A CNN-LSTM Hybrid Model for Wrist Kinematics Estimation Using Surface Electromyography

Bao, T orcid.org/0000-0002-1103-2660, Zaidi, SAR orcid.org/0000-0003-1969-3727, Xie, S orcid.org/0000-0002-8082-9112 et al. (2 more authors) (2020) A CNN-LSTM Hybrid Model for Wrist Kinematics Estimation Using Surface Electromyography. IEEE Transactions on Instrumentation and Measurement, 70. 2503809. ISSN 0018-9456



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Keywords: sEMG , wrist kinematics estimation , deep learning , convolutional neural network , long short-term memory network , hybrid model
  • Accepted: 29 October 2020
  • Published (online): 9 November 2020
  • Published: 9 November 2020
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: 16 Nov 2020 10:39
Last Modified: 26 Jul 2022 11:46
Status: Published
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Identification Number: https://doi.org/10.1109/tim.2020.3036654