Towards Robust, Adaptive and Reliable Upper-limb Motion Estimation Using Machine Learning and Deep Learning--A Survey in Myoelectric Control

Bao, T, Xie, SQ orcid.org/0000-0002-8082-9112, Yang, P et al. (2 more authors) (2022) Towards Robust, Adaptive and Reliable Upper-limb Motion Estimation Using Machine Learning and Deep Learning--A Survey in Myoelectric Control. IEEE Journal of Biomedical and Health Informatics. ISSN 2168-2194

Abstract

Metadata

Authors/Creators:
Copyright, Publisher and Additional Information: © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Keywords: Upper-limb motion estimation, myoelectric control, multi-modal fusion, transfer learning, post-processing
Dates:
  • Accepted: 11 March 2022
  • Published (online): 16 March 2022
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds)
Funding Information:
FunderGrant number
EPSRC (Engineering and Physical Sciences Research Council)EP/S019219/1
Depositing User: Symplectic Publications
Date Deposited: 17 Mar 2022 11:46
Last Modified: 07 Jun 2022 23:55
Status: Published online
Publisher: IEEE
Identification Number: https://doi.org/10.1109/JBHI.2022.3159792

Share / Export

Statistics