Entropy of brain rhythms: normal versus injury EEG

Author

Thakor, N.V. ; Paul, J. ; Tong, S. ; Zhu, Y. ; Bezerianos, A.

Author_Institution

Dept. of Biomed. Eng., Johns Hopkins Univ. Sch. of Med., Baltimore, MD, USA

fYear

2001

fDate

6/23/1905 12:00:00 AM

Firstpage

261

Lastpage

264

Abstract

In communication theory, information measures answer two fundamental questions, viz: the ultimate data compression (by entropy) and the ultimate transmission rate (by the channel capacity). In case of brain and the study of brain function analyzing EEG, the information measures help to show how entropy can be used to remove redundancy in EEG and consequently making it useful for monitoring of brain function in critical conditions and secondly on how information transmission measures describe normal e.g. sleep stages and divergence from normal e.g epilepsy or ischemic brain injury

Keywords

diseases; electroencephalography; entropy; medical signal processing; patient monitoring; sleep; EEG redundancy removal; brain function monitoring; brain rhythms entropy; channel capacity; communication theory; electrodiagnostics; epilepsy; information measures; injury EEG; ischemic brain injury; normal EEG; sleep stages; ultimate data compression; ultimate transmission rate; Channel capacity; Condition monitoring; Data compression; Electroencephalography; Entropy; Epilepsy; Information analysis; Injuries; Rhythm; Sleep;

fLanguage

English

Publisher

ieee

Conference_Titel

Statistical Signal Processing, 2001. Proceedings of the 11th IEEE Signal Processing Workshop on

Print_ISBN

0-7803-7011-2

Type

conf

DOI

10.1109/SSP.2001.955272

Filename

955272