Abstract: This invention concern a system (1) for recognizing online handwriting comprising:—a handwriting instrument (2) including a body (3) extending longitudinally between a first end (4) and a second end (5), the first end (4) having a writing tip (6) which is able to write on a support, the handwriting instrument (2) further including a module (17) comprising at least one motion sensor (7) configured to acquire motion data on the handwriting of a user when the user is calculating unit (8) communicating with the at least one motion sensor (7) and configured to analyze the motion data by a machine learning model trained in a multitask way such that it is capable of performing at least two tasks at the same time, the machine learning model being configured to deliver as an output the sequence of characters which was written by the user with the handwriting instrument.

Abstract: A system for detecting handwriting problems may include a handwriting instrument including a body extending longitudinally between a first end and a second end, the first end having a writing tip which is able to write on a support, the handwriting instrument further including at least one motion sensor configured to acquire data on the handwriting of the user when a user is using the handwriting instrument, and one calculating unit communicating with the motion sensor and configured to analyze the data by an artificial intelligence trained to detect whether the user has handwriting problems.

Abstract: A computer-implemented method for diagnosing mechanical default of a mechanical watch, wherein at least one vibration signal is acquired from the mechanical watch the vibration signal is analyzed by an artificial intelligence trained to detect mechanical default in mechanical watches to determine a diagnosis whether the mechanical watch is working properly or not.

Abstract: A method for recognizing online handwriting comprising acquiring, by a handwriting instrument comprising a module comprising at least one motion sensor, motion data on the handwriting of the user when the user is writing a sequence of characters with the handwriting instrument, the handwriting instrument further including a body extending longitudinally between a first end and a second end, the first end having a writing tip which is able to write on a support, analyzing the motion data with a machine learning model trained in a multi-task way, the machine learning model being configured to deliver as an output the sequence of characters which was written by the user with the handwriting instrument.

Abstract: A method for monitoring an animal with an autonomous monitoring device in close proximity to the animal, the monitoring device having a first sensor and a second sensor of higher electric power consumption. The method includes measuring a first parameter with the first sensor, the second sensor being deactivated. An estimated status of the animal is determined based on the first parameter. If the estimated status corresponds to a particular status, the second sensor is activated and measures a second parameter which is used to determine a specified estimated status of the animal.

Abstract: A method for detecting handwriting problem, comprising: acquiring, by a handwriting instrument comprising one motion sensor, motion data while a user is using the handwriting instrument, analyzing the motion data by an artificial intelligence trained to detect a handwriting problem.

Abstract: A method for monitoring an animal with an autonomous monitoring device in close proximity to the animal, the monitoring device having a first sensor and a second sensor of higher electric power consumption. The method includes measuring a first parameter with the first sensor, the second sensor being deactivated. An estimated status of the animal is determined based on the first parameter. If the estimated status corresponds to a particular status, the second sensor is activated and measures a second parameter which is used to determine a specified estimated status of the animal.

Abstract: A computer-implemented method for diagnosing mechanical default of a mechanical watch, wherein at least one vibration signal is acquired from the mechanical watch the vibration signal is analyzed by an artificial intelligence trained to detect mechanical default in mechanical watches to determine a diagnosis whether the mechanical watch is working properly or not.

Abstract: A method for estimating the acoustic reverberations in an environment comprising the following steps: a measurement step in which one acoustic signal emitted in the environment is captured; a step for determination of acoustic energy decay rate distribution during which an acoustic energy decay rate distribution is determined from the acoustic signal captured in step (a); an estimation step during which a reverberation time and a reverberation level of sound in the environment are estimated by regression from the characteristic function of the acoustic energy decay rate distribution determined in step (b).

Abstract: A method for estimating the acoustic reverberations in an environment comprising the following steps: a measurement step in which one acoustic signal emitted in the environment is captured; a step for determination of acoustic energy decay rate distribution during which an acoustic energy decay rate distribution is determined from the acoustic signal captured in step (a); an estimation step during which a reverberation time and a reverberation level of sound in the environment are estimated by regression from the characteristic function of the acoustic energy decay rate distribution determined in step (b).

Abstract: A method for estimating an instantaneous phase of dereverberated acoustic signal, the method comprising the following steps: measurement of an acoustic signal reverberated by propagation in a medium, estimation of a one short-term Fourier transform of the reverberated acoustic signal with a window function, calculation of an instantaneous frequency of dereverberated signal from said short-term Fourier transform and from an influencing factor of the medium, said influencing factor being a function of a reverberation time of said medium, determination of an instantaneous phase of dereverberated signal by integrating the instantaneous frequency of dereverberated signal over time.

Abstract: A method for estimating an instantaneous phase of dereverberated acoustic signal, the method comprising the following steps: measurement of an acoustic signal reverberated by propagation in a medium, estimation of at least a one short-term Fourier transform of the reverberated acoustic signal with at least one a window function, calculation of at least one an instantaneous frequency of dereverberated signal from said short-term Fourier transform and from an influencing factor of the medium, said influencing factor being a function of a reverberation time of said medium, determination of at least one an instantaneous phase of dereverberated signal by integrating the instantaneous frequency of dereverberated signal over time.