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근전도 패턴 인식 및 분류 기반 다자유도 전완 의수 개발

Title
근전도 패턴 인식 및 분류 기반 다자유도 전완 의수 개발
Other Titles
Development of Multi-DoFs Prosthetic Forearm based on EMG Pattern Recognition and Classification
Author
최영진
Keywords
Prosthetic Forearm; Myoelectric Prosthesis; Multilayer Perceptron; Pattern Recognition
Issue Date
2019-09
Publisher
한국로봇학회
Citation
로봇학회논문지, v. 14, No. 3, Page. 228-235
Abstract
This paper presents a multiple DoFs (degrees-of-freedom) prosthetic forearm and sEMG (surface electromyogram) pattern recognition and motion intent classification of forearm amputee. The developed prosthetic forearm has 9 DoFs hand and single-DoF wrist, and the socket is designed considering wearability. In addition, the pattern recognition based on sEMG is proposed for prosthetic control. Several experiments were conducted to substantiate the performance of the prosthetic forearm. First, the developed prosthetic forearm could perform various motions required for activity of daily living of forearm amputee. It was able to control according to shape and size of the object. Additionally, the amputee was able to perform ‘tying up shoe’ using the prosthetic forearm. Secondly, pattern recognition and classification experiments using the sEMG signals were performed to find out whether it could classify the motions according to the user’s intents. For this purpose, sEMG signals were applied to the multilayer perceptron (MLP) for training and testing. As a result, overall classification accuracy arrived at 99.6% for all participants, and all the postures showed more than 97% accuracy.
URI
http://db.koreascholar.com/Article?code=378898http://repository.hanyang.ac.kr/handle/20.500.11754/120873
ISSN
2287-3961; 1975-6291
Appears in Collections:
COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > ELECTRICAL ENGINEERING(전자공학부) > Articles
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