sEMG-MMG State-Space Model for the Continuous Estimation of Multijoint Angle

Continuous joint angle estimation plays an important role in motion intention recognition and rehabilitation training. In this study, a surface electromyography- (sEMG-) mechanomyography (MMG) state-space model is proposed to estimate continuous multijoint movements from sEMG and MMG signals accurat...

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Main Authors: Xugang Xi, Chen Yang, Seyed M. Miran, Yun-Bo Zhao, Shuliang Lin, Zhizeng Luo
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2020/4503271
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author Xugang Xi
Chen Yang
Seyed M. Miran
Yun-Bo Zhao
Shuliang Lin
Zhizeng Luo
author_facet Xugang Xi
Chen Yang
Seyed M. Miran
Yun-Bo Zhao
Shuliang Lin
Zhizeng Luo
author_sort Xugang Xi
collection DOAJ
description Continuous joint angle estimation plays an important role in motion intention recognition and rehabilitation training. In this study, a surface electromyography- (sEMG-) mechanomyography (MMG) state-space model is proposed to estimate continuous multijoint movements from sEMG and MMG signals accurately. The model combines forward dynamics with a Hill-based muscle model that estimates joint torque only in a nonfeedback form, making the extended model capable of predicting the multijoint motion directly. The sEMG and MMG features, including the Wilson amplitude and permutation entropy, are then extracted to construct a measurement equation to reduce system error and external disturbances. Using the proposed model, a closed-loop prediction-correction approach, unscented particle filtering, is used to estimate the joint angle from sEMG and MMG signals. Comprehensive experiments are conducted on the human elbow and shoulder joint, and remarkable improvements are demonstrated compared with conventional methods.
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institution Kabale University
issn 1076-2787
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language English
publishDate 2020-01-01
publisher Wiley
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series Complexity
spelling doaj-art-7ae4f01d2ab34fbab91469cffcd5516f2025-02-03T01:20:47ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/45032714503271sEMG-MMG State-Space Model for the Continuous Estimation of Multijoint AngleXugang Xi0Chen Yang1Seyed M. Miran2Yun-Bo Zhao3Shuliang Lin4Zhizeng Luo5School of Artificial Intelligence, Hangzhou Dianzi University, Hangzhou 310018, ChinaSchool of Artificial Intelligence, Hangzhou Dianzi University, Hangzhou 310018, ChinaBiomedical Informatics Center, George Washington University, Washington, DC 20052, USADepartment of Automation, Zhejiang University of Technology, Hangzhou 310023, ChinaJinhua Municipal Central Hospital, Jinhua 321000, ChinaSchool of Artificial Intelligence, Hangzhou Dianzi University, Hangzhou 310018, ChinaContinuous joint angle estimation plays an important role in motion intention recognition and rehabilitation training. In this study, a surface electromyography- (sEMG-) mechanomyography (MMG) state-space model is proposed to estimate continuous multijoint movements from sEMG and MMG signals accurately. The model combines forward dynamics with a Hill-based muscle model that estimates joint torque only in a nonfeedback form, making the extended model capable of predicting the multijoint motion directly. The sEMG and MMG features, including the Wilson amplitude and permutation entropy, are then extracted to construct a measurement equation to reduce system error and external disturbances. Using the proposed model, a closed-loop prediction-correction approach, unscented particle filtering, is used to estimate the joint angle from sEMG and MMG signals. Comprehensive experiments are conducted on the human elbow and shoulder joint, and remarkable improvements are demonstrated compared with conventional methods.http://dx.doi.org/10.1155/2020/4503271
spellingShingle Xugang Xi
Chen Yang
Seyed M. Miran
Yun-Bo Zhao
Shuliang Lin
Zhizeng Luo
sEMG-MMG State-Space Model for the Continuous Estimation of Multijoint Angle
Complexity
title sEMG-MMG State-Space Model for the Continuous Estimation of Multijoint Angle
title_full sEMG-MMG State-Space Model for the Continuous Estimation of Multijoint Angle
title_fullStr sEMG-MMG State-Space Model for the Continuous Estimation of Multijoint Angle
title_full_unstemmed sEMG-MMG State-Space Model for the Continuous Estimation of Multijoint Angle
title_short sEMG-MMG State-Space Model for the Continuous Estimation of Multijoint Angle
title_sort semg mmg state space model for the continuous estimation of multijoint angle
url http://dx.doi.org/10.1155/2020/4503271
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