Utilizing Embedded and Machine Learning Techniques to Classify EEG Eye States

Razieh Asgarnezhad; Hind Abdulrazzaq Mohammed Ali; Karrar Ali Mohsin Alhameedawi

Autori

Razieh Asgarnezhad Department of Computer Engineering, Aghigh Institute of Higher Education Shahinshahr, Isfahan, Iran
Hind Abdulrazzaq Mohammed Ali Civil Engineering Department, University of Technology-Iraq, Baghdad, Iraq
Karrar Ali Mohsin Alhameedawi Department of Computer Engineering, Çukurova University, Adana, Türkiye

Cuvinte cheie:

Pre-processing, EEG eye state dataset, Ensemble method, Machine learning technique, Data mining, EEG

Rezumat

Numerous studies focus on epilepsy diseases in order to achieve the detection of eye states and classification systems because of the significance of automatically identifying brain illnesses. Eye condition recognition is essential for biomedical informatics applications like driving detection and smart home device control. Electroencephalogram signals are this problem. In this context, conventional methods and manually derived features are applied in several instances. The extraction of useful features and the choice of appropriate classifiers are difficult problems. This work suggests an ensemble system called "EEG Eye" that employs a new preprocessing stage. In this context, the base classifiers and the most significant classical works are compared to the ensemble approaches in the classification step. A publicly accessible EEG eye state dataset from UCI is used for assessment. At 100%, 100%, 100%, 100%, the maximum accuracy, precision, recall, and F1 are attained.

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Biografii autori

Razieh Asgarnezhad, Department of Computer Engineering, Aghigh Institute of Higher Education Shahinshahr, Isfahan, Iran

Razieh Asgarnezhad received her B.Sc. and MSc. degrees in Computer Engineering from Kashan Azad University in 2009 and Arak Azad University in 2012, respectively. She received Ph.D. degree from Isfahan Azad University in 2020. Currently, she is Assistant Professor in Aghigh Institute of Higher Education in Shahinshahr. Her current researches include Data Mining, Text Mining, Learning Automata, Recommendation System, Sentiment Analysis, and Wireless Sensor Network.
Hind Abdulrazzaq Mohammed Ali, Civil Engineering Department, University of Technology-Iraq, Baghdad, Iraq

Hind Abdulrazzaq Mohammed Ali was born in Baghdad. She got PhD in evolutionary algorithm from University of Bourgogn France Comte, Montbéliard, France in 2018. She obtained M.Sc in Artificial Intelligence from Iraqi Commission for Computers and Informatics, Institute for Post Graduate Studies in Informatics, Baghdad, Iraq, in 2001. Dr. Ali got B.Sc in Computer Science from University of Technology, Baghdad, Iraq. She is experienced in Java Script, Visual Basic.Net. She is serving as a Lecturer in Civil Engineering Department, University of Technology, Baghdad, Iraq. Her Research fields are Evolutionary Algorithm, Rich Problems, Smart Cities, Sensors, IOT, Classifier Learning Systems, Optimization Systems.
Karrar Ali Mohsin Alhameedawi, Department of Computer Engineering, Çukurova University, Adana, Türkiye

Karrar Ali Mohsin Alhameedawi received his BS.c degrees in Computer Engineering in 2018 and M.Sc degree in computer engineering (software) in 2022. And now Ph.D student in Computer Engineering at Çukurova University in Türkiye He received a certified international development trainer specializing in human development from Germany in 2019. One year later, he received the certificate of best humanitarian personality in Iraq in 2020. He has experience as a website developer, programmer, the highest educational social networking site in Iraq, and director of Alpha Software Solutions Company. He is a member of seven international institutions and has received 500 certificates and a letter of thanks from European and local countries. His current research includes Data Mining, Text Mining, deep learning, web semantics, ROS, and reinforcement learning.