Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Affective EEG-Based Person Identification Using the Deep Learning
  Approach   Electroencephalography (EEG) is another mode for performing Person
Identification (PI). Due to the nature of the EEG signals, EEG-based PI is
typically done while the person is performing some kind of mental task, such as
motor control. However, few works have considered EEG-based PI while the person
is in different mental states (affective EEG). The aim of this paper is to
improve the performance of affective EEG-based PI using a deep learning
approach. \textcolor{red}{We proposed a cascade of deep learning using a
combination of Convolutional Neural Networks (CNNs) and Recurrent Neural
Networks (RNNs)}. CNNs are used to handle the spatial information from the EEG
while RNNs extract the temporal information. \textcolor{red}{We evaluated two
types of RNNs, namely, Long Short-Term Memory (CNN-LSTM) and Gated Recurrent
Unit (CNN-GRU). } The proposed method is evaluated on the state-of-the-art
affective dataset DEAP. The results indicate that CNN-GRU and CNN-LSTM can
perform PI from different affective states and reach up to 99.90--100\% mean
Correct Recognition Rate (CRR), significantly outperforming a support vector
machine (SVM) baseline system that uses power spectral density (PSD) features.
Notably, the 100\% mean \emph{CRR} comes from only 40 subjects in DEAP dataset.
To reduce the number of EEG electrodes from thirty-two to five for more
practical applications, the frontal region gives the best results reaching up
to 99.17\% CRR (from CNN-GRU). Amongst the two deep learning models, we find
CNN-GRU to slightly outperform CNN-LSTM, while having faster training time.
\textcolor{red}{Furthermore, CNN-GRU overcomes the influence of affective
states in EEG-Based PI reported in the previous works.

10
The categories of this paper are: q-bio
7
The categories of this paper are: hep-th
2
The categories of this paper are: math
25
The categories of this paper are: patt-sol
37
The categories of this paper are: supr-con
12
The categories of this paper are: nucl-th
14
The categories of this paper are: math-ph
26
The categories of this paper are: bayes-an
29
The categories of this paper are: funct-an
3
The categories of this paper are: physics
11
The categories of this paper are: hep-lat
6
The categories of this paper are: astro-ph
8
The categories of this paper are: hep-ex
33
The categories of this paper are: plasm-ph
16
The categories of this paper are: stat
0
The categories of this paper are: hep-ph