Sleep Apnea

Automatic sleep apnea detection and sleep classification using the ECG and the SpO2 signals, 2009-FCT

Author:
Lara Simons
Supervisors:
Arnaldo Batista
Manuel Ortigueira
Abstract:
The present work describes the aspects to implement a system that can be used
as a swift and accessible screening tool in patients whose complaints are compatible
with OSAS (Obstructive Sleep Apnea Syndrome). This system only uses two signals,
electrocardiogram (ECG) and the saturation of oxygen in arterial blood flow (SPO2).
This system would be applied for the ambulatory automatic screening of OSAS, which
currently are done in a Hospital environment, with a substantial waiting list. The system
also would overcome the time consuming visual sleep scoring that contributes for the
mentioned waiting list. We have developed a system that automatically detects OSAS
based on the ECG and SpO2. However this system has to be paired up with another that
detects the awake/sleep/REM periods (also based on the ECG), which is also part of this
work. This last component has proved to produce results that are complex to classify,
for which there is still a lack of research work. However we have described the
necessary algorithms, and have used state-of-the-art signal processing tools, such as
wavelets.

See thesis here:

http://test01.rcaap.pt/bitstream/10362/2649/1/Simons_2009.pdf