Title :
Losless EEG signal compression
Author :
Gumusalan, A. ; Arnavut, Ziya ; Kocak, Huseyin
Author_Institution :
SUNY Fredonia, Fredonia, NY, USA
fDate :
Aug. 28 2012-Sept. 1 2012
Abstract :
In this work, we study the lossless compression of EEG (electroencephalograph) signals using linear prediction and arithmetic coder. We show that, when we separate the less significant bits of each signal, linear prediction techniques yield better prediction, and with a structured arithmetic coder not only our technique achieves better compression rates than other techniques reported previously, but also our technique is much faster than the others.
Keywords :
data compression; electroencephalography; medical signal processing; arithmetic coder; linear prediction techniques; lossless EEG signal compression; lossless electroencephalograph signal compression; Brain models; Electroencephalography; Encoding; Histograms; Image coding; Standards; Electroencephalography; Mathematics; Signal Processing, Computer-Assisted;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-4119-8
Electronic_ISBN :
1557-170X
DOI :
10.1109/EMBC.2012.6347331