259 results about "Movement pattern" patented technology

Aspects presented herein may enable a UE (e.g., a vehicle, an autonomous vehicle, an on-board unit (OBU) of a vehicle, an advanced driver assistance systems (ADAS) of a vehicle) to calculate and output safety margins for objects around the UE or a vehicle. In one aspect, a UE receives or transmits a request to provide safety margin visualization assistance. The UE obtains, in response to the request, an indication of a safety margin associated with an object based on a distance between the UE and the object and at least one of: a size of the object, a speed of the object, a location of the object, a type of the object, a direction of the object, or a movement pattern of the object. The UE outputs the safety margin associated with the object.

The invention relates to the field of traffic transportation information engineering, and discloses a group division method and system based on individual movement mode dynamic hypergraph clustering, and the method comprises the steps: constructing an individual movement mode feature matrix under each time slice; constructing an individual movement mode hypergraph under each time slice, and modeling a'many-to-many 'complex high-order association relationship among individual movement modes under the whole time period; proposing a dynamic hypergraph clustering model based on a moving mode, and performing category division of individual associated groups; the provided model is applied to a series of empirical data sets for training and testing, and it is proved that the model can obtain good group division performance superior to that of a baseline model.

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.

Aspects of this technical solution can include obtaining, by one or more processors coupled with non-transitory memory, a first plurality of images each including corresponding first time stamps, the plurality of images corresponding to video data of a physical environment, extracting, by the one or more processors and from among the first plurality of images, a second plurality of images each having corresponding second time stamps and each having corresponding features indicating an object in the physical environment, and training, by the one or more processors and with input including the features and the second time stamps corresponding to the features, a machine learning model to generate an output indicating a pattern of movement of one or more objects corresponding to the features and the second time stamps corresponding to the features.

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.

A system and a method for capturing a movement pattern of a person. The method comprises capturing a plurality of images of the person executing a movement pattern by means of a non-contact sensor, the plurality of images representing the movements of the body elements of the person, generating at least one skeleton model having limb positions for at least some of the plurality of images, and calculating the movement pattern from the movements of the body elements of the person by comparing changes in the limb positions in the at least one skeleton model generated.

The embodiment of the invention provides a method for controlling an industrial robot, the industrial robot and a computer readable medium. In the method, a motion pattern for the industrial robot is determined based on a first voice input. One or more motion parameters in the determined motion pattern are determined based on the second speech input. And controlling the industrial robot to move in the determined motion mode according to the one or more motion parameters. According to the embodiment of the invention, by firstly determining the motion mode and then determining the motion parameters in the motion mode, more accurate movement of the industrial robot can be realized through voice control, so that the user experience of robot control is improved.

The invention relates to a panic pedestrian wandering behavior recognition method and system based on a motion trail, and the method comprises the following steps: obtaining a motion image of a pedestrian, recognizing the motion mass center of the pedestrian based on the image, and constructing the motion trail of the pedestrian; according to the pedestrian wandering behavior criterion, performing wandering behavior identification on the motion trail of the pedestrian to obtain an identification result; wherein the establishment of the pedestrian wandering behavior criterion comprises the following steps: drawing possible wandering motion trails in different scenes by referring to common wandering behaviors in public places; and analyzing the wandering motion trails of the pedestrians to obtain a pedestrian wandering behavior criterion. Compared with the prior art, different wandering motion modes in different scenes are considered, and pertinence of pedestrian wandering behavior recognition is improved.

The invention relates to the technical field of action analysis, in particular to a multi-angle dance video analysis system which comprises an action capture feature extraction module, an action data multi-scale analysis module, an action analysis and mapping module and a style classification and prediction module. According to the method, through a multi-angle video recording and Vietories-Rips complex method, the space connection mode of dance is effectively identified and extracted, the geometric structure of the action is captured, three-dimensional action data analysis and multi-scale persistent homology analysis are provided to enhance analysis on the time sequence and the space layout of the action, and the dance style and the action mode are accurately distinguished; high sensitivity to fine difference of styles is brought, dance style evolution can be accurately predicted, action data is mapped to a low-dimensional space through multi-dimensional scale analysis, data visualization and analysis capacity is remarkably improved, action similarity and difference are displayed, dance education, choreography and therapy are assisted, full-process optimization of data analysis is achieved, and the method is suitable for popularization and application. And a comprehensive and deep dance motion analysis tool is provided.

An accessibility diagnosis system is provided for a motion stabilization device for stabilization of a cosmetic applicator. The system includes a mobile user device that includes a touch sensitive display and a motion sensor, the mobile user device including processing circuitry configured to: display a request to a user for an input of a specific drawing motion or a specific movement of the mobile user device, and collect information indicating a movement pattern of the user's hands based on the results of the user's input in response to the request; and a server device that is connected to the mobile user device via a network, the server device including processing circuitry configured to receive the collected information from the mobile user device, determine an amount of motion stabilization required to be set for the motion stabilization device based on the collected information, and output the determined amount of motion stabilization.

The invention provides a cardiopulmonary function training method and device, a computer readable storage medium, a computer program product and terminal equipment. The cardiopulmonary function training method comprises the steps that a target motion mode is determined according to physiological information of a user and first motion information, and the target motion mode is matched with a corresponding target heart rate interval; acquiring second motion information, wherein the second motion information comprises physiological feature data of the user and acceleration data of equipment used by the user; determining a suggested stride frequency according to the second motion information, wherein the heart rate of the user under the suggested stride frequency is close to the target heart rate interval or is within the target heart rate interval. The invention provides a scheme for flexibly carrying out stride frequency training and improving the cardiopulmonary function training effect.

A method for evaluating a user's performance of a medical procedure is disclosed. The method comprises receiving a plurality of training measured metrics collected from a sensor worn by the user during training medical procedures, where these metrics include physiological and biomechanical parameters. An algorithm is trained to identify types of medical procedures, procedural segments, and performance benchmarks. During the medical procedure, the sensor collects similar metrics, which are analyzed to identify the procedure type, procedural segments, and deviations from benchmarks. Feedback is provided based on these deviations. Additional steps include using a training model comprising a neural network with machine learning algorithms to analyze metrics, updating the training model with new data, initiating sensor calibration, detecting a predetermined movement pattern to start data collection, and identifying spatial reference points. The method further comprises providing real-time feedback to the user through haptic, auditory, and visual modalities based on performance deviations.

The invention discloses a novel multi-metamorphic mechanism for multifunctional design, which is an 8R single-ring connecting rod mechanism and comprises eight connecting rods and eight revolute pair joints, and the connecting rods are connected through the revolute pair joints; the eight connecting rods are connected end to end. According to the novel multiple metamorphic mechanism disclosed by the invention, different single-degree-of-freedom 7R metamorphic mechanisms can be formed by stiffening different revolute pairs. Each derivative metamorphic mechanism has various motion branches and bifurcation structures, the mechanism can be bifurcated when moving to a bifurcation point, and enters another motion branch from one motion branch, so that the metamorphic process of the mechanism is realized; by means of the different motion branches, different motion modes can be achieved, and then different functions are achieved. The novel multi-metamorphic mechanism has multiple different motion branches, so that different motion modes can be derived, and different function applications such as a carrying function, a rolling function, a hooking function, a wriggling function and in-hand rotation can be realized by analyzing motion characteristics of the different motion modes.

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

A computing system obtains a plurality of images and associated image information. Each of the plurality of images depicts a particular Point of Interest (POI). For each of the plurality of images, the image information is descriptive of a plurality of image characteristics, such as a geolocation characteristic indicative of a geolocation at which the image was captured and / or an interaction metric derived from previous user interactions with the image. The computing system selects a particular image of the plurality of images based on the image information and generates a movement pattern for a camera viewpoint within a three-dimensional environment. The movement pattern for the camera viewpoint moves around a three-dimensional representation of the particular POI within the three-dimensional environment, and a starting position for the movement pattern is based, at least in part, on the geolocation at which the particular image was captured.

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.

A camera-based optokinetic motor device (OMR) for assessing visual acuity in rodents, consisting of: a. a two-chamber structure consisting of: ◯ an outer rotating chamber with an inner surface of alternating black and white vertical stripes, designed to produce an optokinetic visual stimulus; ◯ an inner static chamber, which is transparent and centrally positioned within the outer chamber and configured to accommodate the test object, wherein the inner chamber contains a centrally arranged, non-rotating platform for placing the rodent; b. a motorized rotation mechanism, comprising: ◯ a stepper motor that is operationally coupled to the outer chamber to enable controlled rotation at a fixed and adjustable speed; ◯ a switch-controlled rotation direction system that enables bidirectional movement, allowing both clockwise (CW) and counterclockwise (CCW) rotation at a predefined speed of 10 revolutions per minute (rpm); c. a high-resolution imaging system, consisting of: ◯ a high-resolution (HD) camera positioned at an optimal height above the device to capture the rodent's movement response in real time; ◯ a motion tracking module, either software-based or hardware-integrated, to analyze and quantify the subject's spatial frequency threshold (SFT) in response to the moving stimulus; d. a closed test environment, consisting of: ◯ a non-transparent housing surrounding the dual-chamber structure, forming a closed box configuration approximately 45 cm long and wide and 30 cm high to minimize interference and distractions from external light; ◯ an internal white LED lighting system on the inner wall of the housing, which ensures uniform lighting conditions and thus guarantees the clarity of the recorded visual data; e. a data acquisition and processing module configured to: ◯ Record the video data received from the HD camera; ◯ Processing and analyzing rodent movement patterns using the rotating stimulus to determine the optokinetic reflex (OKR) and visual acuity response; ◯ Save and export the collected data for later statistical analysis.

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.

Systems and methods are disclosed for device movement-based authentication. One method comprises receiving contextual data from one or more sensors of a user device and determining a device movement pattern based on the received contextual data. The determined device movement pattern is compared with a device movement-based signature associated with a user of the user device. If the determined device movement pattern matches the device-movement based signature within a predetermined threshold, the user is authenticated for an electronic transaction. If the determined device movement pattern does not match the device-movement based signature, a notification indicating authentication failure is sent to the user device.

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.

Systems and methods capable of determining appropriate prioritization of Artificial Intelligence training in a virtual environment and in a multi-agent system. A generation system may provide a heatmap to an avatar during gameplay, using the generation system, identifying an area of movement of the avatar within a game. The generation system may perform an analysis of the positioning of the heatmap using machine learning on the heatmap to identify a movement pattern of the avatar based. The generation system may, in response to inferring the areas of movement within the game, divide the areas based on movement, wherein the areas of the heatmap having lower values of movement have a lower priority area and the areas of the heatmap having the greater values of movement have a higher priority area. The generation system allows for the generation of soft / rigid body elements from evolution and expansion of singular elements.

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).

The invention relates to a motion-based user interface system and method. Some examples of the present disclosure relate to systems and methods for moving a virtual object in a three-dimensional environment according to detected movement of an electronic device. In some examples, the electronic device detects movement according to a first movement pattern or a second movement pattern described more detailed herein. In some examples, in response to detecting the first movement pattern, the electronic device applies a first correction factor to movement of a virtual object in the environment. In some examples, in response to detecting the first movement pattern, the electronic device applies a first correction factor to movement of a virtual object in the environment.

A medical analyzer and coagulation profiler performs various interrogations on specimens. A motor with reduction gearing moves and a video camera observes the samples, the cartridges or parts thereof. Changes in images are compared and recorded with a central processor that controls a display. Power supply, temperature controller, motor and gearing are mounted in a box which attaches to a smartphone. The smartphone provides the video camera, illumination and central processor that control the movement, temperature and display. The device makes testing simpler for small hospitals, clinics, ambulances, remote locations and individuals and controls a number of parallel or serial devices operating simultaneously or sequentially. A cartridge insertion actuates a circular motion to generate a blood profile based on changes. Change is analyzed with a video camera and processor such as in a smartphone and is plotted to show an amplitude and time. A smartphone provides a specific movement pattern.

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.

An electronic device and method for data-driven assistance for users involved in physical activities is provided. The electronic device receives first sensor data associated with a movement pattern of one or more parts of a body of a user and receives first information associated with a location where the user performs the physical activity. The electronic device determines one or more first indicators which are likely to have affected the user or the performance of the user in the physical activity. Thereafter, the electronic device generates presentation data based on an application of a first machine learning model on the determined one or more first indicators and the received first information. The generated presentation data includes one or more improvement suggestions for the user in relation to the physical activity. The electronic device controls a display device to display the presentation data.