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

Click to filter author papers

Bioengineering· 4

Signature Assays, Organisms & Methods

Click to filter · or open tag

Organism:human· 3 Approach:experimental assay· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:dimensionality reduction· 1 Assay:electrophysiology· 1

Frequent Co-Authors

A. H. Y. Chou· 3 shared A. L. Orsborn· 2 shared M. Madduri· 2 shared M. Yamagami· 2 shared A. Christensen· 1 shared B. J. Chasnov· 1 shared F. Hutchison· 1 shared F. L. Hutchison· 1 shared

Activity by Year

2020-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 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

3 shared papersBioengineering

A. H. Y. Chou

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Using Eye Gaze to Train an Adaptive Myoelectric Interface

A. H. Y. Chou, M. Madduri, S. J. Li, J. Isa, A. Christensen, F. L. Hutchison, S. A. Burden, A. L. Orsborn

This study demonstrates that using eye gaze as training data can achieve comparable performance to task-specific training in adaptive myoelectric interfaces for 2D cursor control.

bioRxiv · Apr 8, 2024 · PreprintBioengineering

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