NDLI: Epileptic seizure detection on patients with mental retardation based on EEG features: A pilot study

Content Provider	IEEE Xplore Digital Library
Author	Lei Wang Cluitmans, P.J.M. Arends, J.B.A.M. Yan Wu Sazonov, A.V.
Copyright Year	2015
Description	Author affiliation: Dept. of Electr. Eng., Eindhoven Univ. of Technol., Eindhoven, Netherlands (Lei Wang; Cluitmans, P.J.M.; Arends, J.B.A.M.; Yan Wu; Sazonov, A.V.)
Abstract	Mental retardation (MR) is one of the most common secondary disabilities in people with Epilepsy. However, to our knowledge there are no reliable seizure detection methods specified for MR-patients. In this paper we performed a pilot study on a group of six patients with mental retardation to assess what EEG features potentially work well on this group. A group of EEG features on the time, frequency and spatio-temporal domain were extracted, the modified wrapper approach was then employed as an improved feature subset selection method. Results show high variance on obtained features subset across this group, meanwhile there exist some common features which characterize the high-frequency components of epileptic EEG signals.
Starting Page	578
Ending Page	581
File Size	706954
Page Count	4
File Format	PDF
ISSN	1557170X
e-ISBN	9781424492718
DOI	10.1109/EMBC.2015.7318428
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-25
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electroencephalography Epilepsy Feature extraction Discrete wavelet transforms Complexity theory Databases
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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