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.

Abstract
1. 서 론
2. 니트 데이터 글러브 설계 및 제작
3. 실험 방법 및 결과
    3.1 실험대상 및 방법
    3.2 실험결과
4. 결 론
References

• 이슬아(Department of Electrical and Electronic Engineering, Hanyang University) | Seulah Lee
• 최유나(Department of Electrical and Electronic Engineering, Hanyang University,) | Yuna Choi
• 차광열(Department of Electrical and Electronic Engineering, Hanyang University,) | Gwangyeol Cha
• 성민창(Department of Electrical and Electronic Engineering, Hanyang University) | Minchang Sung
• 배지현(Department of Clothing and Textiles, Hanyang University) | Jihyun Bae
• 최영진(Department of Electrical and Electronic Engineering, Hanyang University) | Youngjin Choi Corresponding author