Publications
Preprints
S Goerttler, F He, M Wu, Stochastic Graph Heat Modelling for Diffusion-based Connectivity Retrieval, arXiv:2402.12785, 2024.
S Goerttler, F He, M Wu, Balancing Spectral, Temporal and Spatial Information for EEG-based Alzheimer’s Disease Classification, arXiv:2402.13523, 2024.
S Goerttler, M Wu, F He, Understanding concepts in graph signal processing for neurophysiological signal analysis, In: Ahmed, A., Picone, J. (eds) Machine Learning Applications in Medicine and Biology. Springer, 2024.
AMH Chan, ML Pay, J Christensen, F He, LC Roden, H Ahmed, M Foo, Red, blue or mix: choice of optimal light qualities for enhanced plant growth through in silico analysis, agriRxiv.2023.00197, 2023.
Recent Journal Papers
D Klepl, M Wu, F He*, Graph Neural Network-based EEG Classification: A Survey, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 32, 493 - 503, 2024.
J-C Hua, E Kim, F He, Information Geometry Theoretic Measures for Characterizing Neural Information Processing from Simulated EEG Signals, Entropy, 26(3), 213, 2024.
D Klepl, F He*, M Wu*, DJ Blackburn, PG Sarrigiannis, Adaptive Gated Graph Convolutional Network for Explainable Diagnosis of Alzheimer’s Disease using EEG Data, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 31, 3978-3987, 2023.
S. Wang, Z. Zhang, F He, Y. Hu, Editorial: Generative AI for Brain Image Computing and Brain Network Computing, Volume 17, Frontiers in Neuroscience, 2023.
SR Gunawardena, PG Sarrigiannis, DJ Blackburn, F He*, Kernel-based Nonlinear Manifold Learning for EEG Channel Selection with Application to Alzheimer’s Disease, Neuroscience, 523, 140-156, 2023.
D Klepl, F He*, M Wu, DJ Blackburn, PG Sarrigiannis, Cross-Frequency Multilayer Network Analysis with Bispectrum-based Functional Connectivity: A Study of Alzheimer’s Disease, Neuroscience, 521, 77-88, 2023.
HJ Choong, E Kim, F He, Causality Analysis with Information Geometry: A Comparison, Entropy, 25(5), 806, 2023.
P Li, RJ Van Wezel, F He, Y Zhao, Y Wang, The role of wrist-worn technology in the management of Parkinson’s disease in daily life: A narrative review, Frontiers in Neuroinformatics, 17: 1135300, 2023.
D Klepl, F He*, M Wu, DJ Blackburn, PG Sarrigiannis, EEG-based Graph Neural Network Classification of Alzheimer’s disease: An Empirical Evaluation of Functional Connectivity Methods, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 30, 2651-2660, 2022.
D Klepl, F He*, M Wu, DJ Blackburn, M De Marco, PG Sarrigiannis, Characterising Alzheimer’s disease with EEG-based Energy Landscape Analysis, IEEE Journal of Biomedical and Health Informatics, 26(3), 992-1000, 2022. [preprint: arXiv] [front cover featured article][code]
M Foo, L Dony, F He, Data-driven dynamical modelling of a pathogen-infected plant gene regulatory network: a comparative analysis, BioSystems, 219:104732, 2022.
B Vasudeva, R Tian, DH, Wu, SA. James, HH Refai, L Ding, F He, Y Yang, Multi-Phase Locking Value: A Generalized Method for Determining Instantaneous Multi-frequency Phase Coupling, [preprint:arXiv], Biomedical Signal Processing and Control, 74(4):103492, 2022.
F He, Y Yang, Nonlinear System Identification of Neural Systems from Neurophysiological Signals, Neuroscience, 458, 213-228, 2021. preprint
IF Kurniawanad, T Asyhari, F He, Y Liu, Mobile computing and communications-driven fog-assisted disaster evacuation techniques for context-aware guidance support: A survey, Computer Communications, 179, 195-216, 2021.
E Tankhilevich, J Ish-Horowicz, T Hameed, E Roesch, I Kleijn, MPH Stumpf, F He, GpABC: a Julia package for approximate Bayesian computation with Gaussian process emulation, Bioinformatics, 36, 3286–3287, 2020. [Julia package]
L Dony, F He, MPH Stumpf, Parametric and non-parametric gradient matching for network inference: a comparison, BMC Bioinformatics, 20, 52, 2019. [code]
F He, MPH Stumpf, Quantifying Dynamic Regulation in Metabolic Pathways with Nonparametric Flux Inference, Biophysical Journal, 116, 2035-2046, 2019.
DJ Blackburn, PG Sarrigiannis, M Marco De, Y Zhao, A Venneri, S Lawrence, ZC Unwin, M Blyth, J Angel, K Baster, ID Wilkinson, SM Bell, F He, HL Wei, SA Billings, TFD Farrow, A Pilot Study Investigating a Novel Non-Linear Measure of Eyes Open versus Eyes Closed EEG Synchronization in People with Alzheimer’s Disease and Healthy Controls, Brain Science, 8(7), 134, 2018.
PG Sarrigiannis, Y Zhao, F He, SA Billings, K Baster, C Rittey, J Yianni, P Zis, H Wei, M Hadjivassiliou, R Grünewald, The cortical focus in childhood absence epilepsy; evidence from nonlinear analysis of scalp EEG recordings, Clinical Neurophysiology, 129(3), 602-617, 2018.
F He, PG Sarrigiannis, SA Billings, H Wei, J Rowe, C Romanowski, N Hoggard, M Hadjivassilliou, D Rao, R Grünewald, A Khan, J Yianni, Nonlinear interactions in the thalamocortical loop in essential tremor: a model-based frequency domain analysis, Neuroscience, 324, 377-389, 2016.
F He, E Murabito, HV Westerhoff, Synthetic biology and regulatory networks: where metabolic systems biology meets control engineering, Journal of The Royal Society Interface, 13(117), 2015.1046, 2016.
F He, HL Wei, SA Billings, Identification and frequency domain analysis of non-stationary and nonlinear systems using time-varying NARMAX models, International Journal of Systems Science, 46(11), 2087-2100, 2015.
F He, SA Billings, HL Wei, PG Sarrigiannis, A nonlinear causality measure in the frequency domain: Nonlinear partial directed coherence with applications to EEG, Journal of Neuroscience Methods, 225, 71-80, 2014.
HV Westerhoff, AN Brooks, E Simeonidis, R García-Contreras, F He, F C Boogerd, VJ Jackson, V Goncharuk, A Kolodkin, Macromolecular networks and intelligence in microorganisms, Frontiers in Microbiology 5, 379, 2014.
F He, HL Wei, SA Billings, PG Sarrigiannis, A nonlinear generalization of spectral granger causality, IEEE Transactions on Biomedical Engineering, 61 (6), 1693-1701, 2014.
F He, SA Billings, HL Wei, PG Sarrigiannis, Y Zhao, Spectral analysis for nonstationary and nonlinear systems: A discrete-time-model-based approach, IEEE Transactions on Biomedical Engineering, 60 (8), 2233-2241, 2013.
F He, V Fromion, HV Westerhoff, (Im) Perfect robustness and adaptation of metabolic networks subject to metabolic and gene-expression regulation: marrying control engineering with metabolic control analysis, BMC systems biology, 7(1),131, 2013.
Y Zhao, SA Billings, H Wei, F He, PG Sarrigiannis, A new NARX-based Granger linear and nonlinear casual influence detection method with applications to EEG data, Journal of Neuroscience Methods, 212(1), 79-86, 2013.
Conference Papers & Book Chapters
Y Zhao, F He, Y Guo, EEG Signal Processing Techniques and Applications, Speical Issue Reprint Book, Sensors, 2024
S Goerttler, F He, M Wu, DJ Blackburn, PG Sarrigiannis, Comparing spatial and spectral graph filtering for preprocessing neurophysiological signals, IEEE Signal Processing in Medicine and Biology Symposium, 2023. PDF, Video
J-C Hua; E Kim; F He, Information Geometry Approach to Analyzing Simulated EEG Signals of Alzheimer’s Disease Patients and Healthy Control Subjects, IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2023.
D Klepl, F He*, M Wu, DJ Blackburn, PG Sarrigiannis, Bispectrum-based Cross-frequency Functional Connectivity: Classification of Alzheimer’s disease, arXiv:2206.05354, IEEE 44th International Engineering in Medicine and Biology Conference (EMBC) 2022, Glasgow.
S Goerttler, M Wu, F He, The Effect of Graph Frequencies on Dynamic Structures in Graph Signal Processing, IEEE Signal Processing in Medicine and Biology Symposium, 2022.
S Ganeshamoorthy, L Roden, D Klepl, F He, Gene Regulatory Network Inference through Link Prediction using Graph Neural Network, IEEE Signal Processing in Medicine and Biology Symposium, 2022.
R Gunawardena, PG Sarrigiannis, DJ Blackburn, F He, Kernel-based Nonlinear Manifold Learning for EEG Functional Connectivity Analysis with Application to Alzheimer’s Disease, IEEE Signal Processing in Medicine and Biology Symposium, 2022.