1591 results about "Motion sensors" patented technology

A real-time system for the multimodal generation of virtual reality scenes based on artificial intelligence for the creation of immersive three-dimensional environments from natural language narratives, consisting of: a speech capture module configured to continuously record a user's spoken narrative via one or more directional microphones, preprocesses the captured signal by noise reduction and temporal alignment, and outputs a digital speech stream; A speech-to-text processing unit that is operationally coupled to the speech capture module and configured for real-time speech recognition using a continuous neural transformer model. The unit is trained to transcribe natural language utterances into structured text data while maintaining contextual continuity throughout the evolving narrative. a semantic interpretation processing unit that is communicatively linked to the speech recognition unit and configured to perform natural language understanding techniques to extract contextual entities, spatial references, temporal relationships, and object attributes from the transcribed narrative; the engine includes a large language model that is fine-tuned for spatial reasoning tasks; a scene graph generation module configured to transform the interpreted semantic data into a structured, hierarchical representation that defines nodes for identified entities and edges for corresponding relationships, with each node associated with metadata describing geometry, position, orientation, texture, and linking attributes between objects; a multimodal image-language model processor coupled with the scene graph generation module, wherein the processor is configured to retrieve, adapt, or synthesize appropriate three-dimensional elements from a pre-trained visual-lexical embedding space and align these elements with their semantic and spatial definitions derived from the scene graph; a scene assembly and rendering controller configured to create a cohesive virtual scene from the aligned assets, perform real-time rendering using a GPU-accelerated ray tracing pipeline, and produce a stereoscopic visual output that corresponds to the evolving narrative; A head-mounted virtual reality visualization device connected to the rendering engine and configured to display the generated immersive environment to the user in real time. The device features motion sensors and inside-out tracking cameras to detect head and body movements, dynamically updating viewing angles and perspective within the rendered scene; and a bidirectional feedback module integrated into the head-mounted device and connected to the semantic interpretation processing unit; the module is configured to interpret corrective commands, gestures, or supplementary comments from the user to refine or modify specific scene elements without interrupting the real-time visualization; The system continuously updates the virtual scene as the narrative develops, ensuring temporal synchronization between speech input and rendered output below a defined latency threshold, thus enabling a natural, dialogic construction of complex three-dimensional virtual environments.

The invention provides an industrial robot control system and method. The system comprises a trajectory planning module, a dynamic compensation module, a feedback control module, an execution module, a sensor module and a data storage module. The trajectory planning module generates an expected trajectory of an end effector of the robot; the dynamic compensation module calculates a dynamic compensation torque based on the expected trajectory and a robot dynamics model; the feedback control module generates feedback control torque according to the deviation between the real-time pose data acquired by the sensor module and the expected trajectory; the execution module drives robot joints to move according to the synthesized moment of the dynamic compensation moment and the feedback control moment; the sensor module collects robot joint angle, angular velocity and torque data in real time; the data storage module stores robot dynamic model parameters, control algorithm parameters and historical motion data. High-precision and smooth robot motion control can be achieved, the dynamic response and stability of the system are improved, and energy consumption and motion errors are reduced.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes such as agent autonomous decision making, financial science and technology and medical health, and discloses a multi-modal sequence data processing method, device and equipment and a medium. Extracting multi-scale feature hierarchies, combining the multi-scale feature hierarchies into a multi-scale feature pyramid set, performing cross-modal feature alignment to generate a multi-scale alignment feature sequence, executing local and global attention processing to generate long-distance dependency features, performing cross-layer information interaction to generate comprehensive multi-scale features, and performing multi-scale feature extraction; and dynamically fusing the multi-modal information and inputting the multi-modal information into a task decision network to obtain a target task result. According to the method, through the multi-scale feature pyramid, cross-modal alignment, attention processing and cross-layer information interaction, the problem of insufficient relevance between different modals and different scales in multi-modal long sequence data is solved, and fine modeling and dynamic fusion of multi-modal and multi-scale features are realized.

The invention relates to a blood oxygen and heart rate monitoring system and method based on PPG signals and motion data, and relates to the technical field of medical health and intelligent wearable equipment. The system comprises a PPG signal acquisition module, a motion sensor module, a signal preprocessing module, a dynamic signal segmentation and quality evaluation module, an oxyhemoglobin saturation calculation module, a heart rate calculation module, a motion state recognition module, a self-adaptive Kalman filtering module and an output display module. The method and the device have the effects of realizing a function of identifying the motion state by the wearable equipment, improving the signal interference suppression capability and widening the application scene.

An electronic door system includes a door frame, a door hingedly coupled to the door frame, an electronic locking mechanism coupled to the door, one or more lights coupled to the door frame, a camera system including at least two of a camera, a proximity or motion sensor, or a doorbell, and a wiring harness extending through the door frame and the door. The wiring harness is coupled to the electronic locking mechanism, the one or more lights, and the camera system. The wiring harness is configured to electrically couple to an external power source.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes such as financial science and technology and medical health, and discloses a task instruction generation method, device and equipment based on cross-modal fusion, and a medium, and the method comprises the steps: carrying out the decoding and noise reduction of an input video, generating a frame sequence, and recognizing a plurality of key frames based on the inter-frame similarity; extracting spatial features of the key frames to form a sequence, and generating video spatial-temporal features in combination with time features; performing semantic preprocessing on the input text to obtain text semantic features, and acquiring motion sensor signals to obtain motion features; fusing the video spatio-temporal features, the text semantic features and the action features to generate fused features; and generating a perception vector based on the fusion feature and outputting a task instruction. According to the method, multi-modal fusion is realized through key frame extraction and space-time fusion mechanisms in combination with text semantic features and action features, and the perception expression ability and the task instruction generation accuracy are improved by using time sequence information and multi-source perception input of the video.

This invention is an article of clothing with electromyographic (EMG) sensors which measures body motion and / or muscle activity. This clothing can be a short-sleeve shirt or a pair of shorts, wherein the electromyographic (EMG) sensors are on the cuffs. The electromyographic (EMG) sensors can be modular; they can be removably attached to different locations in order to create a customized article of electromyographic clothing which optimally measures the muscle activity of a particular person or muscle activity during a particular sport. This clothing can also include bending-based motion sensors.

A device for time-based tracking and cost optimization in construction projects, the device comprising the following: a robust housing suitable for use on construction sites; a processing unit located inside the housing, configured to perform real-time time-stamping, data acquisition and preprocessing tasks; a multimodal sensor unit that is operationally coupled with the processing unit, wherein the sensor unit comprises at least a motion sensor, an RFID reader, sensors for environmental conditions and a vision module with optical character recognition; a real-time clock module that is operationally connected to the processing unit to provide time synchronization for all sensor data streams; a wireless communication module that supports the Wi-Fi, LoRa and LTE protocols and is configured for transmitting time-stamped data to a central project server; a storage module that is operationally coupled with the processing unit to locally buffer time series data of construction activity during offline operation; a housing-mounted, touchscreen-based human-machine interface configured to allow site personnel to enter activity updates and confirm the status of construction tasks; a cost optimization engine running on the central server, the engine being configured to receive time-synchronized sensor data from multiple such devices and dynamically calculate time-cost trade-offs using a predictive planning technique that incorporates the principles of the critical path and the power value; furthermore, the device is configured to be integrated into a digital twin environment of the building under construction in order to provide real-time visualization of progress and to generate suggestions for resource reallocation based on a time-cost-benefit analysis.

The invention relates to a dynamic calibration method and device of a motion sensor for intelligent terminal equipment, and the method comprises the following steps: carrying out the real-time collection of a multi-source sensor on target intelligent terminal equipment through a multi-sensor fusion technology, and obtaining a multi-mode sensor data set; performing feature extraction on the multi-modal sensor data set to obtain a feature vector set; performing error mode recognition on the feature vector set to obtain a sensor error mode; performing error compensation on the multi-modal sensor data set based on the sensor error mode to obtain a compensated multi-modal sensor data set; and performing data reconstruction based on the compensated multi-modal sensor data set to obtain a reconstructed motion trail, thereby solving the technical problem that the measurement precision is reduced due to the fact that the traditional sensor data is often influenced by external interference and self-drift.

The invention discloses a Pick ball motion trail tracking and tactical decision-making auxiliary system which adopts a high-frame-rate camera, a micro sensor installed on a ball and an athlete motion sensor worn on an athlete to respectively collect video image data, ball motion data and athlete motion data in the Pick ball motion process. Precise positioning and trajectory tracking are carried out on a ball through a target detection and tracking algorithm based on deep learning, a tactical knowledge model is constructed by combining site information and athlete action data and applying a decision tree and a neural network algorithm, real-time tactical decision suggestions are provided for athletes and coaches, and the training efficiency is improved. And the competitive level and the training effect of the Pick ball sports can be improved.

A system and method for generating patient care instructions based on real-time sensor and medical data. The method includes receiving time-stamped sensor data from a sensor network comprising motion, occupancy, and environmental sensors, and receiving medical data associated with a patient, including medical conditions, treatment history, medication data, and biometric data. The sensor data is enriched with room-specific information, and activity pattern data is generated in real time using a pattern recognition model. The activity pattern data includes mobility, sleep patterns, medication adherence, statistical measures, temporal patterns, and correlations with medical data. Anomalies indicating potential health risks are detected by comparing current activity patterns with baseline data. A prediction model, trained on historical patient data, assesses the patient's health and generates care instructions accordingly. The care instructions are securely delivered to patient devices, caregiver applications, or automated medication dispensing systems, enabling timely interventions and continuous patient monitoring.

A safety and alarm system for vehicles which is designed to enhance safety by preventing risks associated with leaving vulnerable individuals or pets in locked vehicles is disclosed. The system comprises a durable, weatherproof housing attachable to the ceiling of the vehicle including one or more of a 360-degree infra-red camera, a motion sensor in the vehicle seats, CO2, CO, and temperature sensors. Each sensor is associated with a predetermined threshold. The system includes a processor and a wireless chip, and communicates with a handheld electronic device, enabling real-time alerts and remote monitoring. The smartphone application associated with the system enables for customization of alerts, holographic display controls on the windows, viewing of vehicle interior and communication with vehicle occupants via camera, and system activation / deactivation. Additionally, the system includes GPS functionality for emergency location tracking, enhancing the safety and response measures in critical situations.

Provided herein are methods for Inertial Measurement Unit (IMU) sensor compensation utilizing deep neural network (DNN) technology. In some embodiments, the methods involve receiving sensor values from gyroscopes, accelerometers, and non-motion sensors, then loading these values into a deep learning algorithm alongside true sensor values. Unlike traditional calibration techniques that rely on complex parametric models, this approach may utilize a neural network to directly process raw sensor data and enhance output signal accuracy. In some embodiments, the training process employs ground truth data for approximately 70% of inputs, with the remaining 30% dedicated to sensor compensation. The technique may be implemented in standalone IMUs, augmented IMUs, and navigation systems, offering improved accuracy and reduced computational overhead across various technological applications.

The invention discloses an intelligent voice recognition and analysis system based on a universal smart phone chip, and the system comprises a data collection module which synchronously captures a voice signal and motion sensor data through a built-in microphone array and a motion sensor, and generates an original multi-mode data package with a time sequence stamp; and the noise reduction processing module is used for receiving the original multi-mode data packet, executing environmental noise spectrum analysis, generating an anti-phase sound wave, performing signal enhancement and outputting a pure voice stream. According to the method, through multi-modal noise separation, nonlinear signal enhancement and hierarchical privacy protection, the contradiction between speech recognition precision and privacy security in a complex environment is solved, and meanwhile, by means of dynamic resource scheduling and a lightweight model, the finite computing power of a mobile phone chip is utilized to the maximum extent in the aspect of speech recognition.

Techniques are disclosed to build a map for an area around at least a route traversed by a moving platform. An integrated navigation solution for a device within the moving platform is generated using motion sensor data obtained from a sensor assembly of the device and absolute navigational information for the platform. The integrated navigation solution is then used to project radar measurements obtained from at least one radar of the platform onto the area so that the map is built using the projected radar measurements.

A sink system and methods of making and using sink systems including a sink basin and a discharge conduit coupled to the sink basin, which is positioned to expel fluid into the sink basin via an outlet thereof. The flow of fluid through the discharge conduit may be activated via a motion sensor or switch coupled directly to the basin or a spacer ring positioned between the basin and the countertop. Controls for adjusting the temperature and / or flow rate of fluid through the discharge conduit may also be coupled to the basin or a spacer ring positioned between the basin and the countertop, or alternatively, to a surface of the countertop.

Methods and systems are herein provided for acquiring and analyzing health monitoring data acquired by a wearable finger ring device. In one example, a method comprises acquiring sensor data with one or more motion sensors of a wearable finger ring device; analyzing the sensor data to determine one or more quantities of interest; and outputting the sensor data and the one or more quantities of interest to one or more remote devices.

A vehicle safety alert system designed to monitor the interior of a vehicle and alert users about the presence of unattended individuals or pets, such as children or the elderly, left behind inside the vehicle is disclosed. The system includes a smart alert device which can be in a variety of portable forms including stuffed toys and is equipped with a plurality of sensors including an ignition sensor, a motion sensor, a temperature sensor, a sound sensor, and a camera to capture comprehensive visual data of the vehicle's interior. The device utilizes a processor to analyze sensor data and determine the presence of unattended individuals or pets, sending alerts to a user device through a communication network. Alerts can be audio, textual, or video messages, including real-time footage. The system includes a user-friendly application to configure alert preferences and emergency contacts, enhancing the system's utility and user convenience.

A tracking system is provided. A head-mounted display device is adapted to be mounted on a head of a user and comprises a camera and a processor. The camera obtains a body image includes a body portion of the user. The processor is configured to: determine a relative position between a body motion sensor of a body tracker and the body portion of the user based on the body image; and perform a target tracking of the body portion based on the relative position and sensor data of the body motion sensor of the body tracker. A body tracker is adapted to be mounted on the body portion of the user and comprises a body motion sensor. The body motion sensor obtains the sensor data. The sensor data indicates a movement and / or a rotation of the body portion.

The invention discloses a motion state monitoring and feedback system and method based on electroencephalogram signals, in the system, an electrode array is arranged corresponding to a forehead part and used for collecting the electroencephalogram signals, a motion sensor is used for collecting motion data signals, and a vibration motor is used for sending out vibration feedback; the electroencephalogram collection hair band sends the electroencephalogram signals and the motion data signals to the mobile terminal, and the mobile terminal sends the electroencephalogram signals and the motion data signals to the cloud processing platform; the cloud processing platform is used for predicting input electroencephalogram signals and motion data signals by adopting a physical and mental state prediction model based on a deep neural network to obtain physical and mental state indexes; triggering a self-adaptive feedback intervention strategy according to the physical and mental state indexes, and controlling a vibration motor to send vibration feedback in a preset mode. According to the technical scheme of the invention, the recognition accuracy of the physical and mental state characteristics of the movement of the user is improved, and the wearing comfort and convenience of the signal acquisition device are improved.

The invention provides a wafer vertical stripping mechanism and a wafer vertical stripping method. The stripping mechanism comprises a position adjusting plate, a coplanar sensor, a driving structure for rotating the position adjusting plate, a motion sensor for detecting whether the position adjusting plate is vertical or not, and a wafer auxiliary structure for pushing a wafer to be stripped and the position adjusting plate to rotate in parallel. Through cooperation of the position adjusting plate, the coplanar sensor, the rotation driving structure, the motion sensor and the wafer auxiliary structure, the to-be-stripped wafer and the position adjusting plate rotate in parallel to be perpendicular and then are stripped and taken, the vertical stripping efficiency of the wafer is improved, and defects caused by wafer stripping are avoided; meanwhile, the swing roller is in contact with the to-be-stripped wafer, so that the stress on the to-be-stripped wafer is reduced, and the vertical stripping yield of the wafer is improved; in addition, the stress on the wafer to be stripped is further reduced by materials of the position adjusting plate and the swing roller, and the wafer damage risk is reduced; and finally, the wafer is conveniently and vertically stripped and taken through the wafer taking groove with an opening in the upper part, so that the wafer stripping efficiency and yield are improved.

Disclosed are a method, a device, and / or a system of an earphone having increased comfort through external-facing charging connections, enhanced controls through direction and / or motion evaluation, and / or accurate physiological feature extraction through audio-motion sensor correlation. In one embodiment, an earphone includes a housing, a speaker configured to audibly coupled to an ear canal, a battery, a wireless antenna, and a charging connector. The inside face of the housing faces inward toward a concha of the ear, and the outside face faces outward when the earphone is seated in the ear such that at least an exposed region is unobstructed to a finger of the user. The charging connector of the earphone is electrically coupled to the battery and positioned on the outside face of the housing to prevent contact with the ear, reduce corrosion of the charging connector of the earphone, reduce dirt buildup, and / or improve comfort.

The invention belongs to the technical field of heating equipment, and particularly relates to an omni-directional tower type heater which is used for displaying the current state, temperature setting and operation mode information of the heater through a man-machine interaction module; the sensor module comprises a temperature sensor, monitors the environment temperature in real time and feeds back the environment temperature to the system for intelligent adjustment; the motion sensor is used for detecting whether a person moves in a room so as to determine whether to turn on or turn off the warmer; the control module comprises a microcontroller and is responsible for processing sensor data, executing a user instruction and adjusting heating power; the communication module is convenient for a user to carry out remote control through a mobile phone APP or a smart home system; the intelligent adjusting module comprises a temperature control algorithm and is used for intelligently adjusting the heating power of the warmer according to the real-time temperature data; a user sets a timing switch, the system automatically controls the working state of the warmer according to the preset time, and the effects that man-machine interaction management is conducted on the warmer, and the warmer can be regulated, controlled and supervised in a palm mode in real time are achieved.

Embodiments herein relate to ear-worn devices that can be used to locate other devices such as mobile electronic devices. In a first aspect, an ear-worn device is included having a control circuit, a microphone in electrical communication with the control circuit, an electroacoustic transducer for generating sound in electrical communication with the control circuit, a motion sensor in electrical communication with the control circuit, and a power supply circuit in electrical communication with the control circuit, wherein the ear-worn device is configured to issue a location command to a mobile electronic device and wherein the location command triggers the mobile electronic device to emit a locating signal. Other embodiments are also included herein.

A sign language recognition system is described. The system includes a motion sensor, a processing circuitry and a display device. The motion sensor captures and records a dynamic sign language gesture as a sign video stream. The processing circuitry is configured with a key postures extractor, an accumulative video motion (AVM), and a sign recognition network (SRN). The key postures extractor captures main postures of the dynamic sign language gesture by extracting key frames in the sign video stream. The AVM captures motion of the sign video stream frames and transforms the motion in an AVM frame into a single AVM image. The SRN is configured as a convolutional network. The main postures and AVM image are fed into a two-stream network. The features from the two stream network are concatenated and fed into the SRN for learning fused features and performing classification of the sign language gesture.

The present disclosure relates to a system for detecting the position and / or the operating state of a movable component of an aircraft, wherein the system has one movable component, two actuators, two motion sensors, one asymmetry sensor, one drive train, and one monitoring device; wherein the component can be actuated by the at least two mutually offset actuators; wherein at least one motion sensor is provided for one respective actuator; wherein the motion sensor can monitor a mechanical movement of the drive train; wherein the monitoring device is connected to the motion sensors and to the asymmetry sensor, and wherein the system is configured such that an initialization of the monitoring device and / or of the motion sensors and / or of the asymmetry sensor can take place after a booting of the system and / or when the component has adopted a fully retracted and / or a fully extended position.

The invention discloses an intelligent lighting control system based on the Internet of Things and AI prediction, and relates to the technical field of intelligent lighting, and the system comprises a data collection module which is connected with an ambient light sensor, a motion sensor and an electric quantity sensor through an intelligent lamp, collects the state data of intelligent lighting in real time, and sends the state data to a server; by integrating the ambient light sensor, the motion sensor and the electric quantity sensor, the system can sense environment changes and user behaviors in real time, self-adaptive adjustment of lamplight is achieved, user operation is simplified, a user does not need to frequently and manually adjust lamplight, the indoor illumination brightness can be automatically adjusted according to the ambient light intensity, and the user experience is improved. Meanwhile, through application of the AI prediction module, through deep analysis of user behavior modes and environment data, the illumination requirements of the user in different scenes can be accurately predicted, the lamplight state is adjusted in advance, and the user experience is further improved.

Various implementations disclosed herein include devices, systems, and methods for modifying display of virtual content. In some implementations, the method is performed by an electronic device including a non-transitory memory, one or more processors, a display, an eye tracker and a movement sensor. In some implementations, the method includes displaying, via the display, virtual content. In some implementations, the method includes detecting, via the eye tracker, a movement of a gaze in a first direction. In some implementations, the method includes detecting, via the movement sensor, a movement of a head in a second direction while detecting the movement of the gaze in the first direction. In some implementations, the method includes, in accordance with a determination that the movement of the gaze in the first direction and the movement of the head in the second direction are corresponding opposing movements, modifying a display characteristic of the virtual content.

The invention provides a multi-scene fusion hyperactivity quantitative evaluation system, which is characterized in that motion data of a subject in different diagnosis scenes are acquired through a diagnosis scene data acquisition module, and motion behavior information of the subject is recorded; then, a single diagnosis scene feature extraction module is used for automatically extracting feature vectors corresponding to scene data of motion sensor time sequence data collected in the single task testing process by using a single scene representation network; using a multi-diagnosis scene efficient fusion module to take the feature vector of each scene data as the feature of a corresponding node on a graph, transmitting information among the feature representations of different scene data by adopting a graph neural network, integrating the scores of different options of a prediction scale, and optimizing a diagnosis process to reduce the task burden of a subject and improve the diagnosis accuracy of the subject. The objectivity and efficiency of symptom evaluation are remarkably improved, the accuracy and operability of ADHD clinical auxiliary diagnosis are effectively improved, and the method has wide clinical application prospects.

First and second tracker assemblies each having a single optical marker are secured to a bone, with the first tracker assembly also including a motion sensor. A localizer optically tracks the optical marker positions, and a pose of a tracker coordinate system (TCS) associated with the tracker assemblies according to three positional DOF and two rotational DOF is determined from the tracked marker positions. Measurements from the motion sensor are utilized to determine an angle of inclination with respect to gravity, and an orientation of the TCS according to a further rotational DOF defined about a virtual line extending between the optical markers is determined from the angle of inclination. A pose of the bone according to six DOF is then determined from the determined pose of the TCS according to three positional and two rotational DOF and the orientation of the TCS according to the further rotational DOF.