Segmentation of infant respiratory sounds with Malvar´s wavelets

The authors present an application of the Malvar´s wavelet transform to infant´s respiratory sounds. They first introduce the acoustical analysis of infantile respiratory sounds. Then, they describe the Adaptive Local Trigonometric Transform they use to operate a segmentation of the signal. The authors also present the results obtained with physiological signals, and they show that their approach allows to highlight symptomatic events called stridors among a set of consecutive events