Author

S. A. Burden

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· 3

Signature Assays, Organisms & Methods

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Organism:human· 2 Approach:statistical model· 2 Approach:deep learning· 1 Approach:experimental assay· 1

Frequent Co-Authors

A. H. Y. Chou· 2 shared M. Yamagami· 2 shared A. L. Orsborn· 1 shared B. J. Chasnov· 1 shared F. Hutchison· 1 shared L. N. Peterson· 1 shared M. M. Madduri· 1 shared M. Madduri· 1 shared

Activity by Year

2020-2023 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 16 mutual co-author links

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2 shared papersBioengineering

A. H. Y. Chou

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3 papers

Recent·Most cited

Co-adaptation of dynamic human-machine interfaces

A. H. Y. Chou, M. Yamagami, M. Madduri, B. J. Chasnov, F. Hutchison, L. N. Peterson, S. A. Burden

This study investigates co-adaptation between humans and dynamic machine interfaces, finding that performance and human effort trade-off and developing a model to explain adaptation strategies.

bioRxiv · Jul 14, 2023 · PreprintBioengineering

Evaluating a Human/Machine Interface with Redundant Motor Modalities for Trajectory-Tracking

A. H. Y. Chou, M. Yamagami, S. A. Burden

This study evaluates a multimodal human/machine interface combining manual and muscle inputs for trajectory-tracking, finding it outperforms manual-only and matches muscle-only in performance.

bioRxiv · Jun 29, 2022Bioengineering

A Game-Theoretic Model for Co-Adaptive Brain-Machine Interfaces

M. M. Madduri, S. A. Burden, A. L. Orsborn

This paper develops a game-theoretic model to analyze co-adaptation in brain-machine interfaces, showing how convergence to equilibria depends on learning rates.

bioRxiv · Dec 11, 2020 · PreprintBioengineering