DocumentCode :
1804310
Title :
Performance analysis of a 2-D EEG compression algorithm using an automatic seizure detection system
Author :
Daou, Hoda ; Labeau, Fabrice
Author_Institution :
Dept. of Electr. & Comput. Eng., McGill Univ., Montreal, QC, Canada
fYear :
2012
fDate :
4-7 Nov. 2012
Firstpage :
1632
Lastpage :
1636
Abstract :
A recently developed compression algorithm that uses DWT, SPIHT and smoothness transforms to compress EEG channels in 2-D proved to give very low distortion values for high compression ratios. Although RD performance is a commonly used metric in signal compression, in medical signals, it is important to preserve important diagnostic information. In order to move towards such a diagnostics-oriented performance assessment, we propose in this paper a framework to evaluate the performance of EEG compression mechanisms in terms of post-compression seizure detection capability. In particular, we show that the above-mentioned 2-D algorithm can maintain diagnostic features down to bitrates of 2 bits per sample.
Keywords :
data compression; discrete wavelet transforms; electroencephalography; medical signal detection; trees (mathematics); 2D EEG compression algorithm; DWT; EEG channel compression; SPIHT; automatic seizure detection system; diagnostics-oriented performance assessment; discrete wavelet transform; high compression ratios; post-compression seizure detection capability; set partitioning hierarchical trees; signal compression; smoothness transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signals, Systems and Computers (ASILOMAR), 2012 Conference Record of the Forty Sixth Asilomar Conference on
Conference_Location :
Pacific Grove, CA
ISSN :
1058-6393
Print_ISBN :
978-1-4673-5050-1
Type :
conf
DOI :
10.1109/ACSSC.2012.6489308
Filename :
6489308
Link To Document :
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