1. For scientific and clinical requirements the present objective is a robust automatic online
algorithm to detect rapid eye movement (REM) steep from single channel sleep EEG data …

Artificial neural networks are well known for their good performance in pattern recognition.
Their suitability for detecting REM sleep periods on the basis of preprocessed EEG data in …

In earlier publications we described an automatic online algorithm to detect rapid eye
movement (REM) sleep from a single-channel monopolar EEG recording (Crozinger et al …

An automatic procedure for the online recognition of REM sleep appears to be a necessary
tool for selective REM sleep deprivation in depressive patients. To develop such a …

Sleep stage scoring is generally determined in a polysomnographic (PSG) study where
technologists use electroencephalogram (EEG), electromyogram (EMG), and …

Automatic sleep staging has remained a constant challenge over the years due to scientific
and economic reasons. Rapid eye movement (REM) sleep recognition is a most critical …

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 …

Rapid eye movements (REMs) are a prominent feature of REM sleep, and their distribution
and time density over the night represent important physiological and clinical parameters. At …

This paper presents a critical discussion of methods used for the recording and the
automated detection of sleep rapid eye movements (REMs) via electro‐oculographic (EOG) …

Background In sleep electroencephalographic (EEG) signals, artifacts and arousals marking
are usually part of the processing. This visual inspection by a human expert has two main …