Author

F. Hug

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioengineering· 1 Physiology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Approach:deep learning· 2 Assay:electrophysiology· 2 Research Focus:clustering· 1 Approach:graph neural network· 1 Organism:human· 1 Approach:statistical model· 1

Frequent Co-Authors

S. Avrillon· 2 shared D. Farina· 1 shared J. L. Pons· 1 shared J. T. Levine· 1 shared S. J. Kim· 1 shared Y. Wen· 1 shared

Activity by Year

2022-2023 · peak 1/yr

Co-Author Collaboration Network

6 top collaborators · 11 mutual co-author links

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2 shared papersPhysiology

S. Avrillon

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2 papers

Recent·Most cited

A graph-based approach to identify motor neuron synergies

S. Avrillon, F. Hug, D. Farina

This paper introduces a graph-based method to estimate the number and strength of synaptic inputs to motor neurons using discharge rate correlations, validated through simulations and applied to experimental data.

bioRxiv · Feb 7, 2023 · PreprintPhysiology

A deep CNN framework for neural drive estimation from HD-EMG across contraction intensities and joint angles

Y. Wen, S. J. Kim, S. Avrillon, J. T. Levine, F. Hug, J. L. Pons

This paper introduces a deep CNN framework to estimate neural drive from HD-EMG across varying contraction intensities and joint angles, achieving high accuracy without retraining for new conditions.

IEEE Transactions on Neural Systems and Rehabilitation Engineering · Jan 1, 2022Peer-reviewedBioengineering