An Attention-based Bidirectional LSTM Model for Continuous Cross-Subject Estimation of Knee Joint Angle during Running from sEMG Signals-Reference-Cited by-同舟云学术

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An Attention-based Bidirectional LSTM Model for Continuous Cross-Subject Estimation of Knee Joint Angle during Running from sEMG Signals

Published:2023-07-24 Issue: Volume: Page:
ISSN:
Container-title:2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
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Author:

Zangene Alireza Rezaie¹,Williams Samuel Oluwarotimi²,Abbasi Ali¹,Nazarpour Kianoush³,McEwan Alistair A.²,Li Guanglin⁴

Affiliation:

1. Kharazmi University,Department of Sports Biomechanics,Tehran,Iran

2. University of Derby,School of Computing and Engineering,United Kingdom,DE22 3AW

3. The University of Edinburgh,Edinburgh Neuroprosthetics Laboratory, School of Informatics,Edinburgh,UK,EH8 9AB

4. Chinese Academy of Sciences (CAS),CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology,Shenzhen,Guangdong,China,518055

Funder

National Natural Science Foundation of China

Shenzhen Government

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10339936/10339939/10340791.pdf?arnumber=10340791

Reference21 articles.

1. Running Injuries

2. A Scoping Review of the Relationship between Running and Mental Health

3. Recognition of walking environments and gait period by surface electromyography

4. Robotic gait rehabilitation and substitution devices in neurological disorders: where are we now?

5. Hierarchical Human Machine Interaction Learning for a Lower Extremity Augmentation Device

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