… brain rhythms, we use EEG to score sleep stage in this paper… waves from the EEG signals
of each segment. Then, the … adjacent phases are difficult to discriminate when only EEG …

… framework by excluding EEG sensors and exploring only non-EEG sensors to determine the
… to their correlation with REM sleep and specifically detecting rapid eye movement through …

… ing and obtaining features of EEG signals [10]. They used … In this layer, neurons are only
connected to some adjacent … data point in the entire segment, and then we upsampled the …

… the human brain functions called artificial neural networks(ANN). … to detect false R peaks by
comparing the sum of adjacent RR … collected by other sensors such as EEG, EMG and SpO2. …

… neural network (FDCCNN) is proposed to extract features from raw EEG data and classify
sleep … Discriminating the epochs that occur on adjacent phases is difficult when only EEG is …

… Epoch extraction algorithms have been used repeatedly in segmentation of many … type of
neural networks that introduces the notion of time by using cyclic edges between adjacent steps…

… cyclic neural network to learn the time information in EEG … divided into 30 s each segment.
According to R&K guidelines, … combined effects of multiple, adjacent and similar classes. By …

… manifold-deep convolutional neural network with hyperbolic … The specific division ratio is
shown in Sections 4.4 and 4.5. … The sleep stages are contiguous in the sleep cycle, therefore …

… neural networks (CNN) and bidirectional long short-term … sample to consider the surrounding
epochs. The reported … to decompose a 30-s EEG segment to represent each epoch as a …

… each 30-s EEG segment into spectrograms which were … Subjects were recruited from the
public by online advertisements and … Mov was adjacent to the non-Wake (ie, REM or non-REM), …