Evaluation of CNN algorithm at locomotion mode identification for a knee-assisted exoskeleton-Reference-Cited by-同舟云学术

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Evaluation of CNN algorithm at locomotion mode identification for a knee-assisted exoskeleton

Published:2023-04-20 Issue:11 Volume:37 Page:691-701
ISSN:0169-1864
Container-title:Advanced Robotics
language:en
Short-container-title:Advanced Robotics

Author:

Xu Aimin¹,Qu Chenxi²,Yang Liang¹^ORCID,Yin Peng³,Lv Jiliang¹,Qu Shengguan¹

Affiliation:

1. School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, People’s Republic of China

2. School of Mechanical, Aerospace and Civil Engineering, The University of Manchester, Manchester, UK

3. Guangzhou Shiyuan Electronic Technology Co., Ltd (CVTE), Guangzhou, People’s Republic of China

Publisher

Informa UK Limited

Subject

Computer Science Applications,Hardware and Architecture,Human-Computer Interaction,Software,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/01691864.2023.2197966

Reference42 articles.

1. Estimation of the Continuous Walking Angle of Knee and Ankle (Talocrural Joint, Subtalar Joint) of a Lower-Limb Exoskeleton Robot Using a Neural Network

2. A CNN-SVM combined model for pattern recognition of knee motion using mechanomyography signals

3. PSO-SVM-Based Online Locomotion Mode Identification for Rehabilitation Robotic Exoskeletons

4. High energy spectrogram with integrated prior knowledge for EMG-based locomotion classification

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