Kingfar International Inc.

Nanjing Kingfar Health Technology Inc.

Beijing Film Academy

Qichao Zhao

Ran Yang

Zhao Li

Zichu Yang

Disclosed are an EEG impedance test circuit, a method, and a device. The circuit comprises a frequency selecting circuit, an amplification circuit, a follower circuit, and a power supply terminal AVCC. An input end of the frequency selecting circuit is connected to the power supply terminal AVCC, the input end of the frequency selecting circuit is further connected to the input end of the amplification circuit, an output end of the frequency selecting circuit is connected to the output end of the amplification circuit, and the output end of the amplification circuit is connected to the input end of the follower circuit; the frequency selecting circuit is configured for oscillating so as to generate an oscillation signal; and the follower circuit is configured for isolating the frequency selecting circuit and the amplification circuit; the follower circuit is configured for circuit isolation.

EEG impedance test circuit, method, and device

Disclosed are a wearable multi-index integrated physiological intelligent sensor system and a physiological index monitoring method. The system includes a device body and an intelligent terminal. The device body is provided with a fixing piece, which is configured to fix the device body at a human ear; the device body is further provided with a collecting and processing assembly, which is in wireless communication connection with the intelligent terminal; the collecting and processing assembly collects a corresponding physiological index signal in response to a physiological index collection instruction sent by the intelligent terminal, and analyzes and processes the physiological index signal to obtain a corresponding physiological index data, and sends the physiological index data to the intelligent terminal; in which, the physiological index signal includes electrodermal signal, heart rate signal and blood oxygen signal; the intelligent terminal is configured to receive and display a physiological index data.

Wearable multi-index integrated physiological intelligent sensor system and physiological index monitoring method

The embodiments of the present disclosure provides a device for determining muscle state based on electromyography signal and muscle oxygen saturation. The devices includes: a signal collection module, configured for collecting a human electromyography signal data; a light source detection module, configured for emitting light with different wavelengths; a photosensitive receiver module, configured for receiving light reflected by skin after the light emitted by the light source detection module irradiates the skin; a blood oxygen calculation module, configured for calculating the muscle oxygen saturation based on the light received by the photosensitive receiver module; and a data statistics module, configured for determining the muscle state based on the human electromyography signal data and the muscle oxygen saturation. In this way, an accurate detection of muscle state is realized.

Device for determining muscle state based on electromyography signal and muscle oxygen saturation

An eye movement analysis method comprises: acquiring a first scene video seen by a target user in a preset environment, and simultaneously acquiring eye movement gaze data of the target user in the environment; performing semantic segmentation on the first scene video based on a deep learning algorithm to obtain a second scene video, wherein the second scene video is divided to have eye movement area of interest; superposing the eye movement gaze data with the second scene video to obtain a gaze pixel point corresponding to the eye movement gaze data in the second scene video; and determining the gaze pixel point corresponding to each frame image in the second scene video and outputting eye movement data index of the target user gazing at the eye movement area of interest in combination with time sequence.

Eye movement analysis method and system

An intelligent drawing method for human machine interaction HMI design prototype includes: importing an HMI design prototype to be tested; obtaining an HTML script of the imported HMI design prototype page, and displaying the prototype page including content blocks on a display interface; automatically recognizing the content blocks on the prototype page by reading codes of the HMI design prototype page in the automatic recognition drawing mode, monitoring block selection operations of experimenter on the display interface, recognizing the corresponding content block as an interaction area based on a position of the block selection operation, automatically marking the recognized content block as the interaction area, and adding the recognized content area in a drawing area list; and automatically detecting interaction operations of a subject in a process of the subject testing the HMI design prototype, automatically associating the interaction operation with the corresponding content block.

Intelligent drawing method and system for human machine interaction HMI design prototype

The present disclosure provides an evaluation method, device, and storage medium for intelligent human-machine cooperation system, the method comprises the following steps: recording a real-time objective data of subject during an execution of the intelligent human-machine cooperation system test; inputting the objective data into a pre-trained fitting model to predict and obtain a subjective evaluation of a prediction, the pre-trained fitting model is based on a recorded objective data and subjective evaluation fitting, and the subjective evaluation is obtained based on a first subjective evaluation result of the subject after executing the intelligent human-machine cooperation system test for pre-training; obtaining a real-time human-machine cooperation score based on a predicted subjective evaluation.

Method, device and storage medium for evaluating intelligent human-machine cooperation system

Disclosed are a sensor data transmission method and a device. The method includes: a periodic signal acquisition apparatus receiving a message requesting for data packet description information from a data receiving end and reporting the data packet description information to the data receiving end, wherein the data packet description information includes: signal type information, the acquisition rate for each type of signal, and the sending rate of a data packet; receiving a data reporting request from the receiving end, and sending a data packet to the data receiving end according to the sending rate of the data packet in the data packet description information, wherein the data packet sent to the data receiving end contains a packet header portion and a load portion, the packet header portion includes a frame header field, a load length field, and a check field.

Sensor data transmission method and device

Disclosed are a human-computer interaction movement track detection method, device, apparatus, and computer-readable storage medium. The method comprises: segmenting a movement path of a movement target to obtain one or more sub paths; monitoring and recording movement of the movement target in each of the sub paths to obtain a human-computer interaction movement track of the movement target in each of the sub paths; identifying the human-computer interaction movement track of the movement target in each of the sub paths with a determination model corresponding to each of the sub paths; and detecting a human-computer interaction movement track of the movement target based on identification of the human-computer interaction movement track in each of the sub paths.

Human-computer interaction movement track detection method, apparatus, device, and readable storage medium

The present application relates to a method, apparatus, device, system and storage medium for collecting spatiotemporal behaviors and generating a spatiotemporal behavior track. The method includes: obtaining a first time series containing a plurality of sampling points; taking one sampling point as a current sampling point; setting a window time, and finding a first sampling point and a last sampling point within the window time; taking a first position as a center of a circle, which is a center point of the reality display device corresponding to the current sampling point, and calculating an angular speed between the first sampling point and the last sampling point; if the angular speed is greater than a preset angular speed threshold, taking the current sampling point as a displacement point; processing the plurality of sampling points as described above to obtain a second time series; drawing a moving track map.

Method, apparatus, device, system and storage medium for collecting spatiotemporal behaviors and generating a spatiotemporal behavior track

The present application relates to a clock quartz oscillator synchronization method, system and apparatus, in which the method includes, when a calculation unit is in network connection, calculating a first deviation between a calculation unit time and a network clock time; updating a fundamental deviation according to the first deviation; updating the calculation unit time and calculating an actual refresh frequency of the calculation unit according to the fundamental deviation; calculating a second deviation between the calculation unit time and a sensor time; and according to the second deviation, updating the sensor time and calculating an actual interruption frequency of the sensor. The present application provides a synchronization method for calculation, estimation, correction, compensation of time deviation caused by the clock quartz oscillator, which has a benefit of time deviation reduction when one or more sensors are in data exchange with one or more calculation units.

Clock quartz oscillator synchronization method, apparatus and system

Disclosed are a detection circuit and apparatus based on equipotential shielding. A first connection end of a row control circuit, configured to be connected to a row lead of an array piezoresistive sensor; a control end of the row control circuit, connected to a main control chip for outputting a control signal; a second connection end of the row control circuit, connected to a first power supply terminal; and a row pull-up resistor, with an end connected to the row lead and another end connected to a second power supply terminal. Herein, each row lead corresponds to one row pull-up resistor; each column lead of the array piezoresistive sensor is connected to an input end of an inverse adder; an output end of the inverse adder is connected to a first connection end of the column control circuit.

Detection circuit and apparatus based on equipotential shielding

Provided is a method for identifying a gaze behavior in a three-dimensional space, comprising: acquiring eye movement data of the two eyes of a user; selecting, from the collected eye movement data, eye movement data for gaze behavior identification; calculating eye movement angular velocities, determining gaze point data corresponding to the gaze behavior; combining pieces of gaze point data, which satisfy a time proximity condition and a space proximity condition at the same time, in the gaze point data so as to obtain a gaze duration and the 3D coordinates of gaze points; and based on the combined pieces of gaze point data, determining a gaze point at which the gaze duration is longer than a second set duration, thereby identifying the gaze behavior.

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Beijing, China

Qichao Zhao