Robust Long-Term Hand Grasp Recognition With Raw Electromyographic Signals Using Multidimensional Uncertainty-Aware Models-Reference-Cited by-同舟云学术

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Robust Long-Term Hand Grasp Recognition With Raw Electromyographic Signals Using Multidimensional Uncertainty-Aware Models

Published:2023 Issue: Volume:31 Page:962-971
ISSN:1534-4320
Container-title:IEEE Transactions on Neural Systems and Rehabilitation Engineering
language:
Short-container-title:IEEE Trans. Neural Syst. Rehabil. Eng.

Author:

Lin Yuzhou¹^ORCID,Palaniappan Ramaswamy¹^ORCID,De Wilde Philippe²^ORCID,Li Ling³^ORCID

Affiliation:

1. School of Computing, University of Kent, Canterbury, Kent, U.K.

2. Division of Natural Sciences, University of Kent, Canterbury, Kent, U.K.

3. Department of Engineering, School of Science and Technology, City, University of London, London, Northampton Square, U.K.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering,General Neuroscience,Internal Medicine,Rehabilitation

Link

http://xplorestaging.ieee.org/ielx7/7333/10031624/10017274.pdf?arnumber=10017274

Reference47 articles.

1. Electromyogram pattern recognition for control of powered upper-limb prostheses: State of the art and challenges for clinical use

2. Reliability Analysis for Finger Movement Recognition With Raw Electromyographic Signal by Evidential Convolutional Networks

3. Examining the adverse effects of limb position on pattern recognition based myoelectric control

4. Questioning Domain Adaptation in Myoelectric Hand Prostheses Control: An Inter- and Intra-Subject Study

5. Effects of Confidence-Based Rejection on Usability and Error in Pattern Recognition-Based Myoelectric Control

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