Khalil AlSharabi
King Saud University
19 Papers
29 Citations
Khalil AlSharabi is an academic researcher from King Saud University. The author has contributed to research in topics: Computer science & Electroencephalography. The author has an hindex of 5, co-authored 13 publications. Previous affiliations of Khalil AlSharabi include University College of Engineering.
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Papers
EEG Signal Analysis for Diagnosing Neurological Disorders Using Discrete Wavelet Transform and Intelligent Techniques.
TL;DR: A single system is developed to diagnose one or two neurological diseases at the same time (two-class mode and three- class mode) to aid in the accurate diagnosis of neurological brain disorders: epilepsy and autism spectrum disorder (ASD).
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Detection of Parkinson’s disease from EEG signals using discrete wavelet transform, different entropy measures, and machine learning techniques
TL;DR: In this article , discrete wavelet transform (DWT)-based methods for detecting Parkinson's disease from health control (HC) in two cases, namely, off-and on-medication.
Parkinson’s Disease Detection from Resting-State EEG Signals Using Common Spatial Pattern, Entropy, and Machine Learning Techniques
TL;DR: The results show that the proposed methods, particularly the combination of common spatial patterns and log energy entropy, provide competitive results when compared to methods in the literature.
Common Spatial Pattern Technique With EEG Signals for Diagnosis of Autism and Epilepsy Disorders
Fahd A. Alturki,Majid Aljalal,Akram M. Abdurraqeeb,Khalil AlSharabi,Abdullrahman A. Al-Shamma'a +4 more
TL;DR: In this paper, the authors focused on the diagnosis of epilepsy and autism spectrum disorders (ASDs) through the analysis and processing of EEGs, where artifacts were removed from the EEG datasets using Independent Component Analysis and were filtered using a fifth-order band-pass Butterworth filter to remove interference and noise.