A low computational cost algorithm for REM sleep detection using single channel EEG.

ABSTRACT: The push towards low-power and wearable sleep systems requires using minimum number of recording channels to enhance battery life, keep processing load small and be more comfortable for the user. Since most sleep stages can be identified using EEG traces, enormous power savings could be achieved by using a single channel of EEG. However, detection of REM sleep from one channel EEG is challenging due to its electroencephalographic similarities with N1 and Wake stages. In this paper we investigate a novel feature in sleep EEG that demonstrates high discriminatory ability for detecting REM phases. We then use this feature, that is based on spectral edge frequency (SEF) in the 8-16 Hz frequency band, together with the absolute power and the relative power of the signal, to develop a simple REM

SUBMITTER: Imtiaz SA 

PROVIDER: S-EPMC4204008 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature