Muscle fatigue compensation of the electromyography signal for elbow joint angle estimation using adaptive feature-Reference-Cited by-同舟云学术

Muscle fatigue compensation of the electromyography signal for elbow joint angle estimation using adaptive feature

Published:2018-10 Issue: Volume:71 Page:284-293
ISSN:0045-7906
Container-title:Computers & Electrical Engineering
language:en
Short-container-title:Computers & Electrical Engineering

Author:

Triwiyanto Triwiyanto^ORCID,Wahyunggoro Oyas^ORCID,Nugroho H.A.^ORCID,Herianto Herianto

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,General Computer Science,Control and Systems Engineering

Reference24 articles.

1. Chapter 8. muscle fatigue and time-dependent parameters of the surface EMG signal;Basmajian,1985

2. K. Nishihara and T. Isho, “Location of electrodes in surface EMG,” in EMG Methods for Evaluating Muscle and Nerve Function, pp. 17–30, 2012. DOI: 10.5772/25421.

3. An investigation into time domain features of surface electromyography to estimate the elbow joint angle;Triwiyanto;Adv Electr Electron Eng,2017

4. SEMG-based joint force control for an upper-limb power-assist exoskeleton robot;Li;IEEE J Biomed Heal Inform,2014

5. Continuous wavelet transform analysis of surface electromyography for muscle fatigue assessment on the elbow joint motion;Triwiyanto;Adv Electr Electron Eng,2017

Cited by 34 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Feature evaluation for myoelectric pattern recognition of multiple nearby reaching targets;Medical Engineering & Physics;2024-08

2. Comparing the efficiency of recurrent neural networks to EMG-based continuous estimation of the elbow angle;Neural Computing and Applications;2024-07-29

3. Enhanced Joint Angle Estimation Using Support Vector Machine-Long Short-Term Memory Fusion with Electromyography Signals;2024 American Control Conference (ACC);2024-07-10

4. Deep learning approach to improve the recognition of hand gesture with multi force variation using electromyography signal from amputees;Medical Engineering & Physics;2024-03

5. Deep Convolution Neural Network to Improve Hand Motion Classification Performance Against Varying Orientation Using Electromyography Signal;International Journal of Precision Engineering and Manufacturing;2024-02-28