6 papers
Connectivity Estimation using Stochastic Graph Heat Modelling
Stephan Goerttler, Min Wu, Fei He
A growing number of techniques leverage the spatial structures that underlie many real-world datasets. Despite these advances, the complementary task of estimating spatial structur…
MSA-CNN: A Lightweight Multi-Scale CNN with Attention for Sleep Stage Classification
Stephan Goerttler, Yucheng Wang, Emadeldeen Eldele +2
Recent advancements in machine learning-based signal analysis, coupled with open data initiatives, have fuelled efforts in automatic sleep stage classification. Despite the prolife…
Balancing Spectral, Temporal and Spatial Information for EEG-based Alzheimer's Disease Classification
Stephan Goerttler, Fei He, Min Wu
The prospect of future treatment warrants the development of cost-effective screening for Alzheimer's disease (AD). A promising candidate in this regard is electroencephalography (…
Stochastic Graph Heat Modelling for Diffusion-based Connectivity Retrieval
Stephan Goerttler, Fei He, Min Wu
Heat diffusion describes the process by which heat flows from areas with higher temperatures to ones with lower temperatures. This concept was previously adapted to graph structure…
Understanding Concepts in Graph Signal Processing for Neurophysiological Signal Analysis
Stephan Goerttler, Fei He, Min Wu
Multivariate signals, which are measured simultaneously over time and acquired by sensor networks, are becoming increasingly common. The emerging field of graph signal processing (…
Graph Neural Network-based EEG Classification: A Survey
Dominik Klepl, Min Wu, Fei He
Graph neural networks (GNN) are increasingly used to classify EEG for tasks such as emotion recognition, motor imagery and neurological diseases and disorders. A wide range of meth…