Young, Aaron J.
Georgia Institute of Technology
5 papers on CoChatORCID 0000-0002-5376-2258
Most cited papers
- Verified
A review of current state-of-the-art control methods for lower-limb powered prostheses
Gehlhar, R., Tucker, M., Young, A. J., & Ames, A. D. (2023) · Annual Reviews in Control
Prosthetics and Rehabilitation RoboticsMuscle activation and electromyography studies
Cited by 131
- Verified
Task-agnostic exoskeleton control via biological joint moment estimation
Molinaro, D. D., Scherpereel, K. L., Schonhaut, E. B., Evangelopoulos, G., Shepherd, M. K., & Young, A. J. (2024) · Nature
Prosthetics and Rehabilitation RoboticsMuscle activation and electromyography studies
Cited by 107
- Verified
Subject-Independent, Biological Hip Moment Estimation During Multimodal Overground Ambulation Using Deep Learning
Molinaro, D. D., Kang, I., Camargo, J., Gombolay, M. C., & Young, A. J. (2022) · IEEE Transactions on Medical Robotics and Bionics
Prosthetics and Rehabilitation RoboticsMuscle activation and electromyography studies
Cited by 90
- Verified
Classifying the intent of novel users during human locomotion using powered lower limb prostheses
Young, A. J., Simon, A. M., Fey, N. P., & Hargrove, L. J. (2013) · 2013 6th International IEEE/EMBS Conference on Neural Engineering (NER)
Prosthetics and Rehabilitation RoboticsMuscle activation and electromyography studies
Cited by 55
- Verified
Anticipation and Delayed Estimation of Sagittal Plane Human Hip Moments using Deep Learning and a Robotic Hip Exoskeleton
Molinaro, D. D., Park, E. O., & Young, A. J. (2023) · 2023 IEEE International Conference on Robotics and Automation (ICRA)
Prosthetics and Rehabilitation RoboticsMuscle activation and electromyography studies
Cited by 14
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