We are developing advanced techniques of signal processing and pattern recognition for automatic detection and classification of sleep breathing disorders. These respiratory disorders produce a fragmentation of sleep, causing daytime sleepiness, a reduction of reaction times, lack of concentration, and cardiac problems, among others. The prevalence in the population is very high, but as the studies to detect it are expensive and require of a sleep laboratory where the patient has to sleep all night, the disease is undiagnosed. The research project aims at producing techniques of rapid screening for these breathing anomalies, producing less invasive and easy to use devices, to make the sleep disorders study popular.
Contact: Leandro Di Persia