Chaotic analysis of snore related sounds

Snoring is a noise related sound, which occurs while sleeping owing to narrow upper airway cause hard to breathing. There are a lot of studies available related to diagnosis and specifying the how harmful for people bodies. Some studies have used these sounds depending on acoustical features; the others have used polysomnography devices that produce some data to analyze the illness. In this study, we have used largest Lyapunov exponents (LLE) for chaotic analysis of snore related sounds in case of different snoring stage on sleeping. Estimated feature values were used for classifying of these sounds with adaptive neuro fuzzy inference system (ANFIS) classifier. These estimated feature values was used input for ANFIS classifier. ANFIS can also classify these sounds with the highest accuracy of 97% training and 89.08% testing results.