227 results about "Movement analysis" patented technology

Some embodiments provide a device, method, system, computer program product and user interface for pointer movement analysis with modal continuous controller conversion. Specifically, some embodiments adapt movements issued from a mouse input device, trackpad, or touchscreen to adjust a position of a UI element. Some embodiments analyze a first set of movements and adapt a subsequent second set of movements to adjust the position of the UI element within a range of UI element positions when the first set of movements satisfies a movement threshold. The movement threshold includes a spiral pattern. In some embodiments, adjusting the position of the UI element includes performing scrolling within a scroll area based on the second set of movements when the first set of movements satisfies the spiral pattern.

A system, apparatus, method, and machine readable medium are described for performing eye tracking during authentication. For example, one embodiment of a method comprises: receiving a request to authenticate a user; presenting one or more screen layouts to the user; capturing a sequence of images which include the user's eyes as the one or more screen layouts are displayed; and (a) performing eye movement detection across the sequence of images to identify a correlation between motion of the user's eyes as the one or more screen layouts are presented and an expected motion of the user's eyes as the one or more screen layouts are presented and / or (b) measuring the eye's pupil size to identify a correlation between the effective light intensity of the screen and its effect on the user's eye pupil size; capturing audio of the user's voice; and performing voice recognition techniques to determine a correlation between the captured audio of the user's voice and one or more voice prints.

Motion Analysis is used to classify or rate human capability in a physical domain via a minimized movement and data collection protocol producing a discreet, overall figure of merit of the selected physical capability. The minimal protocol is determined by data mining of a more extensive movement and data collection. Protocols are relevant in medical, sports and occupational applications. Kinematic, kinetic, body type, Electromyography (EMG), Ground Reactive Force (GRF), demographic, and psychological data are encompassed. Resulting protocols are capable of transforming raw data representing specific human motions into an objective rating of a skill or capability related to those motions.

A system is disclosed for monitoring, recording and analysis of exercise in an exercise machine with a device, such as a handle, that enables a user to push or pull against a resistance. A sensor or “load cell” mounted on the machine produces an electronic signal representing the instantaneous force applied by the user, and an electronic computer or the like, is coupled to receive the electronic signal, for storing values representing the force as a function of time. In another embodiment, a system comprises a resistance member for providing resistance to movement by a user, a sensing device coupled to the resistance member, a force sensor, and a CPU. The sensing device generates a first signal representing the position of the resistance member, and the force sensor generates a second signal representing the force applied to the resistance member by the user. The CPU processes the first and second signals to generate useful images, displays, and audio signals.

A system, apparatus, method, and machine readable medium are described for attesting an authenticator. For example, one embodiment of an apparatus comprises: a processor to execute an app; and an authenticator to generate a first authentication key and to securely store the first authentication key, the authenticator to generate an attestation object usable by a relying party to confirm authenticity of the authenticator, the attestation object including a first component provided by the authenticator, a second component provided by the app, and a signature generated by the first authentication key over a combination of the first and second components.

Dynamic nanomechanical analysis of a sample is performed by using a cantilever probe that interacts with the sample using a force applied across a wide range of frequencies that includes frequencies greater than 300 Hz. The motion of the cantilever probe is detected in response to the applied force over the range of frequencies and analyzed over at least a portion of the wide range of frequencies to determine a mechanical response of the sample, preferably including quality factor and modulus of the sample. The analysis of the motion of the cantilever probe is preferably performed in terms of amplitude, phase, and frequency of both the probe and the sample and preferably, where the applied force is analyzed to determine both a real and an imaginary modulus of a mechanical response of the sample. Preferably, the force is applied so as to produce a minimum of phase and amplitude response variation in the absence of the sample. Furthermore the motion of the cantilever can be flexural or torsional and combinations thereof.

The present invention relates to a low cost motion capture system for clinical utilizations, such as for upper-extremity (UE) motor control rehabilitation. As contemplated herein, the present invention records range of motion data and graphs rotation, flexion, and abduction motions of a targeted joint in real time. In certain embodiments, the hardware of the system may include a simple motion node attachment system, motion node labels, a user's manual, and anatomical diagrams to increase accuracy of motion node placement. In other embodiments, additional features include acceleration data collection and graphical display, rhythmic sound cues for assistance in motion emulation, audio cues for patients with visual impairments, hard copy reports of session results, real time range of motion displays, and a spatial visualization option.

A detection and tracking device for moving target based on movement camera comprises a characteristic detection unit, finding characteristic point in a first frame of inputted video frequency; characteristic tracking unit, tracking characteristic point found by characteristic detection unit in following frame; latent movement detection unit, finding latent movement point from characteristic point tracked by characteristic tracking unit; movement analysis unit, determining movement point from latent movement point found by latent movement detection unit; target tracking unit, tracking movement target area from inputted video frequency according to given initial position. The inventive movement target detection and tracking system, device and method provide movement target position for 3A imaging at moving platform.

The work movement analysis method for dividing a moving picture of a worker's work movement into a plurality of movement sections in an apparatus having display, storage, and processing units includes in the processing unit the steps of: defining a plurality of movement section classification buttons and providing the buttons to an operator; reproducing the moving picture in the display unit; allocating movement section identification information defined by a specific movement section classification button to a moving picture of a work; storing a position of a moving picture in the storage unit as an end position of a movement section; defining an end position of a previous movement section as a start position of the movement section and a reproduction start position of a moving picture of the work movement as the start position in a case of no end position, and dividing the work movement into the movement sections.

The invention belongs to the field of target tracking, and in particular relates to a fast target tracking method with an improved SIFT algorithm. The fast target tracking method comprises the steps of: obtaining a dynamic video by a collection device, obtaining a target image from the dynamic video, extracting SIFT features of the target image and storing into a database, matching the SIFT features of the target with SIFT features of every frame image in the dynamic video, after detecting the target, determining the position of the target in the image, initializing a Mean Shift template according to the area of the target position, iteratively tracking every frame image behind the dynamic video by the Mean Shift, and determining the update frequency of the template according to the tracking target. The fast target tracking method achieves a very effective way for fast tracking objects, and can be widely applied to fields of video monitoring, movement analysis and the like. Compared with the traditional SIFT tracking method, the fast target tracking method with the improved SIFT algorithm is greatly promoted in speed and can completely meet the requirement of being real-time.

The invention relates to a set of motion sensing devices HS mounted above and below the injured joint, a mobile application MobApp that receives sensor data, and a web server WS. The mobile application comprises a physiotherapists interface MPTI and a patient interface MPI, an Exercise definition module EDM, an assessment module ASMD and the movement analysis module MAM. The physiotherapist interface MPTI shows the patients their progress, the list of scheduled exercises, receives feedback and delivers assessments. The web server WS hosts a cloud-based database DB which keeps the relevant data, a Machine learning unit MLU and a physiotherapist interface WPTI. The claimed method, ensures an optimized monitoring of the physiotherapy of joints, by neutralizing within the Calibration and compensation unit CCU the influence of the position and drift of the motion sensors and also by implementing the Machine learning unit MLU and relevant algorithm.

The embodiment of the invention provides a brand evaluation method and a brand evaluation device. The method comprises the steps: receiving a brand keyword and a brand attribute; determining a brand data source associated with the brand attribute in the Internet and acquiring brand data associated with the brand keyword from the brand data source; and exposing and analyzing the brand data associated with the brand keyword to determine an expression index of the brand keyword, carrying out text analysis on the brand data associated with the brand keyword to determine a value index of the brand keyword, carrying out forward movement analysis on the brand data associated with the brand keyword to determine a recommended index of the brand keyword, and calculating the weighted values of the expression index, the value index and the recommended index according to a predetermined weight.

The invention discloses a robot spraying trajectory planning method based on a large complex curved surface model. The method comprises the following steps that firstly, mathematical model offline planning is conducted, specifically, region division is conducted on a workpiece model, and robot positions corresponding to all sub-regions are determined; spray gun trajectories of all the sub-regionsare determined by adopting an STL file-based parallel slicing algorithm, and a robot motion program is generated; and finally motion analysis and interference checking are conducted on the robot motion program. If the check is disqualified, region re-division needs to be conducted, the robot positions corresponding to all sub-regions are determined, and if the check is qualified, an actual spraying planning part is entered. The actual spraying planning comprises the following steps that the actual pose of the workpiece is determined by using a vision system, corresponding coordinate transformation is conducted on an offline planning result, simulation analysis is conducted on the transformed motion program, finally, actual spraying can be conducted if the analysis is completely qualified,and otherwise, the offline planning result is properly re-adjusted. By adopting the method, the efficiency of large-scale complex curved surface spraying can be improved, the cost is reduced, and process parameter changing is easy to realize.

Movement analysis is expanded to assist not just in determining the emotional, cognitive, and performance processes of subjects, but to also predict and explain a subject's actions. The analysis is particularly applicable to leaders, but may be applied to other subjects. Additionally, non-expert practitioners may more readily benefit from analyzing a subject's movements.

Emitter target range and heading are estimated from bearing measurements enhancing bearings-only estimator convergence to a target track, and permitting optimization of an observer position relative to the target at the end of the total bearing measurement period. One or more estimates of the target range, speed and heading made from bearing measurements before an observer maneuver are used to determine the most appropriate observer maneuver giving complete bearings-only target-motion-analysis observability. A set of parameters characterizing a set of potential emitter signal sources is generated based on measured emitter characteristics. A most probable set of emitter platforms is identified and the emitter operating mode and corresponding platform set are associated with a kinematic regime set. A specific speed or discrete set of speeds best adapted to a set of all possible platform missions, emitter speed as a continuous function of emitter range, and emitter range are all determined.

The invention relates to a system and a method for human body movement identification of a combined sensor. The system comprises a power supply module, a data acquisition module, a signal processing module, a micro-controller module, a wireless communication module and a movement analysis machine, wherein the power supply module is used for supporting the normal working of the system, the data acquisition module is used for acquiring human body movement signals and is composed of an inertia sensor which is horizontally placed on the front portion of the waist of a human body and a flexible sensor which is placed on the elbow and the knee of the human body, the signal processing module is used for processing data signals and is respectively connected with the inertial sensor and the flexible sensor through leads, the micro-controller module is used for controlling and coordinating the entire system, the wireless communication module is used for transmitting data to the movement analysis machine, and the movement analysis machine is used for movement contrast and is a computer with a built-in movement identification model. The method is the identification of six kinds of daily human movement of walking, running, jumping, falling, standing and sitting with the system. The system and the method for the human body movement identification of the combined sensor are reliable to use, can be used for obtaining movement information of human torsos, and have the advantages of being simple and convenient.

The invention provides a video signal image processing method and a device. The method comprises following steps of movement analysis including extracting characteristics of original image and calculating overall situation movement affine matrix among successive frames, wherein the overall situation movement affine matrix comprises movement parameters among the successive frames and the successive frames of the original image form the movement track of the original image; parameter smoothing including filtering the movement parameters among multiple successive frames, obtaining a movement parameter between the current frame and the previous frame after smoothing, and forming the movement track after the smoothing according to the movement parameter of the successive frames after the smoothing; and affine transformation including forming a new overall situation movement affine matrix and calculating the corresponding image of the current frame after the smoothing according to the movement parameter between the current frame and the previous frame after smoothing and the difference between the movement track of the original image and the movement track after smoothing. In this way, translation, rotation or shaking of overall movement of video images can be reduced or removed.

Motion analysis is used to classify or rate human capability in a physical domain via a minimized movement and data collection protocol producing a discreet, overall figure of merit of the selected physical capability. The minimal protocol is determined by data mining of a more extensive movement and data collection. Protocols are relevant in medical, sports and occupational applications. Kinematic, kinetic, body type, electromyography (EMG), ground Reactive Force (GRF), demographic, and psychological data are encompassed. Resulting protocols are capable of transforming raw data representing specific human motions into an objective rating of a skill or capability related to those motions.

Lock-out mechanisms for driver handheld mobile devices are provided to prevent operation of one or more functions of handheld mobile devices by drivers when operating vehicles based on device location data and device motion data within a vehicle by wirelessly communicating with at least one wireless station access point located inside of the vehicle. The lock-out mechanisms disable the ability of a handheld mobile device to perform certain functions, such as texting or browsing, while one is driving. In one embodiment, a handheld mobile device may provide a lock-out mechanism without requiring any modifications or additions to a vehicle by using a motion analyzer, a mobile device position locator and a lock-out mechanism. In other embodiments, the handheld mobile device may provide a lock-out mechanism with modifications or additions to the vehicle, including the use of wireless signals transmitted by the vehicle or by a wireless station access point disposed within the vehicle.

A movement analysis apparatus includes: a data acquiring unit that acquires moving image data including a series of image data obtained by photographing a human body; a storing unit that stores target range designating information that designates, within the image data, a moving range of a predetermined part of the human body; a detecting unit that designates, for each set of image data included in the obtained moving image data, a plurality of image areas that correspond to the moving range of the predetermined part of the human body that is designated by the target range designating information, and detects, from the plurality of designated image areas, an image area including the predetermined part of the human body; and an output unit that outputs information representing the results detected by the detecting unit.

A movement analysis display apparatus includes a analyzing unit for analyzing waveform data of a time series which is acquired from a movement sensor, and a display unit for displaying an analysis result that is analyzed by the analyzing unit. The analyzing unit includes a movement waveform generating section for generating a movement waveform from the waveform data, an energy balance value calculating means for calculating a movement energy ratio in opposed movement directions in a velocity waveform, an envelope curve generating section for generating an envelope curve at a given time width in a distance waveform, and a time integration curve analyzing section for integrating a movement waveform with respect to time.

A vehicle trunk opening device including an approach checking unit which checks whether a user approaches a trunk of a vehicle and outputs the checked result as an access signal; a movement information acquisition unit for acquiring movement information of the user by responding to an acquisition control signal generated when the vehicle is stationary; a movement analysis unit which analyzes whether the user's movement corresponds to a desired target movement of opening a trunk through the acquired movement information, and which outputs the analyzed result; a trunk opening unit for opening the trunk by responding to an opening control signal; and a main control unit which generates the acquisition control signal by responding to the access signal, and which generates the opening control signal by responding to the analyzed result.

To enable a user such as a store manager to easily grasp movement of persons at a location within a monitored area, a PC for analyzing the movement of persons within the monitored area is provided with a measurement condition setter that causes a user to perform an input operation of specifying a measurement area in a region in the monitored area and specifying an entry zone and an exit zone of a person relative to the measurement area, and sets the measurement area and the entry and exit zones as a measurement condition; a traffic line acquirer that acquires traffic line information of each person detected; a moving person detector that detects, in the measurement area, persons matching movement patterns defined by the entry and exit zones; and a screen generator that generates output information representing a state of movement of persons in relation to the measurement area.

A system which extracts motion data from a video image of an infant, and determines synchronism, symmetry, and / or coordination among the limbs. The system uses the synchronism, symmetry, and / or coordination results to determine whether the infant has a disease and / or what disease it may be. The system uses as an index for coordination one or more of: a movement start / stop order and acceleration of the markers; the trajectory, speed, or acceleration of a midpoint of a line connecting markers attached to various combinations of the arms and legs; and the trajectory, speed, and acceleration of a gravity center of a plane connecting three markers attached to various limbs.

A motion analyzing method includes: acquiring location information of at least one of a sporting tool and a subject in swing motion based on an inertial force generated by the swing motion in time series; acquiring analysis information of the swing motion based on the inertial force; acquiring a time when the analysis information is switched with respect to a preset threshold value; and correlating information of the time with the location information and outputting the information.

The invention discloses a multifunctional child somatic sensation educating system which comprises an input module, a processing module, a control module and an output module. The multifunctional child somatic sensation educating system is further characterized by further comprising a data access module, a movement analysis module, a voice analysis module and a music analysis module. The control module comprises an object cognition control module, a pronunciation correction control module, a dance learning control module, a musicality cultivation control module and a movement arrangement control module. The input module, the processing module, the control module and the output module are connected mutually in sequence, and the data access module, the movement analysis module, the voice analysis module and the music analysis module are respectively connected with the processing module. The multifunctional child somatic sensation educating system has the advantages that the educating system has educational modes of object cognition, pronunciation correction, dance learning, musicality cultivation and movement arrangement at the same time, the educational modes are rich and varied, and the educating system not only can help children to learn knowledge, but also can help the children to do physical exercise, mold character and stimulate imagination.

The invention provides a vocal organ visible speech synthesis system which comprises a voice frequency analysis module, a parameter mapping module, an animation drive module and a motion analysis module; wherein, the voice frequency analysis module is used for receiving the input speech signal of a speaker, judging a mute section according to energy information, coding non-mute section of speech and outputting a speech line spectrum pair parameter; the parameter mapping module is used for receiving the speech line spectrum pair parameter transmitted in real time from the voice frequency analysis module, converting the speech line spectrum pair parameter into a model motion parameter by using the trained Gaussian mixture model; the animation drive module is used for receiving the model motion parameter generated in real time by the parameter mapping module, driving the motion of key points of a virtual vocal organ model so as to drive the motion of the whole virtual vocal organ model. According to the vocal organ visible speech synthesis system, the motion of the model is driven by the corresponding motion parameter generated directly by a frequency domain parameter of the input speech, and therefore, the vocal organ visible speech synthesis system has the advantage of being free from limitations of an online database and a physiological model.