Author

A. M. Grabowski

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· 2 Physiology· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 2 Organism:human· 2 Assay:imaging· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Assay:electrophysiology· 1

Frequent Co-Authors

G. Y. Millet· 1 shared J. R. Tacca· 1 shared O. N. Beck· 1 shared R. S. Alcantara· 1 shared S. P. Allen· 1 shared W. B. Edwards· 1 shared Z. A. Colvin· 1 shared

Activity by Year

2022-2023 · peak 2/yr

Co-Author Collaboration Network

7 top collaborators · 5 mutual co-author links

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1 shared paperBioengineering

G. Y. Millet

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Characterizing the mechanical properties of low-profile prosthetic feet

J. R. Tacca, Z. A. Colvin, A. M. Grabowski

This study characterizes the mechanical properties of a passive-elastic prosthetic foot, finding that stiffness and hysteresis vary with category, size, and shoe addition.

bioRxiv · Apr 14, 2023 · PreprintBioengineering

Evaluating the "cost of generating force" hypothesis across frequency in human running and hopping

S. P. Allen, O. N. Beck, A. M. Grabowski

The study tests how muscle mechanics relate to metabolic energy expenditure in human running and hopping across different step frequencies.

bioRxiv · Mar 9, 2022Physiology

Predicting continuous ground reaction forces from accelerometers during uphill and downhill running: A recurrent neural network solution

R. S. Alcantara, W. B. Edwards, G. Y. Millet, A. M. Grabowski

This paper develops a recurrent neural network to predict continuous normal ground reaction forces during uphill and downhill running from accelerometer data, achieving higher accuracy than prior methods.

PeerJ · Jan 4, 2022Peer-reviewedBioengineering