53 results about "Plantar pressure" patented technology

This invention relates to the field of sports health monitoring technology, and more particularly to a method for monitoring the health status of users based on a treadmill. The method includes: acquiring plantar pressure distribution signals, treadmill belt micro-vibration signals, and drive torque response signals during the user's running process, and synchronizing these signals in time to form a raw signal set that reflects the dynamic coupling characteristics between the treadmill and the human body. In this invention, by simultaneously acquiring plantar pressure distribution signals, treadmill belt micro-vibration signals, and drive torque response signals during running, and synchronizing these signals in time, effective decoupling of mechanical vibration components and gait vibration components is achieved. Finally, a cardiovascular dynamic prediction network is constructed for health status assessment and adaptive adjustment of the monitoring strategy. This improves upon the problem that traditional health monitoring systems, which mostly use a single signal acquisition method, suffer from low accuracy in health assessment due to their inability to dynamically adapt to changes in the user's state.

This invention relates to the design and fabrication method of a flexible sensor array for plantar pressure monitoring. The flexible sensor array includes a first sensing unit and a second sensing unit. The first sensing unit is applied to the 1st metatarsal region, the 2nd-5th metatarsal regions, the medial heel region, and the lateral heel region. The second sensing unit is applied to the 1st metatarsal region, the 2nd metatarsal region, the 3rd metatarsal region, the 4th metatarsal region, the 5th metatarsal region, and the midfoot region. By optimizing the size, number, and distribution of the sensing units, complete representation of plantar pressure information is achieved, effectively solving the problem of low resolution and insufficient representation of plantar pressure information in existing sensors. A swelling process is used to enhance the interface of the quasi-homogeneous materials of the sensor, improving the interface stability and reliability of the sensor. The fabrication method of the plantar pressure monitoring sensor array of this invention has the advantages of low cost, easy mass production, and easy large-area expansion.

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.

The application discloses a kind of multi-source fusion perception systems for exoskeleton robot, belong to robot technical field, system includes:foot bottom pressure acquisition module, is laid in exoskeleton foot component;Inertial measurement module, is laid in exoskeleton limb bar piece;Motor feedback module, is integrated in exoskeleton driving joint;Central processing unit is connected with each module, for receiving and processing multi-source data, method includes: by foot bottom pressure dynamic threshold algorithm real-time determination gait switching point;Fusion inertial measurement data and motor feedback data, carry out limb posture solution and man-machine interaction moment estimation;Based on the redundancy check of multi-source data realizes fault monitoring and safety control.The application solves the problems of high gait recognition delay, poor environmental adaptability and insufficient man-machine interaction transparency in the prior art through deep coupling and synchronous perception of mechanical and kinematic data, and realizes accurate, robust and real-time perception of the wearer's movement intention.

The application discloses an integrated flexible pressure gait monitoring system and a preparation packaging method, relates to the technical fields of wearable flexible sensing and gait monitoring, and comprises a flexible array distributed pressure sensor, a miniaturized signal acquisition circuit module, a battery module and special shoes. The flexible array distributed pressure sensor comprises, from top to bottom, a pressure-sensitive layer, an adhesive layer and a flexible electrode which are laminated in sequence, the flexible array distributed pressure sensor is in the shape of an insole and is laid flat on the inner surface of the shoe sole of the special shoes, the miniaturized signal acquisition circuit module is electrically connected with the flexible electrode, and the battery module is electrically connected with the miniaturized signal acquisition circuit module. The application adopts the above-mentioned integrated flexible pressure gait monitoring system and preparation packaging method, improves product consistency and facilitates large-scale production; the interdigital electrode array greatly improves the plantar pressure resolution and can accurately capture local pressure abnormalities; the integrated microcircuit and the special shoes realize wireless transmission and convenient wearing.

1. Name of the product in this design: Foot pressure measuring device. 2. Purpose of this design: This design is used for the detection of plantar pressure. 3. The key design feature of this product is its shape. 4. The picture or photo that best illustrates the key design points: Design 1 3D diagram 1. 5. Design 1 is designated as the basic design.

The application provides a lower limb muscle strength prediction and balance function evaluation method based on plantar pressure and spatial pose fusion, comprising: collecting plantar pressure data, lower limb spatial pose data and human individual physiological parameters of a subject, and combining a force platform to obtain ground reaction force data; real lower limb muscle strength is calculated by using inverse dynamics and Hill muscle model, and a plantar pressure + spatial pose-lower limb muscle strength data set is constructed; the optimal sensor quantity and layout are obtained by combining a heuristic optimization algorithm and a machine learning regression model, taking prediction accuracy and information redundancy as indexes; a deep forest model is trained based on fusion features, real-time prediction of hip joint, knee joint and ankle core muscle group muscle strength is realized; further, muscle strength symmetry analysis, weak muscle group identification and hip-knee-ankle force ratio analysis are completed, and multi-dimensional quantitative evaluation of balance function is completed. The method can realize high-precision lower limb muscle strength prediction under limited sample conditions, and output multi-dimensional balance function evaluation results.

The application discloses a wearable human gait analysis system, comprising a synchronous data acquisition module, a plantar pressure topology graph module, a pre-training model module, a real scene model module and a pathological gait classification model module; the synchronous data acquisition module collects real force platform data, insole pressure time series data and inertial measurement unit data, and constructs a gait data set; the plantar pressure topology graph module topologically expresses the insole pressure time series data, and outputs a plantar pressure topology graph corresponding to a time sequence based on the insole pressure time series data; the pre-training model module constructs a pre-training model based on a gait data set and a space-time feature fusion network to output a gait dynamics prediction result; the real scene model module performs target domain semi-supervised self-adaptive fine-tuning on the pre-training model to generate a real scene model; and the pathological gait classification model module extracts multi-domain classification features based on the prediction results of the real scene model of each subject in a pathological state, and outputs a final classification result.

A 3D personalized shoe pad variable density lattice structure design method based on multi-source data, first, the three-dimensional data of human foot is collected, and the top surface and bottom surface of the shoe pad are created in the modeling software; the distance between the top surface and the bottom surface of the shoe pad is adjusted, and the uniform Twisted Box frame structure is generated according to the thickness of the shoe pad; the plantar pressure data of the human body in the resting state is collected, and the pressure cloud chart is generated; the pressure cloud chart is imported into the programming software, the pressure gray value interval is divided, the pressure peak interval is screened to generate the interference point group; the interference point group is mapped to the top surface of the shoe pad, and the non-uniform Twisted Box frame structure with pressure gradient-variable density characteristics is regenerated; the porous cell unit is used as the shoe pad hollow lattice structure, and the non-uniform Twisted Box frame structure is filled to generate the variable density lattice structure of the shoe pad; the 3D printing variable density lattice structure shoe pad has the technical advantages of interactivity and customization.

The present application relates to the technical field of intelligent monitoring, in particular to an old people fall monitoring and early warning method and system based on multi-source information fusion, the system comprising a visual perception module, a wearable sensing module, a central processing unit and an early warning module. The method is as follows: collecting human posture video stream, human waist three-axis acceleration and three-axis angular velocity, foot pressure, heart rate and blood oxygen physiological data in the monitoring area; respectively analyzing visual posture information, inertial sensing and foot pressure data, and extracting key motion features; comprehensively analyzing the features of the three types of information sources, especially using the MediaPipe framework to efficiently analyze human posture, combining with wearable sensor data, adopting a multi-modal feature fusion strategy based on attention mechanism, improving the accuracy of multi-source information fusion, so as to accurately judge the stability of the current posture of the old people and the fall risk level, and timely trigger the early warning, improving the accuracy and safety of the monitoring.

This application relates to the field of postoperative rehabilitation assessment technology, and discloses a method for dynamic gait parameter detection, evaluation, and analysis in lower limb postoperative rehabilitation. This method simultaneously acquires acceleration, angular velocity, and plantar pressure sequences; uses plantar pressure to define the double support phase and generates a support phase impact gradient sequence; extracts full-plantar impact events for zero-velocity updates, inversely compensates for inertial sensor integral closure errors, and calculates the interlimb energy transfer ratio; constructs a dynamic weighted envelope using the support phase impact gradient, and performs dynamic weighted cross-correlation calculations on angular velocity within an extended data extraction buffer window to extract intralimb phase coupling delay; constructs a two-dimensional phase plane with energy transfer ratio and phase coupling delay as coordinate axes, analyzes the spatial geometric relationship between the current state point and the historical baseline, and calculates the compensatory attenuation index. This method eliminates integral drift, extracts the transient characteristics of the weight-bearing phase, and achieves an objective quantitative assessment of the patient's lower limb rehabilitation evolution trajectory.

The application provides a neural disease diagnosis device based on fusion information and belongs to the technical field of auxiliary diagnosis, and specifically comprises: a gait acquisition module, a plantar pressure acquisition module, an electroencephalogram signal acquisition module and a result output module. The result output module is responsible for determining the disease probability of a patient according to the time length of an evaluation period, the gait comprehensive similarity in the evaluation period, the pressure comprehensive similarity and the electroencephalogram characteristic quantity, and when the disease probability is greater than a preset probability, the presumed diagnosis result of the neural disease of the patient and the credibility of different presumed diagnosis results are obtained through the gait characteristics, the plantar pressure characteristic quantity and the electroencephalogram characteristic quantity of the patient in the evaluation period, so that the efficiency and accuracy of disease diagnosis are improved.

This invention relates to the field of medical safety protection equipment and discloses a medical shoe with an emergency alarm function, addressing the problems of existing shoe-mounted alarm systems being prone to false alarms under complex gait and missed alarms under weak emergency movements. The shoe includes a shoe body and a built-in processing module. By collecting foot pressure and movement state data, it determines whether the user is stationary. If not stationary, it calculates the ground hardness index and performs impact compensation on the pressure center trajectory. Subsequently, it extracts the action time window, calculates the trajectory fractal dimension, action consistency coupling characteristics, and macroscopic motion intensity characteristics. These characteristics are then normalized and weighted to form a discrimination index, which is compared with a dynamic decision threshold range. If the index exceeds the threshold, it is determined to be a valid alarm action, and an alarm command is output simultaneously. This invention improves alarm accuracy and concealment, making it suitable for medical personnel to quickly and discreetly seek help when facing threats.

The application discloses a kind of intelligent health assessment and physiotherapy system and method for Chinese medicine physiotherapy shop.The method is by collecting the multi-modal health data such as tongue image, face image, body posture, gait, plantar pressure of user, according to national standard to build digital mapping of meridian and acupoint, realize individual acupoint positioning and path planning.The system contains intelligent massage head and moxa control temperature box, can real-time collect the parameters such as intensity, pose, temperature, distance of operation process, and combine with sleep monitoring data.Based on the above data, multi-modal fusion analysis is carried out, and the health assessment and physiotherapy scheme containing recommended acupoint, massage and moxa parameters is automatically generated, and safety control and record are carried out during physiotherapy process.Finally, closed-loop optimization of pre-treatment evaluation, treatment monitoring, post-treatment retest and sleep follow-up is formed, to solve the problems of subjective evaluation of Chinese medicine physiotherapy, unquantifiable process, safety dependent on experience and difficult to objectively evaluate the efficacy, and to improve the standardization and safety of physiotherapy service in the shop.

The application belongs to the field of cross and fusion of material science, flexible sensing technology and electronic information technology, and discloses a preparation method and application of a lithium aluminum iron layered double hydroxide reinforced nano conductive hydrogel strain sensor. A plurality of synergistic networks are constructed through an in-situ polymerization process, so that the strain sensor has excellent flexibility, high mechanical strength (tensile breaking strain ≥ 1875%, breaking strength ≥ 435 kPa) and excellent sensing performance (tensile sensitivity GF = 4.82, sensitivity S = 0.107 kPa-1 in a pressure range of 0-7.5 kPa), and the response is fast (tensile ≤ 150 ms, compression ≤ 180 ms) and long-term stable (signal stability rate ≥ 95% after 3000 cycles). The sensor can be assembled into a flexible array sensor and a foot pressure sensing intelligent insole, a matching APP can realize real-time visualization of foot pressure distribution, evaluate a motion state and provide health suggestions, and the application of the flexible wearable device in motion monitoring and disease prevention is expanded.

The embodiment of the application provides a kind of based on gait capture and counteracting imitation learning exoskeleton assisting method and system, belong to exoskeleton robot intelligent control technical field.The exoskeleton assisting method includes: obtaining the gait original data that human lower extremity IMU and plantar pressure sensor are synchronously collected in free walking state, obtain multi-modal natural gait original feature data;Multi-modal natural gait original feature data is input into human lower extremity dynamics model, and human original joint torque sequence is obtained;Natural gait expert demonstration set of "state-action" pair is constructed;The exoskeleton assisting control model of counteracting imitation learning is constructed, and the model of training completion is deployed to exoskeleton embedded real-time controller.The application improves the assisting efficiency of exoskeleton robot, wear comfort, individual adaptation speed and complex scene generalization ability, provides safe, efficient, high adaptability man-machine collaborative control method for load assisting, movement function rehabilitation training and other scenes.

This invention provides a method for predicting knee joint torque based on plantar pressure characteristics. By collecting and processing gait and plantar pressure data, gait information data is converted into knee joint torque data, thereby constructing a neural network model of plantar pressure information data and knee joint torque data. The model is trained using one of three methods: task-focused, subject-focused, or combined. This allows the predicted value of knee joint torque to be obtained simply by inputting plantar pressure information data. The prediction method of this application has achieved excellent prediction accuracy in experimental verifications at three months, six months, and one year postoperatively.

This invention discloses a humanoid robot motion adaptive learning system, relating to the field of robot control technology. It includes the following steps: during the humanoid robot's movement, collecting foot pressure distribution data, ground friction coefficient data, ground texture images, and body posture data; performing feature fusion processing on the foot pressure distribution data, ground friction coefficient data, and body posture data to obtain a comprehensive feature vector of ground conditions; constructing a condition database and determining the current condition based on the ground condition feature vector; generating gait parameter correction instructions based on the current condition, and controlling the humanoid robot to correct its gait according to the gait parameter correction instructions. This invention can accurately locate the current condition, dynamically adjust the correction coefficient by combining the current control parameter deviation value and texture features, providing precise adaptation and local fine-tuning for gait parameters, and achieving stable gait control of the humanoid robot in scenarios with sudden changes in ground conditions and local differences within the same condition.

The application relates to the field of motion capture technology, and particularly discloses a martial art motion recognition method based on motion capture, which comprises the following steps: acquiring original motion capture data of a user at a current sampling moment; generating a reference plane based on plantar pressure distribution data; classifying pixel points in a depth image according to the spatial distance between the pixel points and the reference plane, extracting a pixel point set D belonging to the user's body entity after classification, calculating the vertical projection contour of the pixel point set D on the reference plane, and marking the vertical projection contour as a real limb contour; generating a posture snapshot at the current moment based on the real limb contour and joint coordinate data; comparing the posture snapshot with a pre-stored standard martial art motion template library, and outputting the martial art motion name at the current sampling moment and the deviation between the posture snapshot and the standard template. The application improves the motion recognition accuracy in a home exercise scene.

The application discloses a kind of foot balance evaluation method and system based on multi-region pressure distribution.It relates to human balance function evaluation technical field.It includes: step 1: the pressure data of foot bottom multi-region is collected;Step 2: the collected pressure data is denoised, filtered, corrected and preprocessed;Step 3: the spatial features and time series features of preprocessed pressure data are calculated, respectively generate foot pressure heat map and multi-region pressure time series matrix;Step 4: the spatial features are extracted by inputting pressure heat map into CNN model, and the time series features are extracted by inputting multi-region pressure time series matrix into LSTM model, and the spatial features and time series features are fused;Step 5: according to the obtained fusion features, output balance evaluation result.The application can simultaneously capture the spatial static distribution and time series dynamic change characteristics of foot pressure, fill the information gap and avoid the evaluation deviation caused by missing key dimensions.

This application belongs to the field of medical devices and protective equipment, specifically involving a design method and layered structure for an enhanced mouthguard based on musculoskeletal stability optimization. The method includes: collecting multimodal data such as the full dentition morphology, jawbone structure, mandibular movement trajectory, surface electromyography, and plantar pressure of the subject; constructing a correlation system between mandibular position and overall stability using a radial basis function neural network; setting anatomical boundaries, joint spaces, and muscle symmetry constraints; and using a genetic algorithm to iteratively optimize and lock in a personalized musculoskeletal stability position; based on this, performing layered digital design of the mouthguard's flexible base layer and posterior tooth retention components, and then 3D printing manufacturing. This application, through precise optimization of jaw position, achieves a leap from passive protection to actively enhancing body stability in sports mouthguards, significantly improving exercise efficiency and wearing comfort while ensuring physical protection.

This invention provides a gait analysis-based walking stability assessment and early warning system for disabled elderly individuals, belonging to the field of geriatric health monitoring technology. It includes a data acquisition unit for collecting plantar pressure data, limb posture data, and global motion data during the walking process of disabled elderly individuals. This invention identifies trends of declining stability before falls occur through real-time assessment of gait characteristics, achieving proactive early warning rather than passively responding to fall events. This invention is based on an individual gait baseline for assessment, adapting to individual differences among disabled elderly individuals, avoiding assessment errors caused by universal standards, and reducing false alarms and false negatives. This invention combines the advantages of wearable devices and millimeter-wave radar, ensuring both detailed local gait acquisition and coverage of global motion states, reducing environmental interference and blind spots. The combination of millimeter-wave radar and flexible insoles avoids the privacy risks of video surveillance and is suitable for everyday home use.

The application relates to the technical field of intelligent monitoring, and particularly discloses a pet health AI monitoring system for a washing and grooming process based on an intelligent sensor. The system comprises an intelligent load-bearing sensing array integrated in a washing and grooming workbench, a non-contact multi-modal physiological sensing module, an edge computing and fusion processing unit, and a health state evaluation and early warning module. Through multi-modal data fusion, dynamic motion interference filtering, and abnormality detection and trend analysis, real-time synchronous monitoring of pet heart rate, respiration, blood oxygen, and foot pressure distribution and health risk early warning are realized. The system deeply integrates the high-density intelligent load-bearing sensing array and the non-contact multi-modal physiological sensing module, and constructs an integrated sensing system capable of synchronously and continuously collecting vital signs and foot load-bearing states during the dynamic washing and grooming process of the pet.

The application relates to a lumbar force line dynamic monitoring and visual feedback system based on foot pressure sensing, relates to the field of intelligent medical rehabilitation apparatuses and wearable devices, and comprises intelligent shoes and a mobile terminal. A pressure sensor array in the intelligent shoes acquires dynamic pressure distribution data of each region of the foot bottom in real time, sequentially transmits the data to a microcontroller after signal acquisition through a multiplexing switch, signal amplification through an instrument amplifier and analog-digital conversion through an analog-digital converter, and sends the pressure distribution data to the mobile terminal through a wireless communication module after processing by the microcontroller. An alarm execution unit receives a control instruction sent by the microcontroller and issues an alarm prompt. A rechargeable lithium battery supplies power for the system, and a power management module provides a stable working voltage for the system. The application converts lumbar load risk into a visual image of foot pressure distribution through foot pressure sensing, realizes home, dynamic and non-invasive monitoring of the lumbar load and instant posture intervention.

The application discloses a lower limb training rehabilitation method and system for orthopedic nursing, and the method comprises the following steps: collecting plantar pressure distribution data of a patient's lower limbs when walking, and extracting gait stability features according to the moving track of the pressure center; inputting the gait stability features into a gait analysis model, and combining real-time electromyographic signals to generate a joint load distribution atlas; calculating the training intensity coefficients of each muscle group based on the joint load distribution atlas through an adaptive adjustment algorithm; generating neuromuscular stimulation parameters according to the training intensity coefficients, and outputting electric stimulation signals with corresponding intensity; and fusing the electric stimulation signals and the gait stability features to generate a personalized rehabilitation scheme containing training duration, intensity gradient and rest interval. By using the embodiment of the application, the rehabilitation effect can be improved, the recovery period can be shortened, and the medical risk can be reduced.

The utility model belongs to the insole technical field, and disclose a kind of arch support insole, including insole body, and insole body is made of zoned density PU foam, and insole body is provided with antiskid line, heel cushioning structure, forefoot cushioning air bag, dynamic support sheet and breathable antibacterial fabric covering insole body surface layer, dynamic support sheet is embedded in insole body inside, it includes core support section and the stable transition section integrally formed with core support section, heel cushioning structure includes the heel silica gel pad that is attached to the heel position of insole body, by above-mentioned scheme, it has solved the existing arch support insole although having certain softness, but lack enough supporting force, for flatfoot population, since arch collapse, foot bottom pressure distribution is uneven when walking normally, forefoot and heel bear excessive pressure, and traditional insole cannot provide effective arch support, long time wearing can lead to foot muscle fatigue, pain, and possibly cause plantar fasciitis and other diseases.

The present application relates to the technical field of fall identification, and discloses a fall early warning and adaptive protection system based on waist-foot causal chain perception, which comprises the following steps: acquiring inertial sensing data and plantar pressure data of the waist and both feet, extracting unilateral plantar pressure distribution tensor and change rate after individual time scale normalization; combining a human motion chain to establish a waist centroid proxy state, and dynamically estimating a causal kernel from the plantar state to the waist state; extracting a causal phase compression rate of the foot load boundary to the waist swing in this way; then compensating the available bound loss of the support margin of the external centroid by using the causal phase compression rate; and finally outputting a warning determination according to the positive and negative support margin after compensation. The present application can effectively identify early instability caused by the deformation hysteresis of the bottom contact surface, effectively prolong the alarm response time, and is suitable for daily monitoring of variable ground and different populations.

The application relates to a posture recognition and posture evaluation method based on a wearable device and relates to the field of human posture detection. The method solves the problems of strong subjectivity, insufficient data dimension and limited evaluation accuracy of traditional posture evaluation which depends on manual observation or a single sensor. The method is as follows: a plurality of parts of an inertial measurement unit and a flexible plantar pressure sensor array are deployed and synchronously collected, time synchronization and other treatments are carried out, time windows of each action are determined by taking a sudden change point of a plantar pressure sequence as an event anchor point, a fusion feature vector is constructed, a deep evaluation is carried out in combination with a fusion feature vector for identifying a motion posture and a preset biomechanical model, differences between an action of a wearer and a standard action or a personal action feature baseline are quantified, and finally a personalized improvement report is generated. The method can be applied to the fields of football, volleyball, tennis and other sports evaluation fields, the fields of posture evaluation, motion control and intelligent manufacturing of industrial robots and man-machine cooperation.

The utility model discloses a kind of foot ankle pressure detection devices, it is related to pressure detection technical field, including shoe body, tongue and sole, the foot wrist of shoe body is provided with flexible pressure sensor.The foot ankle pressure detection device disclosed in the utility model has by being provided with flexible pressure sensor, the flexible pressure sensor on sole is set at the two sides of upper and the lateral side of little toe of toe, so that it can not only gather plantar pressure data when walking, but also detect the pressure data of ankle extrusion shoe body, tongue, so that data acquisition is more accurate, so as to assist doctor to evaluate the result of foot ankle injury rehabilitation and provide part data effect for treatment scheme.