A system, method and apparatus for detecting facial expressions according to EMG signals.

An electronic device, an avatar facial expression system, and a controlling method thereof are provided. The electronic device includes a sensor part that is attached in the facial part of a user and detects a facial electromyography signal according to a facial expression, a processor that extracts a feature based on the facial electromyography signal and determines a data value of an avatar's facial movement corresponding to the extracted feature, and a display that controls a facial movement of the avatar based on the data value of the avatar's facial movement and displays a facial expression of the avatar corresponding to the facial expression of the user.

Biological measurement systems and methods are described. In one embodiment, a biological function monitoring system includes a first monitoring device, including a first sensor, a first processor, and a first transmitter. The first sensor senses a first biological function measurement during monitoring a biological function and derives a first data symbol representing the first biological function measurement. The first processor accesses the first data symbol from the first sensor, and combines two or more chaotic waveforms from a first chaotic waveform ensemble, generating a first composite chaotic waveform. The first transmitter transmits the first composite chaotic waveform to a receiver over a communication channel. The biological function monitoring system may include a second monitoring device that is similar to the first monitoring device. The second monitoring device generates a second composite chaotic waveform and transmits the second composite chaotic waveform to the receiver over the communication channel.

A method for determining an event periodic value includes: acquiring a time series of a target event, where the time series includes a preset number of sequential values; calculating an autocorrelation sequence of the time series, and based on peak values and trough values of the autocorrelation sequence, determining a first candidate periodic value set; calculating a Fourier transform result of the time series, and based on amplitude values of frequency points of the Fourier transform result, determining a second candidate periodic value set; acquiring an union of the first candidate periodic value set and the second candidate periodic value set, determining a total value of confidences corresponding to each candidate periodic value in the union, and based on the total value of confidences, determining the periodic value of the target event.

Systems and methods relating to fault detection and diagnosis. Signals received from sensors are first filtered to remove noise and are then analyzed using wavelet packet transform (WPT) based PCA. The results of the PCA analysis are then automatically classified to thereby quickly and easily determine what issues there may be in a finished product or in a machine being monitored.

This disclosure relates generally to a system and method to identify a plurality of noises or their combination to suppress them and enhancing the deteriorated input signal in a dynamic manner. It identifies noises in the audio signal and categorizing them based on the trained database of noises. A combination of deep neural network (DNN) and artificial Intelligence (AI) helps the system for self-learning to understand and capture noises in the environment and retain the model to reduce noises from the next attempt. The system suppresses unwanted noise coming from the external environment with the help of AI based algorithms, by understanding, differentiating, and enhancing human voice in a live environment. The system will help in the reduction of unwanted noises and enhance the experience of business and public meetings, video conferences, musical events, speech broadcasts etc. that could cause distractions, disturbances and create barriers in the conversation.

A method for converting images to a unified image format for artificial intelligence deep training comprises acquiring a plurality of images and annotating the plurality of images. An annotation site of the plurality of images is determined to be quadrilateral or polygonal. The format of the annotated images is converted according to a first conversion rule when the annotation site of the annotated training images or the annotated verification images is found to be quadrilateral and the format of the annotated images is converted according to a second conversion rule when the annotation site of the annotated training images or the annotated verification images is found to be not a quadrilateral. A device employing the method is also disclosed.

A gated truncated readout system for position sensitive or imaging detectors that improves resolution over traditional readout systems. The readout system includes two or more amplifiers that receive a multichannel output analog data from the detector. Analog gates control circuitry, included in the readout circuit, receives the signals from the amplifiers, determines a fractional value of the sum-integral of the signals, and enables analog gates operation around an area of interest, disabling all other channels where noise dominates the signal value and thereby improving interpolation accuracy of the signals centroid position and the detector resolution. Filtered signals are transmitted to a centroid interpolation signal processing device for computation of the centroid position. As a result disabling all channels where noise dominates the signal value, the gated truncated readout system provides better accuracy improved detector resolution.

Systems and methods for processing measurement data in an electric power system include acquiring the measurement data by a phasor measurement unit (PMU) coupled to a line of the electric power system, and inputting a plurality of the measurement data within a predetermined time window into a K-nearest neighbor (KNN) for identifying bad data among the plurality of the measurement data, wherein when one of the plurality of measurement data contains a bad datum, the machine learning module sends the bad datum to a denoising autoencoder module for correcting the bad datum, wherein the denoising autoencoder module outputs a corrected part corresponding to the bad datum, and when one of the plurality of measurement data contains no bad datum, the machine learning module bypasses the denoising autoencoder module and outputs the one of the plurality of measurement data as an untouched part.

A computer-implemented method for a monitoring device being executed by a processor of the monitoring device comprises acquiring at least two kinds of physiological signals via a sensor of the monitoring device, obtaining a signal quality index of each of the at least two kinds of physiological signals by the processor of the monitoring device, providing a homologous physiological parameter value corresponding to each of the at least two kinds of physiological signals by the processor of the monitoring device, and fusing the homologous physiological parameter values based on the signal quality index of each of the at least two kinds of physiological signals and providing a fused value of the homologous physiological parameter values by the processor of the monitoring device. The disclosed physiological parameter processing method avoids disadvantages caused by relying on a single physiological signal.