Empirical Copula driven hand motion recognition via surface electromyography based templates

Zhaojie Ju; Honghai Liu

doi:10.1007/978-3-642-16584-9_7

Empirical Copula driven hand motion recognition via surface electromyography based templates

Zhaojie Ju^*
, Honghai Liu

^*Corresponding author for this work

University of Portsmouth

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Current tendency of electromyography (EMG) based prosthetic hand is to enable the user to perform complex grasps or manipulations with natural muscle movements. In this paper, a new classifier is introduced to identify the naturally contracted surface EMG patterns for hand motion recognition. The recognition method utilizes a dependence structure as a motion template, which includes one-to-one correlations of surface EMG feature channels. Using an effective EMG feature, the proposed algorithm can successfully classify different complex motions from different subjects with a satisfactory recognition rate. To save the computational cost, re-sampling processing has been employed.

Original language	English
Title of host publication	Intelligent Robotics and Applications - Third International Conference, ICIRA 2010, Proceedings
Pages	71-80
Number of pages	10
Edition	PART 1
DOIs	https://doi.org/10.1007/978-3-642-16584-9_7
State	Published - 2010
Externally published	Yes
Event	3rd International Conference on Intelligent Robotics and Applications, ICIRA 2010 - Shanghai, China Duration: 10 Nov 2010 → 12 Nov 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	6424 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	3rd International Conference on Intelligent Robotics and Applications, ICIRA 2010
Country/Territory	China
City	Shanghai
Period	10/11/10 → 12/11/10

Access to Document

10.1007/978-3-642-16584-9_7

Cite this

Ju, Z., & Liu, H. (2010). Empirical Copula driven hand motion recognition via surface electromyography based templates. In Intelligent Robotics and Applications - Third International Conference, ICIRA 2010, Proceedings (PART 1 ed., pp. 71-80). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6424 LNAI, No. PART 1). https://doi.org/10.1007/978-3-642-16584-9_7

Ju, Zhaojie ; Liu, Honghai. / Empirical Copula driven hand motion recognition via surface electromyography based templates. Intelligent Robotics and Applications - Third International Conference, ICIRA 2010, Proceedings. PART 1. ed. 2010. pp. 71-80 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

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title = "Empirical Copula driven hand motion recognition via surface electromyography based templates",

abstract = "Current tendency of electromyography (EMG) based prosthetic hand is to enable the user to perform complex grasps or manipulations with natural muscle movements. In this paper, a new classifier is introduced to identify the naturally contracted surface EMG patterns for hand motion recognition. The recognition method utilizes a dependence structure as a motion template, which includes one-to-one correlations of surface EMG feature channels. Using an effective EMG feature, the proposed algorithm can successfully classify different complex motions from different subjects with a satisfactory recognition rate. To save the computational cost, re-sampling processing has been employed.",

author = "Zhaojie Ju and Honghai Liu",

year = "2010",

doi = "10.1007/978-3-642-16584-9\_7",

language = "英语",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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booktitle = "Intelligent Robotics and Applications - Third International Conference, ICIRA 2010, Proceedings",

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Ju, Z & Liu, H 2010, Empirical Copula driven hand motion recognition via surface electromyography based templates. in Intelligent Robotics and Applications - Third International Conference, ICIRA 2010, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 6424 LNAI, pp. 71-80, 3rd International Conference on Intelligent Robotics and Applications, ICIRA 2010, Shanghai, China, 10/11/10. https://doi.org/10.1007/978-3-642-16584-9_7

Empirical Copula driven hand motion recognition via surface electromyography based templates. / Ju, Zhaojie; Liu, Honghai.
Intelligent Robotics and Applications - Third International Conference, ICIRA 2010, Proceedings. PART 1. ed. 2010. p. 71-80 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6424 LNAI, No. PART 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Ju, Zhaojie

AU - Liu, Honghai

PY - 2010

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N2 - Current tendency of electromyography (EMG) based prosthetic hand is to enable the user to perform complex grasps or manipulations with natural muscle movements. In this paper, a new classifier is introduced to identify the naturally contracted surface EMG patterns for hand motion recognition. The recognition method utilizes a dependence structure as a motion template, which includes one-to-one correlations of surface EMG feature channels. Using an effective EMG feature, the proposed algorithm can successfully classify different complex motions from different subjects with a satisfactory recognition rate. To save the computational cost, re-sampling processing has been employed.

AB - Current tendency of electromyography (EMG) based prosthetic hand is to enable the user to perform complex grasps or manipulations with natural muscle movements. In this paper, a new classifier is introduced to identify the naturally contracted surface EMG patterns for hand motion recognition. The recognition method utilizes a dependence structure as a motion template, which includes one-to-one correlations of surface EMG feature channels. Using an effective EMG feature, the proposed algorithm can successfully classify different complex motions from different subjects with a satisfactory recognition rate. To save the computational cost, re-sampling processing has been employed.

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DO - 10.1007/978-3-642-16584-9_7

M3 - 会议稿件

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SN - 9783642165832

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Ju Z, Liu H. Empirical Copula driven hand motion recognition via surface electromyography based templates. In Intelligent Robotics and Applications - Third International Conference, ICIRA 2010, Proceedings. PART 1 ed. 2010. p. 71-80. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-642-16584-9_7

Empirical Copula driven hand motion recognition via surface electromyography based templates

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