EEG Subband Analysis using Approximate Entropy for the Detection of Epilepsy

Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2014, Vol 16, Issue 5

Abstract

 Abstract: Epilepsy is a neurological disorder which affects the nervous system. Epileptic seizures are due tosudden hyperactivity in certain parts of the brain. Electroencephalogram (EEG) is the commonly used modality for the detection of epilepsy. Automatic seizure detection helps in diagnosis and monitoring of epilepsy especially during long term recordings of EEG. This paper presents non linear analysis of EEG for the detection of epilepsy using approximate entropy (ApEn). The proposed method involves ApEn measured from EEG subbands applied as features to an artificial neural network (ANN) classifier. The ApEn measured from delta, theta, alpha, beta and gamma subbands of normal EEG, ictal and inter ictal EEGs are used as features. In the present work detection of epilepsy is considered as a two class problem. In the first case the classification is done between normal and ictal EEGs and in the second case, classification is done between normal and interictal EEGs. For both cases artificial neural networks with back propagation training are used as classifiers. The classification accuracy of 100% is obtained for normal and ictal groups and that of 98.9% is obtained for normal and inters ictal EEGs.

Authors and Affiliations

G. R. Kiranmayi , V. Udayashankara

Keywords

Related Articles

 Efficient Fpe Algorithm For Encrypting Credit Card Numbers

 The more highly used Internet world contains many sensitive information. Encryption is a process to secure information. An encrypted data requires more storage space for storing. It also needs many changes in q...

Outage Probability Performance Analysis of a New Hybrid Relay Selection Protocol

In this paper, the diversity gains of wireless relay networks were exploited. The proposed cooperative scheme using the first best relay for providing the highest SNR at the destination, whereas the second best relay is...

A Survey Report on: Become Prudent with Big Data - Technological sophistication in India

In the world of globalization at 360 degree, a heavy digitalized rainy season has raised & the rain drops of digital data is falling from the digitalized sky through lots of clouds of E-Commerce, Mobile-Commerce , So...

 Advanced Redundancy Management Of Heterogeneous Using The Packet Dropper With Nodes For Multipath routing

 Abstract: Developing a secured environment for detectingmalicious nodes in a heterogeneous wireless sensor network(HWSN).Here which is analysing the best redundancylevel using path redundancy and sourceredundancy.P...

Towards Automated Generation of ER-Diagram using a Web Based Approach

Abstract : Diagrams plays an important role in the software development process. Drawing the diagrams manually is the time consuming task, so there are many tools to draw and modify the diagram. From all the diagrams ER...

Download PDF file
  • EP ID EP142355
  • DOI -
  • Views 104
  • Downloads 0

How To Cite

G. R. Kiranmayi, V. Udayashankara (2014).  EEG Subband Analysis using Approximate Entropy for the Detection of Epilepsy. IOSR Journals (IOSR Journal of Computer Engineering), 16(5), 21-27. https://europub.co.uk/articles/-A-142355