On the Dimensionality of Sleep-EEG Data

1995 ◽  
Vol 31 (3) ◽  
pp. 166-172 ◽  
Author(s):  
Elke Niestroj ◽  
Ingrid Spieweg ◽  
Werner M. Herrmann
Keyword(s):  
Sleep Eeg ◽  
Eeg Data

Expert-in-the-loop Learning for Sleep EEG Data

2018 ◽  
Author(s):  
Vaclav Gerla ◽  
Vaclav Kremen ◽  
Martin Macas ◽  
Elizaveta Saifutdinova ◽  
Arnost Mladek ◽  
...  
Keyword(s):  
Sleep Eeg ◽  
Eeg Data

On the Use of Neural Network Techniques to Analyse Sleep EEG Data

1997 ◽  
Vol 36 (4) ◽  
pp. 194-210 ◽  
Author(s):  
R.B. Baumgart-Schmitt ◽  
W.M. Herrmann ◽  
R. Eilers ◽  
F. Bes
Keyword(s):  
Neural Network ◽  
Sleep Eeg ◽  
Eeg Data

Estimation of the Correlation Dimension of All-Night Sleep EEG Data with a Personal Super Computer

1994 ◽  
pp. 283-290 ◽  
Author(s):  
Peter Achermann ◽  
Rolf Hartmann ◽  
Anton Gunzinger ◽  
Walter Guggenbühl ◽  
Alexander A. Borbély
Keyword(s):  
Correlation Dimension ◽  
Sleep Eeg ◽  
Night Sleep ◽  
Eeg Data ◽  
Super Computer

Effects of Lorazepam on the Automatic Online Evaluation of Sleep EEG Data in Healthy Volunteers

1998 ◽  
Vol 31 (02) ◽  
pp. 55-59 ◽  
Author(s):  
M. Grözinger ◽  
P. Kögel ◽  
J. Röschke
Keyword(s):  
Healthy Volunteers ◽  
Sleep Eeg ◽  
Online Evaluation ◽  
Eeg Data

Does sleep EEG data distinguish between UP, BPI or BPII major depressions?

1998 ◽  
Vol 49 (3) ◽  
pp. 181-187 ◽  
Author(s):  
P Fossion ◽  
L Staner ◽  
M Dramaix ◽  
Ch Kempenaers ◽  
M Kerkhofs ◽  
...  
Keyword(s):  
Sleep Eeg ◽  
Eeg Data

scholarly journals Biological differences in endogenous depressive placebo responders versus nonresponders: Dexamethasone suppression test and sleep EEG data

1988 ◽  
Vol 24 (1) ◽  
pp. 97-101 ◽  
Author(s):  
Gary K. Zammit ◽  
Alan H. Rosenbaum ◽  
Peter Stokes ◽  
John Davis ◽  
Frank Zorick ◽  
...  
Keyword(s):  
Dexamethasone Suppression Test ◽  
Sleep Eeg ◽  
Eeg Data ◽  
Suppression Test ◽  
Dexamethasone Suppression ◽  
Biological Differences

scholarly journals Deep learning for classification of sleep EEG data during the epidemic of Coronavirus Disease

2020 ◽  
Vol 1 (2) ◽  
pp. 01-05
Author(s):  
Bin Zhao
Keyword(s):  
The Body ◽  
Sleep Eeg ◽  
Quality Of Sleep ◽  
Eeg Signals ◽  
Eeg Data ◽  
The Impact ◽  
Electroencephalogram Eeg ◽  
Important Basis

Sleep is an important part of the body's recuperation and energy accumulation, and the quality of sleep also has a significant impact on people's physical and mental state during the epidemic of Coronavirus Disease. It has attracted increasing attention how to improve the quality of sleep and reduce the impact of sleep related diseases on health. The electroencephalogram (EEG) signals collected during sleep belong to spontaneous EEG signals. Spontaneous sleep EEG signals can reflect the body own changes, which is also an important basis for diagnosis and treatment of related diseases. Therefore, the establishment of an effective model for classifying sleep EEG signals is an important auxiliary tool for evaluating sleep.

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