectricity features into a symmetric cross-modal attention module, carrying out bidirectional feature interaction and calibration, and generating fusion enhancement features; the symmetric cross-modal attention module realizes mutual enhancement and alignment between the electroencephalogram signals and the electromyographic signals by taking own features as queries and taking another modal feature as a key and a value through a cross attention mechanism; and inputting the fusion enhancement feature into a classifier, and decoding to obtain a corresponding motion intention category.

The invention discloses an upper limb rehabilitation control method and system based on a multimode coordination adaptive brain-computer interface, and belongs to the technical field of neural rehabilitation engineering and brain-computer interfaces. The system comprises a brain signal acquisition module, a self-adaptive residual filtering module, a feature extraction module, a predictive control module, an upper limb rehabilitation actuator and a self-adaptive updating module. The core is that a self-adaptive updating module constructs a composite error cost function by fusing kinematics errors of a physical layer and error correlation potentials of a neurocognitive layer, and on the basis of the composite error cost function, a front-end filtering weight and a network weight of a rear-end control model are synchronously adjusted, so that full-link parameter collaborative optimization from signal preprocessing to motion control is realized. According to the method, the framework limitation of single error feedback and independent parameter optimization of a traditional system is broken through, a closed-loop brain-computer interface system which can sense internal and external states and has system-level self-optimization capability is constructed, and the decoding robustness, the control precision and the practicability under long-term use are effectively improved.

The invention discloses a children language cognition rehabilitation assisting system and method based on a self-adaptive co-creation mechanism, and belongs to the field of medical artificial intelligence and psychological rehabilitation engineering. The system comprises five core modules, the modules are connected in a closed-loop mode in a data flow mode to form a sustainable and optimized interaction system, a semantic vector, an emotion vector and a task vector of child voice are fused, a fusion state vector is constructed through a dynamic weight generation network and a cross-modal attention mechanism, and the fusion state vector and the task vector are integrated. And generating a co-creation control instruction by adopting an attention-enhanced gating circulation unit and a strategy network, and further synthesizing an interactive voice signal with emotional expressive force. Synchronous fusion and linkage feedback of semantic understanding and emotion recognition can be achieved, the interaction strategy is dynamically adjusted according to the real-time state of children, strategy network parameters are optimized through online self-learning, and the naturalness, coherence and individual adaptability of rehabilitation interaction are improved.

The application discloses a kind of children language cognitive rehabilitation auxiliary system and method based on adaptive co-creation mechanism, belong to medical artificial intelligence and psychological rehabilitation engineering field.The system includes five big core modules, and is connected in the form of data stream closed loop between modules, forms sustainable optimization interactive system, which is by fusing the semantic vector of children voice, emotion vector and task vector, via dynamic weight generation network and cross-modal attention mechanism to construct fusion state vector, and using attention enhanced gated recurrent unit and strategy network to generate co-creation control instruction, and then synthesis interactive voice signal with emotional expressiveness.The application can realize the synchronous fusion and linkage feedback of semantic understanding and emotion recognition, dynamically adjust interactive strategy according to the real-time state of children, and optimize strategy network parameters through online self-learning, improve the naturalness, coherence and individual adaptability of rehabilitation interaction.

The application provides a trigger type wearable ultrasonic device and method, and relates to the technical field of medical imaging and rehabilitation engineering. The device comprises: an ultrasonic imaging module for generating an ultrasonic image of a target part; a training intensity monitoring module for monitoring rehabilitation training actions of a user in real time and generating a training intensity signal; a central processing and control module for generating an action type and a training intensity parameter according to the training intensity signal, generating an imaging trigger instruction according to a trigger condition, and synchronously and associatively storing the collected ultrasonic image and the training intensity parameter and the action type at the trigger time. Thus, the ultrasonic imaging is intelligently triggered through the training intensity signal, the system only works in an effective training period, thereby significantly reducing the power consumption of the system and prolonging the endurance time; and the multimodal synchronization and association of the ultrasonic image data and the training intensity parameter are realized, thereby providing an objective and fused data basis for the quantitative evaluation of rehabilitation effects and the accurate formulation of rehabilitation plans.

The application discloses an electroencephalogram guided hip-knee-ankle orthopedic rehabilitation exoskeleton adaptive adjustment method, and relates to the technical field of intelligent rehabilitation engineering and biomedical engineering. On the basis of identifying the continuous electroencephalogram fluctuation characteristics in the intention transition period, the support response of the lower limb three joints is combined to construct a traceable transition identification zone. By extracting the driving dislocation point to set the joint response delay, the problem of early driving before the support is completed is avoided. The forward inclination trend is predicted in combination with the torso posture angle and the foot bottom pressure change, and a reverse support hierarchical matrix is dynamically arranged among the three joints to ensure the timing matching and compensation of the support forces among the joints when the abnormal driving trend occurs. Through the rhythmized inhibition and micro-assistance alternating mechanism, the joint output forms a flexible buffer gait, so that the gait stability, the neural participation degree and the safety of the patient in the rehabilitation training process are significantly improved.

This application relates to the fields of biomedical engineering and rehabilitation engineering technology, and discloses a functional electrical stimulation method and system based on physiological simulation and adaptive closed-loop feedback. The method includes: calculating an ideal muscle activation curve based on a target trajectory; performing spatiotemporal asynchronous co-coding to generate a biomimetic stimulation pulse sequence by simulating temporal asynchrony, spatial and intensity modulation, and multi-muscle synergistic timing; simultaneously applying stimulation while monitoring the actual kinematic state and muscle physiological state in real time using sensors; and dynamically adjusting the internal parameters of the spatiotemporal asynchronous co-coding (T-S-C coding) based on the evaluation results of trajectory error and fatigue index to form an adaptive closed loop. This application, by combining biomimetic coding with an intelligent closed loop, fundamentally solves the problems of motion stiffness, muscle fatigue, and poor control precision caused by traditional FES, achieving smooth, sustained, and precise personalized motor function rehabilitation.

The invention relates to the technical field of medical instruments and rehabilitation engineering, in particular to an elderly cognitive disorder rehabilitation training system based on a brain-computer interface technology, and the system comprises a synchronous collection module which is used for collecting an electroencephalogram signal, behavior response data and self-evaluation input of a user in real time; the state processing module is used for extracting a macroscopic feature set from the electroencephalogram signal and generating a short-term performance indicator from the behavior data; the state fusion module is used for fusing the multi-modal data and outputting a comprehensive state label with confidence; the self-adaptive adjusting module is used for generating an adjusting instruction according to the state label and the confidence coefficient so as to dynamically adjust training task parameters or processes; and the long-term learning module is used for storing training data, updating a user personalized model and continuously optimizing a state evaluation and adjustment strategy. According to the system, closed-loop, self-adaptive and personalized intelligent regulation and control of the cognitive rehabilitation training process are realized.

The invention relates to the technical field of biomedical engineering and rehabilitation engineering, and discloses a functional electrical stimulation method and system based on physiological simulation and adaptive closed-loop feedback. The method comprises the following steps: calculating an ideal muscle activation curve based on a target trajectory; space-time asynchronous cooperative coding is executed, and a bionic stimulation pulse sequence is generated by simulating time asynchronism, space and intensity modulation and a multi-muscle cooperative time sequence; when stimulation is applied, the actual kinematics state and the muscle physiology state are monitored in real time through a sensor; and dynamically adjusting the internal parameters of the time-space asynchronous cooperative coding (T-S-C coding) based on the evaluation results of the trajectory error and the fatigue index to form a self-adaptive closed loop. According to the method, bionic coding and intelligent closed loop are combined, so that the problems of stiff movement, easy fatigue of muscles and poor control precision caused by traditional FES are fundamentally solved, and smooth, lasting and accurate personalized movement function rehabilitation is realized.

The invention discloses a deformable intelligent wheelchair robot for old people, and relates to the technical field of medical instruments and rehabilitation engineering, base wheels are arranged at the lower end of a base, a human body supporting frame is movably mounted on the base, and the two ends of a base adjusting module are connected with the base and the back face of the human body supporting frame correspondingly; the base adjusting module can drive the human body supporting frame to rotate relative to the base under the control of the control module, the seat back cushion is installed on the human body supporting frame and used for making contact with and supporting the head and the trunk of a user, and the leg supporting frame adjusting module is installed on the back face of the human body supporting frame and used for adjusting the leg supporting frame. The leg supporting frame can drive the legs of the human body supporting frame to rotate relative to the main body part of the human body supporting frame under the control of the control module, and the power module is used for providing electric energy. According to the multifunctional wheelchair, people who are inconvenient to move can move, meanwhile, the sitting, standing and lying functions are achieved, and functional diversity of the wheelchair is achieved.

The invention relates to a scoliosis correction recognition method and system based on sensing communication equipment, in particular to the technical field of rehabilitation engineering, and realizes the crossing of scoliosis rehabilitation evaluation from universality to individual specificity through fusion of transfer learning and small sample adaptive technologies. The system can quickly construct a highly personalized evaluation model according to a very small amount of user data, and accurately capture unique biomechanical characteristics of different patients; an online learning mechanism driven by uncertainty estimation is further introduced, so that the model can be autonomously optimized and adjusted along with the rehabilitation process of the user to dynamically adapt to the capability change of the user; finally, prospective modeling is carried out on the rehabilitation track by means of a space-time diagram neural network, decision support information with an early warning function and personalized guiding significance is generated, and therefore the problems that a traditional assessment method depends on a fixed threshold value and lacks dynamic and predictive core pain points are effectively solved; and the accuracy, adaptability and intelligent level of family rehabilitation training are obviously improved.

The utility model discloses a kind of postoperative shaping auxiliary devices for neck and back, applied in rehabilitation engineering technical field, including support plate, the top of the support plate is bolted with fixed plate, the top of the front of fixed plate is bolted with adjusting box;The utility model can reduce blood stasis caused by long-term braking by moderate activity design, accelerate inflammation subsides and wound healing, reduce muscle spasm and nerve compression on the basis of maintaining neck physiological curvature, relieve postoperative pain, reduce postoperative muscle fatigue and joint stiffness by dispersing neck pressure, improve patient comfort degree;While maintaining the stability of spine, allow moderate activity, avoid muscle atrophy or joint stiffness caused by long-term complete braking, support device shares back muscle load, relieve postoperative muscle fatigue and spasm caused by compensatory effort, buffer layer reduces the friction of skin and hard brace, reduce the risk of skin damage caused by long-term wearing.

The invention discloses a PTB socket model optimization design method and device, electronic equipment and a product, and relates to the technical field of rehabilitation engineering and rehabilitation assistive devices. According to the invention, the inner surface of the artificial limb socket model is divided into a pressure sensitive area and a pressure tolerance area, and a load is applied by simulating the maximum ground reaction force supported by a single leg when a shank amputation patient is assembled with an artificial limb to walk; then, the displacement increment of the grid surface in each pressure tolerance area is iteratively optimized through an optimization algorithm by taking the maximum overall comfort degree of the artificial limb socket model as a target, so that optimization design can be carried out according to individual differences of shank amputation patients, and the conditions of stress concentration of a sensitive area and insufficient support of a tolerance area are avoided; discomfort, pain and even secondary injury brought to the patient suffering from shank amputation are avoided, and the use experience of the patient suffering from shank amputation is improved.

The invention relates to the technical field of rehabilitation engineering, in particular to an automatic double-lower-limb biomechanical balance recovery system which comprises a fixing frame, a lifting table, a scanning mechanism, a main machine and an inner air bag, the lifting table is fixedly mounted on the surface of the fixing frame, and the scanning mechanism is rotationally connected to the side face of the fixing frame; a main machine is fixedly installed on the side face of the fixing frame. According to the method, the accuracy and details of collecting the lower limb data of the user are improved by integrating the three-dimensional scanning technology and the infrared thermal imaging technology. According to the technical combination, preliminary health assessment is more accurate, an abnormal heat area can be captured, and a scientific basis is provided for subsequent pressure regulation and dynamic correction. The pressure of the air bag is adjusted to meet the requirements of the ankle joint and the foot arch, and the responsiveness and the effect of correction measures are improved. And through real-time analysis and application of a thermal imaging result, the correction precision is improved, and the rehabilitation process is optimized, so that the method is more scientific and targeted.

The invention discloses a self-adaptive auxiliary method for an ankle joint orthosis, and relates to the technical field of rehabilitation engineering. Comprising the following steps: S1, acquiring real-time gait data of healthy side and affected side limbs of a patient; s2, assistance is applied to the limb on the affected side based on a set of assistance strategy parameters, a preset quantitative gait quality index is calculated according to the real-time gait data, and the current assistance effect is evaluated; s3, using an automatic optimizer to iteratively update the auxiliary strategy parameters by taking the quantized gait quality index as an optimization target; wherein as progressive processing on the iterative updating in the step S3, the method further comprises the following steps: before the first iterative updating or the initial iterative updating is carried out, carrying out coding learning on the motion trail of the healthy side limb so as to generate an initial value of an auxiliary strategy parameter; and in the iterative updating process, historical optimization data are fused to guide current auxiliary strategy parameter optimization. The invention aims to enable the ankle joint orthosis to be automatically customized for a patient and dynamically optimize an auxiliary strategy.

The invention discloses a variable-rigidity soft prosthetic hand and a using method thereof, and the variable-rigidity soft prosthetic hand comprises a soft simulated hand mechanical body which comprises a rigid-flexible coupling bionic finger group module and a palm module; the rigid-flexible coupling bionic finger set module comprises at least two fingers, and each finger is sequentially provided with a movement cavity and a rigid cavity in the direction from the hand back to the palm. The motion chamber is provided with a corrugated structure and is used for driving fingers to bend; the fiber reinforced layer covers the outer wall surface of the stiffness chamber and is used for adjusting the stiffness of the finger and generating a first direction thrust; one end of the palm module is connected with the rigid-flexible coupling bionic finger group module, and the other end is connected with a limb of a patient; and the pneumatic driving control system is packaged in an inner cavity of the palm module and is connected with an air path in the rigid-flexible coupling bionic finger group module. According to the scheme, the problems that an existing artificial limb is heavy, low in load capacity, high in reset delay and inconvenient to maintain are solved.

The invention discloses a working method of an in-vitro simulation system for reproducing a mechanical microenvironment at an internal arteriovenous fistula, and belongs to the technical field of cell mechanical biology experimental devices for health and rehabilitation engineering. A real wall shear stress waveform is obtained based on clinical blood vessel data of an arteriovenous fistula stenosis patient in combination with computational fluid mechanics simulation, quantitative calculation of shear stress is achieved by means of a fluid mechanics simplified formula of a parallel plate flow cavity, and accurate loading of pulsation, oscillation and other forms of shear stress is adapted by means of quasi-steady hypothesis. The wall shear stress microenvironment of the arteriovenous fistula anastomosis position in different physiological and pathological states can be reproduced in the flowing cavity, and meanwhile, the mechanical and biological response indexes of endothelial cells can be quantitatively monitored in real time. According to the method, the real mechanical microenvironment of the vascular endothelial cells at the arteriovenous fistula is highly restored, and a miniaturized, standardized and quantitative experimental platform is provided for researching the quantitative relation between the wall shear stress signal of the area and the mechanical biological effect of the vascular endothelial cells.

The utility model relates to the technical field of rehabilitation engineering, and disclose a kind of rehabilitation support pad, including limiting component, the limiting component includes limiting plate, sliding block, bolt, clamping block and extension spring, the side of limiting plate is fixedly connected in the side of sliding block, the outer surface of bolt is connected in the inner wall of sliding block with screw thread, and the outer surface of limiting plate is equipped with multiple groups of slot, the outer surface of clamping block is clamped in the inside of slot.The rehabilitation support pad, by the setting of limiting plate, sliding block, bolt, clamping block and extension spring, rotate bolt, take out bolt from the inside of sliding block, and remove the positional relationship between limiting plate and support pad body, while cooperating extension spring and pushing the clamping block inside limiting plate into the inside of moving plate, to contact the connecting relationship between limiting plate and moving plate, and then facilitate staff to carry out quick disassembly and installation to adjusting assembly by the movement of limiting plate.

The invention provides a post-injury rehabilitation tracking system and method based on high-density surface electromyographic signals, and belongs to the technical field of sports medicine and rehabilitation engineering, and the system comprises a synchronous collection module which is used for synchronously collecting the high-density electromyographic signals and joint torque signals; the signal preprocessing module is used for preprocessing the electromyographic signals; the neural decoding module is used for constructing a space-time expansion vector, updating signal statistical characteristics and separating to obtain a discharge sequence of the motion unit; the function evaluation module is used for calculating and optimizing a nerve density index; the rehabilitation decision output module is used for calculating indexes of the indexes and generating personalized training suggestions according to whether the indexes reach the standard or not; and the parameter adjusting module is used for receiving the personalized training suggestions and continuously optimizing the suggestions based on the execution feedback information. And the efficiency, the accuracy and the individuation degree of clinical rehabilitation evaluation and training control are remarkably improved.

The invention provides an intermittent heart rate gating ankle rehabilitation robot system and a training method, and belongs to the technical field of rehabilitation engineering, man-machine interaction and motion control. The training method comprises the steps that real-time heart rate data of a patient is collected and processed, and the maximum heart rate is estimated; parameters such as a double-threshold ratio and a state duration time threshold for switching the high power mode and the low power mode are set; automatically switching a power assisting mode according to the heart rate and the duration time, and triggering a protection mechanism when the heart rate exceeds a safety boundary; multi-type patient physiological models are established in a virtual simulation environment, and optimal PID control parameters are matched; issuing the verified prescription to a rehabilitation execution mechanism for execution; heart rate records are monitored in real time during training, and data of the whole process are traced. According to the intermittent heart rate gating ankle rehabilitation robot system and the training method, people with ankle joints injured or needing rehabilitation are helped to conduct more effective and safer training.

The invention provides a limb dyskinesia recognition and active exercise auxiliary control method based on computer vision, and relates to the technical field of exercise rehabilitation engineering. According to the method, the motion image sequence of the upper limbs and / or the lower limbs of the patient is obtained, the multi-joint three-dimensional coordinates are extracted to form the spatial position data, and the joint angles and the angular speeds are calculated to obtain the joint motion state data. Combining with the torque support evidence, identifying joint angle deviation, angular velocity abnormity and compensation behaviors, generating a dyskinesia identification result containing intention intensity and compensation indexes, and determining target auxiliary joint and auxiliary torque output according to the dyskinesia identification result; and active motion auxiliary control is implemented in modes of joint driving assistance, torque compensation, track amplification or lateral force compensation and the like. According to the invention, fine recognition and self-adaptive assistance of dyskinesia can be realized without additional wearable equipment, and the accuracy and safety of rehabilitation training are improved.

The invention discloses a multi-perception immersive photoacoustic stimulation intervention system and method based on ocean bionics, and belongs to the technical field of rehabilitation engineering, digital medical treatment and man-machine interaction, and the system comprises a global immersive projection module which is used for carrying out projection according to the projection content; the multi-modal sensing fusion module is used for collecting multi-modal data of a user; the photoacoustic stimulation regulation and control module is used for regulating and controlling photoacoustic parameters in the bionic ocean scene according to the photoacoustic stimulation content; and the central control unit is used for generating projection content and photoacoustic stimulation content according to the multi-modal data of the user. According to the invention, a wide-range seamless fusion digital ocean bionic scene can be constructed, high-precision motion capture is realized through the motion sensor and the laser radar equipment, and flexible multi-perception stimulation adjustment is realized by controlling parameters such as light, sound and environment, so that the intervention experience is enhanced, the training effect and the subject compliance are improved, and the training efficiency is improved. And the requirements of clinical rehabilitation training on natural interaction, data acquisition and safety are met.

This invention relates to an elastic actuator and an orthosis with active tightening and passive flexible release, belonging to the field of rehabilitation engineering technology. To address the current issue where orthotic devices, through tension adjustment using corrective wires, cannot achieve passive release when the motor is not running, thus restricting daily activities and failing to meet human-computer interaction needs, this invention comprises a coiled wire and a drive shaft. The coiled wire is fitted onto the drive shaft and can rotate clockwise and counterclockwise around it. The elastic actuator also includes a one-way transmission mechanism with unidirectional transmission function, installed at the ends of the coiled wire and the drive shaft. The drive shaft drives the coiled wire to rotate clockwise via the one-way transmission mechanism, allowing the corrective wire to wind around the coiled wire and be wound up. When the corrective wire provides a driving force for the coiled wire to rotate in the opposite direction, the coiled wire, under the action of the one-way transmission mechanism, is not braked by the drive shaft and can rotate freely in the opposite direction. This invention is mainly used for orthotics of the limbs, torso, and other parts of the human body.

The application relates to the fields of brain-computer interface, rehabilitation engineering and intelligent control technology, and provides a brain-computer interface exoskeleton multidimensional feedback adaptive control method and system. The method comprises the following steps: collecting multidimensional state information containing electroencephalogram features, exoskeleton physical states and current decoding intentions, and constructing a multidimensional state space; detecting an error-related potential automatically triggered by the brain due to the fact that the exoskeleton action is inconsistent with the user intention, and taking the error-related potential as an internal reward signal for correcting the multidimensional state information; inputting physical indexes including joint angles of the exoskeleton into the reinforcement learning intelligent agent, combining electroencephalogram signals and physical end feedback, and reversely optimizing decoding parameters of the electroencephalogram decoder; and optimizing decoding parameters corresponding to the multidimensional state information according to real-time performances of each user, generating a dynamically evolved control logic, and realizing adaptive and personalized control.

This invention belongs to the field of stroke rehabilitation engineering technology, specifically relating to a cross-subject gesture recognition method for stroke patients based on a prototype network and high-density surface electromyography (HD-sEMG). The method includes subject screening and preparation, HD-sEMG signal acquisition, signal preprocessing, macro- and micro-feature extraction, feature dimensionality reduction and standardization, prototype network model construction, data augmentation and signal optimization, and model training and validation. This invention improves feature discriminativeness through macro- and micro-feature fusion; simplifies the Transformer encoder to achieve high-quality feature embedding; utilizes a multi-loss collaborative framework to achieve a dynamic balance between cross-domain generalization and classification discriminativeness; enhances the model's anti-interference ability under small sample conditions through physiological data augmentation and signal optimization; and requires only a very small number of patient calibration samples to achieve accurate gesture recognition, significantly reducing calibration costs in clinical applications. This provides a feasible solution for the clinical translation of intelligent rehabilitation robots and closed-loop rehabilitation systems, promoting the intelligent development of stroke rehabilitation.

The invention relates to the technical field of biological rehabilitation engineering and intelligent medical equipment, and discloses a children oral and facial muscle training compliance monitoring system based on multi-modal sensing, which is used for solving the problems of subjectivity, poor compliance and difficulty in remote monitoring of traditional training. The system comprises a wearable multi-mode sensing unit for acquiring surface myoelectricity, occlusal force, inertial measurement and image data; the AI recognition and compliance evaluation module processes data through a deep learning model to realize action recognition, multi-dimensional compliance scoring and personalized self-learning so as to objectively quantify the training quality; the feedback interaction module provides real-time guidance and instant feedback for the user to improve the degree of participation; and the remote management module is used for doctors to monitor data, adjust schemes and obtain analysis reports. Through objective and quantitative data analysis and intelligent interaction, the standardization level and interestingness of child oral and facial muscle training are effectively improved, efficient remote monitoring and personalized intervention are achieved, and the rehabilitation effect is remarkably improved.

The invention relates to the technical field of rehabilitation medicine and intelligent rehabilitation engineering, and discloses a self-adaptive constant-speed rehabilitation training method based on tissue morphology and electrophysiological signal double feedback. According to the method, muscle group tissue morphology and electrophysiological signals are synchronously collected through high-resolution ultrasound and surface myoelectricity, and muscle structure-function joint representation is constructed through multi-modal time sequence alignment; an adaptive impedance adjusting model is used for dynamically generating individualized constant-speed training resistance, and a joint angular speed closed-loop feedback correction track is combined, so that it is ensured that the resistance is accurately matched with the muscle state under full-range constant-speed movement. Rehabilitation normal form transformation from experience driving to physiological feedback driving is achieved, and training accuracy, safety and individual suitability are improved.

The application discloses a PTB receiving cavity model optimization design method and device, electronic equipment and products, and relates to the technical field of rehabilitation engineering and rehabilitation aids. The application divides the inner surface of a prosthesis receiving cavity model into a pressure sensitive area and a pressure resistant area, simulates the maximum ground reaction force loading of single leg support when a below-knee amputee wears a prosthesis, and then iteratively optimizes the displacement increment of the grid surface in each pressure resistant area through an optimization algorithm with the maximum overall comfort of the prosthesis receiving cavity model as the target, so that the individual differences of the below-knee amputee can be optimized and designed, the stress concentration in the sensitive area and the insufficient support in the resistant area can be avoided, the discomfort, pain and even secondary injury of the below-knee amputee can be avoided, and the use experience of the below-knee amputee is improved.

The invention discloses a tenon-and-mortise type 3D printing multi-material composite bionic ankle-foot orthosis, which belongs to the technical field of rehabilitation engineering and additive manufacturing, and comprises a tibia supporting part, a tenon-and-mortise type locking structure, an ankle joint part, a sole supporting part and an ankle-foot orthosis bandage, the tibia supporting part is of a semi-arc surface structure, the section of the tibia supporting part is gradually reduced from top to bottom, and the tibia supporting part is formed by compositely printing an inner side flexible attaching layer and an outer side rigid layer; the tibia supporting part, the ankle joint part and the sole supporting part are sequentially connected in a transition fit and locking manner through a mortise and tenon locking structure; the ankle joint part is of an approximately L-shaped cambered surface wrapping structure, and a bionic skin microstructure contact layer is arranged on the inner side of the ankle joint part; the sole supporting part is of a U-shaped cambered surface structure, and the section of the sole supporting part is gradually increased from inside to outside; a bionic octopus sucker is arranged on the bottom surface of the inner side, and sole anti-skid lines are arranged on the bottom surface of the outer side; the ankle-foot orthosis bandage is used for fixing the shank and the foot respectively. In conclusion, the invention has great application value in the fields of rehabilitation engineering and medical instruments.

This application relates to the field of neurorehabilitation engineering and discloses a rehabilitation system based on central-peripheral fusion decoding and trajectory closed-loop correction. The system's training subsystem collects EEG signals from the affected side, peripheral electromyography (EMG) signals from the healthy side, and peripheral kinematic signals, constructing a "fusion-type teacher signal" of peripheral EMG and peripheral kinematic signals. A deep learning model is then trained to learn the mapping from EEG signals to this fusion signal. The system's application subsystem, based on real-time EEG signals, simultaneously predicts coordinated EMG patterns and coordinated movement trajectories using the model. The coordinated EMG patterns are used to generate feedforward instructions for functional electrical stimulation to reproduce physiological coordination patterns; the coordinated movement trajectory serves as a dynamic target trajectory, compared with the actual kinematic signals from the affected side, and the trajectory error is calculated to generate feedback correction instructions for functional electrical stimulation. This application achieves natural, precise, and personalized motor assistance.