A novel multi-scale approach for quantifying both inter-and intra-component dependence of
a complex system is introduced. This is achieved using empirical mode decomposition …

In this work we propose an extension of the Symmetrical Uncertainty (SU) measure in order
to address the multivariate case, simultaneously acquiring the capability to detect possible …

Neural complexity is thought to be associated with efficient information processing but the
exact nature of this relation remains unclear. Here, the relationship of fluid intelligence (gf) …

Background Impairments in gait and balance function are typical after concussion. There is
evidence that these neuromuscular deficits persist past the typical time of symptom …

Simultaneously analyzing multivariate time series provides an insight into underlying
interaction mechanisms of cardiovascular system and has recently become an increasing …

The rapid development in sensor technology has made it convenient to acquire data from
multi-channel systems but has also high-lighted the need for the analysis of nonlinear …

Speech understanding, watching a movie, listening to music etc., requires perception of the
temporal order of at least two incoming events. A history of performing these tasks may be …

Background The study aimed to determine how the resting-state EEG (rsEEG) complexity
changes both over time and space (channels). The complexity of rsEEG and its sex/gender …

As vectors' similarity is defined on the basis of the hard boundary of Heaviside function in
multiscale multivariate sample entropy, the two families of statistics show high sensitivity to …

Entropy measures are often used to quantify the regularity of postural sway time series.
Recent methodological developments provided both multivariate and multiscale approaches …