88 citations · 140 across the 7 of their papers we have counts for
7 papers
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…
Evaluation of matrix factorisation approaches for muscle synergy extraction
Ahmed Ebied, Eli Kinney-Lang, Loukianos Spyrou +1
The muscle synergy concept provides a widely-accepted paradigm to break down the complexity of motor control. In order to identify the synergies, different matrix factorisation tec…
Muscle Activity Analysis using Higher-Order Tensor Models: Application to Muscle Synergy Identification
Ahmed Ebied, Eli Kinney-lang, Loukianos Spyrou +1
Higher-order tensor decompositions have hardly been used in muscle activity analysis despite multichannel electromyography (EMG) datasets naturally occurring as multi-way structure…
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…
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…
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…