Cargando…
Estimation of the Continuous Pronation–Supination Movement by Using Multichannel EMG Signal Features and Kalman Filter: Application to Control an Exoskeleton
The Hill muscle model can be used to estimate the human joint angles during continuous movement. However, adopting this model requires the knowledge of many parameters, such as the length and speed of contraction of muscle fibers, which are liable to change with different individuals, leading to err...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8921927/ https://www.ncbi.nlm.nih.gov/pubmed/35299701 http://dx.doi.org/10.3389/fbioe.2021.771255 |
_version_ | 1784669419390107648 |
---|---|
author | Zhang, Lei Long, Jingang Zhao, RongGang Cao, Haoyang Zhang, Kai |
author_facet | Zhang, Lei Long, Jingang Zhao, RongGang Cao, Haoyang Zhang, Kai |
author_sort | Zhang, Lei |
collection | PubMed |
description | The Hill muscle model can be used to estimate the human joint angles during continuous movement. However, adopting this model requires the knowledge of many parameters, such as the length and speed of contraction of muscle fibers, which are liable to change with different individuals, leading to errors in estimation. This study established the backpropagation neural network model based on surface electromyography (sEMG) features and human movement angle. First, the function of muscles in joint rotation is defined, and then, sensors are placed on muscle tissues to gain sEMG, and then, a relation model between the surface sEMG features and the joint angle is constructed. As integrated electromyography information cannot be well reflected through a single electromyography feature, a feature extraction method combining the time domain, frequency domain, and time–frequency domain was proposed. As the degree of freedom (DOF) of the pronation–supination movement was controlled by several muscles, it was difficult to make an angle prediction. A method of correcting the estimation error based on the Kalman filter was raised to cope with this problem. An exoskeleton robot with one DOF was designed and put into the tracking experiment. The results show that the proposed model was able to enhance the estimation of the joint angle during continuous pronation–supination movements. |
format | Online Article Text |
id | pubmed-8921927 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-89219272022-03-16 Estimation of the Continuous Pronation–Supination Movement by Using Multichannel EMG Signal Features and Kalman Filter: Application to Control an Exoskeleton Zhang, Lei Long, Jingang Zhao, RongGang Cao, Haoyang Zhang, Kai Front Bioeng Biotechnol Bioengineering and Biotechnology The Hill muscle model can be used to estimate the human joint angles during continuous movement. However, adopting this model requires the knowledge of many parameters, such as the length and speed of contraction of muscle fibers, which are liable to change with different individuals, leading to errors in estimation. This study established the backpropagation neural network model based on surface electromyography (sEMG) features and human movement angle. First, the function of muscles in joint rotation is defined, and then, sensors are placed on muscle tissues to gain sEMG, and then, a relation model between the surface sEMG features and the joint angle is constructed. As integrated electromyography information cannot be well reflected through a single electromyography feature, a feature extraction method combining the time domain, frequency domain, and time–frequency domain was proposed. As the degree of freedom (DOF) of the pronation–supination movement was controlled by several muscles, it was difficult to make an angle prediction. A method of correcting the estimation error based on the Kalman filter was raised to cope with this problem. An exoskeleton robot with one DOF was designed and put into the tracking experiment. The results show that the proposed model was able to enhance the estimation of the joint angle during continuous pronation–supination movements. Frontiers Media S.A. 2022-03-01 /pmc/articles/PMC8921927/ /pubmed/35299701 http://dx.doi.org/10.3389/fbioe.2021.771255 Text en Copyright © 2022 Zhang, Long, Zhao, Cao and Zhang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Bioengineering and Biotechnology Zhang, Lei Long, Jingang Zhao, RongGang Cao, Haoyang Zhang, Kai Estimation of the Continuous Pronation–Supination Movement by Using Multichannel EMG Signal Features and Kalman Filter: Application to Control an Exoskeleton |
title | Estimation of the Continuous Pronation–Supination Movement by Using Multichannel EMG Signal Features and Kalman Filter: Application to Control an Exoskeleton |
title_full | Estimation of the Continuous Pronation–Supination Movement by Using Multichannel EMG Signal Features and Kalman Filter: Application to Control an Exoskeleton |
title_fullStr | Estimation of the Continuous Pronation–Supination Movement by Using Multichannel EMG Signal Features and Kalman Filter: Application to Control an Exoskeleton |
title_full_unstemmed | Estimation of the Continuous Pronation–Supination Movement by Using Multichannel EMG Signal Features and Kalman Filter: Application to Control an Exoskeleton |
title_short | Estimation of the Continuous Pronation–Supination Movement by Using Multichannel EMG Signal Features and Kalman Filter: Application to Control an Exoskeleton |
title_sort | estimation of the continuous pronation–supination movement by using multichannel emg signal features and kalman filter: application to control an exoskeleton |
topic | Bioengineering and Biotechnology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8921927/ https://www.ncbi.nlm.nih.gov/pubmed/35299701 http://dx.doi.org/10.3389/fbioe.2021.771255 |
work_keys_str_mv | AT zhanglei estimationofthecontinuouspronationsupinationmovementbyusingmultichannelemgsignalfeaturesandkalmanfilterapplicationtocontrolanexoskeleton AT longjingang estimationofthecontinuouspronationsupinationmovementbyusingmultichannelemgsignalfeaturesandkalmanfilterapplicationtocontrolanexoskeleton AT zhaoronggang estimationofthecontinuouspronationsupinationmovementbyusingmultichannelemgsignalfeaturesandkalmanfilterapplicationtocontrolanexoskeleton AT caohaoyang estimationofthecontinuouspronationsupinationmovementbyusingmultichannelemgsignalfeaturesandkalmanfilterapplicationtocontrolanexoskeleton AT zhangkai estimationofthecontinuouspronationsupinationmovementbyusingmultichannelemgsignalfeaturesandkalmanfilterapplicationtocontrolanexoskeleton |