Abstract Previous studies have shown that about 90% of traffic accidents are due to human error, which means factors may affect a driver's braking behaviors and thus their driving safety, especially when the driver makes motion. However, most mounted sensors on brake pad, ignoring some extent an analysis behavior before pad is pressed (pre-braking). Therefore, determine effect different drivers...

An automatic sleep staging method is proposed to score wakefulness and three nonrapid eye movement (NREM) stages S1, S2 and S3, based on the Empirical Mode Decomposition (EMD) algorithm. Patients with sleep disorders were tested using this method. Good agreements between manual and automatic staging results were achieved in terms of their Cohen's Kappa value.

Wigner-Ville Distribution (WVD) possesses high time-frequency concentration and resolutions, but brings serious cross-terms in process of a multi-component signal to distort greatly the result of timefrequency analysis. Because of this the use of the WVD is limited for many applications. In this paper a combined method is proposed: Empirical Mode Decomposition (EMD) is first used to decompose t...

In this study, a new speckle reduction method was proposed in terms of by Bidimensional Empirical Mode Decomposition (BEMD). In this method, the SAR image containing speckle noise was decomposed into a number of elementary components by using BEMD and then the extremal points are done the boundary equivalent extension after screening and the residual continue to be done the boundary equivalent ...

The electroencephalogram (EEG) is an invaluable measurement for the purpose of assessing brain activities. The detection of epileptic seizures based on EEG signal is very useful in diagnostics. In this paper, we present a new method for discrimination between seizure and seizure-free EEG signals. The proposed method is based on empirical mode decomposition (EMD) process. We investigated that th...

KOSEKI J. KOBAYASHI-KIRSCHVINK∗, KING-FAI LI†,‡,§, RUN-LIE SHIA† and YUK L. YUNG† ∗Department of Mathematical Engineering and Information Physics The University of Tokyo, Tokyo 113-0033, Japan †Division of Geological and Planetary Sciences California Institute of Technology, Pasadena, California 91125, USA ‡Atomic and Molecular Physics Laboratories Research School of Physics and Engineering Aus...

The problem of filtering low-frequency trend from a given time series is considered. In order to solve this problem, a nonparametric technique called empirical mode decomposition trend filtering is developed. A key assumption is that the trend is representable as the sum of intrinsic mode functions produced by the empirical mode decomposition (EMD) of the time series. Based on an empirical anal...