A Fast EMG-Based Algorithm for Upper-Limb Motion Intention Detection by Using Levant’s Differentiators

Electromyography (EMG) signals are widely used for predicting human movement intention in the operation of robotic assistive devices that improve the quality of people’s lives with motor problems. One of the current challenges controlling such devices is achieving a natural interaction be...

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Main Authors: Mayumi Hori Uribe, Carlos Renato Vazquez, Javier M. Antelis
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9919190/
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author Mayumi Hori Uribe
Carlos Renato Vazquez
Javier M. Antelis
author_facet Mayumi Hori Uribe
Carlos Renato Vazquez
Javier M. Antelis
author_sort Mayumi Hori Uribe
collection DOAJ
description Electromyography (EMG) signals are widely used for predicting human movement intention in the operation of robotic assistive devices that improve the quality of people’s lives with motor problems. One of the current challenges controlling such devices is achieving a natural interaction between the device and the user. However, the most common algorithms applied in motion detection exhibit a slow time response. In this work, we propose the use of robust differentiator algorithms to extract features from EMG signals that allow a fast detection of movement intention. Experimental results show that by using robust differentiator algorithms, we can significantly reduce the latency between the detection movement intention and the real movement, without losing accuracy.
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spelling doaj.art-5d9cdb2e68b04d7d849463b86fbb48362022-12-22T02:41:12ZengIEEEIEEE Access2169-35362022-01-011011162311163510.1109/ACCESS.2022.32145319919190A Fast EMG-Based Algorithm for Upper-Limb Motion Intention Detection by Using Levant’s DifferentiatorsMayumi Hori Uribe0https://orcid.org/0000-0002-7309-4605Carlos Renato Vazquez1https://orcid.org/0000-0003-4191-4143Javier M. Antelis2https://orcid.org/0000-0003-3377-0813Escuela de Ingenieria y Ciencias, Tecnologico de Monterrey, Zapopan, MexicoEscuela de Ingenieria y Ciencias, Tecnologico de Monterrey, Zapopan, MexicoEscuela de Ingenieria y Ciencias, Tecnologico de Monterrey, Zapopan, MexicoElectromyography (EMG) signals are widely used for predicting human movement intention in the operation of robotic assistive devices that improve the quality of people’s lives with motor problems. One of the current challenges controlling such devices is achieving a natural interaction between the device and the user. However, the most common algorithms applied in motion detection exhibit a slow time response. In this work, we propose the use of robust differentiator algorithms to extract features from EMG signals that allow a fast detection of movement intention. Experimental results show that by using robust differentiator algorithms, we can significantly reduce the latency between the detection movement intention and the real movement, without losing accuracy.https://ieeexplore.ieee.org/document/9919190/Electromyography (EMG)decoding motion intentionsliding mode control (SMC)
spellingShingle Mayumi Hori Uribe
Carlos Renato Vazquez
Javier M. Antelis
A Fast EMG-Based Algorithm for Upper-Limb Motion Intention Detection by Using Levant’s Differentiators
IEEE Access
Electromyography (EMG)
decoding motion intention
sliding mode control (SMC)
title A Fast EMG-Based Algorithm for Upper-Limb Motion Intention Detection by Using Levant’s Differentiators
title_full A Fast EMG-Based Algorithm for Upper-Limb Motion Intention Detection by Using Levant’s Differentiators
title_fullStr A Fast EMG-Based Algorithm for Upper-Limb Motion Intention Detection by Using Levant’s Differentiators
title_full_unstemmed A Fast EMG-Based Algorithm for Upper-Limb Motion Intention Detection by Using Levant’s Differentiators
title_short A Fast EMG-Based Algorithm for Upper-Limb Motion Intention Detection by Using Levant’s Differentiators
title_sort fast emg based algorithm for upper limb motion intention detection by using levant x2019 s differentiators
topic Electromyography (EMG)
decoding motion intention
sliding mode control (SMC)
url https://ieeexplore.ieee.org/document/9919190/
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