Azra Yaghoobi Karimoi

Work place: Department of Electronic Engineering, Sadjad University of Technology, Mashhad, Iran



Research Interests: Computational Science and Engineering, Computational Learning Theory, Image Compression, Image Manipulation, Image Processing, Data Structures and Algorithms, Analysis of Algorithms


Azra Yaghoobi Karimoi She received the B.S. degree in electronics engineering from the International University of Imam Reza, Mashhad, Iran, in 2013. Currently, she is a M.S. student at Sadjad University, Mashhad, Iran.

Her research interests include evolutionary algorithms, machine learning and image processing.

Author Articles
The Effects of Beta-I and Fractal Dimension Neurofeedback on Reaction Time

By Reza Yaghoobi Karimoi Azra Yaghoobi Karimoi

DOI:, Pub. Date: 8 Oct. 2014

In this paper, we evaluate the effects of neurofeedback training protocols of the relative power of the beta-I band and the fractal dimension on the reaction time of human by the Test of Variables of Attention (TOVA) to show which of these two protocols have the great ability for the improving of the reaction time. The findings of this research show that both protocols have a good ability (p < 0.01) to improving of the reaction time and can create the significant difference (as mean dRT = 37.3 ms for the beta-I protocol and dRT = 19.6 ms for the fractal protocol) in the reaction time. Of course, we must express, the Beta-I protocol has the more ability to improving of the reaction time and it is able to provide a faster reaction time.

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Classification of EEG signals using Hyperbolic Tangent - Tangent Plot

By Reza Yaghoobi Karimoi Azra Yaghoobi Karimoi

DOI:, Pub. Date: 8 Jul. 2014

In this paper, a novel signal processing method is suggested for classifying epileptic seizures. To this end, first the Tangent and Hyperbolic Tangent of signals are calculated and then are classified into two classes: normal (or interictal) and ictal, using a proposed classifier. The results of this method show that the classification accuracy of normal and ictal classes (97.41%) has been higher than interictal and ictal classes (92.83%) and generally, it has a good potential to become a useful tool for physicians.

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Other Articles