5207results about "Muscle exercising devices" 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 present disclosure provides a foldable small flying and squat rack, which comprises a fixed rack, a pivot rack and pulley blocks disposed on the fixed rack and the pivot rack, wherein the pivot rack can rotate relative to the fixed rack, a counterweight assembly is disposed at the lower part of the fixed rack, and a connecting rope is connected at the upper part of the counterweight assembly; the connecting rope winds around the pulley blocks on the fixed rack and the pivot rack in turn to extend out, and then passes through a flying guide wheel to be connected to a grip part.

The invention relates to a mechanical exoskeleton rehabilitation training system and method based on a brain-computer interface. The system comprises electroencephalogram acquisition equipment, a preprocessing unit, a feature extraction unit, a motion intention decoding unit, a mechanical exoskeleton control unit, a muscular tension state monitoring unit and a self-adaptive functional electrical stimulation feedback unit. The method comprises the following steps: preprocessing electroencephalogram and electromyographic signals; electroencephalogram and myoelectricity time-frequency features are obtained through feature extraction; an electroencephalogram decoding model is used for decoding to obtain the movement intention of the patient, and an exoskeleton control instruction is generated to control a mechanical exoskeleton control unit to drive the limb movement of the rehabilitation patient for rehabilitation training; meanwhile, the muscular tension state of the patient is analyzed according to the time-frequency characteristics of electroencephalogram and myoelectricity, functional electrical stimulation of different intensities is applied in a self-adaptive mode, stimulation feedback is enhanced, and the muscular tension state of the patient is adjusted. According to the invention, deep fusion of brain-controlled exoskeleton training and low-frequency nerve electrical stimulation adjustment can be realized, and the rehabilitation effect of a stroke patient is improved.

The invention relates to the technical field of biomedicine, and discloses a female private rehabilitation training system integrating a breathing method and neural motor control, and the system comprises a data collection module which is used for collecting physiological data of a user; the personalized training scheme generation module is used for generating a personalized nerve-muscle-fascia training scheme; the nerve-muscle synchronous resonance training module is used for constructing a time sequence matching model and generating an adaptive training dynamic control instruction; the space-time adaptability training module is used for adjusting training duration, intensity and stimulation frequency; the multi-dimensional nerve-muscle feedback fusion module is used for constructing a feedback response model; and the fascia synchronous activation and relaxation module is used for coordinating the tension relationship between the fascia and the muscle system. According to the method, feature matching is carried out on an electric activation heat map matrix through the convolutional neural network, analysis of a myoelectricity response state transition probability is carried out in combination with a hidden Markov model, and stimulation parameters and respiratory rhythm are optimized in real time according to a training process.

The present invention relates to a stair stepper, including: a rack provided with two slide rails, each of the slide rails is slidably provided with one pedal component, where the two pedal components form linkage in the form of reverse synchronous movement; and a damping mechanism, including a linear elastic element, where the linear elastic element is straddled between the two slide rails, two ends of the linear elastic element are respectively connected to the pedal components. The linear elastic element expands or contracts with the reverse synchronous movement of the pedal components, to form a changing elastic force, and the changing elastic force acts on the pedal components, to form resistance to the movement of the pedal components.

The invention relates to the technical field of medical rehabilitation, and particularly discloses an anorectal postoperative rehabilitation nursing evaluation method and system based on a sensor. According to the scheme, the system comprises a multi-source physiological information sensing module, a data preprocessing and feature extraction module, a multi-modal data fusion analysis module, a dynamic risk assessment and early warning module and a man-machine interaction and decision support module, multi-dimensional physiological signals are continuously collected, a rehabilitation state index is generated through fusion, the complication risk is assessed in real time, and the rehabilitation effect is improved. Early warning and accurate nursing decision support are realized, and comprehensiveness and timeliness of rehabilitation evaluation are improved.

The invention relates to the technical field of medical treatment, in particular to a child fracture rehabilitation management system based on virtual reality, which comprises a multi-modal sensing and data acquisition module, an intelligent rehabilitation training module, a multi-dimensional evaluation and feedback module and a data intelligent analysis and prediction module, compared with the defects that an existing rehabilitation training technology mainly depends on subjective experience of doctors to formulate a static scheme and lacks multi-source data dynamic feedback, the method comprises the steps that firstly, a comprehensive and accurate patient ability portrait is constructed; intelligent dynamic adjustment of training parameters is realized by utilizing an LSTM gating mechanism, a forgetting gate filters invalid historical data, an input gate fuses real-time action quality evaluation, an output gate generates a personalized difficulty gradient, and a patient ability threshold is continuously memorized in combination with a cell state, so that a training scheme has an adaptive evolution ability, and the training efficiency is improved. The parameter adjustment period of a traditional rehabilitation scheme is compressed from a week level to a real-time level, the accuracy rate of risk prediction of muscle strain and the like is improved, and the utilization rate of effective training time is increased.

A folding mechanism for an armrest handle of a treadmill is provided, including: the armrest handle having left and right bottom ends that are configured to be connected to the treadmill; a rotational assembly, including: a connecting rod, a limiting member being provided on a left section of the connecting rod, and a diameter of the limiting member being greater than a diameter of the connecting rod; a rotation control plate, an arc-shaped sliding groove being disposed on the rotation control plate, one end of the sliding groove being provided with a limiting hole that is in communication with the sliding groove, a width of the sliding groove being greater than a width of the connecting rod and less than a width of the limiting member, and a diameter of the limiting hole being greater than the diameter of the limiting member.

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.

The invention discloses a preparation and measurement method of a polymer-based multi-point force flexible sensor for knee joint pose measurement, and relates to the technical field of polymer-based flexible sensors and soft measurement. The structure of the multi-point force polymer-based flexible sensor shaped like a Chinese character'ao 'is designed for knee joint stress and posture state measurement, and the flexible sensor is prepared and packaged through a silk-screen printing method. A flexible sensor strain input-output knee joint stress data mapping set and a flexible sensor strain input-pose angle output data mapping set required by modeling are completed through a flexible sensor, a thin film force sensor corresponding to multi-point force and an inertial sensor corresponding to pose angle measurement of installed multi-point force polymers. And establishing a neural network soft measurement model based on an MLP algorithm, and carrying out training and verification. And the knee joint pose angle with reliable precision and the maximum stress state of the knee joint are obtained. The sensor has the advantages of being flexible, thin, skin-friendly, high in sensitivity and stable in signal output.

An exercise system includes a base structure including a first cross brace including first cross brace mounting plates disposed at each end of the first cross brace. A pair of base guide rail supports is secured to and extended substantially orthogonal from the first cross brace and includes a pair of base guide rail receivers. A pair of base pulley supports is secured to and extended substantially orthogonal from the first cross brace and further includes a pulley-support pulley housing. A pair of pulley-support pulleys is rotatably secured to the pulley-support pulley housing. A second cross brace includes a central portion substantially parallel to the first cross brace. The central portion is secured to the pair of base guide rail supports and the pair of base pulley supports. Two end portions are disposed at an angle to the central portion and terminate at second cross brace mounting plates disposed at each end of the two end portions and two central-portion pulley housings. A central-portion pulley is rotatably secured to each of the two central-portion pulley housings.

An exercise device comprises a cable, an electromagnetic retraction mechanism for spooling the cable into the exercise device, the electromagnetic retraction mechanism including a shaft, a gear coupled to the shaft, a latch movable between an extended position in which it engages the gear to prevent rotation of the gear in one direction, and a retracted position in which the latch does not engage the gear, an actuator to move the latch to the retracted position when the actuator is powered on, and a spring to move the latch into the extended position when power to the actuator is removed.

The invention relates to the technical field of medical instruments, and discloses a minimally invasive surgery system based on artificial intelligence. Comprising a target identification and positioning module, a multi-mode sensing module, a self-adaptive control module, a man-machine interaction module and a scene adaptation module. The target recognition and positioning module positions an operation target in real time through image recognition and a deep learning algorithm; the multi-mode sensing module collects the stress and movement track of an instrument and physiological signals of a patient. The self-adaptive control module adjusts movement parameters of the instrument according to the data; the man-machine interaction module displays data and provides an operation interface; the scene adaptation module adjusts the instrument form and function according to the operation type. In addition, the system also comprises an operational stability evaluation module, an instrument life prediction module and a biological signal fusion module. The system can achieve precise positioning, real-time monitoring and intelligent control, and the precision, safety and operation convenience of minimally invasive surgery are improved.

The invention discloses a control method, system and equipment of a remote rehabilitation robot, a medium and a product, and belongs to the technical field of robots. The method comprises the steps of obtaining multi-modal data of a patient end, obtaining a time delay prediction value through prediction of a long short-term memory network model, dynamically adjusting admittance parameters of an admittance model according to the multi-modal data and the time delay prediction value, and finally controlling the remote rehabilitation robot according to the dynamically adjusted admittance parameters. According to the method, the admittance parameters of the admittance model are dynamically adjusted in real time based on the time delay predicted value predicted by the long-short-term memory network model and the electromyographic signals of the patient in the multi-modal number, dual adaptation of the network state and the physiological features of the patient is achieved, the admittance parameters are dynamically adjusted through the electromyographic signals, and the change requirement of the complete rehabilitation cycle of the patient is met; admittance parameters are dynamically adjusted through the time delay prediction value reflecting the network time delay state, and the time delay disturbance requirement in the remote communication environment is met.

The invention relates to the technical field of rehabilitation medical treatment, in particular to a rehabilitation instrument motion mode control method and system, and the method comprises the steps: obtaining motion angle data and confrontation moment data of a user; determining whether the deviation between the actual motion track and a preset path exceeds a preset threshold value, determining whether the moment actively emitted by the user presents a continuous attenuation trend, and judging whether the motion performance of the user declines; if it is judged that the athletic performance of the user is reduced, diagnostic mechanical stimulation is applied; collecting mechanical response data; according to the mechanical response data, judging whether a counterforce source is active force reduction or non-autonomous muscle stretching reflex; if yes, the mode of the rehabilitation instrument is switched into a vibration assisting mode and a low-speed movement mode; and if the active force is reduced, switching the mode of the rehabilitation instrument to a force compensation mode. The intelligent rehabilitation instrument has the advantages that the movement mode of the rehabilitation instrument is intelligently adjusted, and the pertinence, safety and effectiveness of rehabilitation training are improved.

A leg exercise assembly includes a stand assembly, a weight carrying member, and a leg extension assembly. The leg exercise assembly is designed to facilitate a modular unit that is operable separate from other workout equipment. A user can use the leg exercise assembly by placing his weight on a base of the stand assembly. The weight carrying member includes a shaft and a weight post. The weight post is coupled to the shaft and is configured to carry weights. The shaft is pivotally coupled to the post. The leg extension assembly is pivotally coupled to the shaft of the weight carrying member and is releasable so as to be selectively oriented on the shaft to allow for the performance of different exercises.

The invention relates to the technical field of intelligent medical treatment, and discloses an intelligent knee joint rehabilitation system based on Internet of Things, comprising: a flexible multi-parameter sensing module for collecting a multi-modal biological signal of a knee joint; the edge calculation module is used for processing and analyzing sensing data in real time; the dynamic impedance adjusting module is used for dynamically adjusting impedance parameters of rehabilitation training according to the real-time data; the cloud-side collaborative decision module is used for realizing efficient transmission and collaborative decision of data; and the self-adaptive rehabilitation strategy engine is used for optimizing rehabilitation training parameters and comprises a real-time intensity adjustment module based on an improved TD3 reinforcement learning algorithm. According to the system, the flexible strain sensor array unit, the 9-axis inertial measurement unit and the surface myoelectricity sensing unit are integrated through the flexible multi-parameter sensing module, and multi-dimensional real-time monitoring of knee joint strain distribution, three-dimensional acceleration, angular velocity, magnetic field data and myoelectricity signals is achieved.

The invention discloses a high-compliance impedance training method and system based on self-adaptive visual servo control and application of the high-compliance impedance training method and system. The training method comprises the steps that historical pose data and historical contact stress data are collected; performing feature processing to obtain stress pose information and generate a corresponding pose mapping relation; constructing a dynamic mapping model associated with the muscle force, the contact stress, the training track and the impedance parameters in combination with the stress pose information and the pose mapping relation; acquiring rehabilitation training information of a current patient, and generating and optimizing a preliminary expected trajectory; calculating deviation data of the real-time trajectory and the expected training trajectory; and an impedance adjusting model is constructed, the input of the impedance adjusting model comprises the deviation data and the real-time contact stress data, and the output of the impedance adjusting model is the impedance adjusting quantity. According to the invention, through visual real-time feedback, fuzzy PID adaptive adjustment and multi-feature fusion modeling, impedance adjustment training with better dynamic adaptability, higher safety, higher flexibility and high personalized precision can be realized.

The invention discloses an urban rail vehicle simulation driving training method and system based on scene simulation, and belongs to the technical field of driving simulation, and the method specifically comprises the steps: collecting rail line parameters, weather data, passenger flow density, vehicle equipment state and driving data in real time, carrying out the preprocessing, constructing a dynamic personalized simulation scene, and simulating driving operation. According to operation of a driver and a preset simulation scene, micro features of eye-brow areas of the driver are recognized, the psychological stress of the driver is analyzed in combination with historical data, the simulation scene is dynamically adjusted according to a psychological stress analysis result, the performance of the driver in the training is scored according to a preset evaluation standard, and a detailed training report is generated. According to the method, pressure analysis is carried out on the eyebrow area, pressure evaluation is carried out in combination with the physiological dimension, the pressure of the driver in a simulation scene can be judged in real time, different simulation scenes are provided for different drivers, and the training effect is greatly improved.

A personal exercise device with a cable and resistance mechanism comprises a sensor arrangement configured to detect two orthogonal angles to define a trajectory of the cable extending in a 3-dimensional space during use. The sensor arrangement comprises a pulley to direct the cable as it extends from the device during use, a cable follower through which the cable passes, the cable follower pivotally mounted to pivot about a first pivot axis and about a second pivot axis, the second pivot axis orthogonal to the first pivot axis, and wherein the first pivot axis is collinear with a rotational axis of the pulley, and one or more sensors configured to detect pivoting of the cable follower about the first and second pivot axes and provide one or more outputs indicative of the two orthogonal angles to define the trajectory of the cable extending in the 3-dimensional space.

The invention discloses an intelligent oral snore-ceasing equipment system based on multi-parameter monitoring, and relates to the technical field of intelligent oral snore ceasing. According to the system, physiological data and structural data of a user are collected through a data collection module, and a physiological and structural data set is constructed; the AI dynamic evaluation model module trains an initial model by using a convolutional neural network, continuously optimizes the model and dynamically predicts the snoring symptom risk of an individual by analyzing physiological and structural data; the physiological monitoring module monitors the physiological status of a user in real time, calculates a physiological stability index PSI, judges whether sleep is abnormal or not by combining with a threshold Q1, and adopts an intervention strategy if the sleep is abnormal; the airway disturbance monitoring module judges abnormal breathing by calculating a breathing disturbance coefficient HXY and combining with a threshold Q2, the sleeping posture monitoring module calculates a sleeping posture airway compression coefficient PSRF and combining with a threshold Q3 to judge whether the sleeping posture is reasonable, and if not, a strategy is provided; according to the system, personalized and precise snore stopping intervention can be realized.

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

The disclosed system for interacting with objects in an extended reality (XR) environment generated by an XR system may include (1) neuromuscular sensors configured to sense neuromuscular signals from a wrist of a user and (2) at least one computer processor programmed to (a) determine, based at least in part on the sensed neuromuscular signals, information relating to an interaction of the user with an object in the XR environment and (b) instruct the XR system to, based on the determined information relating to the interaction of the user with the object, augment the interaction of the user with the object in the XR environment. Other embodiments of this aspect include corresponding apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the methods.

The invention provides hybrid power fitness equipment. The hybrid power fitness equipment comprises a tension assembly; the driving motor and the resistance device are matched through a one-way bearing; the tension assembly is in transmission connection with the one-way bearing through the transmission assembly, when the tension assembly is in a first resistance training state, the resistance device and the driving motor are in transmission connection with the one-way bearing, and the resistance device provides resistance for tension resistance; when the tension assembly is in the second resistance training state, the resistance device and the driving motor are in transmission connection with the one-way bearing, and the resistance device and the driving motor jointly provide resistance for the tension assembly; when the tension assembly is in a tension recovery state, the driving motor is connected with the one-way bearing to provide recovery force for the tension assembly, and the recovery force and resistance are provided on the premise of low-cost improvement by using the resistance device and the driving motor at the same time. The contradiction between the one-way resistance experience bottleneck of a resistance training assembly in the prior art and the cost of traditional two-way force equipment is solved.

The present disclosure provides a method for performing a treatment plan, wherein the method comprises: receiving first patient data, wherein the first patient data includes at least a first patient identifier associated with the first patient and a first treatment plan; receiving second patient data, wherein the second patient data includes a second patient identifier associated with the second patient and a second treatment plan; receiving first measurement data associated with a first performance level of the first treatment plan by the first patient; receiving second measurement data associated with a second performance level of the second treatment plan by the second patient; determining differential data, wherein the determining is based on a contrast of the first or the second measurement data or first or second patient data; and generating, based on the differential data, an instruction to modify an operating state of the treatment apparatus.

A multifunctional fitness pad comprising an attachment part, a support part, and a leg exercise part, wherein the support part is pivotally connected to the attachment part to change the support angle for users; and the leg exercise part provides a leg exercise function.

In all applications of force, all components, internal or external, moving or otherwise, have inertia associated with their mass and geometry. The inertia of the components, internal or external, moving or otherwise, is detrimental to the precision and / or accuracy of the force being applied by and / or to the system, whether the force is applied internally or externally to the system. A motorbased system and / or a method involves mitigating and / or reducing force errors caused by the inertia of the components, internal or external to the system, moving or otherwise, in systems built for the application of force, the forces being internal or external to the system. This is achieved, in part, by addressing the inertial effects of components in the load-application path, including a motor and / or other force-generating devices, force transmitting elements, and carriers of force between a motor and those elements that contribute to force error due to inertial effects.