4489results about "Chiropractic devices" patented technology

The invention discloses an upper limb exoskeleton rehabilitation robot control system and method, and relates to the technical field of rehabilitation robot upper limb control, and the method comprises the steps: collecting multi-modal data such as multi-channel myoelectricity, joint angles, angular velocity and interactive torque; constructing a sliding window feature vector, predicting a next joint angle increment through TCN and Bi-LSTM deep networks, and outputting intention confidence; and based on the confidence coefficient and the muscle fatigue factor, dynamically adjusting an impedance parameter, and combining an impedance control model to generate a power-assisted torque in real time so as to realize power-assisted torque output. By introducing an impedance adjustment mechanism of multi-modal perception, deep time sequence learning and myoelectricity driving, the bottleneck of a traditional upper limb rehabilitation robot in the aspects of intention prediction, parameter adjustment and training individuation is broken through, and the accuracy, safety and active participation degree in the rehabilitation training process are remarkably improved; wide clinical application prospects and industrial transformation values are realized.

Examples of a self-supported device for guiding motions of a target joint of a target body are disclosed. The device comprises a motion generator, a motion transfer system, a target body interfacing system, a load bearing system and a controller. The load bearing system comprises a plate connected to the motion transfer system and a network of joints and links configured to constrain the plate to rotate in three dimensions about a center of rotation of the load bearing system. A position of the center of rotation of the load bearing system being adjustable by adjusting a connection point between the links. The plate of the load bearing system is connected to an adjustable target body interfacing system that is configured to be mounted to the target body. The center of rotation of the load bearing system coincides (or nearly coincides) with a center of rotation of the target joint of the target body.

The invention belongs to the technical field of digital twinning, and discloses a digital twinning rehabilitation robot state monitoring and control system based on the Internet of Things. Multi-dimensional state data such as joint angles, torque output, electromyographic signals and environment temperature of the rehabilitation robot are obtained in real time through an Internet of Things sensor network, a digital twin model is constructed, and hierarchical updating is carried out based on a self-adaptive updating frequency adjustment mechanism. And the system dynamically adjusts the updating periods of the high-frequency updating layer and the low-frequency updating layer according to the change rate of the state parameters and the deviation trend of the prediction response vector, so that accurate synchronization of the digital twin model and the physical system is realized. The state prediction module predicts a future response behavior, the error compensation module generates an error compensation vector adjustment model update and control instruction, and the control module generates an optimization control instruction meeting multiple constraints. The control precision and safety of the rehabilitation robot are remarkably improved, personalized precise rehabilitation is supported, and rapid changes and irregular motions can be effectively coped with.

The invention discloses a brain-computer interface upper limb motion recovery training system, and relates to the technical field of upper limb motion recovery training, the brain-computer interface upper limb motion recovery training system comprises a multi-modal neural signal acquisition module, a combined regulation and control module and a rehabilitation exoskeleton module, the multi-modal neural signal acquisition module is connected with the combined regulation and control module through a wireless Bluetooth protocol, and the combined regulation and control module is connected with the rehabilitation exoskeleton module. The combined regulation and control module is connected with the rehabilitation exoskeleton module through a CAN bus, and the combined regulation and control module is used for synchronously processing fNIRS blood flow signals, tDCS nerve regulation and control parameters and EEG electrophysiological characteristics and generating a closed-loop feedback instruction. By installing the signal fusion unit and the intention analysis unit, time-space complementary fusion of EEG and fNIRS signals is realized, the problem of low precision of traditional single-mode intention recognition is solved, and the motion intention decoding accuracy is 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.

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.

A knee joint rehabilitation apparatus may include a support bar fixed to a height-adjustment bar, the support bar being configured to receive a knee joint posterior; a plurality of pads configured to removably mount to the support bar to adjust an effective outer diameter of the support bar; and a lower leg support connected to the height-adjustment bar, the lower leg support being mounted to the height-adjustment bar so as to allow for changes in an angular position between said lower leg support and said height-adjustment bar.

The invention provides a shank alternating type stretching massage frame and a control system thereof, belongs to the technical field of leg massage equipment, and solves the technical problems that an existing massage frame is single in function, large in transmission gap, obvious in shaking, difficult to give consideration to functionality and safety and the like. Comprising a backrest assembly and a controller, an adjusting assembly is arranged on the front side portion of the backrest assembly, a tendon stretching assembly is arranged at the front end of the adjusting assembly, a foot massage assembly is arranged at the front end of the tendon stretching assembly, the adjusting assembly, the tendon stretching assembly and the foot massage assembly are all electrically connected with the controller, and the backrest assembly, the adjusting assembly, the tendon stretching assembly and the foot massage assembly are all wrapped with outer covering layers. The system comprises a control module, an execution mechanism, an information acquisition module and an active feedback module. The recliner is adopted to guarantee stable operation, double functions of stretching and foot massage are achieved, the adjustable backrest is used for meeting the low-load requirement of people suffering from lumbar disc herniation, a closed-loop control system guarantees that parameters are accurate and controllable, and the use comfort and safety are both considered.

The invention relates to the field of rehabilitation instruments, in particular to an intelligent pneumatic hand function rehabilitation training system which comprises a flexible exoskeleton glove provided with a pneumatic muscle array and used for assisting fingers of a user in grasping training. The fingertip position of the glove is connected with a magnetorheological damper through a flexible cable, and the magnetorheological damper is used for providing dynamic resistance in the training process. The electrical stimulation module is used for activating hand muscle groups in a targeted manner through a surface electrode and enhancing neuromuscular control; the sensor module is used for collecting physiological data of a user in real time; the physiological data comprises electromyographic signals and tissue blood oxygen saturation; the control unit is used for switching training modes, by means of the intelligent air pressure hand function rehabilitation training system, the training intensity can be matched with the real-time ability of a patient all the time, and the rehabilitation training effect is improved.

To provide an apparatus for the treatment or prevention of osteopenia and osteoporosis, stimulating bone growth, preserving or improving bone density, and inhibiting adipogenesis.SOLUTION: A vibration apparatus for treating a subject comprises an actuator configured to generate vibrational energy, a securing mechanism for positioning the actuator upon the body of the subject while maintaining portability of the actuator such that the vibrational energy is directed into an area of the body to be treated, an accelerometer disposed along the securing mechanism, and a controller in communication with the actuator and the accelerometer. The controller is programmed to measure an exposure level of the vibrational energy to the area of the body using acceleration acquired from the accelerometer, and to compare the exposure level with a maximum exposure level such that the exposure level is limited by the maximum exposure level within a predetermined period of time.SELECTED DRAWING: Figure 1

The invention provides a massage control method, a massage chair and a controller applied to the massage chair, the massage chair at least comprises the controller, a massage chair main body, an image acquisition device and at least one massage arm.The method comprises the steps that if it is detected that a user sits stably, the image acquisition device is controlled to acquire a current image of the user; identifying a body model of the user according to the current image; and according to the body type model and the current massage mode, determining an action track sequence of each massage arm, and according to the action track sequence of each massage arm, controlling each massage arm to execute massage. The massage process can cover a wider massage area, the personalized massage path can be automatically generated according to the body shape of the user, the massage fitting degree and comfort degree are improved, the whole body surface of the user is massaged, meanwhile, the personalized adaptation capacity of the massage process is improved, and the user experience is improved. The massage experience of the user in the massage process is enhanced, and the personification of the massage process is improved.

The invention relates to the field of upper limb joint rehabilitation training, in particular to an upper limb joint rehabilitation training method and system based on an exoskeleton mechanical arm, and the method comprises the steps: collecting sEMG signals of a target muscle group of a user in real time in a training process; calculating the root mean square of the amplitude of the sEMG signal in the current time window; if the root mean square is smaller than a muscle force insufficient threshold value, a training mode is switched to a full-assistance mode; if the root mean square is not smaller than the muscle force insufficient threshold value and smaller than the normal muscle force threshold value, the training mode is switched to a semi-assistance mode; if the root mean square is larger than or equal to the normal muscle force threshold value, the training mode is switched to an anti-resistance training mode. The rehabilitation training effect of the upper limb joints can be effectively improved.

The invention relates to the technical field of medical care, in particular to a massage method for avoiding tissue damage through flexible mechanical conduction by Taoist massage, and discloses a massage method named'massage method for avoiding tissue damage through flexible mechanical conduction by Taoist massage '. The invention aims to solve the problems that the existing massage technology is easy to cause tissue damage due to force application rigidity, and the safety, the accuracy and the treatment depth of the massage technology are limited. The method is characterized in that a closed-loop system of tissue stress dynamic dispersion, layer-controlled shear wave guidance and biological impedance coupling feedback is adopted, traditional rigid force is converted into flexible conduction of low-frequency and small-amplitude transverse shear waves, and layer-by-layer, dispersion-type and non-invasive penetration of mechanical energy is achieved. By the adoption of the technical scheme, tissue damage can be effectively avoided, and the deep treatment effect and safety are improved.

A wearable exercise device may obtain a left hip joint angle and a right hip joint angle of a user using at least one angle sensor, process the left hip joint angle and the right hip joint angle to correct a direct current (DC) component of each of the left hip joint angle and the right hip joint angle, determine a first torque value based on the processed left hip joint angle, determine a second torque value based on the processed right hip joint angle, determine one of the first torque value and the second torque value as a target torque value based on movement information of the user, and control a driving module such that a torque based on the determined target torque value is output by the driving module.

An exoskeleton system comprising at least one leg actuator unit configured to be coupled to leg of a user, the leg actuator unit including: an upper arm and a lower arm that are rotatably coupled via a joint, the joint positioned at a knee of the user with the upper arm coupled about an upper leg portion of the user above the knee and with the lower arm coupled about a lower leg portion of the user below the knee, a leg-actuator-unit user interface comprising a plurality of input and feedback elements, and an actuator that extends between the upper arm and lower arms.

A computer-implemented method including receiving, at a computing device, a first treatment plan designed to treat a sexual performance health issue of a user. The first treatment plan comprises at least two exercise sessions that, based on the sexual performance health issue, enable the user to perform an exercise at different exertion levels. While the user uses a treatment apparatus to perform the first treatment plan for the user, the computing device receives cardiovascular data from one or more sensors configured to measure the cardiovascular data associated with the user, and transmits the cardiovascular data. A machine learning model is used to generate a second treatment plan that modifies at least one exertion level, and the modification is based on a standardized measure comprising perceived exertion, the cardiovascular data, and the cardiovascular health issue of the user. The method includes receiving the second treatment plan.

A system for determining, the pressure beneath a compression garment applied around a circumference of a body part, comprises an imaging device to produce image data representing a part of the garment at a measured location and a processing device, arranged to analyse the image data. The processing device uses the data to determine the circumference of the body part at the measured location and a tension in the part of the garment and thus derives a value for the pressure based on the circumference and tension.

The invention discloses a brain-controlled rehabilitation equipment-oriented control strategy generation method, device and equipment and a storage medium, and relates to the technical field of signal processing, and the method comprises the following steps: acquiring a multi-channel electroencephalogram signal, and preprocessing the multi-channel electroencephalogram signal to obtain a target electroencephalogram signal comprising a steady-state visual evoked potential signal and a motor imagery signal, the target electroencephalogram signal corresponds to a preset action category; decoding the steady-state visual evoked potential signal by adopting filter group task related component analysis to obtain a correlation score vector; decoding the motor imagery signal by adopting a Mangban dynamic routing space-time network model to obtain a classification score vector; performing posterior probability distribution conversion and weighted fusion on the correlation score vector and the classification score vector to obtain fusion probability distribution; and generating a target control strategy according to the action category corresponding to the highest probability value in the fusion probability distribution. The control strategy obtained by the invention can consider both intention recognition precision and rehabilitation nerve activation effect.

The invention provides an exoskeleton system assistance control method and device based on a man-machine co-fusion strategy, and the method comprises the steps: collecting basic motion data of a human body and an exoskeleton system through various types of equipment, and initializing the motion state of the exoskeleton system; constructing a man-machine co-fusion kinetic model based on the basic motion data; on the basis of a man-machine co-fusion kinetic model, processing the collected real-time data through an EKF algorithm, and estimating various dynamic parameters of a human body and an exoskeleton system; determining a power-assisted control strategy of the exoskeleton system in combination with the dynamic parameters and a man-machine co-fusion kinetic model, and adjusting the power-assisted control strategy according to the personalized parameters of the user; and controlling the exoskeleton system to execute the adjusted power-assisted control strategy. According to the method, the man-machine collaborative motion intention prediction algorithm is adopted for power assisting control, the power assisting accuracy and flexibility of the exoskeleton system can be improved, and the method can dynamically adapt to individual differences of users.

A telescopic soft silica gel masturbation cup is disclosed, which includes a housing assembly made of a soft silica gel material, where the housing assembly includes an outer housing and a massage body which are integrally formed, and the massage body is a strip-shaped hollow cavity and is arranged in the outer housing; a support assembly detachably arranged in the housing assembly; a transmission assembly arranged in the support assembly; a first magnetic attraction assembly in transmission connection with the transmission assembly; and a second magnetic attraction assembly fixedly connected to the massage body and detachably connected to the first magnetic attraction assembly in a magnetic attraction manner. According to the telescopic soft silica gel masturbation cup provided by the present invention, the transmission assembly and the massage body are fixedly connected through the magnetic attraction effect of the two magnetic attraction pieces.

The invention discloses a cloud intelligent cervical vertebra rehabilitation pillow based on posture induction self-adaptive adjustment and a control method, and relates to the technical field of intelligent home and health monitoring. The method comprises the following steps: calibrating and generating a target steady-state equipotential plane model, wherein the target steady-state equipotential plane model is used for representing a preset mapping relation between a posture load vector of a user and a target support vector; continuously collecting real-time attitude load vectors of the user; determining a target support vector at a current moment based on the real-time attitude load vector and the target steady-state equipotential plane model; and in response to the target support vector at the current moment and a real-time support vector at the current moment, executing a support vector titration operation on a multi-domain pneumatic support matrix so as to drive the real-time support vector to approach the target support vector. The problem that in the prior art, the supporting state is fixed and cannot adapt to sleeping posture changes is solved, and the accuracy and comfort of cervical vertebra supporting are improved.

A support system for a seat includes a suspension coupled to the frame of a seatback. A plurality of pneumatic cells are coupled to the suspension. Each pneumatic cell is expandable and independently controllable to expand between a first position and a second position. A flexible reaction surface covers a forward surface of the plurality of air cells and the reaction plate maintains a smooth transition surface when each of the plurality of pneumatic cells is expanded to the first and second positions.

The invention discloses a hand rehabilitation training device, which belongs to the technical field of medical rehabilitation, and comprises a wearable glove base body, a main body structure, a wrist structure, a multi-mode driving module, a nickel-titanium alloy wire driving unit, a pneumatic driving unit, a sensor detection module, a bending sensor, a myoelectricity sensor and a pressure sensor, the multi-mode driving module comprises a sensor detection module and a wrist structure, the electroencephalogram interaction module comprises a non-invasive EEG electrode and a head band, the self-adaptive control module comprises a control box arranged on the wrist structure, and the self-adaptive control module is electrically connected with the multi-mode driving module, the sensor detection module and the electroencephalogram interaction module through wires and communicates with terminal equipment through a built-in wireless module; according to the hand rehabilitation training device with the structure, flexible adaptation, multi-mode driving, electroencephalogram-sensing closed-loop feedback and intelligent regulation and control of hand rehabilitation training are achieved through cooperative work of multiple modules, and training accuracy and individuation are improved.

The invention discloses a multi-stage control method for a lower limb exoskeleton, is applied to the field of exoskeleton robots, and aims to solve the problem that the design control precision is reduced due to the uncertainty of a model in the prior art. According to the controller designed by the invention, in a high-level control layer, a human body training mode is determined by a motion intention of an operator so as to generate a reference gait track; in the middle control layer, a variable admittance controller is designed, and three training modes of human exoskeleton cooperative movement, namely a passive mode, an active mode and a passive-to-active mode, are planned. In a low-level control loop, a method with a radial basis function neural network estimation function and a fixed-time convergence controller with input dead zone compensation are provided so as to ensure that an exoskeleton joint position tracks an expected trajectory output by an admittance loop. In order to avoid the Zeno phenomenon of the designed controller, an event trigger mechanism is used to determine the execution time of sampling and transmitting signals. Finally, the effectiveness of the proposed control strategy is verified through simulation and experimental results.

The invention discloses an upper limb rehabilitation intelligent self-adaptive system based on multi-modal fusion and MRD-FES cooperation. The system comprises a multi-modal signal acquisition module, a dynamic intention analysis module, a variable damping precise execution module, a neural remodeling strengthening module and a quantitative effect evaluation module. The tDCS-MRD-FES time sequence cooperation protocol is provided, the cortical excitability is improved through tDCS preprocessing, MRD drives training based on intention, FES closed loop strengthens muscle contraction, and vibration tactile feedback is assisted to strengthen sensory movement integration. And the quantitative effect evaluation module further combines a neuroplasticity index and clinical scale digitalization to realize dynamic optimization of training parameters.

Systems, devices, and methods for electrically stimulating peripheral nerve(s) to treat various disorders are disclosed, as well as signal processing systems and methods for enhancing diagnostic and therapeutic protocols relating to the same.

The invention relates to a virtual hand grasping perception and exoskeleton force feedback mapping method based on virtual-real interaction, and belongs to the technical field of virtual reality, the method comprises the following steps: building a hand exoskeleton, and reading joint data in real time; calculating the pose of each joint coordinate system of the virtual hand relative to the virtual world; according to the calculated poses of all the joints of the virtual hand, the virtual hand is driven to synchronously move with the hand exoskeleton in real time; collision and contact events of the virtual hand and the digital object are monitored in real time, and virtual interaction force generated when the virtual hand interacts with the digital object is calculated; calculating feedback torque required to be output by each hand exoskeleton motor of the hand exoskeleton, and driving the motors to output corresponding feedback force through a motor controller of the hand exoskeleton, so as to realize force feedback of the hand. According to the method, the interaction reality sense in the virtual reality application can be enhanced, the user can interact with the virtual environment more naturally in an immersive mode, and the user experience is improved.

The invention discloses an orthopedic rehabilitation hip power exoskeleton posture adjusting system driven by electroencephalogram signals, and relates to the technical field of intelligent motion control. The system comprises a physiological signal processing module, an intention decoding module, an action evaluation module, an action decision module and an instruction generation module. According to the method, electroencephalogram signals and electromyographic signals are obtained in real time and converted into quantized motion intention features, confidence coefficients of the two types of signals are dynamically evaluated, self-adaptive weighted fusion is carried out, a fusion vector capable of reflecting a real intention more stably is formed, the vector is combined with the current physical state of the hip joint, and the motion intention of the hip joint is obtained. According to the method, all the components serve as a decision basis to be input into an intelligent evaluation network, an optimal auxiliary action strategy is output, finally, discrete action decisions are converted into continuous and smooth joint driving instructions through a smooth interpolation algorithm, and conversion from passive execution to active intention driving is achieved. And the man-machine collaboration and the personalized adaptation capability of rehabilitation training are obviously enhanced.

Exemplary task-agnostic exoskeleton control system and method are disclosed that are task-agnostic utilizing instantaneous estimates of biological joint moments from deep neural networks to assist the user movements. The exemplary control system employs multiple body sections and joints in-the-loop estimation to provide multi-joint assistance operation, e.g., within an autonomous, clothing-integrated exoskeleton. The exemplary control system may deploy a deep domain adaptation (DDA) method configured to translate human movement data between a simulated sensor domain and a real sensor domain.