7 citations · 18 across the 9 of their papers we have counts for
14 papers
A noise-robust Multivariate Multiscale Permutation Entropy for two-phase flow characterisation
John Stewart Fabila-Carrasco, Chao Tan, Javier Escudero
Using a graph-based approach, we propose a multiscale permutation entropy to explore the complexity of multivariate time series over multiple time scales. This multivariate multisc…
Multivariate permutation entropy, a Cartesian graph product approach
John Stewart Fabila-Carrasco, Chao Tan, Javier Escudero
Entropy metrics are nonlinear measures to quantify the complexity of time series. Among them, permutation entropy is a common metric due to its robustness and fast computation. Mul…
Permutation Entropy for Graph Signals
John Stewart Fabila-Carrasco, Chao Tan, Javier Escudero
Entropy metrics (for example, permutation entropy) are nonlinear measures of irregularity in time series (one-dimensional data). Some of these entropy metrics can be generalised to…
On the use of higher-order tensors to model muscle synergies
Ahmed Ebied, Loukianos Spyrou, Eli Kinney-Lang +1
The muscle synergy concept provides the best framework to understand motor control and it has been recently utilised in many applications such as prosthesis control. The current mu…
Consistency of Muscle Synergies Extracted via Higher-Order Tensor Decomposition Towards Myoelectric Control
Ahmed Ebied, Eli Kinney-Lang, Javier Escudero
In recent years, muscle synergies have been pro-posed for proportional myoelectric control. Synergies were extracted using matrix factorisation techniques (mainly non-negative matr…
Multiscale Fluctuation-based Dispersion Entropy and its Applications to Neurological Diseases
Hamed Azami, Steven E. Arnold, Saeid Sanei +4
Fluctuation-based dispersion entropy (FDispEn) is a new approach to estimate the dynamical variability of the fluctuations of signals. It is based on Shannon entropy and fluctuatio…