%0 Journal Article
	%A Young-Seok Choi
	%D 2016
	%J International Journal of Electrical and Computer Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 109, 2016
	%T Assessment of Multiscale Information for Short Physiological Time Series
	%U https://publications.waset.org/pdf/10003837
	%V 109
	%X This paper presents a multiscale information measure of
Electroencephalogram (EEG) for analysis with a short data length.
A multiscale extension of permutation entropy (MPE) is capable of
fully reflecting the dynamical characteristics of EEG across different
temporal scales. However, MPE yields an imprecise estimation due
to coarse-grained procedure at large scales. We present an improved
MPE measure to estimate entropy more accurately with a short
time series. By computing entropies of all coarse-grained time series
and averaging those at each scale, it leads to the modified MPE
(MMPE) which provides an enhanced accuracy as compared to
MPE. Simulation and experimental studies confirmed that MMPE
has proved its capability over MPE in terms of accuracy.
	%P 117 - 120