@inproceedings{de19d47e0c714dd89168d661fbb06220,
title = "Analysis of Post_Movement Event-Related Synchronization (ERS) in Leudoaraiosis Patients Tsing Multivariate Empirical Mode Decomposition",
abstract = "This study utilized movement-related sensorimotor Mu rhythm to probe EEG abnormalities in leukoaraiosis patients when they were performing self-paced finger movement task. The differences in EEG Mu rhythms between patients and normal subjects were studied and compared. Leukoaraiosis is a descriptive term used to describe neuroimaging findings of diffuse hemispheric white matter abnormalities, mainly characterized by loss of myelin and/or ischemic injury. The leukoaraiosis has been suggested a major risk factor and prognostic factor for stroke. Since EEG signals are weak (μv) and stochastic, the use of traditional digital filter may be unable to well extract the stochastic sensorimotor rhythms which could result in the pitfall of underestimating subject{\textquoteright}s responses. Accordingly, a novel tool, multivariate empirical mode decomposition (MEMD), was adopted in this study to exact the sensorimotor Mu rhythm in human brain. Our results found the beta event-related synchronization (ERS) of EEG Mu rhythm in Leukoaraiosis patients are significantly lower than those in normal controls using conventional event-related synchronization (conventional beta ERS) (0.44±0.2 uv v.s. 0.84±0.42) (student{\textquoteright}s t-test, p<0.01). Further analyzing the single-trial beta ERS using MEMD approach, the single-trial beta ERS in Leukoaraiosis patients and normal controls were 2.02±1.68 uv and 1.68±0.73 uv (student{\textquoteright}s t-test, p<0.05). It can be observed that the standard variation of single-trial beta ERS in Leukoaraiosis patients is larger than that that in normal controls (1.68 uv. v.s. 0.73 uv). The large signal variation in beta ERS could result in the suppression of conventional ERS values in Leukoaraiosis patients.",
keywords = "Electroencephalograph (EEG), Event-related synchronization (ERS), Multivariate empirical mode decomposition (MEMD)",
author = "Hsu, {H. T.} and Chang, {H. C.} and Lin, {F. J.} and Lee, {P. L.}",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 1st Global Conference on Biomedical Engineering, GCBME 2014 and 9th Asian-Pacific Conference on Medical and Biological Engineering, APCMBE 2014 ; Conference date: 09-10-2014 Through 12-10-2014",
year = "2015",
doi = "10.1007/978-3-319-12262-5_50",
language = "???core.languages.en_GB???",
series = "IFMBE Proceedings",
publisher = "Springer Verlag",
pages = "180--183",
editor = "Fong-Chin Su and Ming-Long Yeh and Shyh-Hau Wang",
booktitle = "1st Global Conference on Biomedical Engineering and 9th Asian-Pacific Conference on Medical and Biological Engineering",
}