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373545

EEG-based human recognition using Hjorth-parameters and LSTM technique

Article

Last updated: 28 Dec 2024

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Abstract

 There is increasing interest in assessing the feasibility of using Electroencephalography (EEG) signals in biometric purposes. Using deep learning techniques has achieved great performance in classification-based systems in general. However using them in EEG–based human recognition systems still limited, this was the main motivation which encouraged the authors to investigate using of these techniques in EEG-based human recognition system. In this paper, the authors suggested a framework that uses the three Hjorth parameters to enhance the Long-Short Term Memory (LSTM) performance for Electroencephalography (EEG)-based human recognition systems. The proposed framework also investigates the ability to optimize two critical factors of EEG-based biometrics, which are the number of channels and the time needed for acquiring data. The proposed approach has been tested on a public data set, which is the public Texas data repository to verify the improvement of recognition and its reliability through the data recording duration of the eight minutes. The study evaluates two optimizers, namely, Stochastic Gradient Descent optimizer and Conjugate Gradient Descent. The results show a significant improvement in the LSTM performance using the proposed framework, by applying the fusion of features with the Hjorth parameters and using Conjugate Gradient Descent optimizer (CGD).

DOI

10.21608/mjcis.2021.373545

Keywords

Pattern Recognition, security, Human Recognition

Authors

First Name

Shaimaa

Last Name

Hagras

MiddleName

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Affiliation

Department of Information System, Faculty of Computers and Information, Mansoura University, Egypt

Email

joshahd@mans.edu.eg

City

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Orcid

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First Name

Reham

Last Name

R. Mostafa

MiddleName

-

Affiliation

Department of Information System, Faculty of Computers and Information, Mansoura University, Egypt

Email

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City

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Orcid

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First Name

Ahmed

Last Name

Abou-elfetouh

MiddleName

-

Affiliation

Department of Information System, Faculty of Computers and Information, Mansoura University, Egypt

Email

-

City

-

Orcid

-

Volume

17

Article Issue

1

Related Issue

49786

Issue Date

2021-06-01

Receive Date

2024-08-13

Publish Date

2021-06-01

Page Start

13

Page End

23

Print ISSN

2090-1666

Online ISSN

2090-1674

Link

https://mjcis.journals.ekb.eg/article_373545.html

Detail API

https://mjcis.journals.ekb.eg/service?article_code=373545

Order

373,545

Type

Original Research Articles.

Type Code

1,784

Publication Type

Journal

Publication Title

Mansoura Journal for Computer and Information Sciences

Publication Link

https://mjcis.journals.ekb.eg/

MainTitle

EEG-based human recognition using Hjorth-parameters and LSTM technique

Details

Type

Article

Created At

28 Dec 2024