147 results about "Movement pattern" patented technology

A wearable device includes an accelerometer, at least three electrodes to detect electromyography signal, a communication circuitry, and a processor circuitry. A user wears a primary and a secondary wearable device on two limbs. When the user performs a two-hand gesture, the wearable devices detect a primary and a secondary movement pattern. The primary device recognizes the two-hand gesture from the primary and secondary movement pattern.

An exercise support device includes a base and a boxing bag mounted on the base. The base includes a processor, a memory storing a movement pattern, and a drive system configured to move the base with the boxing bag mounted on the base. The processor is configured to control the drive system to move the base in accordance with the movement pattern stored in the memory.

The invention discloses an intelligent artificial limb movement intention recognition method based on multi-modal information and a D-S evidence theory, and belongs to the technical field of artificial intelligence, mode recognition and intelligent artificial limb control. According to the method, firstly, electromyographic signals and kinematics signals of user limbs and three-dimensional point cloud information of the terrain where the user limbs are located are synchronously collected; filtering, segmenting and time domain / frequency domain feature extraction are carried out on the physiological signals, rotation correction and dimension reduction are carried out on the environment point cloud, and a binary image is generated; using a deep learning model to identify a preliminary motion mode from the physiological features and identify a terrain category from the environment image; and finally, inputting the two recognition results as evidence bodies into an improved D-S evidence theory model for decision-level fusion, and outputting a final comprehensive motion intention recognition result. According to the method, the human physiological signal and the external environment information are fused, so that the ambiguity and uncertainty of single information source identification are effectively solved, and the intention identification accuracy and adaptability of the intelligent artificial limb in different complex scenes are remarkably improved.

Systems and methods for providing assessments of a disease using sensor data for a subject captured during day-to-day living are provided. The sensor data includes accelerometer data and is acquired by a sensor disposed on the subject's wrist while the subject performs both active and sedentary activities. The sensor data is analyzed for one or more bouts of activity; the sensor data is filtered, optionally rotated, and Fourier transformed. Spectral analysis parameters are then calculated from the transformed data to detect disease-relevant movement patterns. Movement distribution parameters for the accelerometer data associated with the disease-relevant movement patterns are calculated and compared to one or more disease scores to evaluate a progression of the disease or an efficacy of a treatment

The embodiment of the invention relates to a method and system for detecting gestures of both hands. A wearable device includes: an accelerometer; the at least three electrodes are used for detecting the electromyographic signals; a communication circuit arrangement; and processor circuitry. A user wears a primary wearable device and a secondary wearable device on both limbs. The wearable device detects a primary movement mode and a secondary movement mode while the user performs a two-hand gesture. The primary device recognizes both-hand gestures from a primary movement mode and a secondary movement mode.

Systems and methods are disclosed for movement-based signature authentication. One method comprises determining one or more features associated with a user based on one or more two-dimensional images and determining one or more body points associated with the user based on one or more three-dimensional images. A movement pattern of each body point of the user is determined based on the one or more three-dimensional images. The one or more determined features are compared to corresponding one or more stored features associated with the user. If the one or more detected features match the one or more stored features, the one or more determined movement patterns are compared to a unique electronic signature associated with the user. Upon determining that the one or more determined movement patterns match the unique electronic signature, the user is authenticated for electronic transaction.

Systems and methods are disclosed for movement-based signature authentication. One method comprises determining one or more features associated with a user based on one or more two-dimensional images and determining one or more body points associated with the user based on one or more three-dimensional images. A movement pattern of each body point of the user is determined based on the one or more three-dimensional images. The one or more determined features are compared to corresponding one or more stored features associated with the user. If the one or more detected features match the one or more stored features, the one or more determined movement patterns are compared to a unique electronic signature associated with the user. Upon determining that the one or more determined movement patterns match the unique electronic signature, the user is authenticated for electronic transaction.

The invention provides a virtual reality-based joint movement injury rehabilitation mode generation method and a virtual reality-based joint movement injury rehabilitation mode generation system, and relates to the technical field of virtual reality, and the method comprises the following steps: analyzing a rehabilitation path according to movement joint injury data of a user; performing rehabilitation limb posture decomposition based on the rehabilitation analysis path to generate a rehabilitation analysis view; a multi-modal sensor unit is used for collecting rehabilitation feedback actions of a user, and matching recognition of physiological parameters and rehabilitation constraints is carried out in a rehabilitation analysis view; and according to the posture deviation feedback, performing amplitude and muscle power guidance feedback of the rehabilitation limb posture, and synchronously performing virtual reality visual display. The technical problem that in the prior art, most VR rehabilitation systems mainly pay attention to visual feedback, so that only the motion appearance can be evaluated, and the compensatory motion mode cannot be recognized is solved, real-time monitoring and guidance on the force exerting correctness are achieved through combination of posture decomposition and physiological parameter projection, and the effect that the correctness of force exerting is improved is achieved. Therefore, the compensatory motion mode is effectively blocked.

Disclosed embodiments provide bot detection in a virtual environment that is based on avatar motion. The motion of an avatar within a virtual environment such as a metaverse is tracked. The tracked motion is separated into multiple movement segments. The movement segments are compared to a collection of movement patterns in a movement pattern database that are indicative of bots. A similarity metric is determined between the tracked motion and the database of bot motions. In response to the similarity metric exceeding a predetermined threshold, a list of at least one mitigation action is obtained, and the at least one mitigation action in the list is executed, thereby mitigating the adverse effects of bots in a virtual digital environment.

Device (12) for detecting a vegetation object (14) in the environment (16) of a vehicle (18), comprising: an input interface (26) for receiving sensor data from a radar sensor (20) with information about the vehicle's environment, wherein the sensor data includes scan points (32) with associated point velocities; a processing unit (28) for identifying an object in the vicinity of the vehicle based on a clustering of scan points according to the point velocities of the scan points; and an evaluation unit (30) for classifying the object based on an evaluation of the point velocities of the scan points assigned to the object, in order to distinguish between a vegetation object (14) and a living object (22), wherein the evaluation unit (30) is designed to calculate a frequency spectrum of the point velocities of the scan points assigned to the object (32) and to classify the object as a vegetation object (14) if the frequency spectrum does not include pronounced high points; to distinguish between a person, encompassing a pedestrian or a cyclist, and an animal based on the point velocities of the scan points (32) assigned to the object, if the object has been classified as a living object (22); and is trained to recognize typical movement patterns based on a comparison with predefined pattern data; and is trained to recognize a living object (22) that is in front of or behind a vegetation object (14).

In order to improve throughput in an environment where a plurality of moving bodies are operating, the present invention comprises: group setting units (102a, 102b) that set groups of a plurality of moving bodies M on the basis of positions and destinations of the moving bodies M; and movement rule setting units (103a, 103b) that set, for the moving bodies M belonging to a group set by the group setting units (102a, 102b), a movement rule (113) shared by the moving bodies M belonging to the group. The movement rule setting units (103a, 103b) set the movement rule (113) so that the moving bodies M belonging to the group move in the shared movement pattern.

A method and system for providing distance information from a sensor assembly to a flying target. The method comprises detecting the flying target and locking on the flying target by means of a tracking sensor. Directing a light beam at the detected flying target. Generating a movement pattern having a path around the detected flying target and controlling movements of the light beam so that the LOS of the light beam completes moving across the path of the selected movement pattern within a set timeframe. Generating distance information by measuring time- of-flight of the light beam, when being reflected from the flying target while moving the LOS of the light beam across the path of the movement pattern. The system comprises sensors and devices for performing the method.

Provided is a technique capable of controlling a moving body during self-propelled production. A control device for controlling the operation of a moving body capable of moving by unmanned driving is provided with: an acquisition unit for acquiring process information indicating a manufacturing process being performed on the moving body; a determination unit that uses the process information to determine which of an engine movement mode in which movement is performed using the engine and a motor movement mode in which movement is performed using the motor to move the moving body; and a control unit that moves the moving body in the determined movement pattern.

A system configured to forecast movement patterns and density of individuals within a transportation hub. The system includes a transport schedule data orchestrator to generate one or more forecast models in real-time that predicts the movement patterns and density of individuals within a transportation hub based on external transportation schedule information. The system is also configured to generate at least one play for preemptive actions to mitigate disruptions or inconveniences within a transportation hub. The system includes an autonomous play maker to generate the at least one play for preemptive actions to mitigate disruptions or inconveniences within a transportation hub based on the one or more forecast models generated by the transport schedule data orchestrator.

System includes a haptic garment comprising an integrated circuit (IC) controller coupled to the haptic garment. A sensing circuit configured to cause to transmit a motion signal sensed by a portion of the haptic garment surface to the IC controller is provided. The motion signal is based on one or more of a touch pattern, a gesture pattern, and a movement pattern associated with a user of the haptic garment. The IC controller is configured to transmit a first data associated with the motion signal to an external device. Conductive traces embedded in the haptic garment that electrically couple with the sensing circuit.

The present invention discloses an artificial muscle collaborative mirror rehabilitation system and control method based on ultrasonic detection control. The rehabilitation system includes an ultrasonic detection group, a pneumatic muscle group, and an electric control group. The ultrasonic detection group performs high-density array ultrasonic detection on the muscles of the user's healthy limb to obtain the muscle state of the healthy limb, and analyzes the muscle state information through the electric control group to resolve the limb collaborative movement information. The pneumatic muscle group simulates the layout and attachment method of human limb skeletal muscles on the bones, and is controlled by the electric control group for collaborative drive to achieve mirror movement of the healthy limb. The present invention adopts ultrasonic detection and pneumatic muscle simulation of mirror movement, which can detect the movement pattern of the healthy limb (including movement amplitude, movement angle, movement speed and strength, etc.) at the muscle level, and collaboratively control the affected limb in real time to completely imitate the movement of the healthy limb, so that the rehabilitation equipment can assist the patient to achieve the mirror movement effect and improve the rehabilitation efficiency.

A roll manufacturing apparatus includes a rotary device including a rotary encoder, a cutting tool stage that holds a spindle unit, which includes a rotatable cutting blade, reciprocatably in a radial direction of a roll and is movable in the radial direction of the roll, a signal generator that generates, based on signals output from the rotary encoder, a control waveform indicating a movement pattern to reciprocate the cutting blade at positions corresponding to predetermined cutting portions, and a controller that moves the cutting tool stage so that a cutting process of reciprocating the cutting blade in the radial direction of the roll while rotating the cutting blade, according to the control waveform, to perform cutting once or multiple times with the cutting blade at a predetermined cutting depth is performed multiple times.

This invention belongs to the technical field of rehabilitation robots, specifically relating to a continuous phase control method for a lower limb rehabilitation exoskeleton that adapts to user gait. It employs a multi-task learning model, simultaneously outputting user identity probability and movement pattern probability to generate a probability map representing the similarity between the current gait and a certain movement pattern of a sample user in a sample database. A gait phase variable parameter prediction model is used to predict gait phase variable parameters, employing angular velocity data from the initial stage of the current gait cycle and the matched movement pattern to predict the gait phase variable parameters for the current cycle. Finally, a pre-constructed relational constraint model corresponding to the matched sample user and their movement pattern is used to obtain the desired joint angles from the real-time gait phase, and the exoskeleton is tracked and controlled via a PD controller. This invention can adaptively adjust the exoskeleton's motion assistance mode according to the user's gait characteristics, and is suitable for rehabilitation training of patients with lower limb motor dysfunction.

The present invention provides a system for monitoring and improving toothbrushing effectiveness. The system comprises a camera device comprising a camera or similar visual sensor configured to capture real-time footage of a user brushing their teeth an AI-powered software module is designed to analyse the footage using object recognition, pose estimation, and motion tracking algorithms to detect the user's hand, toothbrush, and face, a feedback device that comprises a feedback interface that provides real-time visual, auditory, or haptic feedback based on brushing technique, including parameters such as angle, coverage, and movement speed and movement patterns. Wherein the feedback provided comprises instructions to the user to alter their toothbrushing technique to bring the parameters closer to a predetermined set of ideal values. Thereby providing a system operates independently of sensors, accelerometers, or physical markers embedded in or attached to the toothbrush.

Provided is technology that makes it possible to easily maintain the communication quality of the portable terminal of a user having a specific attribute. A core network system executes the following: a step in which portable terminal information and base station information are acquired; a step in which a movement pattern of a portable terminal is determined; (a) a step in which a movement route of the portable terminal in a future scheduled period is inferred, (b) a step in which one or more base stations estimated to communicate with the mobile terminal on the movement path are determined, and (c) a step in which a base station parameter is calculated, the steps (a), (b), and (c) being executed using a machine learning model generated by learning the movement pattern of the portable terminal; a step in which a setting time for setting the base station parameter in the base stations is determined; and a step in which the base station parameter is set in the one or more base stations at the setting time.

This invention relates to the field of parallel robot technology, specifically to a three-degree-of-freedom (DOF) parallel robot with two translational and two rotational degrees of freedom. Existing parallel robots mostly focus on rotational motion, with insufficient support for translational motion, making it difficult to fully simulate the natural movement patterns of the ankle. To address these problems, this invention provides a three-DOF parallel robot with two translational and two rotational degrees of freedom. Its topology includes a static platform, a moving platform, and hybrid branches I and II connecting the static and moving platforms. This topology realizes the two rotational degrees of freedom (inversion / eversion, dorsiflexion / plantarflexion) and two translational degrees of freedom required by the ankle joint, perfectly matching the natural movement patterns of the ankle. Compared to traditional parallel robots that only focus on rotational motion, this invention can more comprehensively simulate the complex movements of the ankle, providing a movement trajectory closer to the actual physiological state for rehabilitation training, thereby improving rehabilitation outcomes.

The present invention discloses an exhibition interaction method for large-scale XR spaces based on LBE technology, which relates to the technical field of extended reality. The method comprises the following steps: aligning user location coordinates and environmental three-dimensional point cloud data in time and space using an ICP algorithm, filtering noise using a Gaussian filter, and forming a user location matrix; generating a spatial density distribution map using a PPO algorithm from the user location matrix, and dynamically meshing the spatial density distribution map to generate dynamic mesh layout parameters; inputting the dynamic mesh layout parameters into a chaotic prediction model, simulating user movement patterns using an improved Lorenz equation, extracting obstacle positions using a RANSAC algorithm, and simultaneously performing multi-dimensional feature mapping on user movement patterns and obstacle positions to generate a collision risk heat map. The present invention utilizes a chaotic prediction model and a RANSAC algorithm to improve the accuracy of user movement pattern prediction and the ability to identify obstacles in a changing environment, making the interactive experience smooth and natural while ensuring user safety.

The disclosure relates in general to a method and a system for identifying a vehicle via a system. The system comprises at least one sensor, a system control device coupled to the sensor and the vehicle having a vehicle control device. A vehicle having at least one component is detected. The component is movable, can be detected by the sensor and is coupled to the vehicle control device. The system control device is coupled to the vehicle control device. An identifier is forwarded by the system control device to the vehicle control device. A movement pattern is executed by the at least one component of the vehicle based on the identifier. A movement pattern executed by the component of the vehicle is detected by the sensor. The vehicle is identified by the system control device (16) based on the detected movement pattern.

A method and apparatus for generating a random image of an herbal preparation, comprising: a container containing the herbal preparation; a cleaning tool movable in a plurality of degrees of freedom; the controller is operably connected to the cleaning tool and is used for controlling the movement of the cleaning tool; a camera for capturing an image of the herbal preparation within the container; wherein, in use, based on one or more randomly generated movement patterns, the cleaning tool is movable within the container to agitate the herbal formulation within the container; wherein the camera is controlled to capture an image of the herbal preparation within the container after the cleaning tool has stopped moving.

A wearable knee brace system integrates inertial measurement unit (IMU) and electromyography (EMG) sensors with machine learning models to prevent anterior cruciate ligament (ACL) and posterior cruciate ligament (PCL) injuries. The system collects real-time biomechanical and neuromuscular data and analyzes the data using supervised, personalized, or federated learning techniques to identify high-risk movement patterns. Upon detecting elevated injury risk, the system may issue real-time alerts or activate a hybrid actuation system comprising high-force, low-displacement actuators and low-force, high-displacement actuators to reduce joint loading. The system further supports personalized model adaptation using calibration activities and transfer learning, as well as privacy-preserving performance improvements through federated learning. Feedback is provided through visual, auditory, or haptic interfaces and may be integrated with rehabilitation tools or mobile applications. The system may be used in athletic, dance, clinical, or rehabilitative environments to enhance performance, optimize recovery, and reduce the risk of knee ligament injuries.

This invention relates to the field of lower limb rehabilitation data recognition and monitoring technology, specifically disclosing a method for recognizing lower limb rehabilitation movement postures and an intelligent ankle bracelet for preventing VTE, comprising: Step 1, real-time acquisition of three-dimensional spatial motion data and recognition of lower limb motion data, extracting kinematic parameter features; Step 2, identification of movement types based on kinematic parameter features, acquisition of movement pattern consistency scores, and determination of whether rehabilitation training is qualified; Step 3, acquisition of surface electromyographic signals of the rehabilitation participant's leg-raising force exertion movement during rehabilitation training and simultaneous acquisition of lower limb motion data, extraction of force exertion data, evaluation and analysis to generate a muscle activation efficiency score; Step 4, establishment of a mapping model based on historical hemodynamic data, inputting the extracted force exertion data into the mapping model to output a VTE prevention efficiency score; Step 5, calculation of the movement pattern consistency score, muscle activation efficiency score, and VTE prevention efficiency score through movement evaluation analysis to generate a movement evaluation quality coefficient.

The disclosure generally relates to a method (32) and a system (10) for identifying a vehicle (12) by means of a system (10). The system (10) comprises at least one sensor (14), a system control device (16) coupled to the sensor (14), and the vehicle (12) with a vehicle control device (24). A vehicle (12) with at least one component (28) is detected. The component (28) is movable, detectable by the sensor (14), and coupled to the vehicle control device (24). The system control device (16) is coupled to the vehicle control device (24). An identifier is transmitted from the system control device (16) to the vehicle control device (24). A movement pattern is executed by the at least one component (28) of the vehicle (12) based on the identifier. A movement pattern executed by the component (28) of the vehicle (12) is detected by the sensor (14).The vehicle (12) is identified by the system control device (16) based on the detected movement pattern.

The invention relates to a method for issuing an input to a computer from a head-mounted device, the head-mounted device comprising a processing unit and a memory as well as at least one position and / or movement sensor, the head-mounted device being in communication with the computer, the method being implemented while the head-mounted device is worn on a wearer's head.The method comprises steps of:acquisition of position and / or movement data representative of the movement of the wearer's head by the position and / or movement sensor,detection of a specific movement pattern based on said position and / or movement data, the specific movement pattern being taken from a library of movement patterns,determination of a specific input associated with the specific movement pattern in the library, andissuance of the specific input to the computer.

A method executed by a robot, including: starting, from a starting position, a work session in which the robot maps a workspace, wherein a front of the robot faces towards a forward direction in a frame of reference of the robot; the robot traversing, from the starting position, to a first position, a first distance from the starting position in a backward direction in the frame of reference of the robot; after traversing the first distance, the robot rotating; after rotating, the robot traversing a coverage path of at least one area of the workspace, the coverage path including a boustrophedon movement pattern; and the robot cleaning the at least one area of the workspace with a cleaning tool of the robot while traversing the coverage path.

Method for operating an extractor device (2) comprising the steps: - detecting, within a detection area (10), at least one cooking vessel (14) on a cooking zone (12) of a cooking hob (3) and a movement of an object in an area (16) of the detected cooking vessel (14), wherein the object is a hand (H) of a user; - evaluating the detected cooking vessel (14) to determine whether the cooking vessel (14) is closed with a lid and evaluating the detected movement; - determining a cooking level (18) set for the cooking zone (12) of the detected cooking vessel (14); - predicting the amount of vapor generated at the extractor device (2) on the basis of the evaluation result and the determined cooking level (18); and - Controlling the extractor device (2) on the basis of the predicted vapor generation, characterized in that the evaluation of the detected movement comprises determining a movement pattern and determining an intention to actuate the lid of the detected cooking vessel (14) on the basis of the determined movement pattern.