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