Generalized gradient vector flow external forces for active contours
Signal Processing - Special issue on deformable models and techniques for image and signal processing
Automatic extraction of time-frequency skeletons with minimal spanning trees
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 01
Techniques to obtain good resolution and concentrated time-frequency distributions: a review
EURASIP Journal on Advances in Signal Processing
EURASIP Journal on Advances in Signal Processing
Characterization of signals by the ridges of their wavelettransforms
IEEE Transactions on Signal Processing
Time-Frequency ARMA Models and Parameter Estimators for Underspread Nonstationary Random Processes
IEEE Transactions on Signal Processing
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The extraction of the frequency components of a signal can be useful for the characterization of the underlying system. One method for isolating a frequency component of a signal is by the extraction and reconstruction of the local maxima or ridge of its time-frequency representation. We compare here the performances of two well-known ridge reconstruction methods, namely the Carmona and Marseille methods, on synthetic signals as well as real electrohysterogram (EHG). We show that Carmona's method presents lower reconstruction errors. We then used the separately reconstructed frequency components of the EHG independently for labor prediction using a synchronization measure. We show that the proposed synchronization parameters present similar prediction rate to classical parameters obtained directly from the time-frequency representation but also seem to provide information complementary to the classical parameters and may thus improve the accuracy in labor prediction when they are used jointly.