Author

Francesco Cenni

University of JyväskyläORCID 0000-0001-8637-8853Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Assay:electrophysiology· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Assay:proteomics· 1 Research Focus:trajectory inference· 1

Frequent Co-Authors

B. de la CalleiD· 1 shared Carlos GomeziD· 1 shared Carmen Fernández-GonzáleziD· 1 shared Daniel IordanoviD· 1 shared Hichem SaoudiiD· 1 shared Mario Martínez‐ZarzuelaiD· 1 shared

Activity by Year

2026-2026 · peak 1/yr

Co-Author Collaboration Network

6 top collaborators · 15 mutual co-author links

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1 shared paperBioengineering

B. de la CalleORCID

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1 paper

Recent·Most cited

BioengineeringbioRxivPreprintFeb 8, 2026

Estimating Gait Kinematics from Muscle Activity Using Deep Learning in Typically Developing Children

Carmen Fernández-González, B. de la Calle, Carlos Gomez…·Mario Martínez‐Zarzuela

This study uses a 1D U-Net to estimate ankle and knee joint angles from sEMG signals in children, showing improved accuracy with age and stability during gait transitions.

1 citation

humanelectrophysiology

𝕏 PostBluesky