Comparative Analysis of Classifiers for Developing an Adaptive Computer-Assisted EEG Analysis System for Diagnosing Epilepsy
Joint Authors
Ahmad, Malik Anas
Ayaz, Yasar
Jamil, Mohsin
Omer Gillani, Syed
Rasheed, Muhammad Babar
Imran, Muhammad
Khan, Nadeem Ahmed
Majeed, Waqas
Javaid, N.
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-03-05
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Computer-assisted analysis of electroencephalogram (EEG) has a tremendous potential to assist clinicians during the diagnosis of epilepsy.
These systems are trained to classify the EEG based on the ground truth provided by the neurologists.
So, there should be a mechanism in these systems, using which a system’s incorrect markings can be mentioned and the system should improve its classification by learning from them.
We have developed a simple mechanism for neurologists to improve classification rate while encountering any false classification.
This system is based on taking discrete wavelet transform (DWT) of the signals epochs which are then reduced using principal component analysis, and then they are fed into a classifier.
After discussing our approach, we have shown the classification performance of three types of classifiers: support vector machine (SVM), quadratic discriminant analysis, and artificial neural network.
We found SVM to be the best working classifier.
Our work exhibits the importance and viability of a self-improving and user adapting computer-assisted EEG analysis system for diagnosing epilepsy which processes each channel exclusive to each other, along with the performance comparison of different machine learning techniques in the suggested system.
American Psychological Association (APA)
Ahmad, Malik Anas& Ayaz, Yasar& Jamil, Mohsin& Omer Gillani, Syed& Rasheed, Muhammad Babar& Imran, Muhammad…[et al.]. 2015. Comparative Analysis of Classifiers for Developing an Adaptive Computer-Assisted EEG Analysis System for Diagnosing Epilepsy. BioMed Research International،Vol. 2015, no. 2015, pp.1-14.
https://search.emarefa.net/detail/BIM-1056231
Modern Language Association (MLA)
Ahmad, Malik Anas…[et al.]. Comparative Analysis of Classifiers for Developing an Adaptive Computer-Assisted EEG Analysis System for Diagnosing Epilepsy. BioMed Research International No. 2015 (2015), pp.1-14.
https://search.emarefa.net/detail/BIM-1056231
American Medical Association (AMA)
Ahmad, Malik Anas& Ayaz, Yasar& Jamil, Mohsin& Omer Gillani, Syed& Rasheed, Muhammad Babar& Imran, Muhammad…[et al.]. Comparative Analysis of Classifiers for Developing an Adaptive Computer-Assisted EEG Analysis System for Diagnosing Epilepsy. BioMed Research International. 2015. Vol. 2015, no. 2015, pp.1-14.
https://search.emarefa.net/detail/BIM-1056231
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1056231