GADF/GASF-HOG:feature extraction methods for hand movement classification from surface electromyography-Reference-Cited by-同舟云学术

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GADF/GASF-HOG:feature extraction methods for hand movement classification from surface electromyography

Published:2020-07-24 Issue:4 Volume:17 Page:046016
ISSN:1741-2552
Container-title:Journal of Neural Engineering
language:
Short-container-title:J. Neural Eng.

Author:

Xiao Feiyun^ORCID,Chen Yanyan,Zhu Yanhe

Funder

Fundamental Research Funds for the Central Universities of China

National Key R&D Program of China

State Key Laboratory of Robotics and Systems

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Publisher

IOP Publishing

Subject

Cellular and Molecular Neuroscience,Biomedical Engineering

Link

https://iopscience.iop.org/article/10.1088/1741-2552/ab9db9/pdf

Reference45 articles.

1. Detection of movement onset using EMG signals for upper-limb exoskeletons in reaching tasks

2. Adaptive Control of Exoskeleton Robots for Periodic Assistive Behaviours Based on EMG Feedback Minimisation

3. Automated classification of hand movements using tunable-Q wavelet transform based filter-bank with surface electromyogram signals

4. Adaptive Auto-Regressive Proportional Myoelectric Control

5. Adaptive Admittance Control for an Ankle Exoskeleton Using an EMG-Driven Musculoskeletal Model

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2. Research on prediction of yellow flesh peach firmness using a novel acoustic real-time detection device and Vis/NIR technology;LWT;2024-09

3. How to use one surface electromyography sensor to recognize six hand movements for a mechanical hand in real time: a method based on Morse code;Medical & Biological Engineering & Computing;2024-05-03

4. Gearbox fault diagnosis method based on improved semi-supervised MTDL and GAF;Measurement and Control;2024-02-29

5. Novel feature extraction of underwater targets by encoding hydro-acoustic signatures as image;Applied Ocean Research;2023-09

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