Abstract

Sleep studies are used to evaluate and diagnose a variety of sleep problems. A sleep study is very potential in controlling neurological, breathing and movement disorders. Some of the problems that may lead doctor to order a sleep study are snoring, sleep apnea, sleep walking, bedwetting, sleep talking, the feeling of being tired all day, sleeping during a day. A sleeping laboratory can detect these interruptions, analyse and record detailed information to help doctor diagnose problem and determine the best treatment. Light therapies and simulation of day-night environment have been recognized that can stabilize the patterns of delayed sleep phase syndrome and advanced sleep phase syndrome. In this paper we present sleeping laboratory based on smart glass controlled automatically by sensors, ccd camera and real-time pattern recognition environment. We present sensor network and real-time multiparametric algorithms sending signals to intelligent glass controller. For classification we used fast SVM classifier with new kernel method. Historical medical database is used as training set for automated classifier.