BibTex format
@inproceedings{Casson:2012,
author = {Casson, AJ and Rodriguez-Villegas, E},
pages = {4497--4500},
title = {Signal agnostic compressive sensing for body area networks: Comparison of signal reconstructions},
year = {2012}
}
RIS format (EndNote, RefMan)
TY - CPAPER
AB - Compressive sensing is a lossy compression technique that is potentially very suitable for use in power constrained sensor nodes and Body Area Networks as the compression process has a low computational complexity. This paper investigates the reconstruction performance of compressive sensing when applied to EEG, ECG, EOG and EMG signals; establishing the performance of a signal agnostic compressive sensing strategy that could be used in a Body Area Network monitoring all of these. The results demonstrate that the EEG, ECG and EOG can all be reconstructed satisfactorily, although large inter- and intra- subject variations are present. EMG signals are not well reconstructed. Compressive sensing may therefore also find use as a novel method for the identification of EMG artefacts in other electro-physiological signals.
AU - Casson,AJ
AU - Rodriguez-Villegas,E
EP - 4500
PY - 2012///
SP - 4497
TI - Signal agnostic compressive sensing for body area networks: Comparison of signal reconstructions
ER -