Abstract: The monitoring system (1) is used for detecting an incapacitation of the pilot of an aircraft, said aircraft being equipped with a piloting device (40) which can be actuated manually by the pilot. Same includes: at least one pressure sensor integrating a contact sensor (11, 12) mounted on the surface of the piloting device (40), so as to generate an elementary indicator when a pressure exerted by the pilot on the piloting device is adapted to the use of the piloting device; and a computing unit (2) programmed for processing the elementary indicator delivered by the pressure sensor and for determining a current state of the pilot and, when said current state corresponds to an incapacitation of the pilot, for issuing an alarm.

Abstract: An electronic system for monitoring the state of awareness of an operator in a control station of an aircraft. The monitoring system includes a module for receiving a datum from at least two sensors onboard the aircraft, at least one of the sensors being called a worn sensor being in physical contact with the operator and at least one of the sensors being called an off-set sensor being at a distance from the operator, a processing module configured for extracting from each datum at least one parameter representative of the state of awareness of the operator, a fusion module configured for receiving the representative parameters and implementing a machine learning method for determining, depending on the representative parameters, whether the operator is in a nominal or an altered state of awareness.

Abstract: -- 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.

Abstract: 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.

Abstract: A computer-implemented method for determining the state of a system, which includes steps of: collecting data relating to a system, the data being noisy data comprising data of interest and noise; generating a signal to be analyzed from the collected data, the signal being a noisy signal comprising a signal of interest and noise; analyzing the regularity of the signal of interest by compensating the influence of the noise in the computation of the power of the difference between the integrated noisy signal and its trend; and determining the state of the system depending on the result of the analysis of the regularity of the signal of interest.

Abstract: A computer-implemented method for determining the state of a system, which includes steps of: collecting data relating to a system, the data being noisy data comprising data of interest and noise; generating a signal to be analyzed from the collected data, the signal being a noisy signal comprising a signal of interest and noise; analyzing the regularity of the signal of interest by compensating the influence of the noise in the computation of the power of the difference between the integrated noisy signal and its trend; and determining the state of the system depending on the result of the analysis of the regularity of the signal of interest.