Author

B. Eskofier

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

Biology Disciplines

Click to filter author papers

Bioengineering· 2 Physiology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Assay:electrophysiology· 2 Organism:human· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:experimental assay· 1 Assay:imaging· 1

Frequent Co-Authors

A. Casolo· 2 shared A. Del Vecchio· 2 shared D. Farina· 2 shared J. P. Folland· 2 shared N. Maffulli· 2 shared N. R. W. Martin· 2 shared S. Maeo· 2 shared T. G. Balshaw· 2 shared

Activity by Year

2022-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersPhysiology

A. Casolo

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Comparing sparse inertial sensor setups for sagittal-plane walking and running reconstructions

E. Dorschky, M. Nitschke, M. Mayer, I. Weygers, H. Gassner, T. Seel, B. Eskofier, A. Koelewijn

This study evaluates sparse inertial sensor setups for accurate sagittal-plane motion analysis during walking and running, finding that setups with foot and thigh sensors provide reliable results.

bioRxiv · May 25, 2023Bioengineering

Non-invasive muscle biopsy: estimation of muscle fibre size from a neuromuscular interface

A. Casolo, S. Maeo, T. G. Balshaw, M. B. Lanza, N. R. W. Martin, S. Nuccio, T. Moro, A. Paoli, F. Felici, N. Maffulli, B. Eskofier, T. M. Kinfe, J. P. Folland, D. Farina, A. Del Vecchio

This study establishes that motor unit conduction velocity can non-invasively estimate muscle fibre size in humans with moderate accuracy.

bioRxiv · Oct 21, 2022Physiology

Neural decoding from surface high-density EMG signals: influence of anatomy and synchronization on the number of identified motor units

D. Souza de Oliveira, A. Casolo, T. G. Balshaw, S. Maeo, M. Bahia Lanza, N. R. W. Martin, N. Maffulli, T. M. Kinfe, B. Eskofier, J. P. Folland, D. Farina, A. Del Vecchio

This study investigates how anatomical and neural factors affect the number of motor units identified from HD-sEMG signals during isometric contractions.

bioRxiv · Feb 5, 2022Bioengineering