Author

Nadia Dominici

Amsterdam Movement SciencesORCID 0000-0003-2312-915XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 3 Research Focus:differential expression· 2 Assay:electronic health records· 2 Approach:statistical model· 2 Research Focus:cell-cell communication· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Andreas DaffertshoferiD· 2 shared Diego MinciacchiiD· 1 shared Giulia PanconiiD· 1 shared Jaap H. van DieëniD· 1 shared Leila AlizadehsaraviiD· 1 shared Margit M. BachiD· 1 shared Riccardo BraviiD· 1 shared Ruud A.J. KosteriD· 1 shared

Activity by Year

2022-2026 · peak 2/yr

Co-Author Collaboration Network

9 top collaborators · 14 mutual co-author links

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2 shared papersNeuroscience

Andreas DaffertshoferORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

NeurosciencebioRxivPreprintJun 29, 2026

Cortico-muscular control of postural balance in older adults - effects of training on functional connectivity

Ruud A.J. Koster, Leila Alizadehsaravi, Jaap H. van Dieën…·Andreas Daffertshofer

This study examines how balance training in older adults affects cortico-muscular functional connectivity during postural recovery, finding training-induced changes in beta-band coherence with muscle synergies.

DOI 10.64898/2026.06.24.734264

humanelectronic health records

𝕏 PostBluesky

NeurosciencebioRxivPreprintApr 13, 2026

Speed-driven transitions between discrete and rhythmic dynamics in walking revealed by kinematic smoothness and muscle synergies

Giulia Panconi, Diego Minciacchi, Riccardo Bravi, Nadia Dominici

The paper examines how walking speed affects the transition between discrete and rhythmic movement patterns, showing changes in kinematic smoothness and muscle synergies.

DOI 10.64898/2026.04.09.717373

humanelectronic health records

𝕏 PostBluesky

NeuroscienceFrontiers in Sports and Active LivingPeer-reviewedOct 26, 2022

Predicting vertical ground reaction forces from 3D accelerometry using reservoir computers leads to accurate gait event detection

Margit M. Bach, Nadia Dominici, Andreas Daffertshofer

This paper uses reservoir computers to predict vertical ground reaction forces from accelerometry, enabling accurate gait event detection during walking and running.

12 citations

humanimaging

𝕏 PostBluesky