325 citations · 748 across the 26 of their papers we have counts for
7 papers · 1 filter
Tensor-driven extraction of developmental features from varying paediatric EEG datasets
Eli Kinney-Lang, Loukianos Spyrou, Ahmed Ebied +2
Objective. Consistently changing physiological properties in developing children's brains challenges new data heavy technologies, like brain-computer interfaces (BCI). Advancing si…
Amplitude- and Frequency-based Dispersion Patterns and Entropy
Hamed Azami, Javier Escudero
Permutation patterns-based approaches, such as permutation entropy (PerEn), have been widely and successfully used to analyze data. However, these methods have two main shortcoming…
Complex tensor factorisation with PARAFAC2 for the estimation of brain connectivity from the EEG
Loukianos Spyrou, Mario Parra, Javier Escudero
Objective: The coupling between neuronal populations and its magnitude have been shown to be informative for various clinical applications. One method to estimate brain connectivit…
Weighted network estimation by the use of topological graph metrics
Loukianos Spyrou, Javier Escudero
Topological metrics of graphs provide a natural way to describe the prominent features of various types of networks. Graph metrics describe the structure and interplay of graph edg…
Multivariate Multiscale Dispersion Entropy of Biomedical Times Series
Hamed Azami, Alberto Fernandez, Javier Escudero
Objective: Due to the non-linearity of numerous biomedical signals, non-linear analysis of multi-channel time series, notably multivariate multiscale entropy (mvMSE), has been exte…
Are Erdös- Rényi Random Graphs Topologically Random?
Keith Smith, Javier Escudero
No. We prove that Erdos- Renyi Random Graphs are not topologically random.
Graph-Variate Signal Analysis
Keith Smith, Loukianos Spyrou, Javier Escudero
Incorporating graphs in the analysis of multivariate signals is becoming a standard way to understand the interdependency of activity recorded at different sites. The new research…