Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Sleep syndromes onset detection based on automatic sleep staging
  algorithm   In this paper, we propose a novel method and a practical approach to
predicting early onsets of sleep syndromes, including restless leg syndrome,
insomnia, based on an algorithm that is comprised of two modules. A Fast
Fourier Transform is applied to 30 seconds long epochs of EEG recordings to
provide localized time-frequency information, and a deep convolutional LSTM
neural network is trained for sleep stage classification. Automating sleep
stages detection from EEG data offers great potential to tackling sleep
irregularities on a daily basis. Thereby, a novel approach for sleep stage
classification is proposed which combines the best of signal processing and
statistics. In this study, we used the PhysioNet Sleep European Data Format
(EDF) Database. The code evaluation showed impressive results, reaching an
accuracy of 86.43, precision of 77.76, recall of 93,32, F1-score of 89.12 with
the final mean false error loss of 0.09.

4
The categories of this paper are: cond-mat
5
The categories of this paper are: gr-qc
9
The categories of this paper are: nlin
18
The categories of this paper are: econ
30
The categories of this paper are: q-alg
20
The categories of this paper are: acc-phys
23
The categories of this paper are: solv-int
26
The categories of this paper are: bayes-an
7
The categories of this paper are: hep-th
28
The categories of this paper are: alg-geom
17
The categories of this paper are: q-fin
8
The categories of this paper are: hep-ex
6
The categories of this paper are: astro-ph
14
The categories of this paper are: math-ph
24
The categories of this paper are: dg-ga
12
The categories of this paper are: nucl-th