TY - GEN
T1 - Gesture recognition system using optical muscle deformation sensors
AU - Hosono, Satoshi
AU - Nishimura, Shoji
AU - Iwasaki, Ken
AU - Tamaki, Emi
N1 - Publisher Copyright:
© 2019 Association for Computing Machinery.
PY - 2019/4/13
Y1 - 2019/4/13
N2 - Due to the spread of VR(Virtual Reality)/AR(Augmented Reality) applications, gesture input method will be required. In this research, a gesture recognition system is suggested using the optical muscle deformation sensors. Our gesture recognition system adapts machine learning with 8 channel optical muscle deformation sensors on the forearm which doesn’t disturb the movement of the hand. In our experiment, significant differences were found in t-test. It was found that SVM can recognize gesture with higher accuracy more than Logistic Regression. In addition, we conducted an experiment to distinguish the state of bending each finger joint. As a result, it was found that the open hand gesture is erroneously recognized as PIP bent gesture.
AB - Due to the spread of VR(Virtual Reality)/AR(Augmented Reality) applications, gesture input method will be required. In this research, a gesture recognition system is suggested using the optical muscle deformation sensors. Our gesture recognition system adapts machine learning with 8 channel optical muscle deformation sensors on the forearm which doesn’t disturb the movement of the hand. In our experiment, significant differences were found in t-test. It was found that SVM can recognize gesture with higher accuracy more than Logistic Regression. In addition, we conducted an experiment to distinguish the state of bending each finger joint. As a result, it was found that the open hand gesture is erroneously recognized as PIP bent gesture.
KW - Hand gesture
KW - Human activity recognition
KW - Information interface
UR - http://www.scopus.com/inward/record.url?scp=85067844626&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85067844626&partnerID=8YFLogxK
U2 - 10.1145/3324033.3324037
DO - 10.1145/3324033.3324037
M3 - Conference contribution
AN - SCOPUS:85067844626
T3 - ACM International Conference Proceeding Series
SP - 12
EP - 15
BT - Proceedings of the 2nd International Conference on Electronics, Communications and Control Engineering, ICECC 2019
PB - Association for Computing Machinery
T2 - 2nd International Conference on Electronics, Communications and Control Engineering, ICECC 2019
Y2 - 13 April 2019 through 16 April 2019
ER -