An Investigation of Acoustical and Signal Processing Techniques for Classification, Diagnosis and Monitoring of Breathing Abnormalities in Sleep

Abstract

Snoring is the often earliest symptom of Obstructive Sleep Apnoea (OSA) and other respiratory problems. A successful medical outcome depends on an accurate preoperative diagnosis of the anatomical reason for snoring. The perception of snoring is highly subjective; therefore, there is a need for an ob jective measurement of snoring for an accurate patient assessment and the evaluation of treatment effects. The main objective of this study was to distin guish between two types of snoring: palatal and non-palatal snoring considering the acoustic characteristics of the snoring signal. A key innovation is that the snoring signals are not analyzed only subjectively by a medical specialist but also objectively by analyzing recorded snoring signals. The patient’s snoring has been recorded non-invasively during sleeping and processed in both time and frequency domains to determine the origin of the snore and to identify the key features useful to the medical specialist.