Lossless compression of electroencephalographic (EEG) data

Author

Magotra, Neeraj ; Mandyam, Giridhar ; Sun, Mingui ; McCoy, Wes

Author_Institution

Dept. of Electr. & Comput. Eng., New Mexico Univ., Albuquerque, NM, USA

Volume

2

fYear

1996

fDate

12-15 May 1996

Firstpage

313

Abstract

The lossless compression of electroencephalographic (EEG) data is of great interest to the biomedical research community. In this paper, a two-stage technique of lossless compression involving decorrelating the sample points of the EEG signal and then entropy coding the resulting signal is examined. Two alternatives are presented for performing the first task. Specifically, the first stage consists either of a fixed coefficient filter or a recursive least squares lattice filter. The second stage employs arithmetic coding to perform the task of entropy coding the data. In the decompression stage, exact inverse filters are applied to achieve lossless compression. Simulations demonstrate the feasibility of this method for lossless EEG data compression

Keywords

arithmetic codes; data compression; electroencephalography; entropy codes; filtering theory; lattice filters; medical signal processing; recursive filters; EEG data compression; arithmetic coding; decompression stage; electroencephalographic data; entropy coding; exact inverse filters; fixed coefficient filter; lossless compression; recursive least squares lattice filter; sample points decorrelation; two-stage technique; Decorrelation; Digital signal processing; Electrodes; Electroencephalography; Entropy coding; Filters; Image coding; Image storage; Scalp; Sun;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1996. ISCAS '96., Connecting the World., 1996 IEEE International Symposium on

Conference_Location

Atlanta, GA

Print_ISBN

0-7803-3073-0

Type

conf

DOI

10.1109/ISCAS.1996.541709

Filename

541709