TY - GEN
T1 - Spectral collaborative representation based classification by circulants and its application to hand gesture and posture recognition from electromyography signals
AU - Boyali, Ali
AU - Hashimoto, Naohisa
AU - Matsumoto, Osamu
N1 - Funding Information:
The study is supported by the Japan Society for the Promotion of Science (JSPS) fellowship program and the KAKENHI Grant (Grant Number 15F13739).
Publisher Copyright:
© International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2015.All right reserved.
PY - 2015
Y1 - 2015
N2 - In this study we introduce and demystify a novel signal pattern recognition method, Spectral Collaborative Representation based Classification (SCRC) and demonstrate its application for recognition of hand gestures and postures using Electromyography sensors. A recently released Thalmic Labs MYO armband is used to gather muscle electromyography signals. Along with the new signal pattern classification algorithm, we also introduce a training approach which implicitly embeds the gesture boundaries in a training dictionary that allows continous gesture and posture recognition. The worst recognition accuracy we obtained for a set of experiments is over 97% which is the highest recognition results in the literature where bio-signals are used.
AB - In this study we introduce and demystify a novel signal pattern recognition method, Spectral Collaborative Representation based Classification (SCRC) and demonstrate its application for recognition of hand gestures and postures using Electromyography sensors. A recently released Thalmic Labs MYO armband is used to gather muscle electromyography signals. Along with the new signal pattern classification algorithm, we also introduce a training approach which implicitly embeds the gesture boundaries in a training dictionary that allows continous gesture and posture recognition. The worst recognition accuracy we obtained for a set of experiments is over 97% which is the highest recognition results in the literature where bio-signals are used.
KW - Continous gesture recognition
KW - EMG gesture
KW - Gesture training matrix
KW - Myo armband
KW - Spectral representation
UR - http://www.scopus.com/inward/record.url?scp=85006052802&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85006052802&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85006052802
T3 - Proceedings of the 2015 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2015
SP - 30
EP - 35
BT - Proceedings of the 2015 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2015
A2 - Arabnia, Hamid R.
A2 - Deligiannidis, Leonidas
A2 - Tinetti, Fernando G.
A2 - Jandieri, George
A2 - Schaefer, Gerald
A2 - Solo, Ashu M. G.
PB - CSREA Press
T2 - 2015 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2015, at WORLDCOMP 2015
Y2 - 27 July 2015 through 30 July 2015
ER -