Heart rate variability (HRV) is a key indicator for assessing autonomous nervous system activity. Because nonstationary and slow trends which can cause distortion to HRV analysis are usually occurred in HRV signals, detrending scheme is necessary before HRV analysis. Ensemble empirical mode decomposition (EEMD), which offers the ability to break down signals into a set of intrinsic mode functio...

Within a combined EEG-fMRI study of contour integration, we analyze responses to Gabor stimuli with a combined Empirical Mode Decomposition and an Independent Component Analysis. Generaly, responses to different stimuli are very similar thus hard to differentiate. EMD and ICA are used intermingled and not simply in a sequential way. This novel combination helps to suppress redundant modes resul...

Within a combined EEG-fMRI study of contour integration, we analyze responses to Gabor stimuli with an Empirical Mode Decomposition combined with an Independent Component Analysis. Generally, responses to different stimuli are very similar thus hard to differentiate. EMD and ICA are used intermingled and not simply in a sequential way. This novel combination helps to suppress redundant modes re...

The analysis of nonlinear and nonstationary time series is still a challenge, as most classical time series analysis techniques are restricted to data that is, at least, stationary. Empirical mode decomposition (EMD) in combination with a Hilbert spectral transform, together called Hilbert-Huang transform (HHT), alleviates this problem in a purely data-driven manner. EMD adaptively and locally ...

In this paper a signal denoising scheme based a multiresolution approach referred to as Empirical mode decomposition (EMD) [1] is presented. The denoising method is a fully data driven approach. Noisy signal is decomposed adaptively into intrinsic oscillatory components called Intrinsic mode functions (IMFs) using a decomposition algorithm algorithm called sifting process. The basic principle o...

Empirical Mode Decomposition (EMD), introduced by Huang et al, in 1998 is a new and effective tool to analyze non-linear and non-stationary signals. With this method, a complicated and multiscale signal can be adaptively decomposed into a sum of finite number of zero mean oscillating components called as Intrinsic Mode Functions (IMF) whose instantaneous frequency computed by the analytic signa...