Ahmed Abou elfetouh

Work place: Information Systems Department, Faculty of Computers and Information, Mansoura University, Mansoura, Egypt

E-mail: elfetouh@gmail.com


Research Interests: Computer Science & Information Technology, Computer Architecture and Organization, Information Systems, Data Structures and Algorithms, Information Theory, Algorithmic Information Theory


Ahmed Abou elfetouh was born in Mansoura, Egypt. He received the B.S., M.S., Ph.D degrees in information systems from Mansoura University, Egypt in 1984, 1995 and 1999 respectively. Currently he is the vice-dean of the Computers and Information faculty, Mansoura University, Egypt.

Author Articles
A Biometric System Based on Single-channel EEG Recording in One-second

By Shaimaa Hagras Reham R. Mostafa Ahmed Abou elfetouh

DOI: https://doi.org/10.5815/ijisa.2020.05.03, Pub. Date: 8 Oct. 2020

In recent years, there are great research interests in using the Electroencephalogram (EEG) signals in biometrics applications. The strength of EEG signals as a biometric comes from its major fraud prevention capability. However, EEG signals are so sensitive, and many factors affect its usage as a biometric; two of these factors are the number of channels, and the required time for acquiring the signal; these factors affect the convenience and practicality. This study proposes a novel approach for EEG-based biometrics that optimizes the channels of acquiring data to only one channel. And the time to only one second. The results are compared against five commonly used classifiers named: KNN, Random Forest (RF), Support Vector Machine (SVM), Decision Tables (DT), and Naïve Bayes (NB). We test the approach on the public Texas data repository. The results prove the constancy of the approach for the eight minutes. The best result of the eyes-closed scenario is Average True Positive Rate (TPR) 99.1% and 98.2% for the eyes-opened. And it reaches 100% for multiple subjects.

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