30 results about "Gait speed" patented technology

A device comprised of at least a pair of accelerometers and a tilt sensor mounted in fixed relation to a datum plane defining surface (sole of a shoe) may be used for extracting kinematic variables including linear and rotational acceleration, velocity and position. These variables may be resolved into a selected direction thereby permitting both relative and absolute kinematic quantities to be determined. The acceleration is determined using a small cluster of two mutually perpendicular accelerometers mounted on a shoe. Angular orientation of the foot may be determined by double integration of the foot's angular acceleration (which requires a third accelerometer substantially parallel to one of the two orthogonal accelerometers). The two orthogonal accelerations are then resolved into a net horizontal acceleration or other selected direction which may be integrated to find the foot velocity in the selected direction. The average of the foot velocity corresponds to the subject's gait speed.

A prosthetic knee provides a single axis of rotation and includes a hydraulic damping cylinder, a microprocessor, and sensors. Based on input from the sensors, the microprocessor selects a flow path within the hydraulic cylinder in order to provide the proper amount of knee resistance to bending for a given situation. The resistance of each flow path within the hydraulic cylinder is manually preset. Changes in gait speed are accommodated by employing a hydraulic damper with intelligently designed position sensitive damping. Moreover, the knee need not be un-weighted to transition from the stance phase to the swing phase of gait. As a result, the knee safely provides a natural, energy efficient gait over a range of terrains and gait speeds and is simpler, less costly, and lighter weight than the prior art.

A prosthetic knee provides a single axis of rotation and includes a hydraulic damping cylinder, a microprocessor, and sensors. Based on input from the sensors, the microprocessor selects a flow path within the hydraulic cylinder in order to provide the proper amount of knee resistance to bending for a given situation. The resistance of each flow path within the hydraulic cylinder is manually preset. Changes in gait speed are accommodated by employing a hydraulic damper with intelligently designed position sensitive damping. Moreover, the knee need not be un-weighted to transition from the stance phase to the swing phase of gait. As a result, the knee safely provides a natural, energy efficient gait over a range of terrains and gait speeds and is simpler, less costly, and lighter weight than the prior art.

The invention discloses an ultrasonic gait detection device and method. The method is characterized by comprising the following steps: installing an ultrasonic detection system in front of a walking aid robot platform, respectively detecting the distance between the left and right legs of the testee and the ultrasonic detection platform by multiple ultrasonic sensors, extracting gait information in the walking process of the human body, and analyzing and calculating gait parameters, including average step length, average pace, step frequency, instantaneous speed and the like. The device comprises an ultrasonic transceiver, a data acquisition and transmission device, a gait data processing unit and a gait characteristic parameter calculation and analysis unit. The detection device is installed on the walking aid robot platform, and no device is installed on the testee body, so that the ultrasonic gait detection device can detect the gait of the testee without any restriction, thereby reducing the mental load of the testee in the gait detection process; the extracted gait characteristic parameters are more accurate; and the detection system has the advantages of simple structure and low cost, and is convenient to use and install.

The invention provides an assessment method and assessment device for the adaptation effect of an artificial limb. The method comprises the following steps of: collecting gait kinematics parameters, gait dynamics parameters and myoelectricity parameters of an artificial limb wearer in a plurality of gait periods, wherein the gait kinematics parameters comprise the step speed, the step frequency, the step length, the stride, the gait period, the hip joint angle, the knee joint angle and the ankle joint angle, and the gait kinematics parameters comprise the ground reaction force, the hip joint torque, the knee joint torque and the ankle joint torque; determining an optimal stroke from the plurality of gait periods based on the gait kinematics information; obtaining gait characteristic parameters corresponding to the optimal stroke, wherein the gait characteristic parameters comprise multiple index parameters selected from the gait kinematics parameters, the gait dynamics parameters and the myoelectricity parameters; and inputting the gait characteristic parameters into a neural network model to output a score about the adaptation effect of the artificial limb.

The invention discloses a lower limb exoskeleton walking track tracking method controlled by inherited iterative learning. The method includes the steps that a lower limb exoskeleton model is adoptedas a controlled object, a track library corresponding to lower limb exoskeleton step speeds is established, a lower limb exoskeleton inherited iterative learning control method is designed, and tracksat different step speeds are controlled. According to the method, data of hip joints and knee joints at the different step speeds are used as expected tracks tracked by a system, and the inherited iterative learning control method can be used; and the connection between gait periods of the different step speeds is achieved through an inheritance formula, iterative learning control information atthe former step speed is effectively used as initial information at the current new step speed, the different angle expected tracks can be rapidly and effectively tracked without repeated learning, the problem of re-learning at new step speeds is avoided, the learning frequency is reduced, the control time is shortened, the convergence requirement is rapidly met, and the convergence speed is higher than the convergence speed of re-learning.

The present invention discloses an artificial limb movement intention identification method and device based on source-end fusion. A processor collects ground bearing reaction force distribution condition through a pressure sensor arranged on soles of artificial limbs, judges gait cycles and calculates walking speed; road conditions of walking on a flat ground, going upstairs, going up a slope, going downstairs and going down a slope are distinguished through data acquired by an acceleration sensor arranged at artificial limb knee joint positions; going upstairs, going up a slope, going downstairs and going down a slope are distinguished by combining an angle sensor data of artificial foot ankle joint positions, and finally a processor judges movement intention of amputees according to walking speed and road conditions. According to the walking speed and road conditions, the processor controls artificial limbs to change actions according to the walking speed and road conditions, helpsthe artificial limbs to accurately make corresponding action, enables the amputees not need to exert force to change the actions of the artificial limbs, saves more labor of the amputees during use processes of the artificial limbs, and also enables the gait cycles to be more natural.

The invention discloses a gait balance training system based on a six-degree-of-freedom parallel platform. The system comprises six-degree-of-freedom platform mechanical hardware, inertial sensing acquisition nodes, an IMU sensor attitude acquisition system, a robot motion control system and a balance training system. The six-degree-of-freedom platform can provide various angle and displacement changes, apply external stimulation, provide acceleration, speed and angular speed stimulation in combination with related algorithms such as trajectory planning and somatosensory simulation of a robotmotion control system, and train the human body balance perception ability from sensory input. The inertia sensing acquisition nodes are combined with an IMU sensor attitude acquisition system to divide human body gait phases and extract human body key gait data such as stride frequency, stride speed and step length. The extracted human gait data can be used for balance ability evaluation and judgment before training and can also be used for guiding the motion form of the robot in the training process. Two training modes of a balance training system are combined, and active training and passive training of the human body are achieved. According to the invention, a multi-degree-of-freedom platform, motion data acquisition and analysis and related algorithms are introduced to realize a complete gait balance training robot, and the human body balance ability and gait characteristics can be evaluated and judged from feeling input. The blank of domestic related research is filled up, and anew gait balance training mode is added.

The invention relates to the technical field of mobile walking aid equipment, in particular to a method for evaluating the rehabilitation condition of a leg patient and a walking aid robot. The methodcomprises the steps: employing a first laser sensor and a second laser sensor to scan mark points of a left leg and a right leg of the leg patient, and obtaining the coordinates of each mark point; based on the coordinates of the plurality of mark points, establishing a sagittal plane of walking of the leg patient; based on the sagittal plane, gait data of the leg patient are obtained, and the gait data comprise the step length, the step length, the step width, the single-step time, the step speed, the step frequency, the walking symmetry, the adjacent step length ratio, the proportion of thedouble-leg swing phase and the proportion of the supporting phase; based on the coordinates of the multiple marking points, the human body movement intention of the leg patient is obtained; the gaitdata and the human body movement intention of the leg patient are subjected to weighted evaluation, the evaluation result of the rehabilitation condition of the leg patient is obtained, and then the evaluation accuracy is improved.

The invention provides a step-speed-adjustable power-assisted walking device having ready-to-walk / stop mode. The device includes a mounting rack, wherein a waistband is mounted on the front side of the mounting frame; machine covers are arranged on the left side and the right side, shaft arranged in machine cover, a thigh supporting plate, a synchronous pulley A, a driven wheel, a bidirectional ratchet wheel, a driving wheel and a worm wheel are sequentially arranged on the shaft from inside to outside; a baffle B and a baffle A are arranged at the inner lower end of the driven wheel; a transmission wheel fixing piece is cooperatively mounted in the middle of the bidirectional ratchet wheel; a transmission wheel is mounted on the transmission wheel fixing piece in a matched manner; two synchronous belt wheels B are arranged above the bidirectional ratchet wheel, the inner ends of the two synchronous belt wheels B are in transmission connection with the synchronous belt wheel A, a pawlB is arranged at the outer end of the synchronous belt wheel B located on the front side, a pawl A is arranged at the outer end of the synchronous belt wheel B located on the rear side, and an electromagnet B and an electromagnet A are arranged above the pawl B and the pawl A respectively. The walking assisting device solves the problem that old people walk difficultly for a long time, and has theadvantages of ready-to-walk / stop mode, adjustable step speed, safety, reliability, low cost and the like.

A composition comprising a protein source and an antioxidant, optionally in combination with an omega-3 fatty acid, can treat or prevent sarcopenia in elderly males, reduce a loss of muscle functionality (e.g. muscle strength, gait speed, etc.) in elderly males, increase muscle functionality in elderly males, and / or improve recovery of muscle functionality after muscle atrophy in elderly males.

Disclosed herein is a frailty diagnosis apparatus. The frailty diagnosis apparatus includes a physical performance meter and a processor for determining a frailty index of a target person based on physical performance of the target person obtained by the physical performance meter. The physical performance meter includes at least one among a gait speed meter for measuring a gait speed of the target person, a body balance meter for measuring a body balance maintenance time of the target person, and a muscle strength meter for measuring a muscle exercise time.

Embodiments of the present invention disclose an exercise machine including a supporting mechanism, two driving units, and a resistance device. The supporting mechanism supports the two driving units and the resistance device. The two driving units are respectively mounted at the left and the right side of the supporting mechanism for the user to operate. When the exercise machine is operated with a “small pace,” the resistance device is operated in both directions to eliminate the blockage when switching the operating direction of the driving units. When the exercise machine is operated with a “large pace,” the resistance device can provide resistance for the driving units in either direction.

The invention discloses a training data processing method based on a sitting and lying-type lower limb rehabilitation device and a related device. The sitting and lying-type lower limb rehabilitation device at least comprises a rehabilitation mechanism for a patient to carry out sitting and lying training and a connecting mechanism matched with a bedside of a patient. The method comprises the following steps: a training parameter acquisition step: acquiring target training parameters to be carried out by a user, wherein the target training parameters comprise a training mechanism, a step length, a step speed, an angular speed and motion time; a first motion trail calculation step: calculating the target training parameters according to a first preset algorithm to generate a first motion trail; a first motion trail correction step: if a current training mechanism is active, correcting the target training parameters according to data collected by a sensor system in real time to obtain a second motion trail; and a second motion trail execution step: according to the second motion trail, controlling a driver to execute a motion trail to complete target training. The training data processing method achieves technical purposes of rehabilitation individuation and training precision.

The invention discloses an omnidirectional gait detection algorithm based on channel state information (CSI). The omnidirectional gait detection algorithm comprises the following steps that firstly, a relation model MOFS between movement speeds of different parts of a human body and Doppler frequency shift is created, and WiFi signal frequency change components caused by footstep movement are extracted from mixed CSI by using the model; then, frequency spectrum information is analyzed on a time axis by using a frequency spectrum segmentation technology based on frequency energy slicing, and the instantaneous radial step speed of each measurement point is obtained by using an energy cumulative percentile method according to the MOFS model; and finally, a relation model PLCR-Dir of a WiFi signal propagation path length change rate and the walking direction is put forward, and the calculation of the walking period, the step speed and the step length in all directions is realized through the model. Experimental results show that compared with an existing gait detection algorithm, the gait detection algorithm based on the CSI is smaller in detection error, and three gait parameters including the walking period, the step speed and the step length can be detected at the same time.

A system and method for optically setting a pace for an athlete is presented. The method sequentially places a first group of lights and a second group along a path travelled by the athlete. The first group of lights are sequentially lit one after another one at a time with a first predetermined delay between the lighting of each of the lights. After all the first group of lights have been lit, the second group of lights are similarly sequentially lit in sequence with a second predetermined delay between each of the lights. The first and second predetermined delays can be the same if the athlete desires to run several consistent laps of the same speed. However, the athlete may desire to run one part of the laps fast and the another part slower by setting one predetermined delay longer than the other predetermined delay.

A composition comprising one or more polyphenols, such as oleuropein, rutin, curcumin or quercetin, can treat or prevent sarcopenia, reduce a loss of muscle functionality (e.g. muscle strength, gait speed, etc.), increase muscle functionality, and / or improve recovery of muscle functionality after muscle atrophy. The composition can be administered to an individual who is elderly and / or frail.

The invention discloses a motion function evaluation method for a Parkinson's disease patient based on an MEMS sensor. The method comprises the following steps: firstly, carrying out data acquisition on a group of straight movement and turning gait tasks by a subject; carrying out gait HS, FF, HO and TO four-period detection by adopting a rule-based threshold value and peak value detection method, and calculating stride time, support phase time and swing phase time; performing multi-task identification by adopting a rule-based threshold detection method, and outputting turning and straight-going task types; and calculating the step length and the step speed by combining a step length estimation algorithm of double integration and acceleration compensation. The precision meets the requirement of motion analysis, gait evaluation can be effectively and accurately carried out on the Parkinson's disease patient, and a technical basis is provided for clinical motion evaluation of the PD patient.

Described herein are systems, devices, and methods for determining a user's stride length and monitoring various aspects of the user's activities. An apparatus worn or carried by the user may determine and track when a user takes a step and, based at least in part on user-specific information, determine an estimated stride length of the user associated with a respective step rate or step rate range. The apparatus may further monitor the physical location, speed, or pace of the user during an activity and, in conjunction with step count information, determine a verified stride length for the user associated with a respective step rate or step rate range. The estimated and verified stride length determinations may be stored and used to determine one or more aspects of a user's subsequent activities, including but not limited to pace, speed, and calorie expenditure information, even when physical location information is unavailable.

A weight-losing walking passive movement running wheel for a rat with spinal cord injury belongs to the field of rehabilitation training of the rat with spinal cord injury and comprises a running wheel assembly, a hind limb supporting assembly and a suspension assembly, the running wheel assembly comprises a first driving mechanism, a supporting frame, a support and a rotating running wheel, the first driving mechanism is mounted on the upper portion of the support and drives the running wheel to rotate, and the supporting frame is mounted on the supporting frame. The suspension assembly comprises a brace and a suspension frame for suspending the brace, a first opening and a second opening which are opened are formed in the two ends of the brace in the length direction, and two forelimb holes are formed in the positions, close to the first opening, of the outer side of the brace; according to the passive movement running wheel for weight-losing walking of the rat with spinal cord injury, in-situ weight-losing gait rehabilitation training can be carried out on the lower limbs on a running machine, the dragging gait of the rat with spinal cord injury can be changed, nerve regulation and control of walking can be influenced, the effect of muscle training can be achieved for the rat with lower limb strength, the step speed is increased, and the balance function is improved.

The walking direction is calculated according to the walking path; the method comprises the following steps: selecting a speed collected by a transceiver close to a user according to a principle of proximity to synthesize a real walking speed of the user, respectively extracting different percentage speeds to extract fine-grained gait characteristics, and establishing a binary classification identity recognition model for each user through a machine learning method SVM to recognize identities of different people. According to the multi-device cooperative gait sensing and identity recognition method based on ultrasonic waves, two pairs of sensing devices are deployed to weaken walking path constraints; doppler frequency spectrum information captured by different devices is combined, the real-time position of the user is tracked, the walking direction is judged, the step speed is calculated, speed synthesis is conducted according to the triangular relation between the user and the positions of the two sensing devices, the real speed of the user is obtained, and fine-grained gait characteristics are extracted to recognize the identity of the user.

The invention relates to the technical field of robots, in particular to a walking gait planning method for a foot type tabletop pet robot. Comprising a head, a left leg steering engine, a left leg, a left foot steering engine, a left foot, a right leg steering engine, a right leg, a right foot steering engine and a right foot. In the walking gait planning method, the same expression is adopted for the target positions of four steering engines, the advancing direction, the foot lifting sequence, the foot lifting height, the stride and the step speed of the robot can be flexibly controlled by changing parameters, and the problem that the gait design of an existing foot type tabletop pet machine is complex is solved.

The invention discloses a Gaussian process regression-based flexible exoskeleton optimal assistance prediction method, which comprises the following steps of: establishing comfortable assistance data sets of different crowds at different synchronous speeds, determining human body model characteristics of testers, establishing data sets (X, Y) of samples on the basis, establishing the data sets, training the data sets, directly defining distribution of a prediction function in a Gaussian process regression mode, so that the predicted assistance amplitude is within a more reasonable range, smooth assistance to legs is truly achieved, and injured skeletons, muscles and joints are helped to play a role in assisting rehabilitation.

The embodiment of the invention provides a posture detection system, method and device and a storable medium, and belongs to the technical field of sports health, and the method comprises the steps: obtaining a running posture image of an athlete in a detection time period through an image collection device; determining human body key points of the athlete based on the running posture image; on the basis of the human body key points of the athlete, obtaining running feature data of the athlete, wherein the running feature data comprises at least one of stride frequency, stride speed, stride and upper body inclination angle; and determining a posture detection result in the athlete based on the running feature data of the athlete. Through the treatment scheme disclosed by the invention, the situation that the body of the runner is injured due to incorrect postures can be avoided.

The invention relates to a method for detecting the gait stability of a worker in a special environment and an application, and aims to construct a stop braking difficulty coefficient model, quantify the influence of each factor on special environment walking balance, and accurately judge the unbalance risk of the worker in the special environment in the special environment walking process. In the training process, the optimal gait, the optimal step speed and the optimal step length in the advancing process of the special-factor environment operating personnel can be selected, and the advancing stability of the special-factor environment operating personnel is improved. According to the method, the recovery of various gaits is evaluated, an optimal recovery mode is given, and the optimal recovery mode is adopted to train the special-cause environment operating personnel, so that the stability recovery capability of the special-cause environment operating personnel is improved; under the condition that the special environment operating personnel need multi-step braking, the optimal recovery mode prompt is output, and it is guaranteed that the special environment operating personnel recover the gait as soon as possible.