Título:
Efficient sequential compression of multichannel biomedical signals
Otros títulos:
Coordinador:
Director:
Compilador:
Autor:
Capurro, Ignacio
Lecumberry, Federico
Martín Menoni, Alvaro
Ramírez Paulino, Ignacio
Rovira, Eugenio
Seroussi, Gadiel
Lecumberry, Federico
Martín Menoni, Alvaro
Ramírez Paulino, Ignacio
Rovira, Eugenio
Seroussi, Gadiel
Tutor:
Tipo de documento:
Preprint
Editor:
Palabras clave:
Multi-channel signal compression
Electroencephalogram compression
Electrocardiogram compression
Lossless compression
Near-lossless compression
Low-complexity
Electroencephalogram compression
Electrocardiogram compression
Lossless compression
Near-lossless compression
Low-complexity
Descriptores:
Procesamiento de Señales
Año de publicación:
2017
Contenido:
Resumen:
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.
Descripción:
Los resultados preliminares de este trabajo se presentaron en la European Signal Processing Conference (EUSIPCO 2014), Lisboa, Portugal, 2014.
metadata.articulos.dc.description.uri:
Editorial:
EN:
Financiadores:
Citación:
Capurro, I, Lecumberry, F, Martín, Á, Ramírez, I, Rovira, E, Seroussi, G. "Efficient sequential compression of multichannel biomedical signals" [Preprint] Publicado en: IEEE Journal of Biomedical and Health Informatics, vol. 21, no. 4, 2017. doi: 10.1109/JBHI.2016.2582683.
Citación:
metadata.articulos.cc.license.name:
ISBN:
e-ISBN:
ISSN:
ISMN:
Otros identificadores:
Cobertura geográfica:
Cobertura temporal:
Departamento académico:
Procesamiento de Señales
Grupo de investigación:
Tratamiento de Imágenes
Licencia:
Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
Colecciones:
| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| CLMRRS17.pdf | — | 994.55 KB | Adobe PDF |