End-to-end machine learning on raw EEG signals for sleep stage classification

2019 ◽  
Vol 64 ◽  
pp. S139
Author(s):  
E. Gunnlaugsson ◽  
H. Ragnarsdóttir ◽  
H.M. þráinsson ◽  
E. Finnsson ◽  
S.Æ. Jónsson ◽  
...  
Keyword(s):  
Machine Learning ◽  
Sleep Stage ◽  
Eeg Signals ◽  
Stage Classification ◽  
Sleep Stage Classification ◽  
End To End

scholarly journals Classification of Brainwaves for Sleep Stages by High-Dimensional FFT Features from EEG Signals

2020 ◽  
Vol 10 (5) ◽  
pp. 1797 ◽  
Author(s):  
Mera Kartika Delimayanti ◽  
Bedy Purnama ◽  
Ngoc Giang Nguyen ◽  
Mohammad Reza Faisal ◽  
Kunti Robiatul Mahmudah ◽  
...  
Keyword(s):  
Machine Learning ◽  
Sleep Stage ◽  
Machine Learning Algorithms ◽  
High Dimensional ◽  
Sleep Stages ◽  
Eeg Signals ◽  
Stage Classification ◽  
Sleep Stage Classification ◽  
Low Dimensional

Manual classification of sleep stage is a time-consuming but necessary step in the diagnosis and treatment of sleep disorders, and its automation has been an area of active study. The previous works have shown that low dimensional fast Fourier transform (FFT) features and many machine learning algorithms have been applied. In this paper, we demonstrate utilization of features extracted from EEG signals via FFT to improve the performance of automated sleep stage classification through machine learning methods. Unlike previous works using FFT, we incorporated thousands of FFT features in order to classify the sleep stages into 2–6 classes. Using the expanded version of Sleep-EDF dataset with 61 recordings, our method outperformed other state-of-the art methods. This result indicates that high dimensional FFT features in combination with a simple feature selection is effective for the improvement of automated sleep stage classification.

A new approach to eliminating EOG artifacts from the sleep EEG signals for the automatic sleep stage classification

2016 ◽  
Vol 28 (10) ◽  
pp. 3095-3112 ◽  
Author(s):  
Mehmet Dursun ◽  
Seral Özşen ◽  
Cüneyt Yücelbaş ◽  
Şule Yücelbaş ◽  
Gülay Tezel ◽  
...  
Keyword(s):  
Sleep Stage ◽  
Sleep Eeg ◽  
Eeg Signals ◽  
New Approach ◽  
Stage Classification ◽  
Sleep Stage Classification

scholarly journals An end-to-end framework for real-time automatic sleep stage classification

SLEEP ◽  
2018 ◽  
Vol 41 (5) ◽  
Author(s):  
Amiya Patanaik ◽  
Ju Lynn Ong ◽  
Joshua J Gooley ◽  
Sonia Ancoli-Israel ◽  
Michael W L Chee
Keyword(s):  
Real Time ◽  
Sleep Stage ◽  
Stage Classification ◽  
Sleep Stage Classification ◽  
End To End

Sleep stage classification using fuzzy sets and machine learning techniques

2004 ◽  
Vol 58-60 ◽  
pp. 1137-1143 ◽  
Author(s):  
Pedro Piñero ◽  
Pavel Garcia ◽  
Leticia Arco ◽  
Alfredo Álvarez ◽  
M.Matilde Garcı́a ◽  
...  
Keyword(s):  
Machine Learning ◽  
Fuzzy Sets ◽  
Sleep Stage ◽  
Machine Learning Techniques ◽  
Learning Techniques ◽  
Stage Classification ◽  
Sleep Stage Classification

scholarly journals Validation of sleep stage classification using non-contact radar technology and machine learning (Somnofy®)

2020 ◽  
Vol 75 ◽  
pp. 54-61 ◽  
Author(s):  
Ståle Toften ◽  
Ståle Pallesen ◽  
Maria Hrozanova ◽  
Frode Moen ◽  
Janne Grønli
Keyword(s):  
Machine Learning ◽  
Sleep Stage ◽  
Stage Classification ◽  
Sleep Stage Classification
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