Validity and Impact of Methods for Collecting Training Data for Myoelectric Prosthetic Control Algorithms-Reference-Cited by-同舟云学术

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Validity and Impact of Methods for Collecting Training Data for Myoelectric Prosthetic Control Algorithms

Published:2024 Issue: Volume:32 Page:1974-1983
ISSN:1534-4320
Container-title:IEEE Transactions on Neural Systems and Rehabilitation Engineering
language:
Short-container-title:IEEE Trans. Neural Syst. Rehabil. Eng.

Author:

Tully Troy N.¹^ORCID,Thomson Caleb J.¹^ORCID,Clark Gregory A.¹^ORCID,George Jacob A.²

Affiliation:

1. Department of Biomedical Engineering, The University of Utah, Salt Lake City, UT, USA

2. Department of Electrical and Computer Engineering, the Department of Physical Medicine and Rehabilitation, the Department of Biomedical Engineering, and the Department of Mechanical Engineering, The University of Utah, Salt Lake City, UT, USA

Funder

National Science Foundation

National Institutes of Health

Defense Advanced Research Projects Agency

Meta

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

https://ieeexplore.ieee.org/ielam/7333/10398877/10530118-aam.pdf

Reference47 articles.

1. Upper limb prosthesis use and abandonment

2. Upper-Limb Prosthetics

3. Improved Training Paradigms and Motor-decode Algorithms: Results from Intact Individuals and a Recent Transradial Amputee with Prior Complex Regional Pain Syndrome

4. Activities of daily living with bionic arm improved by combination training and latching filter in prosthesis control comparison

5. Deep Learning Movement Intent Decoders Trained With Dataset Aggregation for Prosthetic Limb Control

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