Variable sampling of large-array EEG and MEG

Author

Sun, Mingui ; Liu, Qiang ; Sclabassi, Robert J.

Author_Institution

Departments of Neurosurg., Bioeng., & Electr. Eng., Univ. of Pittsburgh, PA, USA

Volume

3

fYear

2002

fDate

23-26 Oct. 2002

Firstpage

2027

Abstract

Recent development in computer technology has allowed collection of large-array electroencephalograms (EEG) and magnetoencephalograms (MEG) consisting of hundreds of channels. As the amount of collected data increases, there is a clear demand to reduce the data size for efficient database management and network transmission. We investigated this problem and developed a simple method by eliminating data samples at smooth regions of the signal according to the signal´s local frequency content. This method has two major advantages over the existing methods, (1) it reduces data size significantly with a controllable distortion, and (2) the data can be displayed directly without decompression.

Keywords

data compression; electroencephalography; magnetoencephalography; medical signal processing; controllable distortion; data samples elimination; efficient database management; large-array EEG; local frequency content; network transmission; significant data size reduction; smooth signal regions; variable sampling; Biomedical engineering; Computer network management; Data compression; Databases; Electroencephalography; Frequency; Neurosurgery; Sampling methods; Size control; Sun;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology, 2002. 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society EMBS/BMES Conference, 2002. Proceedings of the Second Joint

ISSN

1094-687X

Print_ISBN

0-7803-7612-9

Type

conf

DOI

10.1109/IEMBS.2002.1053150

Filename

1053150