24 results about "Activity sensing" patented technology

A microcontroller coupled to sensors integrated into a physical toy for monitoring free play activity of a human subject wherein patterns in play activity sensed by the microcontroller are graphically visualized for identification of behavioral milestones, developmental progress and / or behavioral disorders. Specifically, accelerometers detect movement of toys which determine: (1) if the toy is being played with; and (2) the intensity in which the toy is moved. Pressure sensors detect the level and location in which a child may hold a toy. Synchronized with an audiovisual record of the play therapy session and a computer-generated avatar representation of the physical object, this data is integrated to find peak levels of behavior giving clinicians more efficient analytical tools.

Described are systems for determining domain observations of an environment. Systems may include: a domain engine module, an active sensing module, a fractal network module, and an execution agent module. Modules may be configured to perform methods for determining domain observations of the environment. Methods may include generating or receiving domain observations, generating or receiving sim actions, generating fractal networks associated with the domain observations or the sim actions, generating observation sequences from the fractal networks, and comparing the observation sequences to the domain observations.

A transcutaneous sensor configured to measure one or more physiological conditions of a patient. The transcutaneous sensor includes a substrate and first and second working electrodes on the substrate. The first working electrode includes a first active sensing area and the second working electrode includes a second active sensing area. The first active sensing area of the first working electrode is longitudinally offset along the substrate from the second active sensing area of the second working electrode.

Clock enable signals are collected and summed. The number of simultaneously enabled clock enable signals can represent switching activity within a system and can be used as an indicator for power management, noise management, etc. of such a system. Digital switching activity sensing include performance of an operation to sum a quantity of open clock gates associated with a plurality of latches that are grouped into multiple subsets of latches. An activity indication is generated based, at least in part, on a result of the operation to sum the quantity of open clock gates associated with the plurality of latches.

The application discloses a kind of based on surface acoustic wave's red blood cell activity evaluation device and method.Device includes injection pump, syringe, silica gel hose, red blood cell activity sensing platform, power signal generator, amplitude phase measurement circuit.Red blood cell activity sensing platform is three-layer structure, from top to bottom respectively microchannel layer, piezoelectric layer and temperature control layer.Temperature control layer uses indium tin oxide conductive glass, and realizes the stable control of temperature by designing corresponding circuit pattern.Lithium niobate is used as piezoelectric layer, and surface acoustic wave is generated.Surface acoustic wave acts on red blood cell in microchannel layer, and judges by measuring the amplitude of output surface acoustic wave to evaluate the activity of red blood cell.

This disclosure relates generally to method and system for monitoring human parameters using hierarchical human activity sensing. The method is based on sensing as service (SEAS) model which processes continuous mobility data from multiple sensors on the client edge-device by optimizing the on-device processing pipelines. The method requests a subject to select a human parameter of the human body to be monitored using a master device and capture the plurality of signals by recognizing sensors corresponding to the health parameter. The master device transmits to the server the subject selected human parameter of the human body to be monitored and requesting the server to recommend a hierarchical classifier structure. Further, the human body is monitored based on the on-device hierarchical sensing pipeline by executing a plurality of algorithms. In addition, the system is suitable for remote monitoring and flexible edge cloud arbitration, optimizing costs, infrastructure, and energy.

Provided herein is a method of detecting cancer in subject. The method includes providing a biological sample comprising one or more proteases from the subject and contacting the biological sample with probes capable of being cleaved by the proteases, wherein the probes comprise (i) at least 6 L-amino acids and (ii) a detectable label. The cleaved probes are the separated and detected. An increase in a signal from the detectable label of the cleaved probes as compared to a control indicates the subject has cancer. Compositions, kits and methods of using the probes to identify proteases are also provided.

This utility model discloses a multifunctional ceiling-mounted lighting device, relating to the field of intelligent lighting technology. It includes: a mounting body for connection to a wall and / or ceiling; a first slot at the first end of the mounting body and a second slot at the second end; the first slot, the second slot, and the mounting body together form an embedded mounting cavity; a lighting component connected to the mounting body; and a sensing component disposed within the mounting cavity. The sensing component includes an air quality sensor, an ambient light sensor, and an activity detection sensor, with the ambient light sensor connected to the lighting component; and a linkage control module connected to both the lighting component and the sensing component. By integrating the sensing component into the embedded mounting cavity, installation efficiency is improved and maintenance costs are reduced, achieving an integrated design of architectural decorative lines and functional modules. By incorporating the air quality sensor and the activity detection sensor, environmental monitoring and human activity sensing functions are simultaneously realized.

The invention relates to the technical field of air conditioning, in particular to a fresh air system of an on-duty platform and a fresh air control method. The system comprises an environment parameter collecting module, a personnel activity sensing module, a control module and a fresh air adjusting module. The environment parameter acquisition module monitors the space environment quality index in the on-duty platform, the personnel activity sensing module obtains the personnel existence state and activity intensity information, and the control module dynamically calculates the fresh air demand value through a built-in control algorithm according to the data and generates a control signal. The fresh air adjusting module responds to the control signal to adjust the fresh air inlet air volume. The control method comprises the steps of collecting environment parameters and personnel activity data, executing multivariable analysis to calculate the target fresh air volume, driving the fresh air execution unit to adjust the air volume and the like. The dynamic demand model is constructed through multi-source data fusion, the model parameters are optimized through an online learning mechanism, and the environment control precision and the energy utilization efficiency are improved through self-adaptive fresh air regulation and control according to the actual use condition of the on-duty platform.

This disclosure relates generally to method and system for monitoring human parameters using hierarchical human activity sensing. The method is based on sensing as service (SEAS) model which processes continuous mobility data from multiple sensors on the client edge-device by optimizing the on-device processing pipelines. The method requests a subject to select a human parameter of the human body to be monitored using a master device and capture the plurality of signals by recognizing sensors corresponding to the health parameter. The master device transmits to the server the subject selected human parameter of the human body to be monitored and requesting the server to recommend a hierarchical classifier structure. Further, the human body is monitored based on the on-device hierarchical sensing pipeline by executing a plurality of algorithms. In addition, the system is suitable for remote monitoring and flexible edge cloud arbitration, optimizing costs, infrastructure, and energy.

Neuroimaging and / or brain activity sensing machines, such as MEG and OPM machines use a helmet-like or head covering device that includes sensors for acquiring information from a participant's brain activity. The machine is operated while the participant undergoes tests, which can include a need for sight. People with glasses, therefore, need access to their glasses, but the glasses need to be non-ferromagnetic. In addition, due to the shape of the helmet-like objects and the need to have the sensors as close to the participant's head as possible, having glasses that include a contour that closely matches the shape of the helmet will improve the information obtained by the machine.

Clock enable signals are collected and summed. The number of simultaneously enabled clock enable signals can represent switching activity within a system and can be used as an indicator for power management, noise management, etc. of such a system. Digital switching activity sensing include performance of an operation to sum a quantity of open clock gates associated with a plurality of latches that are grouped into multiple subsets of latches. An activity indication is generated based, at least in part, on a result of the operation to sum the quantity of open clock gates associated with the plurality of latches.

This invention discloses an object activity sensing system, method, device, and storage medium. The system includes: an ultrasonic transmitting module for continuously transmitting ultrasonic signals; an ultrasonic receiving module for continuously receiving and processing spatially propagating sound wave signals to obtain multi-channel ultrasonic signals; an ultrasonic preprocessing module; an ultrasonic positioning module for calculating the motion trajectory of a moving object; an ultrasonic activity detection module for detecting whether there is a moving object within a specific range; and a decision module for determining whether there is an object within a given distance D1 and whether there is a moving object within a given distance D2, where D2>D1. This invention can simultaneously detect the presence of stationary objects at close range and moving objects at a distant distance. It is fast and convenient to implement, can directly use the audio hardware built into electronic devices without increasing hardware costs, and is highly efficient. It has significant application value and enormous economic value in fields such as smart homes and consumer electronics.

The present invention relates to a method for human activity sensing and recognition based on Wi-Fi signals, comprising the following steps: determining whether high-precision requirements are met. If so, collecting channel state information data; if not, collecting orthogonal frequency division multiplexing symbol stream data; performing principal component analysis on the subcarrier domain of the channel state information data to obtain rough features, extracting the minimum value of cross-correlation data to obtain correlation artificial features, extracting amplitude data to obtain energy spectrum artificial features, and obtaining channel parameter features based on the spatially alternating generalized expectation maximization algorithm; processing the orthogonal frequency division multiplexing symbol stream data to obtain rough features; performing principal component analysis on the rough features to obtain fine features; inputting the sample types and feature sets of the training set samples into a support vector machine for classification and recognition training; and inputting the feature set of the sample to be tested into the trained support vector machine to obtain a classification and recognition result. Compared with the prior art, the present invention has the advantages of low complexity, high recognition accuracy, etc.

An Internet of Things (IoT) device can include a switch module configured to control a power supply for at least one powered device, a WiFi module configured to perform wireless communication and occupancy activity sensing, and a processor configured to determine human activity recognition WiFi measurements from the WiFi module based on the occupancy activity sensing and generate corresponding commands for the switch module based on the determined human activity recognition WiFi measurements.

An accident recording method implemented by an accident recording system, the accident recording system is suitable for being set in a vehicle, and the accident recording method comprises: the accident recording system determines whether the activity of the vehicle meets a collision condition based on an activity sensing data, and when the judgment result is yes, identifies a target object related to the collision condition from an environment sensing data, and generates and outputs an image data based on the environment sensing data, wherein the image data presents the relative position relationship between the vehicle and the target object within a critical period, and the critical period includes the time point when the collision condition is met.

This utility model discloses an intelligent human activity sensing light system, including a control system power supply section, a control chip U1, a control chip U2, and an AC load terminal. The control system power supply section includes input voltage AC1 and input voltage AC2. Input voltage AC2 is connected in series with fuse F1 and connected to the first terminal of rectifier bridge BD1. Input voltage AC2 is connected to the third terminal of rectifier bridge BD1. The control chip U1 is used to convert AC current to DC12V, and the control chip U2 is used to convert DC12V to DC3.3V. The DC3.3V is used to power control chip U3 and a pyroelectric infrared sensor. The control chip U3 is also connected to a photoresistor CDS1. The first terminal of the AC load terminal is connected between TR1 and capacitor C2 and connected in series with capacitor C0. The second terminal of the AC load terminal is connected in series with AC2 after fuse F1. A relay RY1 and a resistor R10 are connected in series between the first and second terminals of the AC load terminal. The control chip U3 is used to control the on / off state of relay RY1.

Provided is a system (40) including multiple electrodes, a treatment delivery circuit (10), a sensing circuit (20) and a controller (30). The multiple electrodes are capable of being positioned within a brain of a patient to deliver a treatment to the patient or sense an electrical activity. The treatment delivery circuit (10) is operably coupled to the multiple electrodes to deliver the treatment to the patient. The sensing circuit (20) is operably coupled to the multiple electrodes to sense the electrical activity. The controller (30) includes a processing circuit system operably coupled to the treatment delivery circuit (10) and the sensing circuit (20). The controller (30) is configured to: control, through the treatment delivery circuit (10), one or more electrodes among the multiple electrodes to deliver the treatment to the patient; sense, through the sensing circuit (20), potentials of the multiple electrodes in a process of delivering the treatment; and calculate, based on the potentials of the multiple electrodes, a difference value between potentials of any two electrodes among the multiple electrodes to obtain a voltage between the any two electrodes. The system (40) can collect the electrical signal of the deep brain of the patient in a case where the patient receives the stimulus.

The invention discloses a fish activity sensing method, device and equipment based on underwater distributed optical fiber sensing and a medium, and the method comprises the steps: obtaining a local disturbance signal in a target water area based on the Rayleigh scattering characteristic or Brillouin scattering characteristic of a distributed optical fiber; acquiring temperature data and flow field characteristic data corresponding to the local disturbance signal under the same time sequence; feature extraction is carried out on the local disturbance signals, the corresponding temperature data and the corresponding flow field characteristic data, corresponding multi-dimensional features are obtained, and the multi-dimensional features comprise time domain features, frequency domain features and time frequency features; and training a deep learning model based on the multi-dimensional features and the fish behaviors of the multi-dimensional feature pairs, and after training is completed, using the deep learning model to predict the fish behaviors. The invention belongs to the field of fish behavior prediction. According to the invention, accurate prediction of fish behaviors in a complex water body can be realized.

The present disclosure provides an animal trap monitoring system that utilises paired sets of motion or activity sensing units, referred to as trap activation units, in close proximity to an animal trap, and camera units placed close by and in wireless communication with the trap activation units. Upon sensing motion or other indications of animal activity the trap activation sends an alert to its paired camera unit which triggers the capture of image date. The camera unit then uploads this image data and other relevant data to one or more servers hosting an online platform through which a user may access and view the image data.

A photographing device comprises a housing, an activity sensing unit for sensing the activity of the housing, a first rotating unit capable of rotating in a roll rotation direction relative to the housing, a second rotating unit capable of rotating in a pitch rotation direction relative to the housing, a photographing lens unit capable of being driven by the first rotating unit and the second rotating unit, and a processing unit. The processing unit is used to control the first rotating unit and the second rotating unit to rotate in the opposite direction of the housing in the roll rotation direction and the pitch rotation direction respectively according to the real-time activity sensing result generated by the activity sensing unit, so as to reduce the rotation amount of the photographing lens unit in the roll rotation direction and the pitch rotation direction in a real environment.

The invention provides a support vector machine-based personnel activity sensing system and method in a 5G indoor environment. According to the invention, the change of the channel state information CSI amplitude of the 5G signal in wireless communication is utilized to reflect the instantaneous shielding of the human body on the signal in the activity process, so that the activity identification of the position is realized, and sensing equipment is not needed. The sensing system is composed of a sensing signal sending end, a sensing signal receiving end and a sensing processing center. According to the invention, human body activities are discriminated based on prior knowledge. Clock synchronization is not needed between the signal sending device and the signal receiving device, sensing can be conducted through most of common commercial devices, and the application range is wide. The method has no special requirements on the placement angle and position of the equipment, can identify activities performed at different angles relative to the equipment, can run in real time, and is convenient and practical.

The invention discloses a multifunctional AI intelligent sensing lighting device, and belongs to the technical field of lighting. The device integrates a power supply module, a lighting module, a sensing module, a control module, a hinting acousto-optic module and a switch operation module, and has an autonomous mode, a long-time lighting mode and an emergency help seeking function at the same time. Ambient light perception, human body activity induction, AI intelligent control and emergency help seeking are achieved through the modules. The main functions of the device include that after a main lighting lamp is turned off, the device automatically and gradually brightens; brightness and lighting duration are intelligently predicted and adjusted according to human body activity information AI, and sensor detection sensitivity is autonomously adjusted to reduce false triggering; human-computer interaction functions such as power supply under-voltage prompt, trigger prompt and power-on self-test are realized; and an energy-saving optimization mechanism is provided in the operation process. According to the device, the LED light source with the specific color temperature is adopted, light is gradually brightened and darkened, and the user experience is improved; a special control circuit is arranged in the device, multi-mode intelligent switching and power supply energy-saving management are achieved, and the problems that an existing lighting device is single in function, insufficient in intelligent degree and poor in emergency capacity are effectively solved.

A method for identifying an event in a room using wireless signals includes pre-processing channel state information to determine one or more aspects a person in a room based on selected channel state information segments, and identifying, using a machine learning model, an event in the room based on the one or more aspects of the person in the room. The method also includes determining, using the machine learning model and based on the event in the room, one or more settings of a machine, and controlling, using the one or more settings, operation of the machine in response to identifying the event in the room.