Advancements in Computer Aided Methods for EEG-based Epileptic Detection

Malik Anas Ahmad, Waqas Majeed, Nadeem Ahmad Khan

2014

Abstract

During the diagnosis of epilepsy, computer aided methods can significantly supplement a neurologist by automatically identifying the epileptic patterns in an EEG. In the last decade immense amount of work has been done in the field of EEG based computer aided diagnosis of epilepsy. Even after so much work these tools are not getting used up to their full potential. In this paper we have very briefly discussed some of the previously used signal processing and machine learning techniques which are proposed for epileptic pattern detection. We have concluded this paper by suggesting some additions in the previous method which can make these systems more helpful, detailed and precise for the neurologist.

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Paper Citation


in Harvard Style

Anas Ahmad M., Majeed W. and Ahmad Khan N. (2014). Advancements in Computer Aided Methods for EEG-based Epileptic Detection . In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2014) ISBN 978-989-758-011-6, pages 289-294. DOI: 10.5220/0004912802890294


in Bibtex Style

@conference{biosignals14,
author={Malik Anas Ahmad and Waqas Majeed and Nadeem Ahmad Khan},
title={Advancements in Computer Aided Methods for EEG-based Epileptic Detection},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2014)},
year={2014},
pages={289-294},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004912802890294},
isbn={978-989-758-011-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2014)
TI - Advancements in Computer Aided Methods for EEG-based Epileptic Detection
SN - 978-989-758-011-6
AU - Anas Ahmad M.
AU - Majeed W.
AU - Ahmad Khan N.
PY - 2014
SP - 289
EP - 294
DO - 10.5220/0004912802890294