The Journal of Korea Robotics Society (로봇학회논문지)

Korea Robotics Society (한국로봇학회)
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Knitted Data Glove System for Finger Motion Classification

손가락 동작 분류를 위한 니트 데이터 글러브 시스템

  • Lee, Seulah (Department of Electrical and Electronic Engineering, Hanyang University) ;
  • Choi, Yuna (Department of Electrical and Electronic Engineering, Hanyang University) ;
  • Cha, Gwangyeol (Department of Electrical and Electronic Engineering, Hanyang University) ;
  • Sung, Minchang (Department of Electrical and Electronic Engineering, Hanyang University) ;
  • Bae, Jihyun (Department of Clothing and Textiles, Hanyang University) ;
  • Choi, Youngjin (Department of Electrical and Electronic Engineering, Hanyang University)
  • Received : 2020.03.12
  • Accepted : 2020.05.06
  • Published : 2020.08.31
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Abstract

This paper presents a novel knitted data glove system for pattern classification of hand posture. Several experiments were conducted to confirm the performance of the knitted data glove. To find better sensor materials, the knitted data glove was fabricated with stainless-steel yarn and silver-plated yarn as representative conductive yarns, respectively. The result showed that the signal of the knitted data glove made of silver-plated yarn was more stable than that of stainless-steel yarn according as the measurement distance becomes longer. Also, the pattern classification was conducted for the performance verification of the data glove knitted using the silver-plated yarn. The average classification reached at 100% except for the pointing finger posture, and the overall classification accuracy of the knitted data glove was 98.3%. With these results, we expect that the knitted data glove is applied to various robot fields including the human-machine interface.

Keywords

References

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