FirsTVR: A muscle deformation sensors array device to detect finger gestures and noise reduction case

Emi Tamaki, Satoshi Hosono, Ken Iwasaki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Hand gesture input has been of growing importance in 3D content and VR/AR. However, a hand gesture detection system by camera was small in scope. And EMG was affected by noise from other electronic devices. Muscle deformation sensor system could only detect large muscles deformation related to wrist gestures because the sensor is covered to prevent light leakage noise. In this research, a device that covers the only sensor side circularly as light noise reduction case and has 14ch photo reflector sensors can detect small muscles deformation: FirstVR is suggested (Fig1, 2). Results of our experiment shows that recognition accuracy average of more than 90% is achieved with three types of PIP joint angles. In the future, FirstVR is expected to be used not only for content inputting finger movements indoors and outdoors but also for muscle displacement recording system.

Original languageEnglish
Title of host publicationProceedings of the 2nd International Conference on Electronics, Communications and Control Engineering, ICECC 2019
PublisherAssociation for Computing Machinery
Pages21-24
Number of pages4
ISBN (Electronic)9781450362634
DOIs
Publication statusPublished - 2019 Apr 13
Event2nd International Conference on Electronics, Communications and Control Engineering, ICECC 2019 - Phuket, Thailand
Duration: 2019 Apr 132019 Apr 16

Publication series

NameACM International Conference Proceeding Series

Conference

Conference2nd International Conference on Electronics, Communications and Control Engineering, ICECC 2019
Country/TerritoryThailand
CityPhuket
Period19/4/1319/4/16

Keywords

  • Hand gesture
  • Muscle deformation sensor array
  • Noise reduction case

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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