Abstract: A method for the continuous recognition of gestures of a user of a handheld mobile terminal fitted with a motion sensor assembly, includes the steps of, for at least one motion sensor measuring signal of the motion sensor assembly, over a time window: detecting (2) a candidate gesture; and comparing (3) said candidate gesture with a set of predetermined gestures. The candidate gesture detection step (2) includes substeps of: calculating the value of a parameter representative of the symmetry of the gesture with respect to at least one axis; and calculating the value of a parameter representative of the energy of the gesture along at least one axis.

Abstract: The invention relates to a portable device to monitor at least an activity of a user The portable device comprises at least a first sensor configured to capture signals representative of at least a physical parameter induced by at least an activity of the user, and a channel of communication to processing capabilities. The processing capabilities are configured to perform a first classification algorithm to classify the signals representative of the at least a physical parameter over a first period of time into a first set of classes of activities of the user, and to perform a second classification algorithm to classify the at least an activity of the user at the output of the at least first classification algorithm over a second period of time which includes the first period of time using a second set of classes which is different from the first set of classes The invention also relates to a method to monitor, a computer program and a system to monitor at least an activity of a user.

Abstract: A method for the continuous recognition of gestures of a user of a handheld mobile terminal fitted with a motion sensor assembly, includes the steps of, for at least one motion sensor measuring signal of the motion sensor assembly, over a time window: detecting (2) a candidate gesture; and comparing (3) said candidate gesture with a set of predetermined gestures. The candidate gesture detection step (2) includes substeps of: calculating the value of a parameter representative of the symmetry of the gesture with respect to at least one axis; and calculating the value of a parameter representative of the energy of the gesture along at least one axis.

Abstract: This method for estimating biological or chemical parameters in a sample (E) comprises steps consisting of putting (102) the sample (E) through a processing chain, obtaining a signal representative of said biological or chemical parameters as a function of at least one variable of the processing chain, and estimating (104, 106, 108, 110) said biological or chemical parameters using a signal processing device by Bayesian inference, on the basis of a direct analytical modeling of said signal as a function of said biological or chemical parameters of the biological sample and as a function of technical parameters of the processing chain. At least two of said biological or chemical and technical parameters have a probabilistic dependence relationship between each other and signal processing by Bayesian inference is further accomplished on the basis of modeling by a conditional prior probability distribution of this dependence.