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.<>