Implementations described herein disclose an artificial intelligence (AI) based method for generating an oxygen saturation level output signal using the trained neural network. In one implementation, the method includes receiving a photoplethysmographic (PPG) signal, the PPG signal including a red PPG signal and an infrared PPG signal, generating an input feature matrix by performing time-frequency transform of the PPG signal, training a neural network using the input feature matrix and an oxygen saturation level input signal, and generating an oxygen saturation level output signal using the trained neural network.

The invention allows an accurate and automated method and system for determining an intrinsic frequency of an EEG band of a person. Intrinsic frequency values (specifically the intrinsic alpha frequency (IAF)) are used to diagnose mental disorders and detect brain anomalies in a person. At present, these estimates are inaccurate for the population that has EEG with low energy in the EEG band. By combining the EEG recording with a stimulus (e.g., light, sound, touch, etc., or a combination), it is possible to determine the IAF, due to the resonant properties of the brain.

Embodiments of a system for controlling an object using brainwaves are disclosed. The system includes a set of EEG electrodes configured to be positioned on a head of a user and to collect EEG signals. The system further includes one or more computer readable storage mediums storing a framework configured to execute an extensible architecture through which EEG signals are interpreted for control of the object. The framework includes an EEG device plugin associated with the set of EEG electrodes and configured to extract the EEG signals from the set of EEG electrodes. The framework also includes an interpreter plugin configured to convert the EEG signals extracted by the EEG device plugin into a command. Further, the framework includes an object control plugin configured to access the command through an extension point of the interpreter plugin and to execute the command to control the object.

The detection and diagnosis of a variety of cardiovascular disorders and levels of heart condition, using a novel method and system, according to a comprehensive analysis of cardiac electrical signal via the frequency domain, time domain, spatial domain.

Disclosed are a method and a device for measuring a biometric signal by using a radar. The disclosed method measures a plurality of biometric signals by using a radar by: (a) receiving the plurality of biometric signals from the radar; (b) calculating distance information of the received plurality of biometric signals and classifying the same on the basis of a distance; (c) selecting a signal having a largest variance according to a time; (d) further selecting a number of signals among signals having a distance with the signal selected in the step (c) smaller than an arbitrary distance from the distance-based classified signals; (e) converting all signals selected from a time domain to a frequency domain; (f) calculating a reliability of each biometric signal from the converted distance-based signals; and (g) detecting a corresponding biometric signal by selecting the distance-based signal where the calculated reliability is highest.

A method and a related device to determine the kinetic state of a subject includes the steps of determining a signal indicative of the acceleration trend on the three Cartesian axes; processing the signal to limit the frequency band and preferably reduce artifacts and compensate the offset of the output signals from a multi-axial measurement system; analyzing frequency and spectrum through the transformation of the signal with the Fournier transform; computing the power spectral density for each Cartesian axis; and comparing the spectral density with a characteristic pattern of a movement.

Systems and methods are provided for performing optical coherence tomography angiography for the rapid generation of en face images. According to one example embodiment, differential interferograms obtained using a spectral domain or swept source optical coherence tomography system are convolved with a Gabor filter, where the Gabor filter is computed according to an estimated surface depth of the tissue surface. The Gabor-convolved differential interferogram is processed to produce an en face image, without requiring the performing of a fast Fourier transform and k-space resampling. In another example embodiment, two interferograms are separately convolved with a Gabor filter, and the amplitudes of the Gabor-convolved interferograms are subtracted to generate a differential Gabor-convolved interferogram amplitude frame, which is then further processed to generate an en face image in the absence of performing a fast Fourier transform and k-space resampling. The example OCTA methods disclosed herein are shown to achieve faster data processing speeds compared to conventional OCTA algorithms.

In an aspect, a method for imaging a target comprises steps of: performing optical coherence tomography (OCT) scanning on the target with one or more beams of source light, the one or more beams of source light comprising a plurality of wavelengths; wherein performing OCT scanning comprises: providing the source light to a reference optical path and to a sample optical path, wherein providing the source light to a sample optical path comprises illuminating the target with the source light; and recording interference data corresponding to an interaction of a light from the reference optical path and a light from the sample optical path; processing the interference data; and identifying blood or one or more blood-features in the target based on an optical attenuation of light in or associated with the sample optical path by the blood or the one or more blood-features.

This disclosure relates generally to assessment of cognitive workload using breathing pattern of a person, where cognitive workload is the amount of mental effort required while doing a task. The method and system provides assessment of cognitive workload based on breathing pattern extracted from photoplethysmograph (PPG) signal, which is collected from the person using a wearable device. The PPG signal collected using the wearable device are processed in multiple stages that include breathing signal extraction to extract breathing pattern. The extracted breathing pattern is used for assessment of cognitive workload using a generated personalized training model, wherein the personalized training model is generated and dynamically updated for each person based on selection of a sub-set of breathing pattern features using feature selection and classification techniques that include maximal information coefficient (MIC) techniques. Finally based on personalized training model, the extracted breathing pattern is classified as high cognitive workload or low cognitive workload.

A device for monitoring a health parameter of a person is disclosed. The device includes a device body, a radio frequency (RF) front-end connected to the device body and including a semiconductor substrate and an antenna array including at least one transmit antenna configured to transmit radio waves below the skin surface of a person and a two-dimensional array of receive antennas configured to receive radio waves, the received radio waves including a reflected portion of the transmitted radio waves, wherein the semiconductor substrate includes circuits configured to generate signals in response to the received radio waves, and an alignment feature integrated into the device body and configured to align the antenna array with an object.