The invention relates to an electronic device for monitoring a neurophysiological state of an operator in a control station of an aircraft including a receiver module configured for receiving a datum from a sensor, a categorization module configured for associating, from the data received, a category with the operator, a processing module configured for extracting from each datum, at least one parameter representative of the neurophysiological state of the operator, and a detection module configured for applying a model derived from a machine learning method, for determining, according to the representative parameters, whether the operator is in a nominal neurophysiological state or in an altered neurophysiological state, the model being chosen from a list of predetermined models according to the category associated with the operator.

The invention relates to an electronic device for monitoring a neurophysiological state of an operator in a control station of an aircraft including a receiver module configured for receiving a datum from a sensor, a categorization module configured for associating, from the data received, a category with the operator, a processing module configured for extracting from each datum, at least one parameter representative of the neurophysiological state of the operator, and a detection module configured for applying a model derived from a machine learning method, for determining, according to the representative parameters, whether the operator is in a nominal neurophysiological state or in an altered neurophysiological state, the model being chosen from a list of predetermined models according to the category associated with the operator.

-- A method including acquisition of useful data during an experiment phase, the useful data being physiological data obtained by means of sensor(s) and each corresponding to an input data of the monitoring application, acquisition of declarative data of the individual, in real-time during the experimental phase and/or in differed time before and/or after the experimental phase, merging of useful data and declarative data in order to calculate a true level of fatigue, labeling the useful data with the calculated true level of fatigue, and storing the labeled useful data in the learning database.

Provided are a method, server, and computer program for designing a customized headgear for transcranial direct current stimulation. According to one embodiment, there is provided a method for designing a customized headgear for transcranial direct current stimulation performed by a computing device and applying electrical stimulation to a preset target point in a brain of a subject, the method including: acquiring a head image of the subject; generating a headgear mask by using the acquired head image; generating a stimulator mask by using an optimal stimulation position combination for applying the electrical stimulation to the preset target point; and generating a customized headgear mask for the subject by performing a subtraction operation between the generated headgear mask and the generated stimulator mask.

A method, a structure, and a computer system for traumatic event detection. The exemplary embodiments may include collecting data using sensors worn by a user and identifying a traumatic event based on applying a model to the data, wherein the model correlates values of the data with traumatic events and traumatic brain injuries. The exemplary embodiments may further include identifying the traumatic brain injury resulting from the traumatic event.

Techniques for compressing neural signals are disclosed herein. The neural signal compression techniques can include lossless compression, lossy compression, binned spike compression, and spike-band power compression. Lossless compression can compress neural signals using a difference predictor to encode compressed neural signals via binary and unary coding. Lossy compression can compress neural signals using quantized wavelet transforms to generate an encoded bit-stream of compressed neural signals. Binned spike and spike-band power compression can leverage the sparse nature of neural signals to threshold the neural signals for generating an appended bit-stream of compressed neural signals.

Novel tools and techniques are provided for the detection and differentiation of activities and/or conditions based on measured bio-signals.

A non-invasive, optical-based physiological monitoring system is disclosed. In an embodiment, the non-invasive, optical-based physiological monitoring system comprises an emitter configured to emit light into a tissue site of a living patient; a detector configured to detect the emitted light after attenuation by the tissue site and output a sensor signal responsive to the detected light; and a processor configured to determine, based on the sensor signal, a first physiological parameter indicative of a level of pain of the patient.

A non-invasive, optical-based physiological monitoring system is disclosed. In an embodiment, the non-invasive, optical-based physiological monitoring system comprises an emitter configured to emit light into a tissue site of a living patient; a detector configured to detect the emitted light after attenuation by the tissue site and output a sensor signal responsive to the detected light; and a processor configured to determine, based on the sensor signal, a first physiological parameter indicative of a level of pain of the patient.

A method and system for determining the state of a patients brain under anesthesia. The present invention recognizes that anesthesia compounds induce different signatures in physiological characteristics of the patient under anesthesia and aids interpretation of physiological characteristics and signatures therein based on a selected anesthesia compound. The present invention aids the monitoring and/or interpreting of the physiological characteristics to a state of the patient's brain.