A DCT based approach to epileptic seizure detection

Author

Bedeeuzzaman, M. ; Farooq, Omar ; Khan, Yusuf U.

Author_Institution

Dept. of Electron. Eng., Aligarh Muslim Univ., Aligarh, India

fYear

2011

fDate

17-19 Dec. 2011

Firstpage

316

Lastpage

319

Abstract

Electroencephalogram (EEG) is a widely used tool for the clinical investigation of epileptic seizures. A new scheme of epileptic seizure detection using statistical features and Discrete Cosine Transform (DCT) is presented in this paper. Median absolute deviation (MAD) and variance is taken as the discriminating features between three different classes of EEG under study. The DCT was used for feature reduction, whose ability to pack input data into as few coefficients as possible makes it a good choice for the purpose. The representative DCT coefficients were given as the input to a linear classifier to yield 100% accuracy.

Keywords

discrete cosine transforms; electroencephalography; medical signal detection; signal classification; statistical analysis; DCT based approach; EEG; MAD; clinical investigation; discrete cosine transform based approach; electroencephalogram; epileptic seizure detection; linear classifier; median absolute deviation; statistical features; Accuracy; Databases; Discrete cosine transforms; Electroencephalography; Feature extraction; Multimedia communication; Support vector machine classification; Electro encephalogram; discrete cosine transform; median absolute deviation; seizure;

fLanguage

English

Publisher

ieee

Conference_Titel

Multimedia, Signal Processing and Communication Technologies (IMPACT), 2011 International Conference on

Conference_Location

Aligarh

Print_ISBN

978-1-4577-1105-3

Type

conf

DOI

10.1109/MSPCT.2011.6150503

Filename

6150503