Zobrazeno 1 - 10
of 40
pro vyhledávání: '"Turky N. Alotaiby"'
Autor:
Fathi E. Abd El-Samie, Turky N. Alotaiby, Muhammad Imran Khalid, Saleh A. Alshebeili, Saeed A. Aldosari
Publikováno v:
IEEE Access, Vol 6, Pp 60673-60688 (2018)
Epilepsy is one of the most serious disorders that affect patients' daily lives. When seizures occur, patients cannot control their behaviors, which can lead to serious injuries. With the great advances in recording both electroencephalogram (EEG) an
Externí odkaz:
https://doaj.org/article/e0eaf47100ae42cc90573020556bf379
Autor:
Muhammad Imran Khalid, Turky N. Alotaiby, Saeed A. Aldosari, Saleh A. Alshebeili, Majed Hamad Alhameed, Vahe Poghosyan
Publikováno v:
IEEE Access, Vol 5, Pp 11658-11667 (2017)
Epilepsy is a brain disorder that may strike at different stages of life. Patients' lives are extremely disturbed by the occurrence of sudden unpredictable epileptic seizures. A possible approach to diagnose epileptic patients is to analyze magnetoen
Externí odkaz:
https://doaj.org/article/d356f4ab074a4750a6e4fd92bba03cc8
Autor:
Saly Abd-Elateif El-Gindy, Fatma E. Ibrahim, Mohamed Alabasy, Hesham M. Abdelzaher, Mahmoud El-Refy, Ashraf A. M. Khalaf, Sami M. El-Dolil, Adel S. El-Fishawy, Taha E. Taha, El-Sayed M. El-Rabaie, Moawad I. Dessouky, Ibrahim El-Dokany, Osama A. Oraby, Turky N. Alotaiby, Saleh A. Alshebeili, Fathi E. Abd El-Samie
Publikováno v:
Wireless Personal Communications. 125:1013-1046
Publikováno v:
2022 International Conference on Electrical and Computing Technologies and Applications (ICECTA).
Autor:
Fathi E. Abd El-Samie, Mohamed Elwekeil, Ghada M. El Banby, Walid El-Shafai, Taha E. Taha, Saleh A. Alshebeili, Heba M. Emara, Adel S. El-Fishawy, El-Sayed M. El-Rabaie, Turky N. Alotaiby
Publikováno v:
Annals of Data Science. 9:393-428
Seizure detection and prediction are a very hot topics in medical signal processing due to their importance in automatic medical diagnosis. This paper presents three efficient frameworks for applications related to electroencephalogram (EEG) signal p
Autor:
Adel S. El-Fishawy, Taha E. Taha, Turky N. Alotaiby, Saleh A. Alshebeili, Ashraf A. M. Khalaf, Saly Abd-Elateif El-Gindy, Sami M. El-Dolil, Walid El-Shafai, Asmaa Hamad, Fathi E. Abd El-Samie
Publikováno v:
Journal of Ambient Intelligence and Humanized Computing. 12:9193-9208
In this paper, we present an approach for the anticipation of electroencephalography (EEG) seizures using different families of wavelet transform. Different signal attributes are investigated to anticipate the seizure onset based on the wavelet trans
Autor:
Heba M. Emara, Mohamed Elwekeil, Adel S. El-Fishawy, Taha E. Taha, Saleh A. Alshebeili, El-Sayed M. El-Rabaie, Turky N. Alotaiby, Fathi E. Abd El-Samie
Publikováno v:
Wireless Personal Communications. 116:3371-3395
This paper is concerned with Electroencephalography (EEG) seizure prediction, which means the detection of the pre-ictal state prior to ictal activity occurrence. The basic idea of the proposed approach for EEG seizure prediction is to work on the si
Publikováno v:
2021 18th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON).
The ever increasing number of e-services provided to users necessitates the efficient and accurate verification of user identity. In this work, we present a user authentication model based on multimodal signals. More specifically, we investigate the
Publikováno v:
ICAIIC
The growing internet-based services such as banking and shopping have brought both ease to human’s lives and challenges in user identity authentication. Different methods have been investigated for user authentication such as retina, finger print,
Autor:
Mahmoud Elreefy, Walid El-Shafai, Adel S. El-Fishawy, Nagy W. Messiha, Waleed Al-Nuaimy, Osama Zahran, Zeinab M. Elsherbeny, Ahmed Sedik, Mohamed Elwakeil, Turky N. Alotaiby, Ashraf A. M. Khalaf, Fathi E. Abd El-Samie, Fatma Ibrahim, Asmaa Hamad, Heba A. El-Khobby, Ghada M. El Banby, Noha A. El-Hag, Mahmoud A. Attia, Heba M. Emara, Ali A. Khalil, Ibrahim M. Eldokany, Eman M. Shahin, Mohamed Rihan, Taha E. Taha, Moawad I. Dessouky, El-Sayed M. El-Rabaie, Saleh A. Alshebeili
Publikováno v:
International Journal of Speech Technology. 22:739-767
Anomaly detection is a very vital area in medical signal and image processing due to its importance in automatic diagnosis. This paper presents three efficient anomaly detection approaches for applications related to Electroencephalogram (EEG) signal