Dexterous hand motion classification and recognition based on multimodal sensing

Yaxu Xue; Zhaojie Ju; Kui Xiang; Chenguang Yang; Honghai Liu

doi:10.1007/978-3-319-65289-4_43

Dexterous hand motion classification and recognition based on multimodal sensing

Yaxu Xue
, Zhaojie Ju^*
, Kui Xiang
, Chenguang Yang
, Honghai Liu

^*Corresponding author for this work

Wuhan University of Technology
University of Portsmouth
Pingdingshan University
Swansea University

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

4 Scopus citations

Abstract

Human hand motions analysis is an essential research topic in recent applications, especially for dexterous robot hand manipulation learning from human hand skills. It provides important information about gestures, moving, speed and the control force captured via multimodal sensing technologies. This paper presents a comprehensive discussion of the nature of human hand motions in terms of simple motions, such as grasps and gestures, and complex motions, e.g. in-hand manipulations and re-grasps. And then, a novel multimodal sensing based hand motion capture system is proposed to acquire the sensory information. By using an adaptive directed acyclic graph algorithm, the experimental results show the proposed system has a higher recognition rate compared with those with individual sensing technologies.

Original language	English
Title of host publication	Intelligent Robotics and Applications - 10th International Conference, ICIRA 2017, Proceedings
Editors	Honghai Liu, YongAn Huang, Hao Wu, Zhouping Yin
Publisher	Springer Verlag
Pages	450-461
Number of pages	12
ISBN (Print)	9783319652887
DOIs	https://doi.org/10.1007/978-3-319-65289-4_43
State	Published - 2017
Externally published	Yes
Event	10th International Conference on Intelligent Robotics and Applications, ICIRA 2017 - Wuhan, China Duration: 16 Aug 2017 → 18 Aug 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10462 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	10th International Conference on Intelligent Robotics and Applications, ICIRA 2017
Country/Territory	China
City	Wuhan
Period	16/08/17 → 18/08/17

Keywords

Contact force
Data glove
EMG
Multimodal sensing
Support vector machine

Access to Document

10.1007/978-3-319-65289-4_43

Cite this

Xue, Y., Ju, Z., Xiang, K., Yang, C., & Liu, H. (2017). Dexterous hand motion classification and recognition based on multimodal sensing. In H. Liu, Y. Huang, H. Wu, & Z. Yin (Eds.), Intelligent Robotics and Applications - 10th International Conference, ICIRA 2017, Proceedings (pp. 450-461). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10462 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-319-65289-4_43

Xue, Yaxu ; Ju, Zhaojie ; Xiang, Kui et al. / Dexterous hand motion classification and recognition based on multimodal sensing. Intelligent Robotics and Applications - 10th International Conference, ICIRA 2017, Proceedings. editor / Honghai Liu ; YongAn Huang ; Hao Wu ; Zhouping Yin. Springer Verlag, 2017. pp. 450-461 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{eefcb07a873a4203ae670a291f4e5445,

title = "Dexterous hand motion classification and recognition based on multimodal sensing",

abstract = "Human hand motions analysis is an essential research topic in recent applications, especially for dexterous robot hand manipulation learning from human hand skills. It provides important information about gestures, moving, speed and the control force captured via multimodal sensing technologies. This paper presents a comprehensive discussion of the nature of human hand motions in terms of simple motions, such as grasps and gestures, and complex motions, e.g. in-hand manipulations and re-grasps. And then, a novel multimodal sensing based hand motion capture system is proposed to acquire the sensory information. By using an adaptive directed acyclic graph algorithm, the experimental results show the proposed system has a higher recognition rate compared with those with individual sensing technologies.",

keywords = "Contact force, Data glove, EMG, Multimodal sensing, Support vector machine",

author = "Yaxu Xue and Zhaojie Ju and Kui Xiang and Chenguang Yang and Honghai Liu",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 10th International Conference on Intelligent Robotics and Applications, ICIRA 2017 ; Conference date: 16-08-2017 Through 18-08-2017",

year = "2017",

doi = "10.1007/978-3-319-65289-4\_43",

language = "英语",

isbn = "9783319652887",

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

publisher = "Springer Verlag",

pages = "450--461",

editor = "Honghai Liu and YongAn Huang and Hao Wu and Zhouping Yin",

booktitle = "Intelligent Robotics and Applications - 10th International Conference, ICIRA 2017, Proceedings",

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Xue, Y, Ju, Z, Xiang, K, Yang, C & Liu, H 2017, Dexterous hand motion classification and recognition based on multimodal sensing. in H Liu, Y Huang, H Wu & Z Yin (eds), Intelligent Robotics and Applications - 10th International Conference, ICIRA 2017, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10462 LNAI, Springer Verlag, pp. 450-461, 10th International Conference on Intelligent Robotics and Applications, ICIRA 2017, Wuhan, China, 16/08/17. https://doi.org/10.1007/978-3-319-65289-4_43

Dexterous hand motion classification and recognition based on multimodal sensing. / Xue, Yaxu; Ju, Zhaojie; Xiang, Kui et al.
Intelligent Robotics and Applications - 10th International Conference, ICIRA 2017, Proceedings. ed. / Honghai Liu; YongAn Huang; Hao Wu; Zhouping Yin. Springer Verlag, 2017. p. 450-461 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10462 LNAI).

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

TY - GEN

T1 - Dexterous hand motion classification and recognition based on multimodal sensing

AU - Xue, Yaxu

AU - Ju, Zhaojie

AU - Xiang, Kui

AU - Yang, Chenguang

AU - Liu, Honghai

N1 - Publisher Copyright: © Springer International Publishing AG 2017.

PY - 2017

Y1 - 2017

N2 - Human hand motions analysis is an essential research topic in recent applications, especially for dexterous robot hand manipulation learning from human hand skills. It provides important information about gestures, moving, speed and the control force captured via multimodal sensing technologies. This paper presents a comprehensive discussion of the nature of human hand motions in terms of simple motions, such as grasps and gestures, and complex motions, e.g. in-hand manipulations and re-grasps. And then, a novel multimodal sensing based hand motion capture system is proposed to acquire the sensory information. By using an adaptive directed acyclic graph algorithm, the experimental results show the proposed system has a higher recognition rate compared with those with individual sensing technologies.

AB - Human hand motions analysis is an essential research topic in recent applications, especially for dexterous robot hand manipulation learning from human hand skills. It provides important information about gestures, moving, speed and the control force captured via multimodal sensing technologies. This paper presents a comprehensive discussion of the nature of human hand motions in terms of simple motions, such as grasps and gestures, and complex motions, e.g. in-hand manipulations and re-grasps. And then, a novel multimodal sensing based hand motion capture system is proposed to acquire the sensory information. By using an adaptive directed acyclic graph algorithm, the experimental results show the proposed system has a higher recognition rate compared with those with individual sensing technologies.

KW - Contact force

KW - Data glove

KW - EMG

KW - Multimodal sensing

KW - Support vector machine

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DO - 10.1007/978-3-319-65289-4_43

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AN - SCOPUS:85028454397

SN - 9783319652887

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

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BT - Intelligent Robotics and Applications - 10th International Conference, ICIRA 2017, Proceedings

A2 - Liu, Honghai

A2 - Huang, YongAn

A2 - Wu, Hao

A2 - Yin, Zhouping

PB - Springer Verlag

T2 - 10th International Conference on Intelligent Robotics and Applications, ICIRA 2017

Y2 - 16 August 2017 through 18 August 2017

ER -

Xue Y, Ju Z, Xiang K, Yang C, Liu H. Dexterous hand motion classification and recognition based on multimodal sensing. In Liu H, Huang Y, Wu H, Yin Z, editors, Intelligent Robotics and Applications - 10th International Conference, ICIRA 2017, Proceedings. Springer Verlag. 2017. p. 450-461. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-65289-4_43

Dexterous hand motion classification and recognition based on multimodal sensing

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Keywords

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