Pre-processing of multi-channel EEG for improved compression performance using SPIHT.
A novel technique for Electroencephalogram (EEG) compression is proposed in this article. This technique makes use of the inter-channel redundancy present between different EEG channels of the same recording and the intra-channel redundancy between the different samples of a specific channel. It uses Discrete Wavelet Transform (DWT) and Set partitioning in hierarchical trees (SPIHT) in 2-D to code the EEG channels. Smoothness transforms are added in order to guarantee good performance of SPIHT in 2-D. Experimental results show that this technique is able to provide low distortion values for high compression ratios (CRs). In addition, performance results of this method do not vary a lot between different patients which proves the stability of the method when used with recordings of different characteristics.
Department of Electrical and Computer Engineering, McGill University, Montreal, QC, Canada. hoda.daou@mail.mcgill.ca
Hoda
H
Daou
Fabrice
F
Labeau
D000465:Algorithms; D044962:Data Compression / Q000379:methods*; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D012815:Signal Processing, Computer-Assisted; D058067:Wavelet Analysis