The lifted wavelet transform for encephalic signal compression

The compression of Electroencephalographic (EEG) signal is of great interest to many in the biomedical community. The motivation for this is the large amount of data involved in collecting EEG information which requires more memory for storage and high bandwidth for transmission. This work shows the...

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Bibliographic Details
Main Authors: Kedir-Talha, Malika-Djahida, Amer, Mohamed Amine Ait
Format: Conference Proceeding
Language:English
Subjects:
Brain models
Compression
Discrete wavelet transforms
EEG
Electroencephalography
Filtering algorithms
LWT
reconstitution
wavelet
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Summary:The compression of Electroencephalographic (EEG) signal is of great interest to many in the biomedical community. The motivation for this is the large amount of data involved in collecting EEG information which requires more memory for storage and high bandwidth for transmission. This work shows the contribution of biomedical signal processing by lifted wavelet transform LWT, in the field of encephalic signal compression. Our results show a high performance compression for normal and pathological EEG. A statistical study on a set of 200 signals healthy and epileptic, confirms these results. The choice of wavelet rbior 5.5 is best suited to the shape of the EEG signal, it allows to increasing the compression ratio and to ensuring a safe recovery. The increase, in the level decomposition and the threshold, allows to increasing the compression ratio while keeping a good performance of reconstitution. Our study allows us to choose the LWT rbio5.5 as tool for encephalic signal compression with a compression ratio of 83.16% and a recovery rate of 99.95%.
DOI:10.1109/TSP.2013.6613992