- Volume 19 Issue 8
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Study on Forearm Muscles and Electrode Placements for CNN based Korean Finger Number Gesture Recognition using sEMG Signals
표면근전도 신호를 활용한 CNN 기반 한국 지화숫자 인식을 위한 아래팔 근육과 전극 위치에 관한 연구
- Park, Jong-Jun (Department of Medical IT Engineering, Soonchunhyang University) ;
- Kwon, Chun-Ki (Department of Medical IT Engineering, Soonchunhyang University)
- Received : 2018.05.15
- Accepted : 2018.08.03
- Published : 2018.08.31
Surface electromyography (sEMG) is mainly used as an on/off switch in the early stage of the study and was then expanded to navigational control of powered-wheelchairs and recognition of sign language or finger gestures. There are difficulties in communication between people who know and do not know sign language; therefore, many efforts have been made to recognize sign language or finger gestures. Recently, use of sEMG signals to recognize sign language signals have been investigated; however, most studies of this topic conducted to date have focused on Chinese finger number gestures. Since sign language and finger gestures vary among regions, Korean- and Chinese-finger number gestures differ from each other. Accordingly, the recognition performance of Korean finger number gestures based on sEMG signals can be severely degraded if the same muscles are specified as for Chinese finger number gestures. However, few studies of Korean finger number gestures based on sEMG signals have been conducted. Thus, this study was conducted to identify potential forearm muscles from which to collect sEMG signals for Korean finger number gestures. To accomplish this, six Korean finger number gestures from number zero to five were investigated to determine the usefulness of the proposed muscles and electrode placements by showing that CNN technique based on sEMG signal after sufficient learning recognizes six Korean finger number gestures in accuracy of 100%.
surface electromyography;forearm;multi finger gesture recognition;electrode placements;Korean multi finger number
Supported by : 순천향대학교
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