student profile: Mr Arun Sebastian


Thesis work

Thesis title: Prediction of Obstructive Sleep Apnea and site of obstruction using the snoring signal.

Supervisors: Peter CISTULLI , Alistair MCEWAN , Philip DE CHAZAL

Thesis abstract:

Sleep apnoea is a sleep related breathing disorder which involves cessation or a decrease in airflow for at least 10 seconds. In particular, obstructive sleep apnoea (OSA) is characterized by repetitive obstruction in the upper airway during sleep which is common in the general population. The obstruction events can occur hundreds of times in a night and may not be aware of any disturbance by the sufferer the next day. It can have significant negative effects on a person’s sleep quality, and hence quality of life and cognitive functions.
Standard diagnosis of sleep apnoea is carried out with an Polysomnography (PSG) where the patient’s sleep is monitored overnight while recording a number of signals such as ECG, EMG, EOG, oxygen saturation etc, to assist with the diagnosis. These signals will help in determining whether a person is awake or asleep and also to determine whether his or her pattern of sleep is normal.. But the overnight PSG in an attended centre are expensive, long waiting times to get a test due to limited resources and patients may not sleep well due to the attachment of various uncomfortable sensors . Therefore an important impetus for the present research is to develop a low cost, non-invasive and convenient method with a reduced number of diagnostic signals to accurately diagnose sleep apnoea, in the familiar home environment.

Snoring is caused by the vibration of different tissues such as soft palate, epiglottis in the upper airway or by the collapsible walls of the airway. Depending on the shape and physical dimensions of the UA, different snoring sounds with diverse acoustic properties, or formant frequencies, are produced. Therefore snoring carries information relating to the site and degree of obstruction of the upper airway. Recently, much
research has been dedicated to the analysis of snore signals in detection and classification of OSA, but not so much effort have been taken to find the relation between snoring and site
of obstruction. The identification of the sites of upper airway obstruction in OSA patient may be beneficial in choosing the appropriate surgical intervention other than continuous
positive airway pressure.

Note: This profile is for a student at the University of Sydney. Views presented here are not necessarily those of the University.