The present invention relates to non-invasive method and system for characterising and certifying cognitive activities by detecting gaseous substances emitted by an organism, by means of the respiration, perspiration, and/or secretion, and changes measureable by sensors during said cognitive activities. Substance detection makes it possible to characterise the olfactory signal in order to determine and certify whether or not a cognitive activity has occurred and to classify said signals into different categories of cognitive activities.

A method for obtaining a near-infrared spectroscopy (fNIRS) cerebral signal in a subject includes: placing a near-infrared emitter and respective proximal and distal near-infrared detectors on a skin of a head of a subject; during a baseline recording stage with the subject in resting-state, record near-infrared signals, the recorded signals including a baseline deep-signal and a baseline shallow-signal; calculate a scaling factor between amplitudes of the baseline deep-signal and the baseline shallow-signal at a given task-frequency; with the subject undergoing a cyclic cerebral stimulation at the task-frequency during a stimulation recording stage, record near-infrared signals, the recorded signals comprising a shallow-signal and a deep-signal; and applying the scaling factor to the shallow-signal, calculating the cerebral signal at the task-frequency as a difference between the deep-signal and the scaled shallow-signal, at the task-frequency.

In some embodiments, the electronic device includes a speaker, a microphone, a memory, a digital signal processor (DSP), a driver, and a processor. The processor is configured to: obtain a first sound signal by combining a first signal, a second signal, and a first anti-phase signal; extract, from a second sound signal related to the first sound signal, a first DPOAE signal; obtain a third sound signal by combining a fourth signal, a fifth signal, and a second anti-phase signal; extract, from a fourth sound signal related to the third sound signal, a second DPOAE signal; obtain a user hearing profile based on the first and second DPOAE signals; and perform, based on the user hearing profile, at least one of a sound volume change and an equalization (EQ) change of a sound to be output.

Methods and devices for determining a load vector on an object are disclosed herein. An example method includes collecting location observations related to the object. The example method further includes filtering the location observations to determine an estimated model path. The example method further includes outputting a set of data from the estimated model path, wherein the set of data includes a model location, a model velocity, a model acceleration, and a model jerk. The example method further includes calculating a load vector from the set of data, scaling the load vector via a scaling index, and transmitting the scaled load vector to a remote device.

A MEM-based device and method of fabrication, the device comprising a biochip substrate comprising one or more compliant materials, a plurality of mechanical and electrical micro-sensors configured in an array to simultaneously measure electrical and mechanical properties of a sample, wherein a first mechanical micro-sensor is formed as a patterned layer of at least one of the compliant materials, wherein the patterned layer is coupled to a first pillar comprising a dielectric material formed onto the compliant materials, the first pillar being coated with a metal film at a contact surface with the sample and along a side of the first pillar to act as a conductive probe for the first electrical micro-sensor, and wherein the first pillar is formed on the first mechanical micro-sensor to transfer a force to the first mechanical micro-sensor.

Unlike state of art eye blink detection techniques that are generalized for usage across individuals affecting accuracy of eye blink prediction from subject to subject, embodiments of the present disclosure provide a method and system for personalized eye blink detection using passive camera-based approach. The method first generates a subject specific annotation data, which is then further processed to derive subject specific personalized blink threshold values. The method disclosed provides three unique approaches to compute the personalized blink threshold values which is one time calibration process. The personalized blink threshold values are then used to generate a binary decision vector (D) while analyzing input test images (video sequences) of the subject of interest. Further, values taken by elements of the decision vector (D) are analyzed for a predefined time period to predict possible eye blinks of the subject.

Disclosed embodiments include methods and systems including a receiver unit of a glucose monitoring system. The receiver is configured for communicating with a remote transmitter unit coupled with a glucose sensor. The glucose sensor generates data signals associated with a glucose level. The receiver unit includes a processor, a display, and a memory for storing instructions which, when executed by the processor: access a transmitter key associated with the remote transmitter unit; transmit a command to the remote transmitter unit after verifying the transmitter key; receive communication packets from the remote transmitter unit including a first data segment with data signals indicative of the glucose level and a second data segment with information corresponding to a remaining life of the remote transmitter unit; estimate a remaining life of the remote transmitter unit; process the data signals; and output the estimated remaining life and the processed data signals for display.

A method for time-synchronizing waveforms from different patient monitors that does not require devices to have high-precision synchronized clocks or to be coupled to a triggering synchronization signal generator. Comparable signals may be obtained from different devices either by placing selected sensors from the devices in the same locations, or by filtering signals from one device to obtain a signal comparable to signals from another device. Filtering may for example transform waveforms into independent components and identify a component that matches a signal from another device. The comparable signals may then be transformed into frequency variation curves, such as time intervals between peak values, to facilitate detection of the time shift between the signals. Cross correlation of the frequency variation curves may be used to locate the precise time shift between the signals. Use of frequency variation curves may be more robust than directly comparing and correlating the original signals.

Systems and methods described provide dynamic and intelligent ways to change the required level of user interaction during use of a monitoring device. The systems and methods generally relate to real time switching between a first or initial mode of user interaction and a second or new mode of user interaction. In some cases, the switching will be automatic and transparent to the user, and in other cases user notification may occur. The mode switching generally affects the user’s interaction with the device, and not just internal processing. The mode switching may relate to calibration modes, data transmission modes, control modes, or the like.

An electronic device is provided. The electronic device includes a communication module, a display, a memory, a biosensor configured to measure oxygen saturation, and at least one processor. The at least one processor may be configured to obtain electronic medical record (EMR) data from an external server through the communication module, identify oxygen saturation-related medical records based on the EMR data, based on occurrence of an event, determine a specified oxygen saturation measurement period and a specified reference oxygen saturation range based on the oxygen saturation-related medical records, measure oxygen saturation based on the specified oxygen saturation measurement period by using the biosensor, identify whether the measured oxygen saturation satisfies the specified reference oxygen saturation range, and display the measured oxygen saturation and information indicating whether the measured oxygen saturation satisfies the specified reference oxygen saturation range on the display.