Citation

BibTex format

@article{Ahmed:2016:10.3390/e19010002,
author = {Ahmed, MU and Chanwimalueang, T and Thayyil, S and Mandic, DP},
doi = {10.3390/e19010002},
journal = {Entropy},
title = {A multivariate multiscale fuzzy entropy algorithm with application to uterine EMG complexity analysis},
url = {http://dx.doi.org/10.3390/e19010002},
volume = {19},
year = {2016}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - The recently introduced multivariate multiscale entropy (MMSE) has been successfully used to quantify structural complexity in terms of nonlinear within- and cross-channel correlations as well as to reveal complex dynamical couplings and various degrees of synchronization over multiple scales in real-world multichannel data. However, the applicability of MMSE is limited by the coarse-graining process which defines scales, as it successively reduces the data length for each scale and thus yields inaccurate and undefined entropy estimates at higher scales and for short length data. To that cause, we propose the multivariate multiscale fuzzy entropy (MMFE) algorithm and demonstrate its superiority over the MMSE on both synthetic as well as real-world uterine electromyography (EMG) short duration signals. Based on MMFE features, an improvement in the classification accuracy of term-preterm deliveries was achieved, with a maximum area under the curve (AUC) value of 0.99.
AU - Ahmed,MU
AU - Chanwimalueang,T
AU - Thayyil,S
AU - Mandic,DP
DO - 10.3390/e19010002
PY - 2016///
SN - 1099-4300
TI - A multivariate multiscale fuzzy entropy algorithm with application to uterine EMG complexity analysis
T2 - Entropy
UR - http://dx.doi.org/10.3390/e19010002
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000392978500002&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR - http://hdl.handle.net/10044/1/45030
VL - 19
ER -