Title :
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
fDate :
6/23/1905 12:00:00 AM
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;
Conference_Titel :
Statistical Signal Processing, 2001. Proceedings of the 11th IEEE Signal Processing Workshop on
Print_ISBN :
0-7803-7011-2
DOI :
10.1109/SSP.2001.955272
