23 results about "Repetitive movements" patented technology

The utility model relates to the technical field of medical machinery, in particular to an arm muscle stretching rehabilitation training auxiliary device which comprises a bottom column, a stand column fixedly connected to the top of the bottom column, a top column fixedly connected to the right side of the stand column, supporting rods fixedly connected to the left side and the right side of the bottom column, and first base plates fixedly connected to the front sides and the rear sides of the bottoms of the two supporting rods. The right side of the bottom of the bottom column is fixedly connected with a bottom block, the bottom of the bottom block is fixedly connected with a second chassis, the right side of the top of the bottom column is fixedly connected with a foot pad, and the front side and the rear side of the top column are each provided with an arm stretching mechanism. When a user feels that the stretching position reaches the arm limit through grip strength, the stretching position can be kept for a period of time and then slowly relaxed, the action is repeated to complete arm muscle stretching rehabilitation training, complete stretching can be achieved, adjustment can be conducted according to the height of a patient, and efficiency is improved.

A method for video processing is disclosed. The method includes receiving an input video of one or more persons from a camera; detecting a sequence of human poses in the input video using an artificial intelligence (AI) based technique; selecting a proper pose from among multiple poses in a given frame of the input video, to generate a sequence of proper poses; detecting one or more key points in the sequence of proper poses; computing changes in coordinates of the one or more key points; computing a function of the changes in the coordinates of the one or more key points in the sequence of proper poses; counting a given user movement as a repetitive motion of an activity based on the function; and computing a plurality of statistics about the activity based on the counting. The activity may be running, jogging, walking, jumping, performing jumping jacks, squatting, and / or dribbling.

The application discloses a sports movement counting and rule-breaking action judging method based on human body posture recognition, and comprises the following steps: step A, human body recognition; step B, personnel screening; step C, repeated action detection based on human body key point detection technology; and step D, rule-breaking action judgment. The application uses human body key point detection technology of deep learning, calculates the relative position and relative angle of each limb part according to the position information, thereby judging what action the test personnel is doing, whether the action is in place, and whether there is a rule-breaking situation. Finally, in combination with time domain information, the preceding and subsequent multiple frames of actions are associated, and whether the human body accurately completes each standard action is judged. When each action is sequentially and normally completed, the system automatically counts. The application automatically adapts to different human body features, and compared with infrared radio frequency technology, the counting accuracy is high.

The present invention discloses a method and system for rehabilitating a patient with a limb disability by providing repetitive motion therapy. The system is configured to receive biomechanical data from the patient regarding repetitive movements performed using a first side and a second side of the body, respectively, and select an entrainment side based on the data to provide the repetitive motion therapy. The system further performs the repetitive motion therapy by: providing auditory stimulation to the patient, the auditory stimulation including a beat signal output at corresponding beat times; receiving time-stamped biomechanical data of repetitive movements performed by the patient using the entrainment side associated with the corresponding beat times of the beat signal; calculating an entrainment potential of the entrainment side by comparing the timing of the repetitive movements with the timing of the beat signal; and modifying the auditory stimulation based on the calculated entrainment potential.

The Pelvic Floor Trainer is the only product of its kind that primarily targets adduction, abduction, and core movements as well as several secondary muscle groups activated by squeezing and / or pushing out focused repetitive movement. This unprecedented product is uniquely designed with a center cross piece that locks in place to allow for reversible exercise, at the user's preference, is carefully crafted with durable, high-quality materials and padded leg pieces to enhance comfort during utilization.

The invention relates to method for calibrating a head-mounted device (1), the head-mounted device (1) comprising a frame (2) and at least one sensor (4) mounted on the frame (2), for measuring position and / or motion, the method being implemented while the head-mounted device (1) is worn on a wearer's head, the method comprising steps of: —detection (DET) of a known repetitive movement pattern of the wearer's head by the sensor (4), —acquisition (ACQ) of three-dimensional motion data by the sensor (4), —selection (SEL) of data relative to the movement pattern from the motion data, —numerical treatment (NUM) of the selected data to obtain a reference base relative to the wearer's head, and —calibrating (CAL) the sensor (4) based on the obtained reference base.

Systems, devices, and methods described herein may involve receiving movement data associated with a subject, the movement data collected during repetitive movement of the subject; generating a phase portrait based on the movement data; calculating a phase portrait metric of a characteristic of the phase portrait; and assigning the subject to a movement phenotype based on the phase portrait metric.

This application discloses a U-Q-Learning-based mobile robot path planning method in unknown environments, comprising: designing a composite reward function including a repetitive movement penalty, a distance reward, and a state transition heuristic reward; initializing a Q-table, an action selection count table, and a state visit count table, as well as an exploration rate, a learning rate, and a discount factor; calculating the upper confidence bound of actions based on the Q-value of the state, the number of action selections, and the number of state visits, and dynamically adjusting the exploration rate; if the current exploration rate is large, randomly selecting an action from the action space; otherwise, selecting the action with the largest upper confidence bound; the robot executing the selected action, transitioning to the next state, and calculating the immediate reward; adaptively adjusting the learning rate, updating the current Q-value by combining the immediate reward, the discount factor, and the maximum Q-value of the next state, updating the state to the next state, repeating multiple iterations until the algorithm converges, and outputting the optimal path based on the optimized final Q-table. This application can improve the efficiency and stability of path planning.

Disclosed herein is an apparatus and method for counting repetitive movements based on Artificial Intelligence. The method may include generating standard movement information that includes a key pose extracted from a demonstration movement image stream based on human skeleton information, which is a set of pieces of positional information of human joints, and major joint information in the key pose and counting repetitive movements depending on whether a user movement matches the standard movement information based on human skeleton information of a user movement image stream.

The invention is suitable for the field of computer vision, and provides a repetitive motion posture counting method, device and equipment and a storage medium. The method comprises the following steps: acquiring a video sequence, and dividing human joints of an image frame into a plurality of main sub-images based on a natural topological structure of a human body; establishing a dependency relationship in the main body sub-graphs locally and establishing a dependency relationship between the main body sub-graphs globally through graph attention to obtain representative features about the image frames; establishing a mapping relationship between the representative features and action categories by using a classification head to obtain a score of the action category of each image frame in the video data; the repetitive actions are counted using an action trigger. According to the method, the mutual relation of the sub-graphs in the components and among the components is explored through graph attention, the local significant features in the components are captured, and the global dependency relation among the components is captured, so that the model performance is improved.

Methods, apparatuses, and systems for wireless monitoring systems, wireless vital monitoring, and wireless proximity sensing are described.SOLUTION: A system includes a transmitter configured to transmit a first wireless signal over a wireless channel of a venue, a receiver configured to receive a second wireless signal over the wireless channel, and a processor. The second wireless signal comprises a reflection of the first wireless signal by at least one living being having at least one repetitive motion at the location. The processor is configured to obtain a time series (TSCI) of channel information of the wireless channel based on the second wireless signal, to generate, for each living being of the at least one living being, a vital signal representative of all repetitive movements of the living being based on the TSCI, to extract a heart rate signal from the vital signal of each living being, and to monitor heart rate variability based on the heart rate signal for each living being at the location.SELECTED DRAWING: Figure 1A

Providing data indicative of heat stress in a ruminant using an activity measurement unit attached to the ruminant that includes a motion sensor and a processor is described. The method comprises measuring, using the motion sensor, ruminant movement of the ruminant over time; and determining, using the processor, that the measured ruminant movement is a repetitive movement indicative of either panting or rumination. A movement pattern indicative of panting and a movement pattern indicative of rumination both include one or more similar parameter values. The method further includes establishing at least one of: whether the repetitive movement is indicative of panting, and / or whether the repetitive movement is indicative of ruminating. The establishing includes: detecting, from the measured ruminant movement the occurrence of a belch action; and identifying, when for at least a predetermined time period the occurrence of the belch action is absent, that the repetitive movement is indicative of panting, for providing the data indicative of heat stress.

A method of monitoring fatigue of an ultrasonic inspector includes obtaining, at a first computer, an estimated pose of the ultrasonic inspector; obtaining, at the first computer, an estimated level of repeated movement of the ultrasound inspector based on data from the sensor (435); obtaining, at a first computer, an estimated level of pressure applied to a transducer by the ultrasound inspector; and determining a level of cumulative physical injury of the ultrasound inspector based on the estimated pose, the estimated level of repetitive movement, and the estimated level of pressure applied by the ultrasound inspector.

When comparing and analyzing multiple recordings of repetitive movements, there is no means to dynamically switch the reference point for synchronized playback. Therefore, it was difficult to recognize the discrepancies between movements that appeared different depending on the selection of the reference point, and to identify their causes. [Solution] The system accepts multiple time-series media data, each recording multiple repetitive actions, with multiple reference point candidates assigned to each recording. It displays these data in parallel or superimposed, and presents the reference point candidates on a timeline. For each type of reference point candidate, the system calculates the median time position across multiple recordings as the representative position, and sets intervals on the timeline using the midpoint between adjacent representative positions as boundaries. The system designates the reference point candidate corresponding to the interval to which the user's input location belongs as the reference point, and realigns all recordings to the time position of that reference point to update synchronized playback.

A computer-implemented method for video processing is disclosed. The method includes receiving an input video of one or more persons from a camera; detecting a sequence of human poses in the input video using an artificial intelligence (AI) based technique; selecting a proper pose from among multiple poses in a given frame of the input video, to generate a sequence of proper poses; detecting one or more key points in the sequence of proper poses; computing changes in coordinates of the one or more key points; computing a function of the changes in the coordinates of the one or more key points in the sequence of proper poses; counting a given user movement as a repetitive motion of an activity based on the function; and computing a plurality of statistics about the activity based on the counting. In some embodiments, the activity is running, jogging, walking jumping, performing jumping jacks, squatting, and / or dribbling.

The sitting-standing-sitting leg muscle strength rehabilitation training device of the present invention belongs to the technical field of leg rehabilitation medical devices, and solves the technical problems in the prior art such as high rehabilitation training cost, time-consuming wearing, and inability to monitor the rehabilitation treatment effect of patients in real time; the present invention includes a base, a power source, and a lead screw sliding table; the present invention can realize a training method with the patient as the main and the robot as the auxiliary. Through standardized repetitive movements, it exercises the leg muscles and restores the lower limb motor function. It not only conforms to the movement law of human sitting and standing conversion, but also can stably assist the patient to complete the sitting-standing-sitting leg muscle strength rehabilitation training.

To provide a notification device capable of notifying a user of an abnormality or sickness of a target person, a notification method, and a program.SOLUTION: A notification device 10 comprises: an image capturing section 11 which captures a picked-up image; a portion discrimination section 12 which discriminates portions of a target person on the basis of the picked-up image; an action detection section which detects a repeated action based on movements of the portions of the target person; a notification determination section 14 which determines whether to perform a notification to a user corresponding to the target person based on a detection result of the repeated action; and a communication section 15 which performs the notification based on a determination result of the notification determination section 14.SELECTED DRAWING: Figure 2

The invention relates to method for calibrating a head-mounted device (1), the head-mounted device (1) comprising a frame (2) and at least one sensor (4) mounted on the frame (2), for measuring position and / or motion, the method being implemented while the head-mounted device (1) is worn on a wearer's head, the method comprising steps of: —detection (DET) of a known repetitive movement pattern of the wearer's head by the sensor (4), —acquisition (ACQ) of three-dimensional motion data by the sensor (4), —selection (SEL) of data relative to the movement pattern from the motion data, —numerical treatment (NUM) of the selected data to obtain a reference base relative to the wearer's head, and —calibrating (CAL) the sensor (4) based on the obtained reference base.

Active wrist brace for guiding and relieving musculotendinous pain at the elbow (epicondylar and epitrochlear) and wrist. The invention relates to a new type of wrist brace that relieves pressure on the forearm muscles and their tendon insertions at the elbow and wrist. Due to repetitive movements, the tendons of the elbow and wrist become inflamed, resulting in tendinitis. The wrist is responsible for this elbow condition. This brace will preferably consist of a flexible sleeve (1) covering the wrist and perforated for the thumb (2). One or more dorsal tunnels (3) (3') will be arranged on this flexible sleeve (1). One or more tunnels (3) (3') will be located on the palmar side of the sleeve (1). One or more flexible elastic strips (5) will be placed in these palmar and dorsal tunnels (3) or tunnels (3').

A method and system for augmented neurorehabilitation (ANR) for patients are disclosed. The ANR system generates rhythmic auditory stimuli (RAS) and visual augmented reality (AR) scenes, which are synchronized according to a common beat speed and output to the patient during a treatment session. Sensors worn by the patient capture biomechanical data related to repetitive movements performed by the patient in sync with the AR visual content and RAS. Critical thinking algorithms analyze the sensor data to determine the spatial and temporal relationships of the patient's movements relative to the visual and audio elements, and to determine the patient's entrainment level and progress toward clinical / therapeutic goals. Furthermore, a 3DAR modeling module configures the processor to dynamically adjust the augmented reality visual and audio content output to the patient based on the determined entrainment level and whether training goals have been achieved.

This invention belongs to the field of pet toy control technology and discloses a control method and system for pet toys. The method includes: acquiring pet location information; determining the escape direction of the pet toy based on the pet location information and the location coordinates of the pet toy; predicting the pet's movement trend based on the pet's current center coordinates and the center coordinates of the previous moment; obtaining a predictive offset direction based on the environmental distance information of the pet toy in a preset direction; superimposing the escape direction and the predictive offset direction to obtain the escape direction vector of the pet toy; determining the distance weight of each direction based on the distance to obstacles; weighting and summing the unit direction vectors of each direction based on the distance weight of each direction to obtain the obstacle avoidance direction vector; and fusing the escape direction weight, obstacle avoidance weight, escape direction vector, and obstacle avoidance direction vector to output control commands, thereby avoiding repetitive movement patterns being perceived by the pet and improving the pet's playtime persistence and fun.

A method and apparatus for providing data indicative of heat stress in a ruminant using an activity measurement unit. The activity measurement unit comprises a motion sensor and a processor. The activity measurement unit is attached to the ruminant. The method comprises measuring, using the motion sensor, ruminant movement of the ruminant over time. The method comprises determining, using the processor, that the measured ruminant movement is a repetitive movement indicative of either panting or rumination. A movement pattern indicative of panting and a movement pattern indicative of rumination both comprise one or more similar parameter values. The method comprises establishing, using the processor, at least one of whether the repetitive movement is indicative of panting or whether the repetitive movement is indicative of ruminating or both. The step of establishing comprises the step of detecting, from the measured ruminant movement, using the processor, the occurrence of a belch action. The step of establishing further comprises the step of identifying, when for at least a predetermined time period the occurrence of the belch action is absent, that the repetitive movement is indicative of panting, for providing said data indicative of heat stress.