Indexing and Classifying Snore Characteristics Using Support Vector Machine and Integrated Signal Processing Algorithm

摘要

Snoring is the loud or severe sound that buzzes when an individual sleep. Snoring can be produced through the nose, throat, uvula, or tongue. Each nature could be a sign that can be beneficial to specify what medical ailment or disorder a person could have. This paper focused on a sleeping disorder called Obstructive sleep apnea (OSA). Initiated from other investigation concerning about snoring detection and indexing, categories of snore have been segregated and classified from their elementary acoustic compositions such as the sound intensity and frequency. The study aims to come up with a device that records a snore sound that classifies the snore to what ailment the patient could be suffering using Support Vector Machine (SVM) and signal processing algorithm.