Assessing the severity of sleep apnea syndrome based on ballistocardiogram.

ABSTRACT:

Background

Sleep Apnea Syndrome (SAS) is a common sleep-related breathing disorder, which affects about 4-7% males and 2-4% females all around the world. Different approaches have been adopted to diagnose SAS and measure its severity, including the gold standard Polysomnography (PSG) in sleep study field as well as several alternative techniques such as single-channel ECG, pulse oximeter and so on. However, many shortcomings still limit their generalization in home environment. In this study, we aim to propose an efficient approach to automatically assess the severity of sleep apnea syndrome based on the ballistocardiogram (BCG) signal, which is non-intrusive and suitable for in home environment.

Methods

We develop an unobtrusive sleep monitoring system to capture the BCG si

SUBMITTER: Wang Z 

PROVIDER: S-EPMC5405918 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature