NDLI: Optimizing dynamical similarity index extraction window for seizure detection

Content Provider	IEEE Xplore Digital Library
Author	Azinfar, L. Rabbi, A. Ravanfar, M. Noghanian, S. Fazel-Rezai, R.
Copyright Year	2014
Description	Author affiliation: Electr. Eng. Dept., Univ. of North Dakota, Grand Forks, ND, USA (Fazel-Rezai, R.) \|\| Biomed. Signal & Image Process. Lab., Grand Forks, ND, USA (Azinfar, L.; Ravanfar, M.) \|\| Hawaii Center for Adv. Commun., Univ. of Hawaii, Honolulu, HI, USA (Rabbi, A.) \|\| Dept. of Electr. Eng., Univ. of North Dakota, Grand Forks, ND, USA (Noghanian, S.)
Abstract	This paper addresses an optimization problem in choosing optimum window length for feature extraction in automatic seizure detection. The processing window length plays an important role in reducing the false positive and false negative rates and decreasing required processing time for seizure detection. This study presents an approach for selecting the optimum window length toward the extraction of dynamical similarity index (DSI) feature. Then, the optimal window value in DSI extraction was used to detect seizure onset automatically. The algorithm was applied to electroencephalogram (EEG) signals from European Epilepsy Database. Although the main purpose of this study was not the seizure detection and mainly focuses on proposing an approach for finding an optimum window length for feature extraction towards the early seizure detection, the results showed that the proposed method achieves 83.99% of sensitivity in seizure detection. The low false positive rate per hour (FPR/h) was also significant due to continuous EEG analysis. The method showed fast computation speed which promises a potential for the real time applications. The proposed method for the window optimization in feature extraction of DSI can be implemented for other features to further improve the performance of seizure detection.
Sponsorship	IEEE Eng. Med. Biol. Soc.
Starting Page	2225
Ending Page	2228
File Size	822193
Page Count	4
File Format	PDF
ISBN	9781424479290
ISSN	1557170X
DOI	10.1109/EMBC.2014.6944061
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Feature extraction Electroencephalography Indexes Optimization Epilepsy Sensitivity
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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