Gesture recognition of air-tapping and its application to character input in VR space

Mamoru Hirota; Masayuki Yokoyama; Ayumu Tsuboi; Masao Yanagisawa

doi:10.1145/3283289.3283335

Gesture recognition of air-tapping and its application to character input in VR space

Mamoru Hirota, Masayuki Yokoyama, Ayumu Tsuboi, Masao Yanagisawa

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

Abstract

The motion of the finger is made up of a combination of forearm part (extrinsic) muscles and hand part (intrinsic) muscles. We have created a wearable fingerless glove controller to sense sEMG(surface Electromyography) from intrinsic muscles using dry electrodes [Tsuboi et al. 2017].Recognition of air-tapping gesture with a sensor attached to wearable finger-less glove controller is a challenging problem. In this study, we focused on motion recognition of air-tapping and performed motion recognition using CNN and evaluated its accuracy. As a result, the accuracy in intra-subject identification was 85.05%. Also, experiments are currently being conducted in anticipation of character input in VR space [Grubert et al. 2018]. Character input experiment in VR space was carried out using sEMG wearable fingerless glove controller, as a primitive experiment of the use of sEMG glove in VR space. Based on the results, we discussed the efficiency of character input using sEMG glove in VR space.

Original language	English
Title of host publication	SIGGRAPH Asia 2018 Posters, SA 2018
Publisher	Association for Computing Machinery, Inc
ISBN (Electronic)	9781450360630
DOIs	https://doi.org/10.1145/3283289.3283335
Publication status	Published - 2018 Dec 4
Event	SIGGRAPH Asia 2018 Posters - International Conference on Computer Graphics and Interactive Techniques, SA 2018 - Tokyo, Japan Duration: 2018 Dec 4 → 2018 Dec 7

Other

Other	SIGGRAPH Asia 2018 Posters - International Conference on Computer Graphics and Interactive Techniques, SA 2018
Country	Japan
City	Tokyo
Period	18/12/4 → 18/12/7

Keywords

Finger Gesture Recognition，I/F
Interface
SEMG
VR

ASJC Scopus subject areas

Computer Graphics and Computer-Aided Design
Human-Computer Interaction
Software
Computer Vision and Pattern Recognition

Access to Document

10.1145/3283289.3283335

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Cite this

Hirota, M., Yokoyama, M., Tsuboi, A., & Yanagisawa, M. (2018). Gesture recognition of air-tapping and its application to character input in VR space. In SIGGRAPH Asia 2018 Posters, SA 2018 [3283335] Association for Computing Machinery, Inc. https://doi.org/10.1145/3283289.3283335

Hirota, M, Yokoyama, M, Tsuboi, A & Yanagisawa, M 2018, Gesture recognition of air-tapping and its application to character input in VR space. in SIGGRAPH Asia 2018 Posters, SA 2018., 3283335, Association for Computing Machinery, Inc, SIGGRAPH Asia 2018 Posters - International Conference on Computer Graphics and Interactive Techniques, SA 2018, Tokyo, Japan, 18/12/4. https://doi.org/10.1145/3283289.3283335

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title = "Gesture recognition of air-tapping and its application to character input in VR space",

abstract = "The motion of the finger is made up of a combination of forearm part (extrinsic) muscles and hand part (intrinsic) muscles. We have created a wearable fingerless glove controller to sense sEMG(surface Electromyography) from intrinsic muscles using dry electrodes [Tsuboi et al. 2017].Recognition of air-tapping gesture with a sensor attached to wearable finger-less glove controller is a challenging problem. In this study, we focused on motion recognition of air-tapping and performed motion recognition using CNN and evaluated its accuracy. As a result, the accuracy in intra-subject identification was 85.05%. Also, experiments are currently being conducted in anticipation of character input in VR space [Grubert et al. 2018]. Character input experiment in VR space was carried out using sEMG wearable fingerless glove controller, as a primitive experiment of the use of sEMG glove in VR space. Based on the results, we discussed the efficiency of character input using sEMG glove in VR space.",

keywords = "Finger Gesture Recognition，I/F, Interface, SEMG, VR",

author = "Mamoru Hirota and Masayuki Yokoyama and Ayumu Tsuboi and Masao Yanagisawa",

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PY - 2018/12/4

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N2 - The motion of the finger is made up of a combination of forearm part (extrinsic) muscles and hand part (intrinsic) muscles. We have created a wearable fingerless glove controller to sense sEMG(surface Electromyography) from intrinsic muscles using dry electrodes [Tsuboi et al. 2017].Recognition of air-tapping gesture with a sensor attached to wearable finger-less glove controller is a challenging problem. In this study, we focused on motion recognition of air-tapping and performed motion recognition using CNN and evaluated its accuracy. As a result, the accuracy in intra-subject identification was 85.05%. Also, experiments are currently being conducted in anticipation of character input in VR space [Grubert et al. 2018]. Character input experiment in VR space was carried out using sEMG wearable fingerless glove controller, as a primitive experiment of the use of sEMG glove in VR space. Based on the results, we discussed the efficiency of character input using sEMG glove in VR space.

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