Efficient sequential compression of multichannel biomedical signals
Ignacio Capurro, Federico Lecumberry, Alvaro Martín Menoni, Ignacio Ramírez Paulino, Eugenio Rovira, Gadiel Seroussi
IEEE Journal of Biomedical and Health Informatics, Volume 21, Number 4, page 904--916- Jul. 2017
Research group(s):  Tratamiento de Imagenes (gti)
Department(s):  Procesamiento de Señales
Download the publication : CLMRRS17.pdf [994KB]  


This work proposes lossless and near-lossless compression algorithms for multi-channel biomedical signals. The algorithms are sequential and efficient, which makes them suitable for low-latency and low-power signal transmission applications. We make use of information theory and signal processing tools (such as universal coding, universal prediction, and fast online implementations of multivariate recursive least squares), combined with simple methods to exploit spatial as well as temporal redundancies typically present in biomedical signals. The algorithms are tested with publicly available electroencephalogram and electrocardiogram databases, surpassing in all cases the current state of the art in near-lossless and lossless compression ratios.

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» Ignacio Capurro
» Federico Lecumberry
» Alvaro Martín Menoni
» Ignacio Ramírez Paulino
» Eugenio Rovira
» Gadiel Seroussi