EPILEPTIC ELECTROENCEPHALOGRAM SIGNAL CLASSIFICATION BASED ON SPARSE REPRESENTATION

Jing Wang, Ping Guo

2011

Abstract

Epilepsy seizure detection in Electroencephalogram (EEG) is a major issue in the diagnosis of epilepsy and it can be considered as a classification problem. According to the particular property of EEG, a novel method based on sparse representation is proposed for epilepsy detection in this paper. Classification accuracy, robustness on noisy data and parameters (the size of dictionary and the number of features) of proposed method are tested and analysed on the public available data. The proposed method can obtain the highest classification accuracy among the discussed methods when the suitable parameters are set, and the proposed method based on sparse representations for classification is robust to noise. This is consistent with the theory that sparse representations can capture the inherent structure of signal. Furthermore, it is shown by experiments that the optimal selection of the parameters is critical to the performance of epilepsy detection.

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Paper Citation


in Harvard Style

Wang J. and Guo P. (2011). EPILEPTIC ELECTROENCEPHALOGRAM SIGNAL CLASSIFICATION BASED ON SPARSE REPRESENTATION . In Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2011) ISBN 978-989-8425-84-3, pages 15-23. DOI: 10.5220/0003667100150023


in Bibtex Style

@conference{ncta11,
author={Jing Wang and Ping Guo},
title={EPILEPTIC ELECTROENCEPHALOGRAM SIGNAL CLASSIFICATION BASED ON SPARSE REPRESENTATION},
booktitle={Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2011)},
year={2011},
pages={15-23},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003667100150023},
isbn={978-989-8425-84-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2011)
TI - EPILEPTIC ELECTROENCEPHALOGRAM SIGNAL CLASSIFICATION BASED ON SPARSE REPRESENTATION
SN - 978-989-8425-84-3
AU - Wang J.
AU - Guo P.
PY - 2011
SP - 15
EP - 23
DO - 10.5220/0003667100150023