Author

A. W. Shehata

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· 3

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:experimental assay· 2 Research Focus:benchmarking· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Assay:electrophysiology· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

E. J. Scheme· 2 shared J. W. Sensinger· 2 shared H. E. Williams· 1 shared J. S. Hebert· 1 shared K. Y. Cheng· 1 shared P. M. Pilarski· 1 shared

Activity by Year

2018-2024 · peak 2/yr

Co-Author Collaboration Network

6 top collaborators · 7 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 papersBioengineering

E. J. Scheme

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Myoelectric Prosthesis Control using Recurrent Convolutional Neural Network Regression Mitigates the Limb Position Effect

H. E. Williams, A. W. Shehata, K. Y. Cheng, J. S. Hebert, P. M. Pilarski

This paper develops and tests RCNN-based controllers for myoelectric prostheses to mitigate the limb position effect, showing improved performance over traditional methods in multiple metrics.

bioRxiv · Feb 5, 2024 · PreprintBioengineering

Audible Feedback Improves Internal Model Strength and Performance of Myoelectric Prosthesis Control

A. W. Shehata, E. J. Scheme, J. W. Sensinger

This study shows that augmented audio feedback improves internal model strength and control performance in myoelectric prostheses.

bioRxiv · May 21, 2018Bioengineering

Evaluating Internal Model Strength and Performance of Myoelectric Prosthesis Control Strategies

A. W. Shehata, E. J. Scheme, J. W. Sensinger

This study evaluates internal model strength and performance of two myoelectric prosthesis control strategies using psychometric measures and a target acquisition task, finding that raw control with raw feedback leads to stronger internal model development.

bioRxiv · Feb 3, 2018Bioengineering