On the Extraction of the Snore Acoustic Signal by Independent Component Analysis

F. Vrins, J. Deswert, D. Bouvy, V. Bouillon, J.A. Lee, C. Eugéne, and M. Verleysen (Belgium)


Snoring, non-invasive measurement, independent component analysis.


Physicians are interested in the acoustic signal of snore, because it allows them to diagnose the patient and eventu ally to avoid several dangerous accidents. Today, its mea sure is not satisfactory for various reasons. In this pa per, we explore a new way to measure this signal: Blind Source Separation (BSS). We give encouraging results of source separation in this application but also stress the obstacles which prevent a perfect separation when BSS is achieved by the classic linear, instantaneous and un noiseless model of Independent Component Analysis, an undoubtfully very promising signal processing method in the biomedical world.

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