439 results about "Motion sensing" patented technology

Techniques and apparatuses are described that perform audioplethysmography and motion-sensing data fusion. Fusing motion-sensing data with audioplethysmography expands the situations in which audioplethysmography can operate. In one aspect, audioplethysmography and motion-sensing data fusion can be used for motion-artifact filtering. With motion-artifact filtering, noise caused by motion of a user can be attenuated to improve sensitivity and accuracy for audioplethysmography. This performance improvement expands the ability of audioplethysmography to support use cases during situations in which the user engages in an activity. In another aspect, audioplethysmography and motion-sensing data fusion can expand a functionality of a hearable to include activity detection and / or activity classification. While activity detection and / or activity classification can provide additional contextual information for other use cases associated with audioplethysmography, either can also be used to control an operation of the hearable and / or a computing device.

The invention relates to a robot positioning method and device and a robot. The method comprises the following steps: acquiring motion sensing data and local scene point cloud information, and performing local pose estimation based on the motion sensing data and the local scene point cloud information to obtain current local pose information; projecting the local scene point cloud information to obtain local scene contour data, and determining a target map corresponding to the local scene contour data in a preset global map; acquiring a corresponding pose correction parameter based on the matching degree of the target map and the local scene contour data; performing global pose conversion on the current local pose information to obtain initial global pose information, and correcting the initial global pose information by using pose correction parameters to obtain target global pose information; and fusing the current local pose information and the target global pose information to obtain target pose information. The method can improve the positioning accuracy of the robot.

The invention discloses a reference video object segmentation method based on semantic consistency and motion perception. The method comprises the following steps: 1, constructing semantic prompt information and video frame information of a reference video object segmentation data set; 2, preprocessing the reference video object segmentation data set; 3, establishing a reference video object segmentation model based on semantic consistency and motion perception: designing a double-branch decoupling strategy for decoupling feature information at semantic and visual levels so as to extract static and motion information of text description and visual features; a hierarchical motion sensing module is designed to capture and align motion information between different frames, and analyze short-term and long-term motion information, so that the model obtains a sensing ability for a long-term motion mode; the semantic consistency module is designed to align semantic description and video features, so that the accuracy of target selection and the integrity of masks are improved, and false detection of negative samples is avoided; a perceptual dynamic fusion mechanism is designed to be used for embedding text information into a visual feature space, so that visual features can obtain text semantic information, and the cross-modal understanding ability of the model is enhanced; 4, constructing a loss function, updating model parameters, setting training parameters, and training to obtain an optimal weight; and 5, detecting the test set image based on the optimal weight to obtain a final segmentation result. According to the method, static and dynamic information is effectively decoupled, the sensing ability to an object motion mode is enhanced, and the segmentation performance is improved.

The invention relates to the field of medical information monitoring, and discloses a doctor monitoring bracelet for receiving infusion information of a patient, comprising: a multispectral sensing module for collecting an original physiological light intensity signal of the wrist of the patient; the motion sensing module is used for collecting motion signals; the micro-electro-mechanical motion compensation module is configured on the multispectral sensing module; the processor is electrically connected with the multispectral sensing module, the motion sensing module and the micro-electro-mechanical motion compensation module; and the communication module is electrically connected with the processor. By integrating a high-sensitivity multispectral sensing module and a micro-electro-mechanical active motion compensation system and combining an advanced signal processing algorithm, the accuracy of real-time monitoring of key vital signs of a patient in a complex infusion scene is remarkably improved, more reliable patient infusion information is provided for a subsequent multi-head infusion intelligent switching control system, and the infusion safety of the patient is improved. High fidelity of a data source is ensured, and tedious work of medical staff is reduced.

The utility model relates to a motion sensing mechanism based on Internet of Things home system, fire extinguishing device and Internet of Things home system, the motion sensing mechanism comprises: a temperature sensing trigger unit, which comprises a temperature sensing assembly and a sliding assembly, the temperature sensing assembly is in contact connection with the sliding assembly, the temperature sensing assembly senses the ambient temperature, and the sliding assembly is in contact connection with the sliding assembly; the sliding component is supported and positioned under the condition that the environment temperature is lower than the set temperature, and is separated from the sliding component under the condition that the environment temperature reaches the set temperature, and the sliding component generates displacement; the detection unit is used for detecting a displacement signal of the sliding assembly; and the control unit is connected with the detection unit, and the control unit is configured to control the Internet of Things home system to be switched from the safety scene mode to the fire scene mode according to the displacement signal detected by the detection unit. According to the utility model, automatic turn-off of the gas pipeline, the gas stove, the power supply and the like can be realized in case of fire, fire intensification can be avoided to a certain extent, and life and property loss of users is reduced.

Systems and methods for predicting problem behavior in individuals with developmental and behavior disabilities. A plurality of sensors are configured to collect multimodal data signals of a subject individual including a wearable upper body motion sensing device with a plurality of inertial measurement units (IMUs). An electronic controller is configured to receive output signals from each of IMUs and to model an upper body position of the subject individual based on the output signals from the IMUs. A trained machine-learning model is then applied by providing an input data set that includes multimodal signal data (e.g., including signal data from at least one IMU) and / or features extracted from the multimodal signal data. The machine-learning model is trained to produce as output an indication of whether a precursor to the problem behavior is detected and, in response to detecting the precursor, a notification (or alarm) is generated.

The invention discloses an ultrafast motion sensing floating gate transistor based on Van der Waals heterojunction and application thereof. The floating gate transistor comprises a back gate substrate, a Van der Waals heterojunction channel layer, a source electrode and a drain electrode, the source electrode and the drain electrode are arranged on the two sides of the channel layer, the back gate substrate is heavily doped silicon, the surface of the heavily doped silicon is covered with hafnium oxide / aluminum oxide / hafnium oxide (HfO2 / Al2O3 / HfO2) used for nonvolatile light storage, and the Van der Waals heterojunction channel layer is composed of bismuth oxygen selenium-palladium selenide nanosheets used for sensing. The floating gate transistor disclosed by the invention has the capability of quickly responding to an ultraviolet-near infrared wide spectrum and non-volatile storage of light at the same time, and the sensitive spectral response range and responsivity of the photoelectric detector can be effectively improved, so that the integration of dynamic target optical signals in devices in a space domain and a time domain is realized.

The disclosure provides devices, systems, and methods for physical therapy. Electrical signals are applied to a subject via electrodes in a device worn on the body part receiving the therapy. The device can be operated remotely. The device can use artificial intelligence to evaluate and design physical therapy routines using the electrodes.

The invention relates to the technical field of medical rehabilitation, in particular to a lung rehabilitation training auxiliary system based on virtual reality. Comprising an equipment wearing module, an education module, a virtual scene generation module, a rehabilitation training scheme customization module, a data acquisition and monitoring module, a real-time feedback and guidance module, a training data recording and analysis module and a user interaction and management module. The motion sensing device, the respiration monitoring device and the like are utilized, by means of the interaction function of the motion sensing device, the respiration monitoring device and the like, limb actions and respiration conditions of a patient are captured in real time, interaction with elements in the virtual environment is carried out, real-time feedback and accurate guidance of training actions and respiration states of the patient are achieved, the training interestingness is greatly improved, and the training effect is improved. And the lung rehabilitation training auxiliary system based on virtual reality customizes personalized rehabilitation training schemes fitting own conditions for different patients, training item selection, intensity arrangement, frequency setting and the like can be varied from person to person, and the promotion effect of rehabilitation training on lung function recovery is played to the maximum extent.

Techniques and apparatuses are described that perform audioplethysmography and motion-sensing data fusion. Fusing motion-sensing data with audioplethysmography expands the situations in which audioplethysmography can operate. In one aspect, audioplethysmography and motion-sensing data fusion (202) can be used for motion-artifact filtering (206). With motion-artifact filtering (206), noise caused by motion of a user (106) can be attenuated to improve sensitivity and accuracy for audioplethysmography. This performance improvement expands the ability of audioplethysmography to support use cases during situations in which the user (106) engages in an activity. In another aspect, audioplethysmography and motion-sensing data fusion (202) can expand a functionality of a hearable (102) to include activity detection (208) and / or activity classification (210). While activity detection (208) and / or activity classification (210) can provide additional contextual information for other use cases associated with audioplethysmography, either can also be used to control an operation of the hearable (102) and / or a computing device.

The invention discloses an unmanned aerial vehicle autonomous landing system based on UWB and visual fusion, and the system comprises a ground unmanned vehicle and an unmanned aerial vehicle, and the ground unmanned vehicle is in communication connection with the unmanned aerial vehicle. The ground unmanned vehicle is further provided with a ground station, a landing mark and a main control module used for controlling movement output of the ground unmanned vehicle, the main control module is connected with a wireless remote control module, the main control module is further provided with a monitoring unit, and the ground station obtains flight information of the unmanned aerial vehicle for path planning; the unmanned aerial vehicle is further provided with an information collection module, a motion sensing module, a controller module and a power module, and the information collection module is used for collecting position information of the landing mark. Compared with the prior art, the unmanned aerial vehicle autonomous landing system and the unmanned aerial vehicle autonomous landing method based on UWB and vision fusion have the advantages that the unmanned aerial vehicle autonomous landing system and the unmanned aerial vehicle autonomous landing method are used by a combined navigation system formed by UWB and IMU for a scene of cooperative operation of an unmanned aerial vehicle and an unmanned vehicle.

The invention discloses an external hanging type motion sensing control system for shooting games and training. The external hanging type motion sensing control system comprises a data acquisition module, a data processing module, a power management module, an output display module, a personal area network interaction module and a cloud service module. The data acquisition module is used for acquiring data required for resolving the spatial attitude of a user through a sensor; the data processing module processes the collected sensor data, maps the sensor data into the actual state and operation of a user, and stores and manages user-defined control parameters; the power supply management module is used for supplying power to the somatosensory control equipment and managing the power supply of the somatosensory control equipment; the output display module is used for displaying the state information of the somatosensory control equipment; the personal area network interaction module is used for communication and information interaction; and the cloud service module is used for a user to customize sensor parameter mapping and equipment information management through a mobile phone. The invention further provides a somatosensory control method which has a wide application scene.

The invention relates to the technical field of data processing, and discloses a mobile robot voice data control method and system based on artificial intelligence. The method comprises the steps that three-channel voice data streams are collected through a multi-channel microphone array, and time synchronization processing is carried out on the three-channel voice data streams and robot motion state data; calculating a motion intensity value according to the motion state data, and performing motion compensation through an MSAP algorithm; inputting the compensated voice signal into a double-path convolutional neural network to extract motion sensing voice features; jointly coding the speech features and the motion state vectors through an MS-LSTM network, and obtaining a speech recognition text by adopting a CTC loss function; and carrying out cross-modal fusion on the text and the robot state information, and carrying out intention recognition through a hierarchical classifier to obtain a structured control instruction. The technical problem that the mobile robot is poor in voice instruction recognition accuracy and high in control delay in a dynamic environment is solved.

The invention provides a Parkinson's disease risk prediction method based on deep learning, an electronic device and a medium, and the method comprises the steps: integrating medical data from different sources, extracting visual features from a hand-drawn spiral line image through a CNN, capturing the dynamic changes in motion and voice from motion sensing data and voice data through an LSTM, and carrying out the prediction of the Parkinson's disease risk. Various data sources can be comprehensively analyzed; the importance of different source features is weighted through an attention mechanism, so that more dynamic and adaptive feature fusion is realized; according to the method, the complex relationship and interaction among different data types can be captured, subtle and complex pathological characteristics of the Parkinson's disease are identified, and the accuracy and efficiency of risk prediction of the Parkinson's disease are improved.

The invention discloses a teleoperation tactile feedback manipulator system which comprises a bionic manipulator, a somatosensory glove and a hand posture recognition module, the bionic manipulator is in wireless communication with the somatosensory glove, and the hand posture recognition module is in wireless communication with the bionic manipulator and the somatosensory glove. According to the teleoperated tactile feedback manipulator system, through cooperative work of the somatosensory glove and the bionic manipulator, an operator can visually and flexibly control the manipulator, the operation precision and efficiency are improved, the flexible pressure sensor is used for detecting the grabbing pressure in real time, and a pressure signal is fed back to the somatosensory glove; the motion sensing glove generates corresponding tactile feedback according to the pressure signal, so that an operator can sense the grabbing condition of the bionic manipulator, the object is prevented from being damaged or sliding off, the operation accuracy and reliability of the bionic manipulator are further improved, support is provided for fine operation in a complex environment, and the motion sensing glove is convenient to install and has good applicability.

The invention discloses a non-therapeutic-purpose hearing and perception training device for non-invasive free mouse training and auditory cortex plasticity stimulation. The device comprises a soundproof box, a training device body in the soundproof box and a processing control system located outside the soundproof box. The training device main body in the soundproof box comprises a training box body, a water and air supply device, an animal action sensing device, an animal position sensing device, a loudspeaker and an illuminating lamp; the training box body comprises an open box and a dark box, and the animal position sensing device is arranged at the relative position of the junction of the open box and the dark box and the relative position of the side wall of the dark box; the processing control system located outside the soundproof box comprises a water and gas control device, a power amplifier and a control computer. The invention further discloses a method and application of the training device in auditory cortex plasticity induction and auditory perception training, and the training device has wide application prospects.

The invention discloses a portable rehabilitation training and intelligent evaluation system, and relates to the technical field of computer-aided diagnosis. The portable rehabilitation training and intelligent evaluation system is mainly composed of wearable motion sensing equipment, a wireless receiver, a portable suitcase, a network communication module and rehabilitation training and intelligent rehabilitation evaluation software. The system has rehabilitation training, rehabilitation evaluation and remote rehabilitation cloud platform interaction functions. According to a patient rehabilitation evaluation result and clinical data, an individualized rehabilitation prescription model is established, a patient individualized rehabilitation prescription is generated, multi-source feature fusion is carried out through a feature fusion formula provided by the invention, a virtual reality scene interactive game is controlled by fused features, and individualized and targeted rehabilitation training is carried out; an artificial intelligence quantitative evaluation model is established through deep learning, a nonlinear dynamic tool is designed to visualize an evaluation result, and a quantitative evaluation result consistent with a clinical Fugl-Meyer scale and an intelligent staging result consistent with a Brunnstrom staging are realized.

The invention provides an intelligent simulation training bomb for ground attack of an unmanned aerial vehicle. The training bomb comprises a bomb body, a thrust reverser, a fairing, a mounting frame, a smoke tank and a control module. Wherein a gas cabin is arranged in the bomb body, and the thrust reverser is composed of an electromagnetic valve and a multi-way pipe. The mounting frame integrates a fuming tank, a control module and a motion sensing module, and the control module calculates the falling speed, the grounding time and the position coordinates in real time based on data of all sensors of the motion sensing module so as to control the electromagnetic valve to be opened, so that compressed gas in the gas cabin is ejected from a reverse thrust gas opening in the circumferential direction of the fairing through the multi-way pipe; in combination with deformation buffering of the fairing made of an elastic material, nondestructive recovery of the training bomb is achieved, and repeated use is facilitated. And meanwhile, the fuming tank is controlled to trigger and release tracing smoke, so that an impact point is marked, and parameters such as latitude and longitude during landing are sent to a ground guide training system to serve as an evaluation basis of throwing precision.

Motion-based management of a logistics container uses elements of a wireless node network including a container node associated with the logistics container and equipped with a motion sensor. The motion sensor detects a motion status (e.g., moving, stationary, accelerating, decelerating) for the logistics container. The container node compares the motion status to a prior motion status, and then identifies a changed motion condition for the logistics container based upon the comparison. In response to the changed motion condition, the container node alters a broadcast profile used by the container node in communicating with other nodes in the wireless node network. The container node may be deployed as an apparatus within a logistics container, be considered together with the logistics container as a motion sensing container node apparatus, and be considered with multiple package ID nodes as a motion-based management system for the logistics container.

Devices and methods for detecting the presence and / or monitoring a movement of an analyte contained in a medium. More specifically, a microcapacitive sensing system is provided that includes a planar micro-capacitive sensor array for detecting the presence of an analyte in a sample media. The sensor structure for sensing recognizing or tracking material movement includes a top planar substrate having a first array non-contacting planar conductive electrodes and a bottom planar substrate having a second array of non-contacting planar conductive electrodes overlapping corresponding aligned electrodes in the first array. The overlapping conducting electrodes are triangular shaped to maximize perimeter-to-area ratio. The first and second planar substrates are parallel and sealed to define a volume therebetween for receiving a medium including the analyte to be detected or monitored. The sensing of movement accomplished by measuring a capacitance change between electrodes in the top substrate and aligned electrodes in the bottom substrate.

The invention relates to the technical field of intelligent wearable equipment, and discloses a motion sensing shoe based on plantar pressure monitoring and a motion trend analysis method. According to the motion sensing shoe, various types of sensors can be adopted to work in a combined mode, state trajectory tracking and pressure change condition collection of the foot are achieved, the problem that the data size is limited due to a single sensor is effectively solved by means of multi-modal data of foot pressure and foot postures, and stability and robustness are improved; real-time data of all the modules are comprehensively analyzed, potential information in the exercise data is fully mined, analysis of the exercise trend is achieved, and therefore more valuable exercise guidance and health suggestions are provided for users.

The invention relates to the technical field of riding wearable equipment, and discloses a riding direction sensing method, system and helmet based on voice control instruction recognition, and the method comprises the steps: receiving a voice instruction of a rider through an embedded voice recognition module; the head motion sensing module detects and analyzes the motion trail and posture change of the head of a rider, monitors the orientation, rotation speed and head motion state of the head of the rider in real time, and senses and obtains head motion data of the head of the rider in real time; acquiring environment sensing data in real time through the environment sensing module, and feeding back the environment sensing data to the cloud navigation processing system; the cloud navigation processing system receives the voice instruction, the head motion data and the environment perception data for fusion processing, and calculates the current position, the driving direction and the target route of the rider; and the cloud navigation processing system generates a corresponding voice navigation instruction and feeds back a riding route planned in real time to the rider through the audio playing module, so that safer and more convenient riding experience is realized.

The invention discloses remote control equipment, which comprises an equipment main body, a first detection component integrated on the equipment main body, a motion sensing module and a controller, the controller is programmed to execute the following logic: when the detection values of the first detection assembly and the motion sensing module jointly meet a preset cooperation condition, the first terminal is remotely controlled to execute a target operation. The remote control accuracy is improved through a dual verification mechanism, instructions such as song switching, volume adjustment and connection equipment switching can be triggered by combining actions such as inclined shaking and knocking when a user presses or touches, an interface is simplified, and functions are expanded. The design of the nested touch control and the optical sensor can distinguish finger operation from clothes mistaken touch, and the terminal switching mechanism of long pressing and knocking further reduces the risk of mistaken triggering. The device can be designed into a ring shape, and is small in size, high in customization and reliable in remote control experience.

An exemplary method and system is disclosed that facilitates the monitoring of worker's productivity and safety, for example, at a construction site and other like labor-intensive occupation and settings. The exemplary method and system provides wearable-based motion sensing and / or proximity sensing between worker and construction equipment. A study discussed herein suggests that sensing at two or more torso locations can provide 95% accuracy in classifying worker's action or motion at a construction site. In some embodiments, as discussed herein, the acquired sensed data are transmitted, over a mesh network, e.g., established between the wearable devices, to a cloud infrastructure to facilitate the real-time monitoring of action and actions that such sites.

Physical object boundary detection techniques and systems are described. In one example, a method implemented by at least one computing device is presented, the method comprising: receiving, by the at least one computing device, motion sensing data and a digital image corresponding to a physical environment comprising a physical object; generating, by the at least one computing device, point cloud data based on the motion sensing data and a digital image corresponding to a physical environment including the physical object; generating, by the at least one computing device, a three-dimensional boundary of the physical object from point cloud data generated based on the motion sensing data and the digital image corresponding to the physical environment including the physical object; generating, by the at least one computing device, digital content based on the three-dimensional boundary, the digital content indicating availability of the physical object; and displaying, by the at least one computing device, the digital content in a user interface.

The invention discloses a complex motion perception method based on human visual inspiration, and the method comprises the steps: firstly capturing an athlete image in a motion process, recognizing a key image region through evaluating the semantic and visual importance of an image region, and then dynamically processing the region features of the key image region. And then, for the dynamically processed region features, a low-rank active learning technology is adopted, an objective function is optimized, and an optimized image region is obtained. And finally, classifying the optimized image area by using a support vector machine (SVM) to obtain a motion sensing result. According to the method, the extracted key region can be ensured to have visual saliency while better calculation efficiency is ensured, and the performance in a complex motion environment is remarkably improved.

Disclosed are systems and methods that provide a decision-intelligence (DI)-based, computerized framework for advanced device naming and localization of Wi-Fi connected devices at a location. The disclosed framework operates to manage, control and / or manipulate devices on a Wi-Fi network, which provides intuitive mechanisms to select devices to name, group and / or locate in a WiFi app with WiFi motion and / or detected gesture(s) by leveraging voting and ranking mechanisms via a compiled cross-correlation matrix of channel frequency response (CFR) motion signatures and / or channel state information (CSI) motion signatures. Accordingly, motion signature information can be leveraged to control, enable and / or permit Wi-Fi connections among and / or between devices at a location.

The invention relates to the technical field of image recognition, in particular to an intelligent recognition and detection method for preceding vehicle starting. The method comprises the following steps: acquiring an image of an automobile data recorder, and judging whether an automobile is in a static or moving state; extracting a plurality of view angle regions and carrying out region separation according to texture density; detecting the area smoothness to determine a motion detection sensitivity; and according to the state and sensitivity of the vehicle, front vehicle starting identification is carried out on each area, starting early warning response is sent out based on an identification result, and the detection accuracy and real-time performance are improved. According to the method, the driving video and the motion sensing data are fused, and multi-view region segmentation, adaptive sensitivity adjustment and a dynamic early warning mechanism are combined, so that high-robustness and high-precision recognition of the starting behavior of the front vehicle under various illumination and working conditions is realized, and the method has good universality and compatibility.

An electronic device may use information about the location of nearby devices to make sharing with those devices more intuitive for a user. The electronic device may include control circuitry, wireless circuitry including first and second antennas, and motion sensor circuitry. The control circuitry may determine the location of a nearby electronic device by calculating the angle of arrival of signals that are transmitted by the nearby electronic device. To obtain a complete, unambiguous angle of arrival solution, the electronic device may be moved into different positions during angle of arrival measurement operations. At each position, the control circuitry may calculate a phase difference associated with the received signals. Motion sensor circuitry may gather motion data as the electronic device is moved into the different positions. The control circuitry may use the received antenna signals and the motion data to determine the complete angle of arrival solution.

The invention provides a self-generating wearable motion sensing device convenient for collecting motion information. The self-generating wearable motion sensing device comprises two hinged torsion arms, a rotating shaft of the one-way rotating disc assembly and a hinged shaft of the two torsion arms are coaxially arranged, a plurality of protruding parts are arranged in the circumferential direction of the one-way rotating disc assembly, and a plurality of piezoelectric triggering units are arranged on the rotating disc in the circumferential direction. The piezoelectric module comprises a piezoelectric cantilever, one end of the piezoelectric cantilever is fixed with one torsion arm, and the other end of the piezoelectric cantilever is matched with the piezoelectric trigger unit; the friction electricity module is connected with the other torsion arm and comprises two films, the two films are oppositely arranged, and the protruding part can be matched with the first film, so that the two films are close to or away from each other. According to the invention, the piezoelectric module is matched with the piezoelectric trigger unit, and the triboelectric module is matched with the lug boss, so that the legs are matched with the piezoelectric trigger unit and the triboelectric module respectively in two stages included in one walking period, and motion signals in different stages in the walking period are collected respectively; therefore, the accuracy of signal acquisition is improved.