Human-machine interface based on multi-channel single-element ultrasound transducers: A preliminary study

Yuefeng Li; Keshi He; Xueli Sun; Honghai Liu

doi:10.1109/HealthCom.2016.7749483

Human-machine interface based on multi-channel single-element ultrasound transducers: A preliminary study

Yuefeng Li
, Keshi He
, Xueli Sun
, Honghai Liu^*

^*Corresponding author for this work

Shanghai Jiao Tong University

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

36 Scopus citations

Abstract

Ultrasound (US) imaging is a promising sensing technique in the field of human-machine interface, and many positive results have been reported in literature on hand gesture recognition or finger angle prediction based on US imaging. However, in most of these studies, linear array ultrasound probes were used to generate US images, which made the US device expensive and bulky. In this paper, a method of extracting forearm muscle information via multiple single-element US transducers is proposed. By using this kind of transducers, a low-cost and small-size human-machine interface can be expected. Preliminary results show that an average recognition accuracy of 96% can be achieved for six motions, including five finger flexions and rest state.

Original language	English
Title of host publication	2016 IEEE 18th International Conference on e-Health Networking, Applications and Services, Healthcom 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509033706
DOIs	https://doi.org/10.1109/HealthCom.2016.7749483
State	Published - 18 Nov 2016
Externally published	Yes
Event	18th IEEE International Conference on e-Health Networking, Applications and Services, Healthcom 2016 - Munich, Germany Duration: 14 Sep 2016 → 17 Sep 2016

Publication series

Name	2016 IEEE 18th International Conference on e-Health Networking, Applications and Services, Healthcom 2016

Conference

Conference	18th IEEE International Conference on e-Health Networking, Applications and Services, Healthcom 2016
Country/Territory	Germany
City	Munich
Period	14/09/16 → 17/09/16

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Human-machine interface
Rehabilitation robotics
Single-element transducer
Ultrasound

Access to Document

10.1109/HealthCom.2016.7749483

Cite this

Li, Y., He, K., Sun, X., & Liu, H. (2016). Human-machine interface based on multi-channel single-element ultrasound transducers: A preliminary study. In 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services, Healthcom 2016 Article 7749483 (2016 IEEE 18th International Conference on e-Health Networking, Applications and Services, Healthcom 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/HealthCom.2016.7749483

Li, Yuefeng ; He, Keshi ; Sun, Xueli et al. / Human-machine interface based on multi-channel single-element ultrasound transducers : A preliminary study. 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services, Healthcom 2016. Institute of Electrical and Electronics Engineers Inc., 2016. (2016 IEEE 18th International Conference on e-Health Networking, Applications and Services, Healthcom 2016).

@inproceedings{3096e5b810914f11bb32bf0e5ba794d3,

title = "Human-machine interface based on multi-channel single-element ultrasound transducers: A preliminary study",

abstract = "Ultrasound (US) imaging is a promising sensing technique in the field of human-machine interface, and many positive results have been reported in literature on hand gesture recognition or finger angle prediction based on US imaging. However, in most of these studies, linear array ultrasound probes were used to generate US images, which made the US device expensive and bulky. In this paper, a method of extracting forearm muscle information via multiple single-element US transducers is proposed. By using this kind of transducers, a low-cost and small-size human-machine interface can be expected. Preliminary results show that an average recognition accuracy of 96\% can be achieved for six motions, including five finger flexions and rest state.",

keywords = "Human-machine interface, Rehabilitation robotics, Single-element transducer, Ultrasound",

author = "Yuefeng Li and Keshi He and Xueli Sun and Honghai Liu",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 18th IEEE International Conference on e-Health Networking, Applications and Services, Healthcom 2016 ; Conference date: 14-09-2016 Through 17-09-2016",

year = "2016",

month = nov,

day = "18",

doi = "10.1109/HealthCom.2016.7749483",

language = "英语",

series = "2016 IEEE 18th International Conference on e-Health Networking, Applications and Services, Healthcom 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2016 IEEE 18th International Conference on e-Health Networking, Applications and Services, Healthcom 2016",

address = "美国",

}

Li, Y, He, K, Sun, X & Liu, H 2016, Human-machine interface based on multi-channel single-element ultrasound transducers: A preliminary study. in 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services, Healthcom 2016., 7749483, 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services, Healthcom 2016, Institute of Electrical and Electronics Engineers Inc., 18th IEEE International Conference on e-Health Networking, Applications and Services, Healthcom 2016, Munich, Germany, 14/09/16. https://doi.org/10.1109/HealthCom.2016.7749483

Human-machine interface based on multi-channel single-element ultrasound transducers: A preliminary study. / Li, Yuefeng; He, Keshi; Sun, Xueli et al.
2016 IEEE 18th International Conference on e-Health Networking, Applications and Services, Healthcom 2016. Institute of Electrical and Electronics Engineers Inc., 2016. 7749483 (2016 IEEE 18th International Conference on e-Health Networking, Applications and Services, Healthcom 2016).

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

TY - GEN

T1 - Human-machine interface based on multi-channel single-element ultrasound transducers

T2 - 18th IEEE International Conference on e-Health Networking, Applications and Services, Healthcom 2016

AU - Li, Yuefeng

AU - He, Keshi

AU - Sun, Xueli

AU - Liu, Honghai

PY - 2016/11/18

Y1 - 2016/11/18

N2 - Ultrasound (US) imaging is a promising sensing technique in the field of human-machine interface, and many positive results have been reported in literature on hand gesture recognition or finger angle prediction based on US imaging. However, in most of these studies, linear array ultrasound probes were used to generate US images, which made the US device expensive and bulky. In this paper, a method of extracting forearm muscle information via multiple single-element US transducers is proposed. By using this kind of transducers, a low-cost and small-size human-machine interface can be expected. Preliminary results show that an average recognition accuracy of 96% can be achieved for six motions, including five finger flexions and rest state.

AB - Ultrasound (US) imaging is a promising sensing technique in the field of human-machine interface, and many positive results have been reported in literature on hand gesture recognition or finger angle prediction based on US imaging. However, in most of these studies, linear array ultrasound probes were used to generate US images, which made the US device expensive and bulky. In this paper, a method of extracting forearm muscle information via multiple single-element US transducers is proposed. By using this kind of transducers, a low-cost and small-size human-machine interface can be expected. Preliminary results show that an average recognition accuracy of 96% can be achieved for six motions, including five finger flexions and rest state.

KW - Human-machine interface

KW - Rehabilitation robotics

KW - Single-element transducer

KW - Ultrasound

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M3 - 会议稿件

AN - SCOPUS:85006355721

T3 - 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services, Healthcom 2016

BT - 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services, Healthcom 2016

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 14 September 2016 through 17 September 2016

ER -

Li Y, He K, Sun X, Liu H. Human-machine interface based on multi-channel single-element ultrasound transducers: A preliminary study. In 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services, Healthcom 2016. Institute of Electrical and Electronics Engineers Inc. 2016. 7749483. (2016 IEEE 18th International Conference on e-Health Networking, Applications and Services, Healthcom 2016). doi: 10.1109/HealthCom.2016.7749483

Human-machine interface based on multi-channel single-element ultrasound transducers: A preliminary study

Abstract

Publication series

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UN SDGs

Keywords

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