Abstract: A system for observing a walking activity of a person comprises a device (DISP) adapted for delivering at output, for a footstep of the person, a first difference of angular speeds of the corresponding tibia between the instant at which the heel of the foot is planted and the instant at which the foot is laid flat, a second difference of angular speeds of the corresponding tibia between the instant at which the heel of the foot is planted and the instant at which the last toe of the foot is lifted, and an angular speed of the corresponding tibia at the instant at which the foot is laid flat. The system comprises analysis means (AN) for analyzing the signals delivered by the device and adapted for determining a type of walking of the user as a function of time by using a hidden Markov model with N states corresponding respectively to N types of walking.

Abstract: This method for detecting activity (A) of a physical system carrying a motion sensor comprises the following steps: extracting (100) a sequence (M) of measurements provided by the motion sensor; deducing (102) therefrom an observation sequence (O) calculated on the basis of the measurement sequence (M); determining (104) the activity (A) of the physical system in the form of a sequence of states corresponding to the observation sequence, using a statistical model of components of the observation sequence in view of a plurality of possible predetermined states of the physical system. At least one component of the observation sequence (O) is calculated on the basis of a reference value ({circumflex over (?)}) of a vector representing a reference axis.

Abstract: The system for determining the activity of a person lying down has at least one motion sensor (CM) having at least one measurement axis, which is provided with a fastener (MF) for firmly connecting the motion sensor (CM) to a user. The system includes a filter (FILT) for selecting, for at least one measurement axis of the motion sensor (CM), a high-frequency signal (HF) and a low-frequency signal (BF); a first calculation unit (CALC1) for calculating a first variable (x(n)) representing a temporal variation of the low-frequency signal (BF); a second calculation means (CALC2) for calculating a second variable (y(n)) comprising the Euclidean norm, along at least one measurement axis, of the high-frequency signal (HF); and an analysis unit (AN) that determines an activity of prone user as a function of time using a hidden Markov model having N states corresponding to N activities respectively.

Abstract: A method for configuring a device for detecting a situation from a set of situations where a physical system comprises the following steps: reception of a learning sequence corresponding to a given situation of the physical system; determination of parameters of a hidden-state Markov statistical model recorded in the detection device and relating to the given situation, on the basis of a prior initialisation of these parameters.

Abstract: A method for detecting the presence of an OFDM signal in a received signal wherein said received signal is down converted into baseband and subjected to a passband filtering corresponding to a band of interest before being sampled. The thus sampled signal is subjected to a second filtering for eliminating at least one interfering line in the band of interest. The presence of an OFDM signal is detected if the signal filtered by the second filtering is cyclostationary.

Abstract: A method of estimating at least one modulation parameter of an OFDM signal, the signal being sampled during a time window in order to provide a sequence of samples, the method including: (a) grouping together consecutive samples of the sequence according to a tested value of the parameter, in order to form a plurality of vectors; (b) estimating a covariance matrix of the vectors; (c) calculating a theoretical covariance matrix that would be obtained using an OFDM signal of which the modulation parameter would have the tested value; (d) measuring a distance between the covariance matrix and the theoretical covariance matrix; and iterating the steps (a), (b), (c) and (d), wherein the estimated value of the parameter is that achieving a shortest distance in the step (d).

Abstract: A device detecting at least one scenario from predetermined scenarios wherein a physical system observed by at least one sensor is likely to be found, including: at least one sensor providing a physical system observation data sequence; a storage storing at least one statistical model associating possible observation data values with the predetermined scenarios; a computer programmed to select at least one of the scenarios based on the observation data sequence and at least one statistical model. The storage includes plural statistical models broken down into plural ordered levels between an input level, wherein each statistical model associates possible values of at least a portion of the observation data with intermediate states for the statistical model, and an output level, wherein each statistical model associating possible values of at least a portion of the intermediate states of a lower level with at least a portion of the predetermined scenarios.

Abstract: The present invention relates to a method for blind estimation of at least one parameter of an OFDM signal according to a maximum likelihood (ML) criterion. In one embodiment, the estimation method uses a deterministic maximum likelihood criterion. In another embodiment, the estimation method assumes that the modulation symbols modulating the sub-carriers of the OFDM multiplex are i.i.d. and Gaussian random variables. The estimation of said parameter is carried out while minimizing a cost function depending on the chosen criterion.

Abstract: This invention relates to a method of searching for free band using a cognitive telecommunication terminal operating in a zone covered by a primary telecommunication system using a plurality of frequency bands (B). The terminal classifies said bands as a function of their conditional probabilities of being available (p(bmax|Bocc,Bopp)), knowing a first set of bands already occupied by the primary telecommunication system (Bocc) and a second set of bands not occupied by this primary telecommunication system but already used by another cognitive terminal (Bopp), said terminal beginning its search by the band with the highest conditional probability (bmax).

Abstract: A method for detecting a cyclostationary signal in a signal to be analyzed, received from a transmitter by a receiver or read from a recording medium by a reader device. According to this method, the value of a discrimination function J is estimated, expressed as a quadratic form of the cyclic correlation coefficients of the signal to be analyzed for a set (I*M) of non-zero time shifts and a set (IK) of cyclic frequencies, and the value 1 - ? ? ( v , U ? 4 ? J ) is compared with a wrong detection rate ? in order to determine whether said cyclostationary signal is present in the signal to be analyzed, wherein ?(?,x) is the normalized lower incomplete gamma function, ? is the product of the cardinal (M) of said set of non-zero time shifts and of the cardinal (K) of said set of cyclic frequencies, U is the width of the autocorrelation window on which the cyclic correlation coefficients are calculated, and ?4 is the square of the noise variance.

Abstract: This invention relates to a method for determining at least one characteristic of an OFDM signal within a received signal, characterized in that: a plurality of cyclic correlation coefficients (?k/(?+?)(?)) for the received signal is calculated (420, 520) for a correlation time difference (?) and a plurality of cyclic frequencies ( k ? + ? ) ; a discrimination function is calculated (430, 530) as a function of the amplitude of said cyclic correlation coefficients; said OFDM signal characteristic is deduced (440, 561, 562) as a function of at least one value of said discrimination function.

Abstract: The invention relates to a method for estimating the orientation in an inertial reference frame of a solid in motion equipped with an accelerometer and a magnetometer which are mounted on said solid. According to this method, an orientation of the solid is measured at a reference instant, said orientation being defined by a rotation matrix for rotating from the mobile reference frame of the solid at the reference instant to the inertial reference frame. A rotation matrix for rotating between the orientation of the solid at a subsequent instant n and said orientation of the solid at the reference instant is thereafter estimated. The orientation of the solid at the instant n is thereafter determined with the aid of the previously estimated rotation matrix and of the known orientation of the solid at the reference instant.

Abstract: The present invention relates to a method for the blind estimation of at least one parameter of an OFDM signal by maximizing an objective function depending on said parameter. The objective function implements a parameterized model of the OFDM modulation and a matched filtering corresponding to that model. The OFDM signal, baseband demodulated and then sampled in an observation window, is the object of the adapted filtering to calculate the objective function. It is also proposed to include, in the parameterized model, the temporal offset between the observation window and an OFDM symbol as well as the frequency offset between the frequency of the OFDM signal carrier and the baseband demodulation frequency.

Abstract: A system for detecting an epileptic seizure in a prone person, comprising: at least one motion sensor with at least one measurement axis having fastening means for securing said motion sensor to said person; first means for determining a first probability of at least a first state transition diagram of the nocturnal activity of a prone person with respect to data representing the measurement signals of the motion sensor, said first diagram comprising predetermined probabilities of oriented transitions between two different or identical states, the probabilities of the states of said first diagram being predetermined; and second means for determining a second probability of at least a second state transition diagram for an epileptic seizure with respect to data representing the measurement signals of the motion sensor, said second diagram comprising predetermined probabilities of oriented transitions between two different or identical states, the probabilities of the states of said second diagram being pred

Abstract: System for determining the activity of a mobile element (EM), includes at least one motion sensor (CM) having at least one measurement axis, which is provided with a fattener (MF) for securely connecting said motion sensor (CM) to the mobile element (EM).

Abstract: The present invention concerns a blind estimation method of at least one temporal modulation parameter of an OFDM signal, in which a plurality of demodulation attempts of said OFDM signal are carried out using a plurality of respective values of this temporal parameter and, for each demodulation attempt, a cost function representative of the entropy of the demodulated signal is calculated, the estimate of said temporal parameter then being obtained as the value of this parameter minimizing said cost function.

Abstract: A system for determining the posture of a person has a motion sensor (CM) with at least one axis of measurement, which is provided with fixing means (MF) for rigidly connecting said motion sensor (CM) to a user. Analysis means (AN) are also included for determining a posture of the user. The analysis means (AN) utilize: (A) joint densities of probabilities of a low-frequency component and a high-frequency component, these densities of probabilities being defined for each posture; and (B) probabilities of transition between two successive postures.

Abstract: An OFDM signal identification method in a received signal, wherein the received signal is sampled and cut off into blocks of P samples, each block being subjected to an inverse Fourier transform to obtain a plurality of symbols at a plurality of frequencies. For each frequency of the plurality, the kurtosis of the set of symbols thus obtained at this frequency is calculated, and then it is determined whether the kurtosis has a periodicity in frequency domain from kurtosis values calculated for the frequencies of the plurality, and the presence of an OFDM signal in the received signal is identified if the kurtosis has such a periodicity.

Abstract: The system for determining the activity of a person lying down has at least one motion sensor (CM) having at least one measurement axis, which is provided with a fastener (MF) for firmly connecting the motion sensor (CM) to a user. The system includes a filter (FILT) for selecting, for at least one measurement axis of the motion sensor (CM), a high-frequency signal (HF) and a low-frequency signal (BF); a first calculation unit (CALC1) for calculating a first variable (x(n)) representing a temporal variation of the low-frequency signal (BF); a second calculation means (CALC2) for calculating a second variable (y(n)) comprising the Euclidean norm, along at least one measurement axis, of the high-frequency signal (HF); and an analysis unit (AN) that determines an activity of prone user as a function of time using a hidden Markov model having N states corresponding to N activities respectively.

Abstract: A system for observing a walking activity of a person comprises a device (DISP) adapted for delivering at output, for a footstep of the person, a first difference of angular speeds of the corresponding tibia between the instant at which the heel of the foot is planted and the instant at which the foot is laid flat, a second difference of angular speeds of the corresponding tibia between the instant at which the heel of the foot is planted and the instant at which the last toe of the foot is lifted, and an angular speed of the corresponding tibia at the instant at which the foot is laid flat. The system comprises analysis means (AN) for analyzing the signals delivered by the device and adapted for determining a type of walking of the user as a function of time by using a hidden Markov model with N states corresponding respectively to N types of walking.