지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2013.10
- 수록면
- 169 - 172 (4page)
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초록· 키워드
오류제보하기
Surface electromyography (sEMG) signals have been applied as control commands in numerous humanrobot interface systems and have been deployed for rehabilitation or clinical applications. Although lots of previous workers have tried to determine features appropriate for specific sEMG-signal classification problems, little of this work has involved deeply searching for the inner characteristics of the signals. In this study, we try to evaluate the properties of the transient state of sEMG signals on randomly mounted, dry-type electrodes and use this to rapidly predict three kinds of hand configurations - rock, scissors and paper motions. In experiments, subjects performed a rock-scissor-paper game with a virtual hand. For data acquisition, the sEMG signals were sampled at 1 kHz with eightchannel electrodes (wearable, dry type) that were randomly mounted on forearms [2]. The results verified that the proposed algorithm, using the property of the transient state of sEMG signals, works successfully.
목차
Abstract
1. INTRODUCTION
2. BACKGROUND
3. Methods and Algorithms
4. EXPERIMENT AND RESULTS
5. CONCLUSION
REFERENCES
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