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Prediction of Epileptic Seizure by Analysing Time Series EEG Signal Using k-NN Classifier
Joint Authors
Rashid, M. A.
Hasan, Md. Kamrul
Ahamed, Md. Asif
Ahmad, Mohiuddin
Source
Applied Bionics and Biomechanics
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-08-13
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Electroencephalographic signal is a representative signal that contains information about brain activity, which is used for the detection of epilepsy since epileptic seizures are caused by a disturbance in the electrophysiological activity of the brain.
The prediction of epileptic seizure usually requires a detailed and experienced analysis of EEG.
In this paper, we have introduced a statistical analysis of EEG signal that is capable of recognizing epileptic seizure with a high degree of accuracy and helps to provide automatic detection of epileptic seizure for different ages of epilepsy.
To accomplish the target research, we extract various epileptic features namely approximate entropy (ApEn), standard deviation (SD), standard error (SE), modified mean absolute value (MMAV), roll-off (R), and zero crossing (ZC) from the epileptic signal.
The k-nearest neighbours (k-NN) algorithm is used for the classification of epilepsy then regression analysis is used for the prediction of the epilepsy level at different ages of the patients.
Using the statistical parameters and regression analysis, a prototype mathematical model is proposed which helps to find the epileptic randomness with respect to the age of different subjects.
The accuracy of this prototype equation depends on proper analysis of the dynamic information from the epileptic EEG.
American Psychological Association (APA)
Hasan, Md. Kamrul& Ahamed, Md. Asif& Ahmad, Mohiuddin& Rashid, M. A.. 2017. Prediction of Epileptic Seizure by Analysing Time Series EEG Signal Using k-NN Classifier. Applied Bionics and Biomechanics،Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1121098
Modern Language Association (MLA)
Hasan, Md. Kamrul…[et al.]. Prediction of Epileptic Seizure by Analysing Time Series EEG Signal Using k-NN Classifier. Applied Bionics and Biomechanics No. 2017 (2017), pp.1-12.
https://search.emarefa.net/detail/BIM-1121098
American Medical Association (AMA)
Hasan, Md. Kamrul& Ahamed, Md. Asif& Ahmad, Mohiuddin& Rashid, M. A.. Prediction of Epileptic Seizure by Analysing Time Series EEG Signal Using k-NN Classifier. Applied Bionics and Biomechanics. 2017. Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1121098
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1121098