Body Sensor Networking, Design and Algorithms

5Polysomnography and Sleep Analysis

5.1 Introduction

Although most body sensor network (BSN) techniques are used for human monitoring during both awake and sleep situations, some types of measurements and methods are more suitable for monitoring humans during sleep. In this chapter some popular sleep monitoring systems and methods together with their analytical approaches are revised or presented and the applications explained in detail.

Human sleep monitoring is crucial for the diagnosis and management of certain medical conditions, such as sleep related disorders, which affect millions of people [1, 2]. A good state of mental and physical health is closely related to a high quality of sleep. There are various physiological parameters which can be used to detect or predict sleep related disorders and assess the quality of sleep. Wearable sensors can be used to measure these physiological parameters and use them in an inference system for monitoring, treatment, and the management of medical conditions.

There are various sleep disorders which stem from neurological, physiological, and even physical disabilities, abnormalities, or diseases. Obstructive sleep apnoea, upper airway resistance syndrome, periodic limb movement disorder, restless leg movement disorder, narcolepsy, rapid eye movement (REM) sleep behaviour, insomnia, circadian rhythm disorder, and consciousness disorder are probably the most common and important sleep abnormalities.

Currently, the use of wearable sensors ...