Application of the neural network in the study of skeletal muscle with multi-parameters

Jun Shi; Zhuangzhi Yan; Yongping Zheng; Zhang Ha

doi:10.1109/WCICA.2006.1712915

Application of the neural network in the study of skeletal muscle with multi-parameters

Jun Shi, Zhuangzhi Yan, Yongping Zheng, Zhang Ha

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

Abstract

The mechanical properties of skeletal muscles are always related to its architectural changes. But at present, there are very few documents that report the comprehensive study on skeletal muscle with structure morphology, mechanics, electrophysiology and so on. This paper introduced that the muscle thickness and surface electromyography (SEMG) sampled from the extensor carpi radialis by the ultrasound measurement of motion and elasticity system were used to fit the wrist angle with several regression algorithms. The results illuminate that the wrist angle is well fitted by combining the SMG and SEMG signals together, especially with the neural network algorithm, and the results are better than the results fitted by SMG or SEMG alone. So it is better to use multi-parameters to study the skeletal muscle.

Original language	English
Title of host publication	Proceedings of the World Congress on Intelligent Control and Automation (WCICA)
Pages	2993-2997
Number of pages	5
Volume	1
DOIs	https://doi.org/10.1109/WCICA.2006.1712915
Publication status	Published - 1 Dec 2006
Event	6th World Congress on Intelligent Control and Automation, WCICA 2006 - Dalian, China Duration: 21 Jun 2006 → 23 Jun 2006

Conference

Conference	6th World Congress on Intelligent Control and Automation, WCICA 2006
Country/Territory	China
City	Dalian
Period	21/06/06 → 23/06/06

Keywords

Neural network
Sonomyography
Surface electromyography
Ultrasound

ASJC Scopus subject areas

Control and Systems Engineering
Software
Computer Science Applications

More information

10.1109/WCICA.2006.1712915

Cite this

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title = "Application of the neural network in the study of skeletal muscle with multi-parameters",

abstract = "The mechanical properties of skeletal muscles are always related to its architectural changes. But at present, there are very few documents that report the comprehensive study on skeletal muscle with structure morphology, mechanics, electrophysiology and so on. This paper introduced that the muscle thickness and surface electromyography (SEMG) sampled from the extensor carpi radialis by the ultrasound measurement of motion and elasticity system were used to fit the wrist angle with several regression algorithms. The results illuminate that the wrist angle is well fitted by combining the SMG and SEMG signals together, especially with the neural network algorithm, and the results are better than the results fitted by SMG or SEMG alone. So it is better to use multi-parameters to study the skeletal muscle.",

keywords = "Neural network, Sonomyography, Surface electromyography, Ultrasound",

author = "Jun Shi and Zhuangzhi Yan and Yongping Zheng and Zhang Ha",

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doi = "10.1109/WCICA.2006.1712915",

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Shi, J, Yan, Z, Zheng, Y & Ha, Z 2006, Application of the neural network in the study of skeletal muscle with multi-parameters. in Proceedings of the World Congress on Intelligent Control and Automation (WCICA). vol. 1, 1712915, pp. 2993-2997, 6th World Congress on Intelligent Control and Automation, WCICA 2006, Dalian, China, 21/06/06. https://doi.org/10.1109/WCICA.2006.1712915

Application of the neural network in the study of skeletal muscle with multi-parameters. / Shi, Jun; Yan, Zhuangzhi; Zheng, Yongping et al.
Proceedings of the World Congress on Intelligent Control and Automation (WCICA). Vol. 1 2006. p. 2993-2997 1712915.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - Application of the neural network in the study of skeletal muscle with multi-parameters

AU - Shi, Jun

AU - Yan, Zhuangzhi

AU - Zheng, Yongping

AU - Ha, Zhang

PY - 2006/12/1

Y1 - 2006/12/1

N2 - The mechanical properties of skeletal muscles are always related to its architectural changes. But at present, there are very few documents that report the comprehensive study on skeletal muscle with structure morphology, mechanics, electrophysiology and so on. This paper introduced that the muscle thickness and surface electromyography (SEMG) sampled from the extensor carpi radialis by the ultrasound measurement of motion and elasticity system were used to fit the wrist angle with several regression algorithms. The results illuminate that the wrist angle is well fitted by combining the SMG and SEMG signals together, especially with the neural network algorithm, and the results are better than the results fitted by SMG or SEMG alone. So it is better to use multi-parameters to study the skeletal muscle.

AB - The mechanical properties of skeletal muscles are always related to its architectural changes. But at present, there are very few documents that report the comprehensive study on skeletal muscle with structure morphology, mechanics, electrophysiology and so on. This paper introduced that the muscle thickness and surface electromyography (SEMG) sampled from the extensor carpi radialis by the ultrasound measurement of motion and elasticity system were used to fit the wrist angle with several regression algorithms. The results illuminate that the wrist angle is well fitted by combining the SMG and SEMG signals together, especially with the neural network algorithm, and the results are better than the results fitted by SMG or SEMG alone. So it is better to use multi-parameters to study the skeletal muscle.

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Application of the neural network in the study of skeletal muscle with multi-parameters

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Keywords

ASJC Scopus subject areas

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